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Anexo I

D/Dª...............................................................SECRETARIO/A DEL DEPARTAMENTO DE....................................................................... DE LA UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA,

CERTIFICA,

Que el Consejo de Doctores del Departamento en su sesión de fecha.............................tomó el acuerdo de dar el consentimiento para su tramitación, a la tesis doctoral titulada “Oxigenación Cerebral y Fatiga Durante el Ejercicio en Hipoxia Aguda” presentada por el/la doctorando/a D/Dª Rafael Sánchez de Torres-Peralta y dirigida por el/la Doctor/a Jose Antonio López Calbet Y para que así conste, y a efectos de lo previsto en el Artº 6 del Reglamento para la elaboración, defensa, tribunal y evaluación de tesis doctorales de la Universidad de Las Palmas de Gran Canaria, firmo la presente en Las Palmas de Gran Canaria, a...de.............................................de dos mil............

Anexo II

UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA

Departamento/Instituto/Facultad___ Educación Física__________ Programa de doctorado___ Avances en Traumatología, Medicina del Deporte y Cuidado de Heridas_______________________________________________

Título de la Tesis Oxigenación Cerebral y Fatiga Durante Ejercicio en Hipoxia Aguda

Tesis Doctoral presentada por D/Dª ____ Rafael Sánchez de Torres-Peralta___ Dirigida por el Dr/a. D/Dª. __________José Antonio López Calbet___________ Codirigida por el Dr/a. D/Dª. ________________________________________ El/la Director/a, El/la Codirector/a El/la Doctorando/a, (firma) (firma) (firma) Las Palmas de Gran Canaria, a 4 de noviembre de 2015

Contenidos

Rafael Sánchez de Torres-‐Peralta Página 9

CONTENIDOS

Agradecimientos ……………………………………………………………… 11

Lista de publicaciones originales ……………………………………………………………… 13

Fuentes de financiación ……………………………………………………………… 15

Abreviaturas ……………………………………………………………… 17

Resumen general ……………………………………………………………… 21

Summary ……………………………………………………………… 23

1. Introducción ……………………………………………………………… 25

1.1. Aparato músculo-esquelético……………………………………………………………. 25

1.2. Aspectos cardiovasculares y de flujo sanguíneo...................................................... 27

1.2.1 Respuesta cardiovascular al sprint……………… 31

1.3. Aspectos neuromusculares........................……...................................................... 32

1.4. Cambios que se mantienen tras el ejercicio .............…………………..................... 33

1.5. Fatiga . ……………………………………………………………. 35

1.6. Fatiga e hipoxia …………………………………………………………..... 37

1.7 Consideraciones metodológicas.............................................................................. 40

2. Objetivos ……………………………………………………………… 43

3. Hipótesis ……………………………………………………………… 45

4. Metodología ……………………………………………………………… 47

5. Resultados ……………………………………………………………… 63

6. Discusión ……………………………………………………………… 69

7. Conclusiones ……………………………………………………………… 81

8. Conclussions ……………………………………………………………… 83

9. Bibliografía ……………………………………………………………… 85

10. Apéndices-estudios I-III ………………………………………………………………

Contenidos

Página 10 Rafael Sánchez de Torres-‐Peralta

Agradecimientos


AGRADECIMIENTOS

A José Antonio López Calbet por haberme descubierto el mundo de la investigación y haberme aceptado en el grupo Rendimiento Humano y Salud. No es fácil reducir en un párrafo la influencia de un maestro sobre un alumno. Y es toda influencia, como en el camino de cualquier proyectil, más visible al final del camino. Por eso ha sido tan importante recibirla ahora, al principio de este camino. Gracias por regalarme el más preciado tesoro que un ser humano puede regalar a otro: su tiempo. Mucho más de lo que pueda haber aprendido de fisiología y de otras ciencias, que es sin duda lo que buscaba y he conseguido, valoro lo que he aprendido de actitudes hacia la investigación y hacia el trabajo que he visto a diario.

A Cecilia Dorado García por permitirme participar en sus estudios. Pero sobre todo por siempre estar dispuesta a ayudarnos con una sonrisa. A José Ricardo Navarro del Tuero por haber sido un ejemplo de integridad y bondad durante todos estos años. Por el consejo adecuado, el mantenimiento idóneo y la ayuda en el momento preciso, por todo ese trabajo silencioso e invisible sin el que no podríamos hacer ni aprender a hacer. Pero, sobre todo, por preocuparse por los alumnos como si fuéramos su familia.

A Amelia Guadalupe Grau, gracias por haberme dado la oportunidad de mi primer poster en un congreso internacional, por haber valorado mi trabajo y por las técnicas que me has enseñado. Pero también por haber compartido momentos estupendos.

Para Jesús Ponce González gracias por haber liderado como post-doc el equipo que formamos

en algunos de los experimentos vitales en mi tesis y haberme enseñado durante ese tiempo, con tu ejemplo, otra forma de hacer las cosas. Pero sobre todo por enseñarme la importancia del carisma en el equipo, a disfrutar de mi tiempo de estrés y por la capacidad de sonreír en los tiempos difíciles.

Para David Morales Álamo por las largas conversaciones en el despacho y por haber

compartido la entrega y la dedicación, la docencia y el aprendizaje. Debatir contigo ha sido enriquecedor. A José Losa Reyna gracias por aguantar el esfuerzo y abrir camino. Por estar convencido de que

puedes lograrlo. Eres la personificación de que el laboratorio mejora con los años. A María Carmen García Chicano gracias por siempre estar dispuesta a ayudar a todos. Gracias

también por compartir con nosotros todos tus conocimientos sobre las técnicas de laboratorio. A los que ya no están o apenas estuvieron cuando llegué, a Teresa Fuentes, Lorena García,

Hugo Olmedillas, Borja Guerra, Ignacio Ara, Jorge Pérez y Germán Vicente, gracias porque todavía encuentro protocolos con vuestros nombres y sobre todo gracias por haber estado ahí cada vez que he tenido una duda con algo, demostrando que uno nunca debe olvidar de donde viene.

A Francisco José Vera García por abrirme las puertas de su laboratorio y del centro de

investigación del deporte de la Universidad Miguel Hernández de Elche noche y día para que pudiera aprender las técnicas de biomecánica que atesoraba. Por siempre tener tiempo para reunirse conmigo y aportarme todo su conocimiento. Guardo muy buenos recuerdos de mi estancia en su grupo y su ayuda.

To the personnel of the Sportswischanschaft at Salzburg Universtät. Thank you very much for

allowing me in your laboratories. It was a pleasure to work with your team. Thanks for having time for our meetings, and for your dedication. It was a honor to make my stay in your university.

Gracias a Javier Chavarren, Rafael Arteaga, José Antonio Serrano, Joaquín Sanchís Moysi,

Juan José Gonzalez Henriquez, por toda la ayuda recibida.

Agradecimientos


He de agradecer a la Universidad de Las Palmas de G.C. al servicio de Tercer Ciclo y

especialmente al Departamento de Educación Física las facilidades que me ha brindado.

Gracias al personal de la Facultad, Jose Luis, Mila, Anselmo, Julio, Yolanda, Macu y Maribel.

A todos los sujetos de ese estudio que tanto me ha dado “OXY”, y que han hecho posible todo

éste trabajo. A mi madre, porque crecí con la dedicación constante de una profesional muy reputada en el

campo del conocimiento que sin embargo sacrificó gran parte de su tiempo para imbuirnos la necesidad de educarnos, el respeto por el conocimiento y por enseñarnos el camino hacia la excelencia académica desde la niñez más temprana. Gracias por haberme enseñado a estudiar.

A mi padre, por ser una de las personas capaces de ver las cosas dando prioridad al sentido

común, pero desde el conocimiento y la reflexión. Gracias por enseñarme a tomar distancia, a centrarme en lo verdaderamente importante, a saber renunciar. Pero sobre todo gracias por haberme enseñado a pensar.

A Susana Jato-Sánchez O´Shane por ser la primera persona en haberme acercado a la ciencia desde dentro. En resumen el niño que te conoció y tuvo el honor de aprender de ti no sería el adulto que soy de no haber compartido una parte del camino. Has sido un ejemplo para mí en todos los aspectos de mi vida.

A Fernando Carrillo Cremades por haber sido un modelo para todas las personas que le rodeaban durante la formación que tuve el honor de recibir de usted. En ella aprendí junto a otras cosas los verdaderos límites de mi cuerpo y de mi mente. Pero especialmente por haberme enseñado la diferencia entre poder hacer algo y estar dispuesto a hacerlo. Y porque haciéndolo puso mi propia vida en mis manos y me dio la oportunidad de reeducarme a mí mismo

A Daniela Penz, sin quien nada de lo que hago o he hecho sería posible. Un proyecto de vida en

común no es lo único que nos une. Gracias por ser un ejemplo en organización, rigor, dedicación y constancia y por estar siempre a mi lado. Gracias por haberme enseñado a crecer.

A Leonardo, mi hijo, que con su valentía, tesón, y grandeza pero, sobre todo, con su insaciable

curiosidad, me ha enseñado a saber qué hacemos y cuáles son los límites de lo que hacemos, pero sobre todo por qué hacemos lo que hacemos. Y mi máxima motivación para seguir estudiando es algún día llegar a ser un modelo para ti que te ayude a ser la mejor versión de ti mismo que puedas llegar a ser.

Agradecimientos


LISTADO DE PUBLICACIONES ORGINALES

La presente tesis se basa en las siguientes publicaciones:

1º/ Muscle activation during exercise in severe acute hypoxia: role of absolute and relative intensity. Torres-Peralta Rafael, Losa-Reyna José, González-Izal Miriam, Perez-Suarez Ismael, Calle-Herrero Jaime, Izquierdo Mikel, and Calbet José A.L. High Altitude Medicine & Biology. December 2014, 15(4): 472-482. 2º/ Task failure during exercise to exhaustion in normoxia and hypoxia is due to reduced muscle activation caused by central mechanisms while muscle metaboreflex does limit performance. Rafael Torres-Peralta, David Morales-Alamo, Miriam Gonzalez-Izal, Jose Losa Reyna, Ismael Perez-Suarez, Mikel Izquierdo, Jose Antonio L Calbet. (Under review). 3º/ Oxygenation at fatigue in hypoxia increases muscle activation and relieves fatigue: influence of PIO2. Rafael Torres-Peralta, Jose Losa Reyna, David Morales-Alamo, Miriam Gonzalez-Izal, Ismael Perez Suarez, Mikel Izquierdo, Jose Antonio L Calbet. (Submitted).

Fuentes de financiación


Fuentes de financiación


Fuentes de financiación:

Los estudios que componen esta tesis doctoral han sido cofinanciados por el Ministerio

de Educación y Ciencia (DEP2009-11638; DEP2010-21866, and FEDER) y VII Convocatoria de

Ayudas a la Investigación Cátedra Real Madrid- Universidad Europea de Madrid (2015/04RM).

Rafael Sánchez de Torres-Peralta ha recibido financiación como becario de pregrado

para la realización de Tesis de la Universidad de Las Palmas de Gran Canaria dentro del

programa de Formación de Profesorado Universitario.

Listado de Abreviaturas




LISTADO DE ABREVIATURAS

ADP: Adenosín difosfato.

ATP: Adenosín trifosfato.

AMP: Adenosín monofosfato.

BF: (Biceps femoris), bíceps femoral.

BMC: (Bone mineral content), contenido mineral óseo.

Ca: Calcio.

CNS: (Central Nervous System), sistema nervioso central.

d.w.: (Dry weight), peso seco.

diff a-vO2: (arteriovenous oxygen difference), diferencia arteriovenosa de oxígeno.

DXA: (Dual -energy X-ray absorptiometry), absorciometría fotónica dual de rayos X.

ECG: (Electrocardiogram), electrocardiograma.

EMG: (Surface electromyogram), electromiograma de superficie.

EMGRMS: (Root mean square of EMG), raíz cuadrada de la media de los cuadrados del EMG.

FIO2: (Inspired oxygen fraction), fracción inspiratoria de oxígeno.

H+: (Hydrogen ion) hidrón.

Hb: (Hemoglobine), hemoglobina.

HR: (Heart Rate), frecuencia cardiaca.

HRmax: (Maximal heart rate), frecuencia cardiaca máxima.

Hyp: (Hypoxia), hipoxia.

Hypb: (Session in hypoxia with biopsies taken), sesión en hipoxia con obtención de biopsias.

IE: (Incremental exercise to exhaustion) ejercicio incremental hasta el agotamiento

Lac: (Lactate), lactato.

MAP: (Median arterial pressure), presión arterial media.

MdPF: (Median power frequency), frecuencia mediana de la densidad espectral de potencia.

MPF: (Mean power frequency), frecuencia media de la densidad espectral de potencia.

MPO: (Wingate Mean Power Output), potencia media en el test de Wingate.



MVC: (Maximal voluntary contraction), contracción máxima voluntaria (fuerza isométrica

máxima).

NO: (Nitric Oxide), óxido nítrico.

Nx: Normoxia

Nxb: (Session in normoxia with biopsies taken), sesión en normoxia con obtención de biopsias.

ODC: (Oxygen dissociation curve), curva de disociación del oxígeno.

PaO2: (Arterial oxygen pressure), presión arterial de oxígeno.

PCr: (Phosphocreatine), fosfocreatina.

PETCO2:(End tidal Carbon Dioxide Pressure), presión de CO2 al final de la espiración.

PETO2: (End tidal Oxygen Pressure), presión de O2 al final de la espiración.

Pi: (inorganic phosphate), fosfato inorgánico.

PIO2: (Inspiratory O2 pressure), presión inspiratoria de oxígeno.

PO2: Presión de oxígeno en vena femoral

PPO: (Peak Power Output), pico de potencia en el test de Wingate.

Q: (Cardiac output) , gasto cardíaco.

RER: (Respiratory Exchange Ratio), cociente respiratorio.

RF: (Rectus femoris), recto femoral del cuadriceps.

RMS: (Root mean square), raíz cuadrada de la media de los cuadrados.

RMSNz: (Normalized root mean square), RMS normalizado.

RPM: (Revolutions per minute), revoluciones por minuto.

RR: (Respiratory Ratio), frecuencia respiratoria.

CNS: (Central Nervous System), sistema nervioso central.

SaO2: (oxygen arterial saturation), saturación arterial de oxígeno.

SD: (standard deviation), desviación standard.

SV: (Systolic Volume), volumen sistólico

TAI: (Total activation index), índice de activación total.

TPR: (Total peripheral resistance), resistencia periférica total.

VE: (Minute ventilation), ventilación por minuto.



VM: (Vastus medialis), vasto medial del cuádriceps.

VL: (Vastus lateralis), vasto lateral del cuádriceps.

VO2: (Oxygen consumption), consumo de oxígeno.

VO2max: consumo de oxígeno máximo

VO2peak: (Peak oxygen uptake), pico de consumo de oxígeno.

Wingate: (30s all out test on cycloergometer), sprint máximo de 30s en cicloergómetro.

Wmax: (Peak power output at exhaustion during the incremental exercise test), vatios máximos

en el test incremental realizado para determinar el VO2max.

Wmean: (Mean power output during the 10s sprint test), potencia media durante sprints de 10s.

Wpeak-i: (Instantaneous peak power output), potencia instantánea máxima en el test de sprint.

w.w.: (wet weight), peso húmedo.

Resumen


Resumen


RESUMEN GENERAL

La fatiga humana es la incapacidad para mantener el nivel de potencia o generar

máxima potencia durante el esfuerzo, que puede ser causada por mecanismos neurales, de

transmisión o musculares. Las diferencias entre el rendimiento en condiciones de hipoxia

aguda o normoxia han sugerido un posible papel de la oxigenación cerebral en estos procesos.

Para comprobar si la oxigenación cerebral es el factor determinante en el cese del esfuerzo en

una prueba incremental hasta el agotamiento reclutamos a 11 sujetos sanos que realizaron 8

ejercicios incrementales hasta la fatiga, muchos de ellos con sprints previos y posteriores, en

distintas condiciones de oxigenación. Estos experimentos combinaron hipoxia severa aguda,

distintos cambios en fatiga a distintas oxigenaciones relativas, normoxia y oclusión de los

miembros inferiores durante distintas recuperaciones. En el estudio I demostramos que los

durante el ejercicio incremental hasta el agotamiento la activación muscular es mayor en

hipoxia que en normoxia a la misma intensidad absoluta, pero menor en hipoxia que en

normoxia a la misma intensidad relativa..En el estudio II la recuperación del muscular fue

bloqueada ocluyendo la circulación con un compresor rápido durante los descansos entre el

test incremental y el sprint subsiguiente. Como consecuencia se produjo un aumento del 20%

de la concentración muscular de lactato tras un minuto de isquemia, sin que ello produjera

deterioro alguno de la capacidad de sprint, a pesar de un descenso de la actividad registrada

en el electromiograma. En el estudio II demostramos que el fallo en la tarea o imposibilidad de

continuar el ejercicio incremental hasta el agotamiento se debe a mecanismos centrales y no a

incapacidad del músculo para responder a las órdenes del sistema nervioso. La suma de

resultados muestran que la decisión de detener un esfuerzo incremental radica

fundamentalmente en el sistema nervioso y que la oxigenación del mismo juega un papel

importante en la percepción del esfuerzo y la capacidad de activación de los sistemas

cardiorespiratorio y músculo-esquelético durante el ejercicio incremental. En el estudio III de la

presente tesis se demostró que la hipoxia severa equivalente a una altitud superior a los 4300

Resumen


m sobre el nivel del mar, pero no la hipoxia moderada, genera una disminución en la activación

muscular durante el ejercicio.

Summary


SUMMARY

Human fatigue is the inability to maintain the intensity of exercise or generate maximum power,

which may be caused by neural mechanisms or muscular mechanism. The differences in

performance between exercise in acute hypoxia and normoxia have suggested a possible role

of cerebral oxygenation in these processes. To test whether brain oxygenation is the main

determining factor in the cessation of effort during an incremental test to exhaustion, we

recruited 11 healthy subjects who performed eight incremental exercise test to fatigue, many

with pre- and post sprints at different oxygenation levels. These experiments combined

incremental exercise to exhaustion in severe acute hypoxia, with transitions to different levels of

oxygenation, and incremental exercise followed by vascular occlusion of the lower extremities of

different durations and sprint exercise. In the study I, it has been shown that muscle activation is

higher in hypoxia than in normoxia at the same absolute intensity, but lower in hypoxia than in

normoxia at the same relative intensity, during incremental exercise to exhaustion. In the study

II, we showed that the task failure or inability to continue the incremental exercise to exhaustion

is due to central mechanisms rather than inability of the muscle to respond to the orders of the

central nervous system. In study II, muscle recovery was blocked by occluding circulation with a

fast compressor during the breaks between the incremental test and subsequent sprint. As a

result there was a 20% increase in muscle lactate concentration after 60 s of ischemia.

However, performance was increased with ischemic recovery despite lower root mean square

electromyogram values. In the study III of this thesis, it has been shown that severe hypoxia

equivalent to an altitude above 4300 m, but not moderate hypoxia, causes a decrease in muscle

maximal activation during incremental exercise to exhaustion. Overall, this thesis shows that the

decision to stop an incremental exercise to exhaustion relies primarily on the central nervous

system, with brain oxygenation playing a critical role in the perception of effort and the ability to

activate the cardiorespiratory and musculoskeletal systems during exercise incremental.

Introducción


Introducción


1.INTRODUCCIÓN

El ejercicio incremental hasta el agotamiento (IE) probablemente sea el test más usado

para examinar la condición física y las capacidades cardiorespiratorias. Este tipo de test es

considerado el “gold standard” para determinar el consumo de oxígeno máximo (VO2max)

(Mitchell et al., 1958; Tipton, 2003). Pero paradójicamente los mecanismos que determinan el

agotamiento o fallo en la tarea, es decir, la incapacidad para continuar el esfuerzo no son

suficientemente conocidos todavía.

1.1 Aparato músculo-esquelético

El movimiento como herramienta fundamental para la supervivencia es imprescindible

para los humanos desde el momento en que los movimientos cardiacos y respiratorios son

inevitables. Pero más allá de estos pequeños movimientos inevitables, los que nos permiten

mover nuestro esqueleto son también cruciales para la conducta de relación con el medio y,

por ello, para la supervivencia.

Para lograrlo tenemos células responsables de generar fuerza, la fibra muscular. Estas

fibras son capaces de contraerse para transformar energía metabólica en fuerza física de

tracción. No obstante tienen límites. Algunos de ellos en cuanto a la capacidad de generación

de potencia son fundamentalmente conocidos y tienen que ver con la estructura o la función de

la célula. Pero existen otros que aún desconocemos.

La activación muscular se ha representado frecuentemente utilizando la amplitud de la

señal electromiográfica (EMG). Esta señal va aumentando a medida que se aumenta la

intensidad de un ejercicio incremental hasta el agotamiento (Taylor & Bronks, 1996; Osawa et

al., 2011) debido a la combinación de reclutamiento adicional de unidades motoras junto al

aumento en las frecuencias de descarga de las motoneuronas aumentando la intensidad de la

contracción y aumentando la potenia generada (Gottlieb & Agarwal, 1971; Ericson, 1986; Weir

et al., 1992; Gonzalez-Izal et al., 2012). Pero también aumenta cuando realizamos

contracciones repetidas submáximas (Viitasalo & Komi, 1977), estáticas o dinámicas, aun sin

Introducción


aumentar la potencia a realizar durante el ejercicio (Bigland-Ritchie et al., 1986; Hausswirth et

al., 2000; Sarre & Lepers, 2005), posiblemente a través de reclutamiento de unidades motoras

adicionales a medida que se van fatigando (Fulco et al., 1996). Puede estar acompañado de

aumentos o disminuciones en frecuencia media (Xie & Hampf) o mediana (Xie & Hampf)

dependiendo de las intensidades (Arendt-Nielsen et al., 1989) o tipo de contracciones, número

de repeticiones realizadas y momento en el que se efectúa el registro de en relación al grado

de fatiga muscular y comportamiento de la potencia (Tesch et al., 1990; Pincivero et al., 2001;

Sarre & Lepers, 2005; Izquierdo et al., 2011). No obstante, existe cierto consenso al considerar

que durante contracciones repetidas a alta intensidad un descenso de MPF reflejaría fatiga

muscular (Amann et al., 2006) especialmente si la potencia está disminuyendo aunque en

ocasiones es difícil separar un factor del otro. De acuerdo con esta idea a intensidades

constantes también se ha descrito una reducción de MPF al quedar exhausto (Hausswirth et

al., 2000).

A cualquier intensidad absoluta, el esferzo percibido es mayor si se está realizando en

hipoxia severa (e.g. FIO2<0.115) y se considera una intensidad relativa mayor debido a que

durante el ejercicio incremental llegará a un menor VO2max (Calbet et al., 2003a) y se espera

por tanto que el uso de masa muscular será mayor y la amplitud de EMG también será mayor.

Incrementar la intensidad de ejercicio sobre el umbral de producción sostenible de lactato

genera un reclutamiento de unidades motoras que ha sido demostrado con resonancia

magnética (Endo et al., 2007). La hipoxia reduce la activación de origen central (Millet et al.,

2012) debido a menor oxigenación del cerebro (Goodall et al., 2012) aunque los datos han sido

contradictorios por la existencia de estudios que no mostraron este efecto de la hipoxia durante

ejercicio estático (Millet et al., 2012) o dinámico (Taylor & Bronks, 1996; Donnelly & Green,

2013) o incluso el efecto contrario (Fulco et al., 1996). Discrepancias probablemente debidas a

los distintos músculos medidos, los tipos de activación registrados y la marcada

heterogeneidad inter e intra-músculo en cuanto a los patrones de activación (Hug et al., 2004;

Cannon et al., 2013). Probablemente por este motivo la relación entre activación motora de

Introducción


origen central, la activación voluntaria y los parámetros de EMG ha sido bastante controvertida

(Verges et al., 2012).

La fibra muscular no trabaja sola. La contracción muscular genera eventos eléctricos,

iónicos, mecánicos, metabólicos y oxidativos. Campos electrostáticos asociados con la

descarga de la motoneurona, liberación de calcio en el músculo, tensión mecánica en el hueso,

disminución de disponibilidad de energía en la célula y producción de radicales libres. Cada

uno de estos fenómenos influencia la actividad enzimática y la expresión génica en cada uno

de los órganos afectados por el ejercicio de manera independiente, pero además se influencian

entre sí y actúan en conjunción con la estimulación hormonal y con las propiedades específicas

de cada órgano de generar sus propias vías de señalización, de manera redundante y

alternativa a los mecanismos del sistema nervioso y el endocrino (Borer). así que haremos un

corto repaso de aspectos sistémicos que colaboran sinérgicamente para el movimiento y que

puedan ser considerados relevantes a efectos de esta tesis.

1.2. Aspectos cardiovasculares y de flujo sanguíneo

La presión aórtica aumenta durante el ejercicio mientras que la presión en la aurícula

derecha se mantiene cercana a 0 para aumentar el flujo sanguíneo, mientras que la resistencia

periférica total (TPR) desciende debido, en parte, a sustancias vasodilatadoras excretadas

desde los músculos activos y vasoconstrictoras por parte de los vasos que los rodean para

mantener la presión arterial media (MAP) a pesar de la vasodilatación muscular (Smith &

Fernhall, 2011).

La respuesta vasoconstrictora es imprescindible para evitar hipotensión durante el

ejercicio con grandes masas musculares y es provocada por activación simpática desde los

centros de control cardiovascular en el cerebro que causan una vasoconstricción sistémica a la

que se oponen las fibras musculares activas a través de la liberación de sustancias

vasodilatadoras que impiden el efecto vasoconstrictor de la noradrenalina (ATP y tal vez óxido

nitrítico) en un proceso de recibe el nombre de "simpatolisis funcional".

Introducción


Esta activación simpática está mediada por receptores adrenérgicos alfa1 y alfa2

(Rosenmeier et al., 2003). Los factores liberados desde las células endoteliales (óxido nítrico

(NO) y prostaciclinas) tienen también una función en la hiperemia al causar la relajación de la

musculatura lisa, lo que produce dilatación de los vasos ante un aumento en el flujo que ya se

está produciendo. La presión genera no sólo un aumento de la liberación de NO sino también

un aumento de la producción. Para que se produzcan estos cambios han debido darse

aumentos en flujo probablemente causados por un aumento en la concentración de adrenalina

y/o valores intersticiales de potasio que produciría la hiperpolarización de la fibra de músculo

liso y con ello a su vasodilatación. Además el descenso de pH y de valores intramusculares de

oxígeno bien por la hipoxia que causaría un descenso en el aporte o por el incremento de su

consumo durante el ejercicio puede también inducir una vasodilatación concurrente (Clifford &

Hellsten, 2004). Dado que las células endoteliales se comunican con las siguientes (Bartlett &

Segal, 2000) y sortean los saltos con conexiones para transmitir la señal vasodilatadora a

través de la microcirculación (Little et al., 1995) se puede producir una respuesta altamente

integrada que permite la perfusión suficiende de los músculos activos, evitando la perfusión de

zonas no activas.

La vasodilatación mediada por el flujo se llama así por necesitar ejercer presión sobre

las células epiteliales y, como tal no, parece que sea de importancia al inicio del ejercicio pero

resulta de importancia para mantener la hiperemia. Tenemos dos mecanismos mecánicos que

trabajan sinérgicamente, la vasodilatación mediada por el flujo y el bombeo muscular, que

contribuyen a la hiperemia durante el ejercicio al forzar la presión la dilatación de las venas y

simultáneamente exprimirlas.

Para controlar los cambios rápidos de presión de perfusión que crearían desviaciones

de la presión de flujo existen cambios compensatorios del tono vascular llamados regulación

miogénica (Walker et al., 2007).

La combinación de un sistema de vasoconstricción con uno vasodilatador local permite

redistribuir el aporte de sangre durante el ejercicio en flujos diferentes para tejidos distintos de

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manera regulada por la necesidad, mientras que se mantiene la presión arterial media dentro

de los límites de seguridad tanto superior como inferior.

Podría pensarse que, si un aumento en la actividad aumenta el flujo a través de la

liberación de sustancias, en gran medida es la fibra muscular la que regula su propio flujo, pero

está lejos de ser tan sencillo.

A pesar de estos datos hay cierta discusión sobre los papeles de la vasodilatación y el

bombeo muscular al inico y mantenimiento del esfuerzo. Se ha sugerido que la acumulación de

metabolitos podría ser demasiado lenta para causar el aumento de flujo de los primeros

segundos, por lo que el bombeo podría ser lo más importante en esta fase (Tschakovsky et al.,

1996). En este sentido también se ha visto que la frecuencia de contracción puede ser más

importante que la fuerza con la que se contrae para este aspecto (Sheriff & Hakeman, 2001).

Pero por otro lado algunos estudios han mostrado que puede aumentar la hiperemia aunque el

bombeo esté minimizado (Shoemaker et al., 1998; Tschakovsky et al., 2004). En este sentido

también se ha visto que si se causa vasodilatación farmacológicamente antes del ejercicio no

se causa más dilatación durante el esfuerzo (Hamann et al., 2003). Lo que se ha confirmado

con músculo animal es una vasodilatación rápida a 2s del inicio del ejercicio y una pérdida de la

hiperemia inicial si se inhibe la vasodlatación bloqueando la hiperpolarización de la musculatura

lisa (Hamann et al., 2004).

Una unidad microvascular perfundida durante el ejercicio depende de la intesidad a la

que las fibras adjaventes liberan sustancias vasoactivas, pero no existe una relación de

igualdad entre número de fibras y de unidades microvasculares. La inervación es un diseño

tipo mosaico con cierta tendencia a perfundir fibras inactivas. De modo que el músculo en su

conjunto sería la unidad responsable de su propia regulación del flujo a recibir, pero esto sería

así de no existir competencia entre áreas vasculares por el aporte sanguíneo.

El flujo sanguíneo al músculo durante el ejercicio aumenta en función de la intensidad

pero hasta alcanzar el límite de las posibilidades de suministro que ofrece la bomba cardiaca

(Calbet et al., 2004). Existe una cantidad límite de flujo (Q) lo que fuerza una competición entre

lechos vasculares y la redistribución del flujo desde músculos que se ejercitan hacia otras

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áreas limitando el aporte que reciben. Se trata de un mecanismo que ha sido demostrado con

resistencia aplicada a los músculos respiratorios durante el esfuerzo. Esta limitación hace

necesarios algunos mecanismos que produzcan un cierto nivel de vasoconstricción incluso

durante el ejercicio para mantener la presión sanguínea mientras la noradrenalina ayuda a

contractuar contra los vasodilatadores locales en otras áreas (Rowell, 1997).

Durante el ejercicio una proporción creciente del flujo (Q) se dirige a la circulación

cutánea para disminuir la temperatura central compitiendo con las necesidades de otras zonas.

Aunque inicialmente se constriñen los vasos cutáneos al iniciar el esfuerzo debido al impulso

simpático y baja el flujo sanguíneo inicial (Kellogg et al., 1991) favoreciendo su envío al

músculo que se ejercita, cuando el centro corporal alcanza su umbral de temperatura el

hipotálamo causa una vasodilatación cutánea (Johnson & Park, 1981). Este aumento de flujo

correlaciona con el aumento de temperatura hasta un límite superior alrededor de los 38ºC

cuando se atenúa la señal vasodilatadora a la circulación de la piel (Kenney et al., 1991). En

cualquier caso se ha propuesto que el flujo sanguíneo correlacionaría con el consumo de

oxígeno independientemente del tipo de fibras que compongan el músculo (Marsh & Ellerby,

2006). Aparentemente el flujo a la musculatura estaría más relacionado con la intensidad del

metabolismo de la actividad contráctil que con el trabajo que se realiza (Clifford et al., 2005)

El volumen sistólico (SV) en un incremental va aumentando hasta alcanzar un plateau

salvo en individuos muy entrenados que podrían seguir aumentándolo hasta sus cargas

máximas (Zhou et al., 2001).

Es importante recordar que existe una diferencia importante en la respuesta del cuerpo

a un ejercicio de larga duración como un IE que fundamentalmente utiliza vías aeróbicas para

la obtención de energía y la que da a un ejercicio de fuerza o potencia de duración corta como

un test de sprint en cicloergómetro (Wingate). La respuesta cardiovascular responde de

manera coordinada e integrada para asegurar que se le aporta suficiente sangre a los

músculos activos en función de la proporción de energía que se obtiene por vía aeróbica,

fundamentalmente relacionada con la intensidad, y la duración. Al recibir una proporción

importante de la energía a través de vías anaeróbicas en algunos ejercicios la respuesta es

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diferente, pero recordemos que siempre existe una proporción de energía que será producida

aeróbicamente. Para los sprints la respuesta es muy parecida a la que se produce en ejercicio

de fuerza, pero es generalmente difícil de estudiar por problemas metodológicos. A pesar de

ello sabemos que se producen altos aumentos de presión sanguínea y modestos incrementos

en gasto cardiaco.

1.2.1 Respuesta cardiovascular en sprint

El aumento de frecuencia cardiaca (HR) está probablemente relacionada a la retirada

de impulso vagal mientras que el sistema nervioso simpático estimula el corazón utilizando

comando central y la información proporcionada por los mecanoreceptores y quimioreceptores

musculares. Aún en ejercicios de grandes grupos musculares dinámicos de corta duración

cercanos a los dos minutos la HR ya aumenta hasta un 40% descendiendo el volumen sistólico

(SV) solamente en un 5% (Elstad et al., 2009). La ausencia de cambios en SV pueden deberse

a una disminución de la precarga, aumento de la postcarga y una contractilidad aumentada.

La precarga puede haber disminuido al disminuir el tiempo de llenado por la mayor HR

además de un decreso en retorno venoso por oclusión mecánica mientras el músculo esté

contraído y en el caso de ejercicios de fuerza por la maniobra Vasalva. El aumento de presión

arterial aumenta la postcarga con lo que disminuye el SV a pesar de que se aumente la

contractilidad del corazón.

Durante los ejercicios de fuerza de doce repeticiones hasta la fatiga en duraciones

cercanas al minuto y medio, la HR aumenta 50 latidos por minuto pero el SV cae un 20% (Miles

et al., 1987), apenas aumentando 1L el gasto cardiaco. Incluso aumentando la intensidad en

prensa de piernas hasta el fallo al 95% de la fuerza máxima dinámica los autores vieron que el

gasto cardiaco aumentó sólo modestamente y dependiente de la HR (Lentini et al., 1993). Pero

además cuando se llega a la fatiga con cargas submáximas se alcanzan cantidades de trabajo

y HR superiores que las que se alcanzan con una repetición máxima (Fleck & Dean, 1987)

aunque en algunos ejerciciods de fuerza de alta intensidad sobre el 80% del máximo se

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detectan HR elevadas, especialmente altas justo antes de la extenuación (MacDougall et al.,

1985).

La resistencia periférica aumenta a niveles importantes pero no extremos durante

ejercicios de fuerza (MacDougall et al., 1985), así que la presión sistólica aumenta y la HR

aumenta modestamente por lo que podemos asumir un incremento similar de consumo de

oxígeno miocárdico (Nelson et al., 1974). Esta resistencia periférica y la HR han resultado ser

mayores en ejercicios cíclicos hasta la extenuación a diferentes cargas, mientras que la presión

sistólica fue similar (Featherstone et al., 1993). La evidencia sugiere un equilibrio más favorable

de aporte de oxígeno al corazón durante ejercicios cíclicos de resistencia por una presión

diastólica más alta y una HR más baja (Braith & Stewart, 2006).

En ejercicios de fuerza con cargas muy altas no obstante aumenta la presión

sanguínea más que en los ejercicios aeróbicos tanto la sistólica como en diastólica con poco

incremento del gasto cardiaco.

Durante una serie o un sprint va aumentando la presión sanguínea. La maniobra

Vasalva, mantener el aire inspirado, aumenta significativamente esta presión (McCartney,

1999), y se ha sugerido que podría tener un efecto protector de la presión que sufriría el arbol

cerebrovascular y el corazón. Por otro lado espirar permite bajar la presión sanguínea un 40%

(Narloch & Brandstater, 1995) pero intcrementa la presión intracraneal (Haykowsky et al., 2003)

y la presión en la pared ventricular al final de la fase sistólica (Haykowsky et al., 2001).

La resistencia periférica total (TPR) depende de la intensidad del ejercicio de fuerza,

siendo su comportamiento simliar a la aeróbica mientras se trate de intensidades bajas pero

con un menor descenso (Lewis et al., 1985), mientras que a altas intensidades la TPR

aumenta, probablemente, debido al aumento de presión intramuscular y los valores retornan a

los valores de resposo durante las fases no activas (Lentini et al., 1993).

1.3 Aspectos neuromusculares

El reclutamiento de fibras musculares ha sido explicado por el principio de Heinemann

o principio del tamaño, que dicta que las fibras más pequeñas son más fáciles de activar que

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las mayores y por ello serían reclutadas antes. Este principio ha sido comprobado en animales

y humanos con varios modelos experimentales (Rothwell et al., 1991; Bawa & Lemon, 1993), y

la conclusión lógica sería que el orden de reclutamiento estaría muy relacionado con el tipo de

fibras de la unidad motora y, por ende, del tamaño de la motoneurona. Esto sería así de

tratarse de incrementos de estímulo progresivos o de trabajo muscular exclusivamente

isométrico con contracciones tetánicas máximas, pero no explica todas las formas de

movimiento posibles.

Actualmente se está cuestionando el verdadero sentido del tamaño de la motoneurona

y se están teniendo en cuenta algunos otros factores en la explicación del movimiento

voluntario humano, como que sólo usamos algunas fibras de cada músculo en un movimiento,

que las usamos en cualquier grado de sus capacidades de creación de fuerza y que la

generación de fuerza de las fibras no está sincronizada de manera que cada movimiento es

una suma de contracciones de distintos tipos (Gardiner, 2011), pero parece que existen una

serie de maneras sistremáticas de reclutar fibras durante el ejercicio. Parece que neuronas de

varios tipos son utilizadas por el sistema nervioso central en combinaciones de reclutamiento y

dedicaciones variadas apropiadas para cada tarea.

Afortunadamente las propiedades de la señal electromiográfica de superficie permiten

estimar los patrones de reclutamiento, dado que las unidades motoras rápidas y lentas tienen

potencia espectral similar pero frecuencias distintas y se están investigando variaciones en los

patrones de reclutamiento motor durante ejercicios cíclicos (Wakeling, 2004).

.

1.4. Cambios que se mantienen tras el ejercicio

También tenemos que tener en cuenta ciertos cambios que se producen después de

terminado el ejercicio que pueden afectar a ejercicios realizados a continuación, como el sprint

posterior.

En primer lugar el volumen de plasma disminuye debido a la pérdida de fluido durante

el ejercicio y al cambio de compartamento del mismo. Durante los ejercicios de fuerza se ha

hallado una fuerte correlación entre este descenso de plasma y el aumento de área debido a

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un movimiento de fluido desde el espacio vascular a los músculos activos tras este tipo de

ejercicios (Ploutz-Snyder et al., 1995) probablemente causado por aumento de osmolaridad del

músculo debido a un aumento en lactato y otros solutos (Sjogaard & Saltin, 1982) y a una

mayor presión hidrotstática por aumento de la presión sanguínea. En cualquier caso los

volúmenes de plasma desplazados por este motivo se normalizan de nuevo tras 30 minutos.

El ejercicio aeróbico también aumenta la distensibilidad arterial durante y hasta 30

minutos después del ejercicio favoreciendo un descenso de lapresión arterial (Kingwell et al.,

1997). Esta vasodilatación pobablemente está causada por cambios en tono simpático, niveles

de hormonas circulantes o liberación de metabolitos desde los tejidos. Con ello la velocidad de

pulso de la onda, relacionada con esta distensibilidad, se mantiene disminuida durante una

hora en las arterias (Kingwell et al., 1997) pero no tiene relación con la presión arterial media

(MAP), que se normaliza apenas diez minutos después del ejercicio (Naka et al., 2003).

Tras ejercicio aeróbico el Q de reposo se mantiene usando una más baja HR (Rowland

& Roti, 2004) posiblemente relacionado con el tono vagal (Shi et al., 1995).

El ejercicio agudo altera la función de los factores sanguíneos relacionados con la

coagulación y la fibrinolisis que inducen un estado procoagulatorio y profibrinolítico. Se activan

las plaquetas y la agregación de las mismas en proporción directa a la intensidad del ejercicio

Además se produce un aumento de rigidez de las arterias centrales cuando se ejercita

el cuerpo entero a alta intensidad. Se ha sugerido que podría ser debido a la alta presión

sanguínea (Fahs et al., 2009). a pesar de que dura 30 minutos tras el ejercicio mientras que la

presión vuelve a valores iniciales a los 15 minutos (DeVan et al., 2005) por lo que otras

explicaciones como un aumento del tono simpático que aumentaría el tono vasoconstrictor de

la musculatura lisa (Heffernan et al., 2007) se han propuesto a pesar de la pequeña cantidad

de musculatura en estas arterias y una similar modulación en ejercicios aeróbicos y de fuerza.

Por otro lado se produce y mantiene una disminución en la rigidez de las arterias

periféricas que se cree sea debida a la vasodilatación en respuesta al ejercicio al aparecer sólo

en los músculos ejercitados (Heffernan et al., 2006). Algunos estudios muestran aumentos en

la microcirculación tras ejercicio agudo de fuerza independiente del nivel de entrenamiento

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previo (Fahs et al., 2009). Contrariamente a lo anteriormente pensado se ha aceptado el

descenso de la presión arterial de reposo tanto sistólica como diastólica tras un ejercicio de

fuerza (Cornelissen & Fagard, 2005) y se piensa que puede tener que ver con la modulación

del tono vascular miogénica (Heffernan et al., 2009).

1.5. La fatiga

La fatiga muscular podemos entenderla como cualquier reducción reversible por el

descanso (Gandevia, 2001) en la capacidad de generar potencia o fuerza muscular,

independientemente de la capacidad o no de mantener una tarea (Bigland-Ritchie & Woods,

1984). Existe dentro del concepto un aspecto que genera más complicación en el proceso de

medida de este fenómeno que sería la pérdida de eficiencia durante el ejercicio, de manera que

conllevaría la necesidad de hacer más esfuerzo para generar el mismo trabajo. Se entiende

que conllevaría la disminución de la capacidad de generar una potencia máxima, lo que en

parte simplifica su medición, pero se comienza a generar antes de que se interrumpa una

tarea.

Puede haber mecanismos que causan este fenómeno tanto a nivel neural (central)

como muscular (periférico) y a efectos de esta tesis vamos a incluir los fenómenos que se

produzcan en la unión neuromuscular dentro de la categoría de fenómeno "periférico". No

parece probable que exista una sola explicación para el fenómeno de la fatiga durante el

ejercicio, que describe fenómenos y respuestas a estímulos muy variados, pero aún en un sólo

tipo de esfuerzo se han descrito multitud de posibles mecanismos que causarían distintas

formas de fatiga y que no son mutuamente excluyentes tanto como probablemente sinérgicos.

Dentro de las posibles causas neuromusculares de la fatiga se han descrito factores de

origen periférico que podrían afectar a la eficiencia de la contracción provocando un aumento

del esfuerzo para generar la misma potencia. Estas propuestas se basan en estudios que

muestran que las fibras fatigadas tienen contracciones más lentas y de menor amplitud y una

menor capacidad de fuerza máxima junto a una ratio de desarrollo de la tensión menor (Fitts,

2008). Al darse un cambio en la relación fuerza-velocidad la pérdida de potencia sería mayor.

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Estas deficiencias podrían estar relacionadas con cambios en las concentraciones de calcio

(Ca), hidrogeniones (H+), fósforo inorgánico (Pi) o radicales libres, que causarían cambios en la

velocidad de la cinética de las uniones de la miosina, en el número de puentes o en la fuerza

que se generaría en cada puente. Se está cuestionando el papel de la acumulación de

metabolitos, especialmente del lactato, y la acidificación del músculo (Cairns, 2006; Knuth et

al., 2006; Karatzaferi et al., 2008) proponiéndose su efecto, de tenerlo, sobre el sistema

nervioso.

Además durante actividad contráctil submáxima se ha descrito una serie de cambios en

el sistema nervioso a medida que progresa el esfuerzo que pueden influir sobre la eficacia de

los patrones de reclutamiento de las fibras contráctiles.Se ha descrito cierta fatiga

neuromuscular que podría estar causada por consumo de los neurotransmisores, fallo de la

membrana postsináptica o fallos en la propagación del potencial de acción en los ramales del

axón (Aldrich et al., 1986; Van Lunteren & Moyer, 1996).

Se ha sugerido que la velocidad a la que se produce o acumula fatiga está regulada

desde el sistema nervioso central , el cual recibe retroalimentación a través de los aferentes

metaboreceptores desde los músculos que responden a la acumulación de metabolitos (Amann

& Dempsey). Se ha comunicado inhibición del impulso corticoespinal por estimulación de los

aferentes tipo III/IV (Amann & Dempsey, 2008; Rossman et al., 2012; Kennedy et al., 2015) con

más efecto sobre los músculos extensores que sobre los flexores (Martin et al., 2006).

El aumento de presión sanguínea desde el inicio hasta el final de una serie de

movimientos de fuerza o un sprint podría tener relación con niveles incrementales de fatiga y

una producción relativamente más alta de producción de fuerza al final del esfuerzo

(MacDougall et al., 1985; MacDougall et al., 1992), que es la variable principal determinante de

la presión por encima de factores omo tamaño del músculo, o fuerza absoluta.

Pero para complicar la determinación de las causas de la fatiga, algunas variables

pueden afectar mecanismos centrales y periféricos simultáneamente, como la hipoxia.

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1.6. Fatiga e hipoxia.

La hipoxia puede generarse por cambios de la fracción inspiratoria de oxígeno (FIO2),

en la presión inspiratoria de oxígeno (PIO2) de encontrarnos en altitud, de la saturación de

oxígeno de la hemoglobina (SaO2) , por cambios en la concentración de hemoglobina (Hb) o

por la llamada hipoxemia arterial inducida por el ejercicio (EIAH) que se podría producir en

humanos tras ejercicio de resistencia de larga duración a alta intensidad. La hipoxia genera

cambios de consumo de oxígeno que pueden ser debidos al transporte del contenido arterial de

oxígeno al músculo, a cambios en el flujo sanguíneo o a ambos. Cuando se realiza ejercicio en

hipoxia el descenso de oxígeno disponible conlleva descensos en los rendimientos y en el

VO2max especialmente pronunciados en esfuerzos de resistencia.

Cuando el IE se realiza en hipoxia parece que los niveles de fatiga periférica podrían

ser menores, como también lo es la potencia alcanzada y el trabajo total llevado a cabo,

indicando que posiblemente sean mecanismos centrales probablemente relacionados con la

oxigenación del cerebro (Rasmussen et al., 2010) los que predominan sobre los mecanismos

locales determinando el cese del esfuerzo (Amann et al., 2007a). Parece que el oxígeno

entregado sería la variable regulada en los procesos más que el flujo sanguíneo per sé (Marsh

& Ellerby, 2006) y se ha sugerido que estaría mediado por el oxígeno unido a la hemoglobina

independientemente de la presión de oxígeno en sangre (Gonzalez-Alonso et al., 2001; Calbet

et al., 2007). Coincidente con esta hipótesis el incrementar instantáneamente el oxígeno

inspirado no cambia los síntomas de fatiga al final de un incremental cuando se realiza en

normoxia y el suministro al final es hiperóxico (Calbet et al., 2003a), pero genera un cambio

instantáneo significativo cuando se trata de un ejercicio realizado en hipoxia severa aguda

normobárica, sea incremental o constante (Kayser et al., 1994; Calbet et al., 2003a, b; Amann

et al., 2007a). Complica un poco las conclusiones el hecho de que la hiperventilación que se

produce cuando la intensidad de ejercicio es elevada en hipoxia (comparada con la de los

mismos valores absolutos en normoxia) podría causar la fatiga del diafragma y la musculatura

respiratoria, lo que a su vez activa aferentes que causarían vasoconstricción sobre el miembro

activo a través de reflejos supraespinales (Dempsey et al., 2006) para desviar parte del flujo

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sanguíneo a los músculos respiratorios, lo que aumentaría la fatiga del miembro ejercitado

(Amann et al., 2007a) como ha sido mostrado dificultando y facilitando el trabajo ventilatorio.

Aunque se ha sugerido que los aumentos de flujo atenuarían los efectos de la fatiga y que la

restricción aumentaría la fatiga por el lavado incompleto de metabolitos, lo cierto es que no

parece ser el factor principal (Hogan et al., 1999; Hepple, 2002). Curiosamente al redirigir flujo

sanguíneo al aparato respiratorio la extracción de oxígeno de los músculos de la pierna no

cambió causando una relación directa entre flujo sanguíneo en las piernas y VO2 max (Harms

et al., 1997). El aumento en consumo de O2 dentro del músculo causa el gradiente de PO2

mientras que aumenta la superficie capilar al aumentar la perfusión aumentando la difusión de

oxígeno al músculo esquelético activo. Esto lleva al límite a la difrencia arterio-venosa (diff a-

vO2). Recientemente se ha mostrado efectos de fatiga en hipoxia independientes del trabajo

ventilatorio y de sus efectos sobre el flujo de la musculatura activa (Amann et al., 2007a).

La medición de fatiga periférica medida con descensos de la contracción potenciada de

cuadriceps (potentiated twitch) confirmó menos fatiga periférica tras ejercicio a intensidad

constante en hipoxia (Amann et al., 2007a). Se asume que cuando la fuerza que produce una

contracción isométrica máxima no aumenta por estimulación eléctrica o magnética sobre

nervio, músculo o corteza motora estaríamos el mecanismos predominante en la fatiga sería

periférico, mientras que en el caso de aumentar se trataría de fatiga central (Goodall et al.,

2010; Rasmussen et al., 2010; Goodall et al., 2012; Fernandez-del-Olmo et al., 2013). Esta

técnica de valoración de la fatiga ha sido cuestionada dado que la fatiga es específica para

cada tarea por lo que los patrones de movimiento utilizados en la medición del fenómeno han

de ser los mismos que lo han provoado para que el reclutamiento utilice vías neurales similares

(Gandevia, 2001). Pero además es necesario obtener un registro de los metabolitos en estas

situaciones para poder comparar fatiga periférica, que además comienza a recuperarse

rápidamente en cuanto se termina la contracción y en el caso de la fosfocreatina es casi

completa para cuando se hacen las mediciones de algunos estudios (Bogdanis et al., 1996;

Dawson et al., 1997; Yoshida et al., 2013). No respetar estos tiempos impide registrar el

impacto de la recuperación temprana (Marcora & Staiano, 2010b; Coelho et al., 2015). Es

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además importante comprobar los descensos de potencia pico porque es posible tener

descensos de contracción potenciada sin descensos en pico de potencia (Fernandez-del-Olmo

et al., 2013; Hureau et al., 2014).

Debido a estas consideraciones entre otras, se han documentado todas las

combinaciones posibles de resultados tras ejercicios dinámicos en normoxia e hipoxia y se han

interpretado como diferentes contribuciones de fatiga central o periférica en un amplio abanico

de posibilidades (Amann et al., 2007b; Sidhu et al., 2009; Goodall et al., 2010; Marcora &

Staiano, 2010a; Millet et al., 2012; Sidhu et al., 2012; Fernandez-del-Olmo et al., 2013).

Además es posible que haya habido diferentes niveles de retroalimentación desde los

aferentes III/IV, dado que no se puede medir su descarga directamente en el ejercicio corporal

dinámico de humanos junto a las dificultades de interpretación que ofrecen los experimentos

con fentanilo al alterara la ventilación y el contenido de O2 y CO2 arteriales, la frecuencia

cardiaca y la presión arterial en función de la intensidad y duración del ejercicio, así como de la

población objeto de estudio (Dempsey et al., 2014; Olson et al., 2014; Poon & Song, 2015). Por

ello, aunque algunos modelos han demostrado que inhibición de las aferencias musculares del

grupo III y IV puede disminuir la fatiga muscular (Sidhu et al., 2014), áun se discute su

contribución real al descenso del rendimiento a través de mecanismos centrales (Millet et al.,

2009; Marcora, 2010; Millet et al., 2012; Kennedy et al., 2015).

Se desconoce si en el momento de máxima fatiga, justo antes del fallo en la tarea, la

activación muscular es menor en hipoxia que en normoxia o hiperoxia lo que podría significar

que la hipoxia esté efectivamente conduciendo a un menor impulso motor desde el sistema

nervioso central y produciendo una menor activación en el músculo. Se cree que este efecto

está predominantemente causado por mecanismos centrales debidos a la sensibilidad a la

disminución del aporte de oxígeno al cerebro (Goodall et al., 2012) o bien a la presión

intersticial de oxígeno en el cerebro (Amann & Calbet, 2008). Pero además el aplicar normoxia

(Calbet et al., 2003a) o hiperoxia (Amann et al., 2007b) en el momento de la extenuación alivia

rápidamente estos síntomas de fatiga permitiendo continuar con la tarea. Sería lógico pensar

Introducción


que si la hipoxia disminuye la activación muscular, un aumento de la oxigenación podría

acompañarse de un aumento de la activación muscular a la misma carga absoluta.

Además es relevante señalar que existe una importante diferencia entre realizar

esfuerzos en hipoxia moderada o severa. A efectos de nuestros estudios resulta importante

porque en hipoxia severa el intercambio de gases ocurre en la región más recta de la curva de

disociación de oxígeno (ODC), lo que conlleva que un pequeño aumento de presión arterial de

oxígeno significa una gran elevación de la saturación arterial de oxígeno (Calbet et al., 2003a;

Calbet & Lundby, 2009) mientras que en hipoxia moderada el efecto es mucho menor. Es

posible que la oxigenación sólo mitigue la fatiga cuando se aplica en hipoxia severa si es

precisa una elevación significativa de contenido arterial de oxígeno. Pero también podría

deberse a que la fatiga sólo se solucione con oxigenación cuando se haya alcanzado un cierto

nivel de hipoxia durante el ejercicio, lo que implicaría que el aumento de PaO2 sería más crítico

que la elevación del contenido de oxígeno.

1.7.Consideraciones metodológicas

Estudios previos usando EMG pueden diferir de los hallazgos que reportamos debido a

la variabilidad intrínseca de la señal de EMG (Taylor & Bronks, 1995; Hug et al., 2004), la cual

aumenta cdurante el ejercicio dinámico, debido a que la amplitud the EMG aumenta con la

velocidad angular en las contracciones concéntricas (Westing et al., 1991).

Para reducir la variabilidad se han utilizado diferentes métodos de normalización,

comparando la señal RMS en el experimento con la recogida en condiciones estandarizadas

reproducibles considerada la referencia. Esto permite la comparación de amplitud de las

activaciones entre sujetos, músculos o momentos distintos (Albertus-Kajee et al., 2010). El

sistema más utilizado ha sido comparar la señal del experimento sea dinámico o estático con la

registrada durante contracciones estáticas máximas (MVC) (Marsh & Martin, 1995; Hug &

Dorel, 2009) pero parecería más apropiado usarlo para condiciones estáticas en ángulos de

movimiento cercanos a los utilizados para la esñal de referencia. Para la amplitud de señal

EMG de movimientos dinámicos se está utilizando señal del movimiento dinámico en

Introducción


condiciones de referencia (Westing et al., 1991; Taylor & Bronks, 1995; Amiridis et al., 1996).

Otro aspecto para reducir la variabilidad es promediar varias repeticiones del experimento

como se ha hecho en los estudios de cinética de O2 (Jones et al., 2012) aunque este

procedimiento no ha sido aplicado a estudios electromiográficos con anterioridad.

Objetivos


Objetivos


2. OBJETIVOS

1) Determinar la influencia de la hipoxia severa aguda sobre la activación muscular

durante ejercicio de intensidad progresiva hasta el agotamiento con grandes grupos

musculares (Estudio I).

2) Determinar si el fallo en la tarea durante un ejercicio incremental hasta el agotamiento

es principalmente debido a mecanismos centrales y modulados por niveles de

oxigenación (Estudio II).

3) Determinar el papel que juega en la disminución de la activación muscular en hipoxia el

nivel de hipoxia (Estudio III).

4) Determinar el aumento mínimo de presión arterial de oxígeno y de contenido arterial de

oxígeno necesarios para aumentar la activación muscular en el músculo fatigado en

hipoxia (Estudio III).

5) Confirmar si el efecto ergogénico de la oxigenación se acompaña siempre de aumento

de activación muscular como indicador de un mecanismo predominantemente central

(Estudio III).

6) Determinar si el aumento en feedback de los aferentes musculares III y IV disminuye el

rendimiento en un ejercicio de sprint reduciendo la activación muscular medida

mediante electromiografía de superficie (Estudio III).

Hipótesis


Hipótesis


3. HIPÓTESIS

1) En un ejercicio incremental hasta el agotamiento en hipoxia severa los sistemas

cardiovascular y respiratorio, así como la activación muscular, alcanzarán menor

activación máxima comparados con los alcanzables en normoxia (Estudio I).

2) A cualquier intensidad relativa la activación muscular en un ejercicio incremental en

hipoxia será menor comparada con la activación obtenida en un ejercicio incremental

realizado en normoxia. (Estudio I).

3) Promediando los valores de dos ejercicios incrementales en la misma condición

disminuirá la variabilidad de la señal EMG. (Estudio I).

4) La fatiga durante un ejercicio incremental en hipoxia severa aguda se producirá con

menor activación muscular que en normoxia (Estudio II).

5) La oxigenación en el momento de fatiga aumenta la activación muscular dependiendo

del nivel de hipoxia al quedar exhausto y de la presión inspiratoria de oxígeno del gas

(Estudio III).

6) El efecto ergogénico de la oxigenación depende de la saturación arterial de oxígeno en

mayor medida que del aumento de presión arterial de oxígeno (Estudio III).

7) El aumento de la retroalimentación por parte de los aferentes musculares del grupo III

y IV disminuirá el rendimiento en el ejercicio de sprint (Estudio III).

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4. RESUMEN DE LOS METÓDOS Y PROCEDIMIENTOS UTILIZADOS

4.1 Sujetos

En este estudio participaron 11 sujetos sanos estudiantes de educación física. Los

valores medios de los parámetros edad, talla, peso corporal y porcentaje de grasa de los

sujetos que participaron en los estudios realizados se describen en la Tabla 1. Todos los

sujetos fueron informados, de forma oral y escrita, acerca de los procedimientos y objetivos del

estudio, así como de los posibles riesgos y beneficios, tras lo cual firmaron la correspondiente

autorización. Además, todos los estudios fueron realizados de acuerdo a la Declaración de

Helsinki y fueron aprobados por el Comité Ético de la Universidad de Las Palmas de Gran

Canaria.

N=11

Media ± DE

Edad (Gaitanos et al.) 21.5 ± 2.0

Talla (Jones et al.) 174 ± 8

Peso (Kg) 72.3 ± 9.3

Grasa Corporal (%) 16.1 ± 4.9

Tabla 1. Características de los sujetos experimentales que participaron en los estudios que

componen esta Tesis Doctoral.

4.1.1 Antropometría.

La talla se midió en bipedestación con los talones, los glúteos la espalda y la región

occipital en contacto con el plano del tallímetro. Estas medidas se efectuaron mediante un

tallímetro de 1mm de precisión (Atlántida, Añó Sayol, Barcelona, España), manteniendo la

cabeza en el plano de Francfort. La masa corporal se midió mediante una báscula (Atlántida,

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Añó Sayol, Barcelona, España) de 50 g de precisión, calibrada a 50.0, 70.0 ó 90.0 Kg,

mediante masas patrón de la clase M1.

4.1.2 Masa muscular, masa ósea y porcentaje de masa grasa.

La masa magra (masa corporal – [masa grasa + masa ósea]) se determinó mediante

absorciometría fotónica dual de rayos X (DXA) (QDR-1500, Hologic Corp., Software versión

7.10, Waltham, MA). Los sujetos fueron escaneados tumbados en posición supina junto a una

barra de calibración de diferentes grosores y densidades. A partir del análisis regional y de

cuerpo entero se calculó la masa magra (g), la masa grasa (g), el área ósea total (cm2) y el

contenido mineral óseo (BMC) (g), tal como se ha hecho en trabajos previos de nuestro

laboratorio (Ara et al., 2004; Ara et al., 2006).

4.2 Aspectos generales

Estos estudios formaron parte de un proyecto mayor que incluyó varios experimentos

diseñados para estudiar los mecanismos limitantes de la capacidad de ejercicio en humanos.

Los resultados que se enfocaban al transporte de oxígeno y el metabolismo muscular han sido

publicados recientemente (Calbet et al., 2015; Morales-Alamo et al., 2015c).

Inicialmente realizaron varias visitas al laboratorio en un proceso de familiarización. El

primer día se les realizaron las mediciones antropométricas y las medidas de composición

corporal. El proceso de familiarización de los sujetos con los procedimientos incluyó ejercicios

incrementales hasta el agotamiento en normoxia e hipoxia (FiO2= 0.21 y 0.104, presión

barométrica 735-745mmHg) para detectar su consumo de oxígeno máximo (VO2max), su

frecuencia cardiaca máxima (HRmax) y su potencia máxima (Wmax). Una semana después se

familiarizaron con el test de Wingate isocinético a 80rpm. A partir de entonces se realizaron

diferentes pruebas en días separados para llevar a cabo los experimentos.

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Figura 1. Estudio I. Invasivos

Estudio I. Invasivos

Estudio Ia. Invasivo Incremental

Los sujetos participaron en un estudio invasivo que incluía ejercicio incremental hasta

el agotamiento en cicloergómetro (Excalibur Sport 925900, Lode) en normoxia (PIO2 ~143

mmHg) e hipoxia severa aguda (PIO2 ~73 mmHg) en orden aleatorio. Se midieron

hemodinámicas central y local, transporte de oxígeno e intercambio pulmonar de gases y

muscular. El consumo de oxígeno se midió con un ergoespirómetro (Vmax N29 Sensormedics)

calibrado antes de cada test con gases de calibración (Carburos Metálicos, Las Palmas de

Gran Canaria) y se recogieron respiración a respiración. Las respiraciones fueron promediadas

cada 20 segundos para determinar el consumo de oxígeno.

Se cateterizó a los sujetos previa anestesia local (lidocaína 2%) en ambas venas

femorales y una arteria femoral (Calbet et al., 2006). Se inyectó solución salina helada para

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medir el flujo sanguíneo de la pierna por termodilución (Andersen & Saltin, 1985). También se

midió la temperatura de la sangre en la vena femoral, y se midió la presión arterial y la

temperatura en la sangre arterial. Se obtuvieron muestras sanguíneas periódicas de sangre

arterial y venosa antes de finalizar cada escalón de carga y al final de la prueba. Los gases

sanguíneos fueron inmediatamente analizados en un analizador de gases (ABL90 Radiometer).

Durante toda la prueba se registro un electrocardiograma (ECG). Todos los datos fueron

recogidos en un sistema de captación y procesamiento de señales (Powerlab ML880 de

ADInstruments) a 200Hz y guardados para el análisis posterior. Para más detalles puede

consultarse el artículo donde se exponen en detalle estos experimentos (Calbet et al., 2015).

Estudio Ib. Invasivo Sprint

Se llevaron a cabo dos sprints máximos de 30 segundos ( Wingate) isocinéticos a

80rpm utilizando servocontrol con ajuste instantáneo (Excalibur Sport 925900). Uno de ellos se

llevó a cabo en normoxia y otro en hipoxia, en orden aleatorio y con las mismas presiones

inspiratorias que en los test incrementales. Antes de cada test de Wingate sólo calentaron

realizando 3 minutos de pedaleo sin carga. Entre ellos los ejercicios de sprint descansaron

unos 90 minutos. Durante los sprints se midió el gasto cardiaco y el flujo sanguíneo de la pierna

junto con la diferencia arteriovenosa de oxígeno para determinar el consumo de oxígeno de la

pierna. También se recogió el consumo de oxígeno respiración a respiración (Vmax N29,

Sensormedics), que fue posteriormente promediado cada 5 segundos de sprint. Las muestras

sanguíneas se recogieron de arteria y vena femorales simultáneamente antes de cada sprint y

durante el ejercicio cada 5 segundos de sprint en el caso de la vena y cada 10 segundos en el

caso de la arteria. Las muestras se colocaban en hielo y eran analizadas en el mismo orden en

que se obtuvieron utilizando el mismo analizador de gases que en los incrementales. De ellas

se obtuvo concentración de hemoglobina y saturación de gases.

Durante el sprint se midió el flujo de la pierna por termodilución.

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Estudio II. Oclusión

Fig2. Estudio II Oclusión

El procedimiento experimental del estudio llamado Oclusión se resume en la figura 3.

Los voluntarios llegaron en ayunas en una primera visita al laboratorio y se les

determinó la composición corporal utilizando absorciometría fotónica dual de rayos-x (DEXA)

(Hologic QDR-1500, Hologic Corp., software versión 7.10, Waltham, MA) (Calbet et al., 1997) y

se calculó la masa muscular de la pierna utilizando el modelo de Wang (Wang et al., 1999).

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Figura 3. Estudio II. Oclusión

En los días de experimento los sujetos llegaron al laboratorio a las 8:00 tras ayuno

desde las 22:00h. Se les colocaron manguitos de inflado en los muslos conectados a un

inflador rápido (SCD10, Hokanson E20 AG101, Bellevue, USA). Los sujetos llevaron a cabo un

calentamiento en cicloergómetro (2 minutos a 50W, 2 min a 100W y 1 min a 160W) y después

4.5 min de pedaleo sin carga. A continuación descansaron inmóviles durante 30 s antes de

realizar un sprint máximo de 10 s de duración en un cicloergómetro en modo isocinético a 80

rpm que utilizamos como sprint control (Excalibur Sport 925900, Lode, Groningen, The

Netherlands). El servo-control del cicloergómetro varió instantáneamente la resistencia aplicada

a los pedales en función de la fuerza ejercida lo que causa un pedaleo constante de 80rpm.

Cinco minutos después iniciaron dos ejercicios incrementales en cicloergómetro en normoxia

(PIO2: ~143 mmHg) e hipoxia (PIO2: ~73 mmHg, Altitrainer200, SMTEC, Switzerland) separados

por 120 min, efectuados en orden aleatorio. El test en normoxia se inició a 80W y aumentando

las cargas en 30W cada 2 minutos hasta la extenuación. El test en hipoxia se inició con 60W y

la carga se incrementó en 20W cada 2 minutos. Se consideró que el sujeto estaba exhausto

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cuando a pesar de fuerte apoyo verbal fue incapaz de mantener una frecuencia de pedaleo

superior a 50 rpm durante 5 s o incluso se detuvo.

Inmediatamente de la interrupción del esfuerzo (con el sujeto agotado) se inflaron los

manguitos con velocidad y presión máximas (300mmHg) ocluyendo completa e

instantáneamente la circulación (isquemia). En apenas 3 a 5 s se produjo anoxia dentro del

miembro como se constata en una de las publicaciones ya mencionadas (Morales-Alamo et al.,

2015c). Se emplearon dos duraciones distintas de 10 y 60 s de descanso mientras la

circulación sanguínea permanecía ocluida. Las duraciones de la oclusión fueron aplicadas de

forma aleatoria.

Al final del período de oclusión se desinflaron los manguitos reinstaurándose

instantáneamente el flujo sanguíneo al inicio del sprint post-isquemia. Se registró la potencia

durante los sprints y el test incremental, determinándose la potencia instantánea y la media. El

intercambio de gases se midió con un equipo (Vmax N29; Sensormedics, Yorba Linda,

California, USA) calibrado previamente antes de cada test siguiendo las instrucciones del

fabricante usando gases para la calibración (Carburos Metálicos, Las Palmas de Gran

Canaria). Se analizaron las variables respiratorias respiración a respiración y se promediaron

cada 20s durante los test incrementales, utilizando el valor más alto de estos promedios como

VO2max.

Las variables respiratorias y electromiográficas se midieron del mismo modo que en el

estudio II.

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Página 54 Rafael Sánchez de Torres-Peralta

Todas las variables se comportaron de manera similar en los cuatro sprints de control

(uno antes de cada incremental) por lo que para disminuir la variabilidad se promediaron los

valores. También para reducir variabilidad se promediaron los valores de EMG de vastus

medialis y lateralis, aunque también se presentan los valores por separado también. Puesto

que los test incrementales en hipoxia y normoxia fueron repetidos en dos ocasiones, se

generaron promedios representativos de hipoxia y normoxia, respectivamente.

Figura 4. Señal EMG de los experimentos de oclusión.

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Estudio II. Biopsias

Figura 5. Estudio II. Biopsias

Unas semanas más tarde se realizaron los experimentos denominados Biopsias. Para

ello se emplearon dos sesiones experimentales, llamadas respectivamente Nxb (PIO2: ~143

mmHg) y Hypb (PIO2: ~73 mmHg), realizadas en orden aleatorio. Las sesiones comenzaron

con 10 minutos de descanso en decúbito supino y a continuación se les realizó una biopsia

con anestesia local (lidocaína al 2%, 2ml) del vasto lateral. Se llevó a cabo teniendo en cuenta

que la aguja apuntara distalmente a 45º de inclinación (Guerra et al., 2011) y usando la técnica

Bergstrom con succión (Bergstrom, 1962). Antes de iniciar el ejercicio también se llevó a cabo

una incisión en la pierna contralateral y se le colocó un manguito en la pierna izquierda.

Durante el ejercicio ambas incisiones fueron cubiertas con plástico transparente. Una vez los

sujetos estuvieron sentados en el cicloergómetro se les realizaron las mediciones de reposo.

Dos minutos después se inició el ejercicio incremental en normoxia o tras cinco minutos de

exposición a la hipoxia, para los ejercicios en hipoxia. Cuando el sujeto alcanzó el final del test

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de esfuerzo (extenuación) se infló el manguito instantáneamente (300mmHg) y se tomó una

biopsia perpendicular al muslo a los 10 s del final del test incremental. Por último 60 s después

del final del incremental se obtuvo una última biopsia con la punta apuntando proximalmente a

45º de inclinación.

Todas las biopsias fueron inmediatamente congeladas en nitrógeno líquido y

guardadas a -80ºC. Se registró la potencia durante los ejercicios a través de la potencia

instantánea y la media proporcionada por el cicloergómetro. El resto de técnicas comunes

fueron las mismas que en el estudio I. Para más detalles consultar la sección de material y

métodos del Estudio II anexado.

Los metabolitos musculares se obtuvieron mediante el análisis de 30mg de tejido

húmedo de cada biopsia, liofilizado, limpiado y pulverizado refrigerado en hielo con un mortero

manual. A continuación las muestras se suspendieron en 0.5 M HClO4 y se centrifugaron a

15000g a 4ºC durante 15 minutos. El sobrenadante se neutralizó con KHCO2 2.1 M y se

determinaron las concentraciones de ATP, PCr, creatina, piruvato y lactato enzimáticamente en

extracto neutralizado usando análisis fluorométrico (Lowry & Passonneau, 1972; Morales-

Alamo et al., 2013).

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Estudio III. Ejercicio incremental

Figura 6. Ejercicio incremental

Unas semanas más tarde los sujetos realizaron cuatro test incrementales en dos días

distintos separados por al menos una semana. Entre cada test descansaron 90 minutos. Cada

test se compuso de una fase inicial incremental (20-30W cada 2 minutos, a 80rpm) en hipoxia

severa (PIO2 73-74mmHg), similar a la de los test invasivos, que llevan hasta el agotamiento

(Exh 1). En este momento se les suministró una mezcla de gases con la misma o menor

hipoxia y se les animó a continuar el ejercicio incremental con el mismo ritmo hasta llegar al

agotamiento de nuevo (Exh 2). Cuando no pudieron continuar con el esfuerzo, se les cambió a

respirar aire ambiental y se les animó de nuevo a continuar con el esfuerzo hasta llegar al

agotamiento final en normoxia (Exh 3). Las mezclas de gases que se les suministraron en Exh1

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incluyeron una PIO2 de 73-74mmHg que consideramos un placebo, y en sucesivas ocasiones

aleatoriamente PIO2 de 82, 92 y 99 mmHg con un diseño de doble ciego.

Las variables respiratorias se midieron del mismo modo que en el estudio III añadiendo

un pulsoxímetro (OEM III module, 4549-000) para estimar la saturación de oxígeno de la

hemoglobina utilizando una ecuación derivada del test invasivo (SaO2 = (1.004xSpO2) - 0.4543.

Fig7. Fijación de los electrodos en la pierna.

Se monitorizó la activación muscular usando electromiografía de superficie (EMG)

continuamente registrada en ambos vastos, medialis y lateralis, rectus femoris y bíceps femoris

durante todos los test. En el primer artículo se comunican también resultados del rectus femoris

y el bíceps femoris, Debido a su mayor variabilidad y dificultad de análisis y a que alargan

además los resultados innecesariamente se omitieron en el segundo artículo. Antes de aplicar

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los electrodos de EMG se afeitó y limpió con alcohol la piel para reducir la impedancia cutánea.

Se aplicaron electrodos bipolares rectangulares (DE-2.3 Delsys Inc.) longitudinalmente en los

músculos siguiendo las recomendaciones SENIAM (Merletti & Hermens, 2000), se marcó la

posición utilizando tinta quirúrgica para mantener el posicionamiento en los experimentos

repetidos y se utilizó cinta adhesiva de uso médico para fijarlos y evitar artefactos de

movimiento mientras se evitó una irritación de la piel o sudoración excesiva. Se adquirió la

señal con una frecuencia de muestreo de 1000 Hz. La señal se filtró usando filtros Butterworth

de quinto orden permitiendo señales desde 20 a 450Hz. Cada pedalada fue considerada

separadamente en su análisis utilizando para detectarlas un electrogoniómetro (Goniometer

Biosignal Sensor S700 Joint Angle Shape Sensor; Delsys Inc. Boston) fijado a la rodilla

izquierda y recogiendo datos a 500Hz simultáneamente. Todos las señales de EMG y

goniometría fueron captadas mediante un equipo de electromiografía (Myomonitor IV, Delsys

Inc., Boston, MA) y transmitidas telemétricamente a un ordenador (EMGWorks Wireless

application and EMGWorks Acquisition 3.7.1.3; Delsys, Inc. Boston).

Para el análisis de la señal se programaron rutinas específicas para nuestros

experimentos en Matlab (Matlab R2012b, MathWorks, Natick, MA, USA), que permitieron

rectificar la señal, suavizarla usando una ventana móvil de 25 ms y cortarla seleccionando el

20% de la señal máxima EMGRMS de cada movimiento (Baum & Li, 2003; Hug & Dorel, 2009;

Torres-Peralta et al., 2014) en lugar de un umbral medio de 15 movimientos seguidos

(Ozgunen et al., 2010) permitiéndonos el reconocimiento automático del 100% de los

movimientos, contrastado con análisis visual durante toda la prueba incremental y el sprint.

Todas las variables se reportan para el primer artículo como los valores medios de las

pedaladas recogidas durante el último minuto de cada escalón en el incremental y un minuto o

la parte disponible de la última carga si no alcanzara esta duración. En el segundo artículo se

reportan los últimos 10s de ejercicio incremental y los 10s de sprint. En el tercer artículos se

emplearon los 30 últimos segundos del ejercicio incremental en hipoxia severa, los 30 s

siguiente a una nueva PIO2, los 30 s últimos segundos justo antes del final del segundo

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segmento del test incremental, los 30 s siguientes en normoxia y los 30s últimos segundo del

test en normoxia.

La normalización se realizó respecto al último minuto de la carga de 2 min de 80W

durante la prueba de normoxia. Definimos un índice de actividad muscular total durante el

sprint (TAI) como el valor que arroja la media de valores de amplitud de EMGRMS promediado

durante la contracción x la duración de la contracción muscular x número de pedaladas durante

el sprint. Es similar a la señal integrada de EMG pero se computa separadamente para cada

contracción muscular (burst) y excluye los valores de línea base de EMG entre contracciones

(Ozgunen et al., 2010). Usamos los valores del último minuto de la carga de 80W en normoxia

para normalizar la señal.

La frecuencia media (Xie & Hampf, 1994) y la frecuencia mediana (MdPF) del espectro

se calcularon con una transformación rápida de Fourier (Solomonow et al., 1990).

Figura 8. Saco de anestesia

Resumen de Métodos


4.3 Análisis estadístico.

Se comprobó la distribución normal de las variables con el test Shapiro-Wilks. Para

analizar las respuestas observadas durante los sprints se utilizó una ANOVA de medidas

repetidas con las condiciones de FIO2 (normoxia frente hipoxia) y la duración de la oclusión (10

s frente 60 s). El contraste entre valores en puntos específicos se hicieron usando la prueba T

de Student y las comparaciones por parejas fueron ajustadas para evitar la propagación del

error debido a las comparaciones múltiples usando el método de Holm-Bonferroni. El impacto

de la frecuencia de pedaleo sobre la duración de las contracciones se analizó mediante análisis

de la covarianza (ANCOVA) de medidas repetidas, utilizando la frecuencia de pedaleo como

covariable. Los datos cuantitativos están expresados como media ± desviación estándar (SD).

Se consideraron significativos los resultados con una probabilidad de ser debidos al azar igual

o inferior al 5% (P ≤ 0.05). El análisis estadístico se realizó mediante la versión 15.0 del

programa informático SPSS (SPSS, Chicago, IL).

Resumen de Resultados




5. RESUMEN DE RESULTADOS

En el siguiente apartado se resumen los resultados más relevantes de cada estudio

pero la descripción detallada de los resultados se encuentra en las publicaciones anexas que

forman parte de esta tesis doctoral.

5.1 Resumen de resultados artículo I.

Rafael Torres-Peralta, José Losa-Reyna, Miriam González-Izal, Ismael Perez-Suarez, Jaime Calle-Herrero, Mikel Izquierdo and José A.L. Calbet. Muscle activation during exercise in severe acute hypoxia: role of absolute and relative intensity. HAMB 2014. Los resultados de potencia fueron similares en los dos test realizados en hipoxia (184 ±

23 W y 182 ± 34 W p=0.72) y lo mismo sucedió con los realizados en normoxia (284 ± 30 W y

278 ± 34 W P=0.34). Los test en normoxia fueron ligeramente más largos que los de hipoxia

(850 ± 109 s y 747 ± 84 s P<0.05) pero sin diferencias significativas en la relación entre

consumo de oxígeno y potencia generada (VO2/potencia). La frecuencia de pedaleo se

mantuvo en 80 rpm hasta llegar al 86% del VO2max cuando se redujeron hasta las 70rpm

durante el último minuto en ambas condiciones a pesar del fuerte estímulo verbal, siendo

ligeramente menores en hipoxia que en normoxia (P<0.05) a la misma intensidad absoluta pero

sin diferencias a la misma intensidad relativa. Al final de los test en hipoxia el VO2pico fue un

34% menor que el de los test incrementales en normoxia. A misma potencia generada (valores

absolutos), la ventilación pulmonar (VE), la frecuencia cardiaca (HR) y la tasa de intercambio

respiratorio (RER) fueron mayores en hipoxia que en normoxia, mientras que en las mismas

condiciones la PETO2 y la PETCO2 fueron menores en hipoxia.

La amplitud aumentó con la intensidad de ejercicio en todos los músculos examinados

(RMS y TAI) especialmente en el rectus femoris (Sogaard et al.), a una velocidad mayor en

hipoxia que en normoxia en RF y vastus medialis (VM). Sin embargo, no hubo influencia de la

FIO2 aire sobre el bíceps femoris (BF). A pesar de ello, a la misma intensidad relativa la



amplitud de señal (EMGRMS y TAI) fue mayor en normoxia que en hipoxia para todos los

músculos, aunque en el vasto medial fue similar.

La frecuencia mediana (MdPF) aumentó significativamente con la intensidad del

ejercicio en ambos vastos pero no fue significativa en RF y BF. A una misma intensidad

absoluta la frecuencia mediana del VL era mayor en hipoxia pero no se vio ningún efecto

significativo de la FIO2 sobre la mediana de frecuencias en los demás músculos, ni diferencias

cuando se comparan las mismas intensidades relativas. Las medias de frecuencia (Xie &

Hampf) fueron similares.

La duración de las contracciones musculares aumentaron con la intensidad del ejercicio

sólo en los vastos (p<0.05) a pesar de tener en cuenta el efecto de pequeños cambios en la

frecuencia de pedaleo, pero lo hicieron de manera independiente de la proporción de oxígeno

en el aire inspirado.



5.2 Resumen de resultados artículo II.

Task failure during exercise to exhaustion in normoxia and hypoxia is due to reduced muscle activation caused by central mechanisms while muscle metaboreflex does limit performance. Rafael Torres-Peralta, David Morales-Alamo, Miriam Gonzalez-Izal, Jose Antonio L Calbet, Jose Losa Reyna, Ismael Perez Suarez, Mikel Izquierdo. (under review).

Los últimos diez segundos de ejercicio incremental en hipoxia muestran una

disminución de las variables respiratorias como ventilación pulmonar, frecuencia respiratoria,

pico de consumo de O2, así como de frecuencia cardiaca y de la potencia máxima alcanzada,

comparadas con los valores en normoxia determinados en este estudio II. El rendimiento en el

ejercicio de sprint, es menor tras un incremental, como ya se ha reportado antes (Morales-

Alamo et al., 2015b), en un (32-46% P ≤ 0.05). La potencia pico y la potencia de un sprint

fueron ~11% menores tras un incremental en normoxia comparado con el sprint tras un

incremental en hipoxia (P ≤ 0.05). El rendimiento en el sprint aumentó con la recuperación

isquémica. Tras 60 segundos de isquemia la potencia pico y potencia media fueron un 11 y

23% mayores que las observadas cuando el sprint se realizó a los 10 s (P ≤ 0.05) (Morales-

Alamo et al., 2015b).

Durante los test incrementales el pH, ATP, y PCr se redujeron en la misma proporción,

independientemente de la oxigenación (ANOVA de efecto tiempo: P ≤ 0.05). Se mantuvieron al

menos igual de bajos desde los 10 a los 60 segundos de isquemia. A la inversa el lactato

aumentó igualmente en ambas condiciones y siguió acumulándose durante la isquemia.

La respuesta de la señal EMG de los dos vastos fue similar y se combinaron ambos

para reducir la variabilidad. La amplitud registrada en los últimos 10 segundos de prueba fue

menor ambos vastos en hipoxia, comparada con la observada en el test incremental en

normoxia. La RMS fue un 16% menor y el TAI normalizado un 23% (P ≤ 0.05).

Comparados con los sprint control la amplitud durante los sprints tras el incremental se

redujo en un 36% (RMS) y un 35% (RMSNz) y el TAINz se redujo un 42% tras el test

incremental en normoxia y un 34% tras el test incremental en hipoxia. Durante los sprints post-

incremental la amplitud de señal RMS, RNSNz y TAINz fue aún 1.6, 1.7 y 2.9 veces mayor que

la recogida durante los 10 s finales de los incremental anteriores (P ≤ 0.05). También la



mediana de frecuencia (MdPF) se redujo, un 18% tras normoxia y un 9% tras hipoxia (ambos P

≤ 0.05), siendo por tanto un 9% menor tras normoxia. La frecuencia media (Xie & Hampf) tuvo

un compartimento similar.

Tras 60s de reposo isquémico la RMSNz comparada con la de 10s de oclusión tendió a ser un

14% menor (P=0.059). También se redujo un 9% la duración de los burst tras la oclusión de 10

s comparados con el sprint control, pero se recuperó tras 60 s de oclusión. La duración de los

burst fue un 3% más larga en sprint tras hipoxia que tras normoxia.



5.3 Resumen de resultados artículo III (Rafael Torres-Peralta et al, Submitted).

Oxygenation at fatigue in hypoxia increases muscle activation and relieves fatigue: influence of PIO2. Rafael Torres-Peralta, Jose Losa Reyna, David Morales-Alamo, Miriam Gonzalez-Izal, Ismael Perez Suarez, Mikel Izquierdo, Jose Antonio L Calbet. (Submitted).

Los últimos treinta segundos de ejercicio incremental en hipoxia se caracterizaron por

una menor potencia máxima (Wmax), un menor consumo de oxígeno (VO2peak), una menor

ventilación (VEpeak), frecuencia respiratoria (RR), frecuencia cardiaca (HRpeak), saturación de

la oxígeno de la hemoglobina (SpO2), así como de las presiones parciales de oxígeno y dióxido

de carbono al final de la espiración (PETO2, PETCO2), que en normoxia (ver tabla 1, en el

artículo incorporado en el anexo). No obstante, la tasa de intercambio respiratorio (RER) fue

mayor en hipoxia (todos P≤0.05).

La activación muscular medida como RMS en bruto, RMSNz y TAI de los vastos lateral

y medial fue de un 8 a 20% menor en hipoxia que en normoxia. La MPF fue un 5% menor en

normoxia que en hipoxia, mientras que el comportamiento fue similar para la MdPF.

Cuando se administra un gas más oxigenado se pudo continuar el ejercicio en todos los

casos. Comparados con los valores obtenidos en los últimos 30 s de hipoxia, en los primeros

30 s de la nueva oxigenación siempre aumentaron los consumos de oxígeno y la PETO2, a la

vez que disminuyó la RER. Cuando se aumentó la SpO2 desde 68 hasta 70 o 78%

correspondiente a 92 o 99mmHg la activación RMS, RMSNz, TAINz aumentó un 8%, y cuando

se aumentó a 82 mmHg aumentó un 6% (SpO2 de 63 a 67%). Sin embargo la MPF y la MdPF

no cambiaron. Hicimos un análisis de 10 s obviando los 5s posteriores al cambio de gas

inspirado para confirmar estos cambios y así fue.

No hubo efecto del paso a normoxia (143 mmHg) desde 92 y 99mmHg. Sin embargo,

aumentó de un 5 a 9% la activación desde 82 a 143 mmHg y la de las dos condiciones más

hipóxicas combinadas, aunque no lo hizo el TAI. Tampoco en este caso se modificaron las

MPF o MdPF.

No hubo cambios de activación al pasar al placebo, aunque mantuvieron el esfuerzo

brevemente.



Las duraciones de las contracciones (bursts) se redujeron al aumentar la cadencia con

el aumento de la PIO2.

Discusión


DISCUSIÓN GENERAL

Se han presentado datos confirmando que la activación muscular aumenta casi

linealmente con la intensidad del ejercicio. Los datos confirman que esta activación muscular

está modulada por la fracción inspiratoria de O2, pero que esta influencia es específica para

ciertos grupos musculares durante el ejercicio en cicloergómetro. Pueden darse diferentes

comportamientos en distintos músculos debido a un cambio de patrones de activación de

origen central (Amann et al., 2007b; Millet et al., 2012), una modulación de la activación de

origen corticoespinal (Gerdle & Fugl-Meyer, 1992), diferentes respuestas metabólicas a la

hipoxia (Parolin et al., 2000) o diferencias en el tipo de fibras y la vascularización de los

músculos (Moritani et al., 1992). En roedores se ha demostrado una respuesta metabólica a la

hipoxia específica de cada región en función del tipo de fibra predominante y el grado de

capilarización (Wust et al., 2009).

Este efecto de la fracción inspiratoria de oxígeno se muestra con una activación mayor

en hipoxia de los extensores de la rodilla a una misma carga absoluta si la comparamos con

normoxia. Consecuentemente esta mayor activación resulta en una mayor amplitud de la señal

EMG. Posiblemente durante la mayor actividad de las motoneuronas se cause una demanda

metabólica superior que, en el caso de aporte de oxígeno al cerebro limitado, como puede

ocurrir en un ejercicio incremental en hipoxia aguda, puede aumentar la glicolisis, la liberación

de lactato por el cerebro y alterar el metabolismo neuronal (Rasmussen et al., 2010; Overgaard

et al., 2012). El aumento de la actividad de EMG a cargas submáximas podría reflejar un

reclutamiento más de unidades motoras para compensar la fatiga de las unidades motoras que

han estado más activas (Moritani et al., 1992). Esta mayor activación puede depender del

grado de hipoxia durante ejercicio dinámico con grandes masas musculares (whole-body

exercise), dado que experimentos realizados con mayores fracciones inspiratorias que las

usadas en este experimento no han encontrado diferencias (Amann et al., 2007b). Lo mismo ha

sucedido en el caso de tratarse de pequeños grupos musculares donde, de darse impacto de la

hipoxia sobre la activación muscular, sería de menor entidad y no ha sido encontrada (Goodall

Discusión


et al., 2010; Millet et al., 2012; Donnelly & Green, 2013). Dado que, de tratarse de un efecto de

la oxigenación sobre el cerebro, sabemos que durante ejercicio con grupos musculares

pequeños se perturba menos el intercambio gaseoso pulmonar, por lo que parece razonable

que la oxigenación del cerebro se vea menos alterada (Amann & Calbet, 2008; Calbet &

Lundby, 2009; Calbet et al., 2009) y los efectos sobre metabolismo del músculo y la capacidad

de ejercicio son menores (Roach et al., 1999) o sólo se observan en hipoxia severa (Goodall et

al., 2010).

Cuando analizamos la mayor activación en hipoxia comparada con normoxia en

nuestro modelo de manera relativa vemos que la activación es menor en hipoxia comparada

con normoxia en todas las cargas relativas similares, desde el inicio hasta el máximo del

ejercicio incremental donde se manifiesta una finalización prematura del ejercicio al no alcanzar

los mismos valores de activación o potencia que en normoxia. La duración de las contracciones

aumenta don la intensidad del ejercicio para los vastos, músculos responsables de generar

gran parte de la fuerza de la extensión de rodilla, independientemente de la oxigenación que se

reciba durante el incremental. Paralelamente la MPF y la MdPF se incrementan con la

intensidad del esfuerzo (Peltonen et al., 1997) sin diferencias entre ambas oxigenaciones. Se

ha propuesto que las estrategias de reclutamiento motor podrían ser determinadas

indirectamente a través de la MPF y la MdPF (Solomonow et al., 1990; Sbriccoli et al., 2003). El

hecho de tener que reducir la cadencia de pedaleo al alcanzar los 140 a 160W en hipoxia

confirma un patrón de activación muscular alterado. Se sabe que este aspecto puede aumentar

la señal EMG en algunos músculos (Marsh & Martin, 1995; Neptune et al., 1997; Sarre et al.,

2003; Bieuzen et al., 2007). Al aumentar la cadencia de pedaleo por encima de 60 rpm podría

aumentar la intensidad relativa del ejercicio (aunque la intensidad absoluta no cambie)

(Chavarren & Calbet, 1999). Por ello, al menos una parte de ese incremento en EMG que se

produce con cadencias mayores se debe probablemente al aumento en intensidad relativa.

Pero en este caso aún habiendo descendido la cadencia en hipoxia ha seguido siendo superior

a la que se produce en normoxia para la misma carga absoluta. Dado que la frecuencia de

pedaleo disminuyó en ambas condiciones de oxigenación al alcanzar el 86% de su VO2max,

Discusión


parece claro que sería la intensidad relativa y no las pequeñas diferencias en la cadencia de

pedaleo la que dicta la estrategia de activación motora.

Parecería que la fatiga supraespinal, entendida como una disminución en la fuerza

debida a un impulso nervioso inferior al óptimo desde la corteza motora (Gandevia, 2001),

podría estar relacionada con una oxigenación del cerebro reducida en hipoxia severa aguda

causando inhibición corticospinal de la activación central.

Nuestro estudio II confirma que la imposibilidad de continuar un ejercicio incremental

en normoxia no está causado por fatiga muscular, como ya se había propuesto en estudios

anteriores de ejercicio incremental (Coelho et al., 2015) y de intensidad constante (Marcora &

Staiano, 2010a). Se extienden estos hallazgos también a los ejercicios incrementales en

hipoxia aguda severa. Al haber realizado registro de la ergoespirometría incluyendo HR

tenemos más información sobre el sistema respiratorio en estas condiciones y sabemos que la

ventilación y la frecuencia respiratoria así como la frecuencia cardiaca fueron menores durante

los últimos 10 segundos de un incremental en condiciones de hipoxia severa comparado con

un incremental en normoxia. Pero simultáneamente mostramos que la activación muscular

durante los últimos 10 segundos de un incremental en condiciones de hipoxia severa es menor

que la obtenida en un incremental en normoxia. Es una diferencia que no puede explicarse de

acuerdo a la acumulación de metabolitos. Sabemos que la percepción del esfuerzo por parte

del sujeto es máxima, pero sin embargo la potencia generada es mucho menor en hipoxia que

en normoxia y sin embargo no refleja un agotamiento de reservas energéticas de las fibras que

tienen que realizar esta actividad, puesto que son capaces de realizar una activación y una

potencia mucho mayor durante un sprint 10 s, que la potencia desarrollada en el momento de

la extenuación durante el ejercicio incremental. Esto probablemente refleje un mecanismo

central de fatiga que se habrá recuperado al menos parcialmente durante la isquemia de los

miembros inferiores en los siguientes 10 s o 60 s antes del sprint. La oclusión durante estos

periodos de reposo provocó un aumento de las señales aferentes de las terminaciones

nerviosas del grupo III/IV musculares al exacerbar la fatiga periférica. En caso de ser un

problema de disponibilidad de energía del músculo o de acumulación de metabolitos, el

Discusión


descenso de reservas y la mayor acumulación de metabolitos hubieran debido causar un

descenso aún mayor de la activación y la potencia generadas. Al realizar los sprints tras tan

solo 10 s de reposo y compararlos con las recuperaciones tras 60 s tenemos información sobre

recuperación central temprana.

Hemos demostrado que la fatiga muscular, medida a través del rendimiento en un

ejercicio de sprint al final de un ejercicio incremental, resulta ser menor tras un incremental en

cicloergómetro en hipoxia severa aguda de lo que resulta en el caso de realizarlo en normoxia,

a pesar de que la acumulación de metabolitos fue similar en ambos casos. Esto es compatible

con el predominio de un mecanismo central de fatiga. Al emplear sprints isocinéticos se han

evitado las diferencias de potencia que se generan con distintas cadencias de pedaleo, que en

cualquier caso son menores en sujetos fatigados, en los que a 80 rpm se puede alcanzar el

pico máximo de potencia (Beelen & Sargeant, 1991). Esta reducción en el rendimiento en sprint

conlleva aparejada una disminución de la activación muscular que monitorizamos con EMG. Al

haber medido la activación muscular con EMG ha sido posible detectar cambios de activación

neural. El usar como test de potencia sprints nos ha permitido emplear un test específico de

las tareas desarrolladas durante el test incremental.

La disminución de la activación muscular tras el esfuerzo incremental (más notoria en

normoxia que en hipoxia) podría significar la presencia de una recuperación más lenta de la

fatiga central tras el incremental en normoxia, donde no hay cambio de oxigenación en la

extenuación que pudiera tener un efecto ergogénico; o bien podría tratarse de que se haya

producido una mayor activación de las rutas de utilización de oxígeno en la hipoxia que

permitiera una mayor recuperación central en el mismo tiempo de descanso al normalizar la

oxigenación.

Curiosamente cuando el descanso se produce con los miembros en isquemia pero se

alarga en su duración, el rendimiento de sprint aumentó en ambas condiciones (Morales-Alamo

et al., 2015b). Este hallazgo no es compatible con un gran impacto de las aferentes musculares

del grupo III/IV sobre el rendimiento de sprint. Curiosamente se realizó un aumento de

rendimiento con menor activación EMGRMS que la recogida en los sprints tras 10 segundos de

Discusión


isquemia, lo que demuestra una disociación entre la recuperación de señal EMGRMS y la

recuperación del pico de potencia. Dada esta disociación cuando la potencia se ha recuperado

relativamente no parece razonable creer que una menor EMGRMS tras 60 segundos de

isquemia refleje realmente un fallo de las fibras musculares para responder a la activación

neural.

Al realizar biopsias y medir los metabolitos se puede conocer el estado metabólico de

los músculos. En nuestros experimentos se produjo acumulación de lactato y H+ tras 60

segundos de oclusión. Puesto que la señal EMGRMS fue menor, pero la potencia mayor, tras

60 s de recuperación isquémica, nuestros datos indican que la acidificación de los músculos

reduce la señal EMGRMS sin necesariamente reflejar aumento de fatiga muscular o reducción

de activación desde el sistema nervioso central. Sin embargo, a pesar de unas concentraciones

similares de metabolitos al inicio de los sprints la MPF y MdPF durante el ejercicio de sprint se

vieron reducidas por fatiga muscular sin signos de recuperación, lo que indicaría que la MPF y

la MdPF son sensibles al estado metabólico del músculo y no son buenos marcadores del

patrón de reclutamiento de la motoneuronas medulares. Estos resultados parecen confirmar

que las reducciones de MPF y MdPF estarían relacionadas con factores periféricos (Brody et

al., 1991) completamente independientes de la acumulación de lactato y de H+ (Vestergaard-

Poulsen et al., 1995). Hemos medido también las duraciones de las contracciones, que

deberían ser siempre iguales al tratarse de un esfuerzo isocinético. No obstante, esta

investigación demuestra que la duración de los burst disminuye con la fatiga. Este cambio

revierte durante los 60s de recuperación en isquemia mientras la concentración de metabolitos

sigue incrementándose.

Para demostrar fatiga central es necesario mostrar que se produce un incremento de

fuerza durante una contracción máxima estimulando eléctrica o magnéticamente la corteza, las

vías nerviosas o el músculo (Gandevia et al., 1996), pero estos procedimientos tienen graves

problemas para ser aplicados a tareas complejas como pedalear, por lo que se aplican a otros

tipos de tareas máximas lo antes posible tras una tarea agotadora. Como ya se ha mencionado

en la introducción, esto tiene asociados algunos problemas, desde la diferencia de las vías de

Discusión


reclutamiento en tareas diferentes, la dificultad de reproducir la complejidad de las órdenes

motoras que conllevan miles de unidades motoras de distintos músculos descargando a

diferentes frecuencias y reclutados en momentos específicos, o la velocidad de la recuperación

de algunas de las vías como la fosfocreatina. Por otro lado, la respuesta a sacudidas

musculares (contracciones musculares aisladas provocadas eléctrica o magnéticamente)

podría ser debida también en parte a mecanismos intracelulares y no necesariamente reflejar

una fatiga central aumentada (Gandevia et al., 2013).

Una estrategia alternativa es medir la potencia máxima que se genera en la misma

tarea que provocó la fatiga (Cairns et al., 2005; Marcora & Staiano, 2010b; Coelho et al., 2015),

pero generalmente en cicloergómetro ha planteado el problema de que la fatiga genera la

disminución de la frecuencia de pedaleo tanto en hipoxia como en normoxia como mostramos

en el primer artículo anexado (Torres-Peralta et al., 2014). Dada la dependencia de la potencia

a la frecuencia de pedaleo y la velocidad de contracción (Sargeant & Dolan, 1987), la fatiga

debería, al menos en condiciones ideales, ser testada a las mismas velocidades de contracción

que la que se utilizó durante la tarea que creó esta fatiga y a la misma velocidad de contracción

que el control que queramos utilizar, es decir, durante pedaleo isocinético.

Aparentemente la electromiografía de superficie es más sensible detectando fatiga

central que periférica a pesar de que sólo tenemos las frecuencias y el rendimiento al haber

descartado los metabolitos como indicadores. En este sentido en este trabajo hemos podido

analizar varios componentes de la señal EMG sin la variabilidad producida por las diferencias

en la velocidad de movimiento. Se sabe que la duración de las contracciones musculares

durante un ejercicio incremental aumenta con la intensidad del ejercicio manteniendo

frecuencias de pedaleo similares, hasta alcanzar sus máximos cerca de la potencia máxima

como mostramos en el primero de los artículos anexados (Torres-Peralta et al., 2014). Pero a

pesar de que las potencias medias alcanzadas durante los sprints posteriores al incremental

fueron superiores a las potencias alcanzadas al final de los incrementales en todos los casos

las duraciones de las contracciones no fueron superiores sino que incluso fueron inferiores a

las del sprint de control. Esto nos muestra que los músculos se contrajeron durante una

Discusión


fracción menor del ciclo de la pedalada. Es posible que este efecto pueda ser causado por un

descenso en la excitabilidad del sarcolema debido a la fatiga (Sejersted & Sjogaard, 2000;

Sidhu et al., 2012). En coherencia con esta explicación la duración del burst se recupera en

menos de 60 segundos, lo que concuerda con una recuperación rápida de la fatiga central

(Fernandez-del-Olmo et al., 2013).

Durante contracciones de alta intensidad la enzima miosin-ATPasa y las bombas

iónicas son las responsables de la mayoría del gasto energético en los músculos dado que no

puede desviarse energía a procesos anabólicos, debido al bloqueo de las enzimas necesarias.

En nuestro modelo suponemos que cuando se finaliza el ejercicio las bombas iónicas estarán

activadas al máximo de sus posibilidades, particularmente la bomba sodio-potasio, que tiene un

papel crítico en la restauración de la excitabilidad del sarcolema (Pedersen et al., 2003;

Hostrup et al., 2014). Durante la isquemia la energía necesaria para mantener la actividad de

las bombas iónicas se produjo a través de la glicólisis y en menor medida usando la poca

cantidad que quedó disponible de PCr (Morales-Alamo et al., 2015a), ya que el poco oxígeno

que pudiera quedar unido a la mioglobina cuando se ocluye la circulación fue utilizado

rápidamente (3-5 s) debido a la gran activación de la respiración mitocondrial por el ADP

acumulado en el momento de finalizar la tarea (Morales-Alamo et al., 2015a).

Los catéteres insertados han permitido conocer la evolución de los gases sanguíneos.

La presión de oxígeno en la vena femoral fue más baja en la extenuación en los test

incrementales de hipoxia que cuando llegan a su máximo y fallan en la tarea en los test

incrementales realizados en normoxia (Calbet et al., 2015). Por tanto, la posible contribución de

oxígeno atrapado en el miembro ocluido, sea en los capilares o en la mioglobina, ha sido

menor en hipoxia que en normoxia. Esto último implica que el O2 atrapado por la oclusión ha

podido contribuir en menor medida a la resíntesis de ATP durante los 10 segundos de reposo

antes del sprint, cuando el test finalizó en normoxia que en hipoxia. Sin embargo, el

rendimiento en sprints realizados tras un test incremental en normoxia ha sido menor que tras

un incremental en hipoxia, sugiriendo de nuevo que en hipoxia se produce una incapacidad de

continuar la tarea con una fatiga periférica menor.

Discusión


Estudios efectuados en animales (Hill et al., 1992; Lagier-Tessonnier et al., 1993) han

demostrado que a PO2 similares a los observados en la vena femoral en nuestro estudio, las

aferentes musculares del grupo III/IV causan una inhibición mayor del flujo corticoespinal

durante ejercicio severo en hipoxia tal y como se ha sugerido previamente (Calbet et al., 2015).

Se ha propuesto la contribución de las aferentes musculares del grupo III/IV y quizás otras

terminaciones nerviosas de articulaciones y tendones (Amann et al., 2013), aunque su papel en

el proceso de la fatiga está sin determinar.

Se ha comprobado que cuando las motoneuronas son estimuladas repetitivamente

disminuyen la frecuencia de descarga o cesan de hacerlo (Kernell & Monster, 1982). La

combinación de estos dos fenómenos podría explicar la percepción incrementada del esfuerzo

(Marcora, 2009) que lleva a detener la tarea en el incremental en hipoxia a pesar de la menor

fatiga periférica (Pierrefiche et al., 1997). Oxigenar al terminar el esfuerzo puede llevar a que la

recuperación de la fatiga central sea más rápida tras ejercicio en hipoxia.

La inhibición motora causada por activación de las aferentes musculares del grupo

III/IV no incrementan el rendimiento, lo que ha sido argüido como evidencia en contra de un

papel importante de estas aferencia como limitantes de la capacidad de esfuerzo en personas

sanas (Marcora, 2010). Experimentos con fentanilo (Amann et al., 2009; Amann et al., 2011)

(un bloqueador de los receptores opiáceos µ; que se utiliza como anestésico) junto a los del

presente estudio, sugieren que la causa de la fatiga en el test incremental no es la fatiga

periférica.

Se ha propuesto que el lactato y la acumulación de hidrogeniones pueden facilitar la

recuperación al mejorar la conductancia del cloro (Nielsen et al., 2001; Pedersen et al., 2003).

La combinación de una tasa glicolítica elevada con alta temperatura por tener circulación

ocluida, podría haber contribuido también a la recuperación periférica durante la oclusión.

Nuestra investigación sugiere que el papel inhibidor de las aferentes musculares del

grupo III/IV es pequeño o es superado por el comando central. Sin embargo, en ejercicios de

prensión con una mano la activación voluntaria se ve consistentemente inhibida por la

activación de las aferentes musculares del grupo III/IV (Kennedy et al., 2015).

Discusión


Lo cierto es que los sprint tras la normoxia y la hipoxia tienen la misma duración de

contracciones, más corta que el sprint control, pero los que habían sido precedidos por hipoxia

generaron más potencia por lo que la fuerza aplicada ha debido ser mayor. De acuerdo con

esto la MPF y la MdPF son mayores sugiriendo mayores frecuencias y menor fatiga central tras

hipoxia o una recuperación más rápida del fenómeno de fatiga central por la oxigenación del

cerebro (Kayser et al., 1994; Calbet et al., 2003a)

Al final del test incremental la activación es menor que durante el sprint, por lo que el

cese de la actividad no lo causó una incapacidad de actuación por fatiga muscular, sino por

insuficiente activación y que el componente central se recuperó con rapidez.

De ese modo lo que recogeríamos durante los primeros segundos del sprint sería lo

máximo que pueden dar de sí el sistema nervioso y el muscular sin inhibiciones de la

percepción de esfuerzo que ha sido borrada durante los segundos de reposo de sistema

central.

La percepción del esfuerzo por parte de los sujetos fue máxima siempre. Aunque los

factores psicológicos no fueron analizados parece poco probable que influyeran en el aumento

de potencia tras el sprint efectuado con 60 s de isquemia comparado con el realizado tras 10 s

de isquemia, pero podrían influir en la reducción de la motivación para mantener el esfuerzo

máximo en el test incremental.

En resumen, la finalización del ejercicio incremental depende más de los mecanismos

centrales de fatiga que de los periféricos, tal y como indica el menor nivel de activación

muscular observado en los últimos segundos del test incremental comparados con los del

sprint realizado tras una isquemia. Se reducen durante la fatiga la duración de las

contracciones musculares, la MPF y la MDPF a máxima intensidad de movimiento (sprint). La

acción inhibitoria de las aferentes musculares del grupo III/IV tiene poco o ningún impacto en el

rendimiento durante sprints cortos. La oxigenación aumenta la activación muscular cuando la

fatiga ocurre durante un esfuerzo producido en condiciones de hipoxia severa.

Discusión


Nuestro estudio III ha confirmado que hay menor activación muscular cuando se

alcanza la fatiga en hipoxia severa aguda (Calbet et al., 2003a; Amann et al., 2007b) y de que

la fatiga queda aliviada rápidamente si administra aire con mayor PO2 en el momento del

agotamiento. Aunque esta oxigenación generalmente viene acompañada de una mayor

activación muscular cuando los niveles de hipoxia son severos (PIO2 ≤82mmHg, altitudes sobre

los 4300m), también encontramos que no es precisa esta mayor activación muscular para ver

efectos ergogénicos en la oxigenación de sujetos durante la fatiga en hipoxia. Se cree que la

imposibilidad de mantener la potencia deseada provendría de mecanismos centrales

dependientes de la liberación de oxígeno o la presión intersticial de oxígeno y esta idea viene

refrendada por la velocidad con la que se atenúan los síntomas de fatiga con la oxigenación;

esto coincide con una gran reserva funcional en la fatiga en hipoxia, que es superior a la

reserva funcional disponible al finalizar el esfuerzo en normoxia (Amann et al., 2007b; Morales-

Alamo et al., 2015a).

La administración de aire con mayor PIO2 no atenúa la fatiga en el ejercicio en hipoxia

moderada o en ejercicios de músculos pequeños aún en hipoxia severa (Calbet & Lundby,

2009), lo que podría estar relacionado con niveles menores de fatiga supraespinal en este tipo

de esfuerzo (Goodall et al., 2010). Aparentemente la activación muscular se ve reducida

cuando la hipoxia causa un descenso de la SaO2 por debajo del 70%.

Esta reducción de la activación muscular podría producirse aumentando la

retroalimentación inhibitoria a niveles espinal y supraespinal, lo que reduciría la frecuencia de

descarga de las motoneuronas espinales comparada con las frecuencias de normoxia (Hill et

al., 1992; Lagier-Tessonnier et al., 1993; Arbogast et al., 2000; Amann & Kayser, 2009). Pero

parece extraño que pueda ocurrir sin perturbar la frecuencia media o la mediana, lo que van en

contra de un aumento del activación de los reflejos metabólicos de la musculatura en este tipo

de esfuerzos (Millet et al., 2009). O bien podría reducir el reclutamiento de unidades motoras

de umbral alto, al reducir la oxigenación de las zonas prefrontales, premotoras y motoras,

debido a un desequilibrio entre la demanda de energía y la resíntesis de ATP lo que limitaría el

impulso nervioso corticoespinal (Rasmussen et al., 2007; Verges et al., 2012). Además, en este

Discusión


estudio hemos podido descartar que los cambios de activación dependan de cambios en la

frecuencia de pedaleo (Amiridis et al., 1996). En conjunto los hallazgos indican que uno de los

mecanismos centrales por los que la hipoxia severa puede causar fatiga central es reduciendo

la capacidad de activación máxima del músculo.

Conclusiones


Conclusiones


CONCLUSIONES

Las siguientes conclusiones han sido extraídas de los resultados de los estudios

experimentales incluidos en la tesis.

1/ La activación muscular aumenta en relación casi lineal con la intensidad en el

ejercicio incremental en cicloergómetro con un patrón específico para cada músculo.

2/ El patrón de incremento de la activación se ve modulado por la fracción inspiratoria

de oxígeno y la intensidad relativa del esfuerzo.

3/ A una misma intensidad absoluta la activación es mayor en hipoxia severa aguda.

4/ A una misma intensidad relativa la activación es menor en hipoxia severa aguda.

5/ La duración de las contracciones del vasto medial y lateral del cuádriceps aumenta

con la intensidad del ejercicio.

6/ En hipoxia severa equivalente a altitudes superiores a 4300 m sobre el nivel del mar

la activación muscular máxima que se puede alcanzar durante un ejercicio incremental hasta el

agotamiento es menor que en normoxia.

7/ La oxigenación en el punto de fatiga permite continuar el ejercicio cuando el

agotamiento se ha producido en hipoxia moderada y severa de manera independiente de su

efecto sobre la activación muscular.

Conclusiones


8/ La oxigenación en el momento de la extenuación aumenta la activación muscular

cuando el esfuerzo se ha efectuado en hipoxia equivalente a altitudes sobre los 4300 m (PIO2 ≤

82 mmHg) si logra una SaO2 ≥67%.

Conclusiones


CONCLUSIONS

The following conclusions have been extracted from the results of the experimental studies

includes in this thesis.

1/ Muscle activation increases linearly with intensity during incremental exercise in

whole body exercise following a muscle-specific pattern.

2/ The pattern of muscle activation is modulated depending on FIO2 and relative

intensity of exercise.

3/ At a given absolute intensity muscle activation will be higher under severe hypoxia

compared to normoxia.

4/ At a given relative intensity muscle activation will be lower under severe hypoxia

compared to normoxia.

5/ Duration of burst of vastus medialis and vastus lateralis increases with exercise

intensity.

6/ Under severe hypoxia equivalent to altitudes above 4300m the maximal muscular

activation attainable in an incremental exercise to exhaustion is lower than under normoxia..

7/ Oxygenation at task failure under moderate or severe hypoxia will allow continuing to

exercise independently of the effect of the new inspired fraction of oxygen on the activation of

the muscles.

Conclusiones


8/ Oxygenation at exhaustion under hypoxia equivalent to altitudes above 4300m (PIO2

≤ 82 mmHg) whenever it reaches SaO2 ≥67%

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Scientific Article

Muscle Activation During Exercise in Severe Acute Hypoxia:Role of Absolute and Relative Intensity

Rafael Torres-Peralta,1,3 Jose Losa-Reyna,1,3 Miriam Gonzalez-Izal,2 Ismael Perez-Suarez,1

Jaime Calle-Herrero,1 Mikel Izquierdo,2 and Jose A.L. Calbet1,3

Abstract

Torres-Peralta, Rafael, Jose Losa-Reyna, Miriam Gonzalez-Izal, Ismael Perez-Suarez, Jaime Calle-Herrero,Mikel Izquierdo, and Jose A.L. Calbet. Muscle activation during exercise in severe acute hypoxia: Role ofabsolute and relative intensity. High Alt Med Biol 15:000–000, 2014.—The aim of this study was to determinethe influence of severe acute hypoxia on muscle activation during whole body dynamic exercise. Eleven youngmen performed four incremental cycle ergometer tests to exhaustion breathing normoxic (FIo2 = 0.21, two tests)or hypoxic gas (FIo2 = 0.108, two tests). Surface electromyography (EMG) activities of rectus femoris (RF),vastus medialis (VL), vastus lateralis (VL), and biceps femoris (BF) were recorded. The two normoxic and thetwo hypoxic tests were averaged to reduce EMG variability. Peak Vo2 was 34% lower in hypoxia than innormoxia ( p < 0.05). The EMG root mean square (RMS) increased with exercise intensity in all muscles( p < 0.05), with greater effect in hypoxia than in normoxia in the RF and VM ( p < 0.05), and a similar trend inVL ( p = 0.10). At the same relative intensity, the RMS was greater in normoxia than in hypoxia in RF, VL, andBF ( p < 0.05), with a similar trend in VM ( p = 0.08). Median frequency increased with exercise intensity( p < 0.05), and was higher in hypoxia than in normoxia in VL ( p < 0.05). Muscle contraction burst durationincreased with exercise intensity in VM and VL ( p < 0.05), without clear effects of FIo2. No significant FIo2

effects on frequency domain indices were observed when compared at the same relative intensity. In conclu-sion, muscle activation during whole body exercise increases almost linearly with exercise intensity, followinga muscle-specific pattern, which is adjusted depending on the FIo2 and the relative intensity of exercise. BothVL and VM are increasingly involved in power output generation with the increase of intensity and thereduction in FIo2.

Key Words: electromyogram; exercise; fatigue; human; hypoxia, median frequency; root mean square

Introduction

Muscle activation, as represented by the amplitudeof surface electromyogram (EMG) increases during

incremental exercise to exhaustion (Taylor and Bronks, 1996;Osawa et al., 2011). Greater EMG amplitude may originatefrom the combination of progressive recruitment of additionalmotor units and increases in the firing rate to raise musclecontraction intensity with the progression of power output, asshown using different contraction modes (Gottlieb and Agar-wal 1971; Ericson 1986; Weir et al., 1992; Gonzalez-Izal et al.,2012). Muscle activation is also increased during repeatedstatic (Viitasalo and Komi, 1977; Hausswirth et al., 2000) anddynamic (Sarre and Lepers, 2005) submaximal muscle con-

tractions at a given absolute exercise intensity, mostly throughadditional motor unit recruitment as fatigue develops (Bigland-Ritchie et al., 1986; Fulco et al., 1996). The latter may beaccompanied by increasing mean power frequency (MF)during low-intensity prolonged isometric contractions (10%–20% of maximal voluntary contraction (MVC)) or decreas-ing MF at slightly higher intensities (30%–40% of MVC)(Arendt-Nielsen et al., 1989).

A clear decrement of median power frequency (MPF) isobserved during repeated high-intensity dynamic musclecontractions when power output is also declining due to fa-tigue (Tesch et al., 1990; Izquierdo et al., 2011). However,MPF increases (vastus lateralis) or remains at the same level(vastus medialis) during 5 sec knee extension isometric

1Department of Physical Education, and 3Research Institute of Biomedical and Health Sciences, IUIBS, University of Las Palmas deGran Canaria, Campus Universitario de Tafira s/n, Las Palmas de Gran Canaria, Spain.

2Department of Health Sciences, Public University of Navarra, Tudela, Spain.

HIGH ALTITUDE MEDICINE & BIOLOGYVolume 00, Number 00, 2014ª Mary Ann Liebert, IncDOI: 10.1089/ham.2014.1027

1

https://www.researchgate.net/publication/20429813_Changes_in_muscle_fiber_conduction_velocity_mean_power_frequency_and_mean_EMG_voltage_during_prolonged_submaximal_contractions?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

https://www.researchgate.net/publication/44803477_Effects_of_Strength_Training_on_Muscle_Fatigue_Mapping_from_Surface_EMG_and_Blood_Metabolites?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

contractions going from 10% to 90% of the MVC interspacedwith 2 min recovery periods (Pincivero et al., 2001). Duringrepeated dynamic muscle contractions at high intensities, adecline in MPF reflects muscle fatigue (Amann et al., 2006),particularly if power output is declining (Tesch et al. 1990;Izquierdo et al., 2011), while an elevated MPF (or MF) maybe indicative of fatigue during prolonged exercise at a fixedpower output when the intensity of exercise is low or mod-erate (Sarre and Lepers, 2005). Nevertheless, a reduction inMPF has been also reported during prolonged exercise toexhaustion (Hausswirth et al., 2000).

At a given absolute intensity, dynamic exercise is per-ceived as harder during exercise in severe hypoxia (i.e., FIo2

< 0.115), and the relative intensity of exercise is higher due tothe lower Vo2max (Calbet et al., 2003). Consequently, theamount of muscle mass used and EMG amplitude is expectedto be higher during exercise at the same absolute intensity inhypoxia, since the relative intensity is higher in hypoxia. Theincrease of exercise intensity, particularly above the lactatethreshold, causes progressive muscle recruitment as shownusing magnetic resonance (Endo et al., 2007). However, se-vere hypoxia has been shown to reduce central motor output(Millet et al., 2012) and, hence, muscle activation due tolower brain oxygenation in hypoxia than in normoxia(Goodall et al., 2012). So far experimental data are contra-dictory, with some studies reporting no effect of severehypoxia on EMG amplitude during dynamic ( Taylor andBronks, 1996; Donnelly and Green, 2013) or static (Milletet al., 2012) muscle contractions, and other reporting in-creased activity (Fulco et al., 1996). Moreover, the relation-ship between central motor output, voluntary activation, andEMG parameters is quite uncertain (Verges et al., 2012).

Part of the discrepancies between studies could be due tothe different muscles and/or different muscle type of actions(i.e., isometric vs. dynamic), evaluated in each study, since ithas been recently shown that muscle activation patternsduring incremental exercise in normoxia show marked intraand between-muscle heterogeneity (Hug et al., 2004), as re-flected by the tissue water spin-spin transverse relaxationtime (T2) from 1H magnetic resonance imaging combinedwith local measures of exercise 31P chemical shift imaging(Cannon et al., 2013). It remains unknown if EMG amplitudeor MPF are affected by changes in the relative intensity ofexercise due to differences in oxygenation during dynamicmuscle actions.

Therefore, the aim of this study was to determine the in-fluence of severe acute hypoxia on thigh muscle activation,assessed with surface EMG, during dynamic exercise. Wehypothesized that muscle activation would be higher duringexercise in acute hypoxia with a muscle-specific pattern.Since severe hypoxia may reduce central motor output(Millet et al., 2012), we hypothesized also that at the samerelative intensity muscle activation would be lower in severehypoxia. To reduce EMG variability, two incremental exer-cise tests in normoxia were averaged and compared with theaverages of two incremental exercise tests in severe hypoxia.

Methods

Subjects

Eleven physically active and healthy men [mean – SD:21.2 – 2 years old, 71.7 – 9 kg body weight, 173.6 – 8 cmheight, 16 – 5% body fat, 52.4 – 5 mL.kg - 1.min - 1 maximal

oxygen consumption (Vo2max)] volunteered to participate inthis project. Prior, to the experiment, all procedures and anypotential risks were explained to each subject, and an in-formed consent document was signed. This study was ap-proved by the ethics committee of the University of LasPalmas de Gran Canaria, and all experiments were performedin accordance with the Declaration of Helsinki.

General procedures

On the first visit to the laboratory, the body compositionwas determined by dual-energy x-ray absorptiometry (Ho-logic QDR-1500, Hologic Corp., software version 7.10,Waltham, MA) as described elsewhere (Calbet et al., 1998).Thereafter, subjects reported to the laboratory to becomefamiliar with maximal exercise tests in normoxia and nor-mobaric hypoxia (Altitrainer 200, SMTEC, Switzerland) onseparate days. An average of 10 days later, subjects reportedto the laboratory on 2 different test days, at least 1 week apart.In each test day, two sets of incremental cycle ergometer(Lode Excalibur Sport 925900, Groningen, The Netherlands)exercise tests to exhaustion, interspaced by a 90 min restperiod, one in normoxia (inspired oxygen pressure, PIo2 =143 – 1 mmHg) and another one in acute hypoxia PIo2 =74 – 1 mmHg, were carried out in random order. In hypoxia,subjects were connected to the Altitrainer and after 2 minresting recordings were started. In both conditions, restingvalues were recorded during 2 min prior to the start of exer-cise. Thus, subjects were exposed to hypoxia 4 min before thestart of the test in hypoxia. After the resting period, the loadwas set to 60W (hypoxia) or 80W (normoxia), and after 2 minthe intensity was increased by 20–30W (hypoxia) or 30–40 W(normoxia) every 2 min until exhaustion, to have incrementalexercise tests not too different in terms of duration betweennormoxia and hypoxia. Subjects were requested to keep apedaling rate of 80 rpm. Exhaustion was defined as the in-ability to maintain a pedaling rate above 50 rpm despitestrong verbal encouragement during 5 seconds. Oxygen up-take was measured with a metabolic cart (Vmax N29; Sen-sormedics, California, USA), calibrated prior to each testaccording to the manufacturer instructions. Respiratory var-iables were analyzed breath-by-breath and averaged every20 sec for the assessment of Vo2peak and every minute forsubmaximal loads. The value recorded during the last minuteof each submaximal load was used in the analyses.

Electromyography

Electrical muscle activation was monitored by means ofsurface electromyography (EMG). EMG signals were con-tinuously recorded from four muscles of the left lower limb:rectus femoris (RF), vastus medialis (VM), vastus lateralis(VL), and biceps femoris (BF). Prior to the application of theEMG electrodes the skin surface was carefully shaved andwiped with alcohol to reduce skin impedance. Bipolar singledifferential electrodes were placed longitudinally on themuscles following the SENIAM recommendations (Merlettiand Hermens, 2000) and taped to the skin to minimizemovement artifacts. The reference electrode was placed onthe skin over the acromion. The position of the electrodes wasmarked on the skin with indelible ink, and these referenceswere used for precise electrode placement on repeated ex-periments. The EMG signals were acquired using a 16-channel recording system (Myomonitor IV, Delsys Inc.,

2 TORRES-PERALTA ET AL.

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https://www.researchgate.net/publication/8606469_Heterogeneity_of_muscle_recruitment_pattern_during_pedaling_in_professional_road_cyclists_A_magnetic_resonance_imaging_and_electromyography_study?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

https://www.researchgate.net/publication/6369128_Thigh_muscle_activation_distribution_and_pulmonary_VO2_kinetics_during_moderate_heavy_and_very_heavy_intensity_cycling_exercise_in_humans?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

https://www.researchgate.net/publication/12359549_Evolution_of_Electromyographic_Signal_Running_Economy_and_Perceived_Exertion_During_Different_Prolonged_Exercises?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

https://www.researchgate.net/publication/221822143_Severe_hypoxia_affects_exercise_performance_independently_of_afferent_feedback_and_peripheral_fatigue?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==


https://www.researchgate.net/publication/221817932_Cerebral_perturbations_during_exercise_in_hypoxia?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

https://www.researchgate.net/publication/6988631_Determinants_of_maximal_oxygen_uptake_in_severe_acute_hypoxia?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

https://www.researchgate.net/publication/223986257_Supraspinal_fatigue_after_normoxic_and_hypoxic_exercise_in_humans?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

Boston, MA) at a sampling rate of 1000 Hz using rectangular-shaped (19.8 mm wide and 35 mm long) bipolar surfaceelectrodes with 1 x 10 mm 99.9% Ag conductors, and an inter-conductor distance of 10 mm (DE-2.3 Delsys Inc.) and filteredwith a high pass filter of 20 Hz and low pass filter of 450 Hz.The system has an input impedance of > 1015O // 0.2pF, acommon mode rejection ratio of > 80 dB, signal-to-noiseratio < 1.2 lV, and a pre-amplifier gain 1000 V/V – 1%. Eachpedal revolution was detected by using an electrogoniometer(Goniometer Biosignal Sensor S700 Joint Angle Shape Sen-sor; Delsys Inc.) fixed on the left knee and sampled at 500 Hz.EMG; joint movement were simultaneously recorded by aportable device (Myomonitor IV, Delsys Inc.) and wirelesstransmitted to a computer (EMGWorks Wireless applicationand EMGWorks Acquisition 3.7.1.3; Delsys, Inc.).

EMG recordings were later analyzed using a custom-madeapplication (Matlab R2012b, MathWorks, Natick, MA). TheEMG signals were full wave rectified and RMS calculatedusing a 25 ms rolling window. Burst onset and offset detec-tion was determined using as a reference 20% of the maximalRMS activity of each burst (Baum and Li, 2003; Hug andDorel, 2009), rather than using a mean threshold value from15 consecutive bursts (Ozgunen et al., 2010). This approachyielded the same result as direct simple visual discrimination,with 100% detection of all bursts in the four muscles. TheRMS recorded during the last min of a 2 min 80 W load (innormoxia) was used to normalize the rest of the RMS data. Inaddition, we calculated a total activity index per minute(TAI) defined as TAI = RMS x burst duration (ms) x pedalingrate (rpm), which is similar to the integrated EMG signal, butcomputing separately each burst and excluding the baselineEMG between burst. The TAI recorded during the last min ofa 2 min 80 W load (in normoxia) was used to normalize therest of the TAI values.

Mean (MF) and median (MPF) power spectrum frequen-cies were calculated using Fast Fourier Transform (FFT)(Solomonow et al., 1990). All variables were reported as themean values of the pedal strokes recorded during the lastminute of each load, or the fraction completed in the case ofthe last load.

Methodological considerations

Disagreements between previous studies could have beencaused by the intrinsic variability of EMG recordings (Taylorand Bronks, 1995; Hug et al., 2004). For example, integratedEMG (iEMG) increases with increasing angular velocityduring concentric contractions (Westing et al., 1991; Amir-idis et al., 1996). Several normalization procedures have beenused to reduce EMG variability. Normalization is achievedby comparing the root mean square (RMS) signal recordedduring a given experimental condition to a reference RMSsignal recorded during standardized reproducible conditions.This approach allows the comparison of RMS across mus-cles, time, and subjects (Albertus-Kajee et al., 2010). Themost applied normalization method is achieved by dividingthe RMS recorded during dynamic or static contractions bythat obtained during a maximal voluntary contraction (MVC)under static conditions (isometric contraction) (Marsh andMartin, 1995; Hug and Dorel, 2009). This method of nor-malization is appropriate for static conditions, especially ifperformed at muscle length and joints angles close to thoseused in the reference contraction. However, this approach is

less specific and less reproducible when the RMS obtainedduring an MVC is used to normalize dynamic contractions.An alternative procedure is to use RMS obtained during areference dynamic condition as the normalizing value(Westing et al., 1991; Taylor and Bronks, 1995; Amiridiset al., 1996). Variability could be also reduced averagingsome experiments performed under similar conditions, asusually done in O2 kinetics studies ( Jones et al., 2012).However, this latter approach has not been applied in EMGresearch.

Statistical analysis

A Students t-test was used to determine if there was atest order effect between the two tests performed in similarconditions. Since there were no significant test order ef-fects, or differences between the tests performed in thesame conditions, the two normoxic exercise tests wereaveraged and the two hypoxic tests, as well. Thus, onlyone set of data was left to represent each condition (nor-moxia and hypoxia). Exercise tests were compared using atwo-way ANOVA for repeated measures followed bypairwise comparisons with the Student’s t-test adjusted formultiple comparisons with the Bonferroni-Holm correc-tion. The impact of pedaling rate on burst duration wasassessed with ANCOVA for repeated measures usingpedaling rate as a covariate. P £ 0.05 was considered sig-nificant. Analysis was performed using a commerciallyavailable software package (SPSS version 15.0, SPSS,Inc., Chicago, IL). Data are reported as means – standarddeviation (SD), unless otherwise stated.

Results

Similar results were obtained in the two test performedin hypoxia (184 – 23 and 182 – 23 W, respectively, p =0.72) and normoxia (284 – 30 and 278 – 34 W, respec-tively, p = 0.34). However, the tests in normoxia wereslightly longer than in hypoxia (850 – 109 and 747 – 84 sec,p < 0.05). No significant differences were observed in theVo2/power relationship between normoxia and hypoxia;however, peak Vo2 was 34% lower in hypoxia than innormoxia ( p < 0.05). At the same absolute load, pulmonaryventilation (VE), heart rate and RER were higher in hyp-oxia than in normoxia (all, p < 0.05), whilst PETO2 andPETCO2 were lower in hypoxia ( p < 0.05) (Fig. 1). Pedal-ing rate was maintained around 80 rpm up to 86% ofVo2max; then it declined attaining a value close to 70 rpmin the last min of exercise in both conditions (Fig. 2). Athigh submaximal exercise intensities, pedaling rate waslower in hypoxia than in normoxia ( p < 0.05), while it wasnot affected by FIo2 at the same relative intensity (Fig. 2).

The RMS and TAIm increased with exercise intensity inall the examined muscles; this effect being more accentuatedin the RF than in the other muscles ( p < 0.05) (Figs. 3 and 4).The rate of increase of RMS and TAIm with absolute exerciseintensity was greater in hypoxia than in normoxia in the RFand VM (interaction intensity x FIo2 p < 0.05), while a similartrend was seen in VL for RMS ( p = 0.10). No significant FIo2

effects were seen in RMS and TAI responses of the BF.However, at the same relative intensity the RMS was higherin normoxia than in hypoxia in RF, VL and BF (bothp < 0.05), while a similar trend was seen in VM ( p = 0.08).Similar results were obtained in TAI [i.e., greater values in

MUSCLE ACTIVATION DURING EXERCISE 3

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normoxia than in hypoxia in RF, VM, and VL (the three,p < 0.05), but not in BF ( p = 0.08)] (Fig. 4).

At the same absolute intensity, median frequency in VL washigher in hypoxia, while no significant effects of FIo2 on medianfrequency were observed in the other muscles (Fig. 5). A sig-nificant increase of median frequency with exercise intensitywas observed in VM and VL, while no significant influence ofexercise intensity on RF and BF median frequencies were ob-

served. The duration of the burst increased with exercise in-tensity only in VM and VL ( p < 0.05), while no significant FIo2

effects on burst duration were observed in any muscle (Fig. 5).This effect remained after accounting for small changes inpedaling rate. Mean frequency results (data not shown) wereessentially similar to MPF. No significant effects of FIo2 onfrequency domain indices were observed when comparisonswere performed at the same relative intensity.

FIG. 1. Ergospirometric variables during incremental exercise to exhaustion in normoxia (FIo2 = 0.21, PIo2 = 141 mmHg)and hypoxia (FIo2 = 0.108, PIo2 = 74 mmHg), each point represents the mean and the error bars the standard error of themean (n = 11), only the points for which n = 11 are depicted. *P < 0.05 normoxia vs. hypoxia, same point.


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Discussion

Although the exercise protocols were slightly different,this study shows that exercise muscle activation increasesalmost linearly with exercise intensity, and is modulated bythe inspired O2 fraction. We have also shown that FIo2 in-fluences muscle activation with a muscle-specific pattern.During cycling at the same absolute intensity, greater muscleactivation in severe hypoxia is only clearly seen in RF andVM, although a trend to higher levels of activation was alsodetected in VL and BF. In contrast, the muscle activation islower in hypoxia than in normoxia when compared at thesame relative intensity. Median and mean frequencies re-mained at the same level or increased slightly with exerciseintensity, following also a muscle specific pattern modulatedby FIo2. Finally, we have also shown that the duration of theburst increases (37%–55%) with exercise intensity mostly inVL and VM. On the basis of increases in both RMS and burstduration, it can be inferred that the contribution of VL andVM to the overall mechanical impulse increases with exer-cise intensity similarly in normoxia and hypoxia.

This muscle specificity may originate from changes in theneural activation pattern caused by the effect of FIo2 oncentral nervous system oxygenation (Amann et al., 2007;Millet et al., 2012), afferent modulation of corticospinalmotor drive (Gerdle and Fugl-Meyer, 1992), and differencesin muscle metabolic response to hypoxia (Parolin et al.,2000), muscle fiber type composition and muscle vasculari-zation (Moritani et al., 1992). For example, more activemotoneurones have an increased metabolic demand, whichunder circumstances of limited O2 supply to the brain, asduring exercise in severe acute hypoxia, may lead to in-creased glycolysis, brain release of lactate, and alteration ofneuronal metabolism and function (Rasmussen et al., 2010;Overgaard et al., 2012). Experiments using intrathecal fen-tanyl in humans during cycling have shown that opioid-me-diated muscle afferents inhibit central motor drive (Amannet al., 2009; Gagnon et al., 2012); thus changes in afferentdischarge with fatigue or oxygenation are expected to alter

the pattern of muscle activation. Although a comparativeanalysis of the metabolic responses of the different portionsof the quadriceps muscle in man has not been performed,rodent studies have shown that the metabolic response tohypoxia are region specific, depending on the predominantmuscle fiber type and the degree of capillarization (Wustet al., 2009).

In agreement with our results, increased quadriceps muscleiEMG was observed during dynamic knee extension exerciseat 21 W in hypobaric hypoxia (barometric pressure: 464mmHg) compared to normoxic exercise (Fulco et al., 1996).Likewise, increased mean VL iEMG during cycling in hyp-oxia at FIo2 of 0.10 (Amann et al., 2007) and 0.116 (Tayloret al., 1997) was observed, compared to normoxia, after oneminute of exercise at the same absolute intensity. Never-theless, VL iEMG was not significantly increased when theFIo2 was 0.15 (Amann et al., 2007), indicating that the in-crease in muscle activation at a given absolute exercise in-tensity depends on the magnitude of hypoxia during wholebody exercise. In partial agreement with our results, Peltonenet al. (1997) reported reduced iEMG (sum of gastrocnemius,VL, RF, BF, gluteus maximus, erector spinae, and bicepsbrachii muscles) during a 2500 m rowing test in mild hypoxia(FIo2 = 0.158) compared to normoxia without significant ef-fects on mean power frequency. No muscle specific analysiswas reported by Peltonen et al. (1997).

In contrast with our results, Taylor and Bronks (1996)observed similar iEMG responses in RF, VM, and VL at thesame absolute intensities in normoxia and moderate hypoxia(FIo2 = 0.135) during cycling. It should be noticed that, al-though in Taylor and Bronks (1996) the differences were notstatistically significant, the mean iEMG values were higher inhypoxia than in normoxia. Given the intrinsic variability ofthe EMG, the results of Taylor and Bronks (1996) could justbe due to a type II error caused by the combination of smallereffect of a milder level of hypoxia with the intrinsic vari-ability of EMG. Goodall et al. (2010) measured RMS duringsubmaximal fatiguing isometric leg extension contractionsand reported no significant differences in VL between severe

FIG. 2. Pedaling rate during incremental exercise to exhaustion in normoxia (FIo2 = 0.21, PIo2 = 141 mmHg) and hypoxia(FIo2 = 0.108, PIo2 = 74 mmHg), each point represents the mean and the error bars the standard error of the mean (n = 11).*P < 0.05 normoxia vs. hypoxia, same point. There was a significant main effect of relative intensity on pedaling rate( p < 0.05).



https://www.researchgate.net/publication/6487994_Severity_of_arterial_hypoxaemia_affects_the_relative_contributions_of_peripheral_muscle_fatigue_to_exercise_performance_in_humans?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

https://www.researchgate.net/publication/6487994_Severity_of_arterial_hypoxaemia_affects_the_relative_contributions_of_peripheral_muscle_fatigue_to_exercise_performance_in_humans?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

https://www.researchgate.net/publication/226257515_Oxygen_availability_and_motor_unit_activity_in_humans._Eur_J_Appl_Physiol_Occup_Physiol?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

https://www.researchgate.net/publication/13825089_Effects_of_oxygen_fraction_in_inspired_air_on_force_production_and_electromyogram_activity_during_ergometer_rowing?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

https://www.researchgate.net/publication/46124465_Effect_of_graded_hypoxia_on_supraspinal_contributions_to_fatigue_with_unilateral_knee-extensor_contractions?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

FIG. 3. Root mean square (RMS) during incremental exercise to exhaustion in normoxia (FIo2 = 0.21, PIo2 = 141 mmHg)and hypoxia (FIo2 = 0.108, PIo2 = 74 mmHg), each point represent the mean and the error bars the standard error of the mean(o = 11). *P < 0.05 normoxia vs. hypoxia, same point.



FIG. 4. Total activation index per minute (TAI) during incremental exercise to exhaustion in normoxia (FIo2 = 0.21,PIo2 = 141 mmHg) and hypoxia (FIo2 = 0.108, PIo2 = 74 mmHg), each point represents the mean and the error bars thestandard error of the mean (n = 11). *P < 0.05 normoxia vs. hypoxia, same point. The horizontal line indicates that the meanof the last two relative loads was compared between conditions using a t-test.



FIG. 5. Median power frequency and burst duration during incremental exercise to exhaustion in normoxia (FIo2 = 0.21,PIo2 = 141 mmHg) and hypoxia (FIo2 = 0.108, PIo2 = 74 mmHg), each point represents the mean and the error bars thestandard error of the mean (n = 11). Post hoc pair-wise comparisons at the same time points between conditions yieldednonstatistically significant differences.



hypoxia (FIo2 = 0.10) and normoxia. Likewise, Donnelly andGreen (2013) reported no effect during graded exercise ofsevere hypoxia (FIo2 = 0.105) on RMS in the triceps suraemuscles, with the exception of gastrocnemius medialis,which reached relatively higher RMS values in hypoxia.Millet et al. (2012) reported similar biceps brachii RMS re-sponses during submaximal contractions in normoxia andsevere hypoxia (FIo2 = 0.09). Thus, it seems that when theactive muscle mass is small (arm flexion, leg extension, andin some instances knee extension exercise), the impact ofhypoxia on muscle activation may be absent or is lower thanobserved during exercise with a large muscle mass, such ascycling.

The increased EMG amplitude during submaximal exer-cise at a given absolute intensity in hypoxia may reflect in-creased motor unit recruitment to compensate for fatigue ofactive muscle units (Moritani et al., 1992). In fact, using wireelectrodes, Moritani et al. (1992) showed both increases inamplitude and firing frequency of individual motor units withfatigue. Motor unit recruitment strategies can be indirectlyassessed by determining the MPF of the power spectralanalysis of the EMG (Solomonow et al., 1990; Sbriccoliet al., 2003). The fact that the pattern of muscle activationwas altered by hypoxia is clearly demonstrated by the re-duced pedaling rate at 140 and 160 W in hypoxia (Fig. 2). Theinfluence of pedaling cadence on EMG activity is contro-versial, but in general it seems that EMG activity increaseswith pedaling rate with a muscle-specific pattern. EMG ac-tivity has been reported to increase with cadence in VL(Marsh and Martin, 1995; Bieuzen et al., 2007), VM (Neptuneet al., 1997), BF (Neptune et al., 1997), RF (Marsh andMartin, 1995; Sarre et al., 2003), and medial gastrocnemius(Neptune et al., 1997), whereas no changes in EMG withcadence has been also reported for VM (Sarre et al., 2003),VL (Sarre et al., 2003), RF (Neptune et al., 1997; Bieuzenet al., 2007), and BF (Marsh and Martin, 1995; Bieuzen et al.,2007). At a given absolute exercise intensity, the relativeintensity increases with cadences above 60 rpm (Chavarrenand Calbet, 1999), implying that part of the increase in EMGamplitude with cadence is likely due to the increase in rela-tive intensity. Despite the slightly lower cadence during ex-ercise in hypoxia at 140 and 160 W, EMG activity was higherin hypoxia than in normoxia. Furthermore, pedaling ratedeclined similarly in normoxia and hypoxia at exercise in-tensities above 86% of Vo2max, implying that the relativeintensity rather than the small differences in pedaling ratewas the main factor dictating the motor activation strategy.

Supraspinal fatigue has been defined as an exercise-induced decline in force caused by suboptimal output fromthe motor cortex (Gandevia, 2001). Reduced brain oxygen-ation may cause central fatigue during exercise, particularlyin severe acute hypoxia (Goodall et al., 2010; Millet et al.,2012) leading to the corticospinal inhibition of motor drive.Interestingly, hypoxia has, if any, a small effect on musclemetabolism and exercise capacity when the muscle massrecruited is small (Roach et al., 1999; Calbet et al., 2009) orthe impairment in exercise capacity is only observed in se-vere hypoxia (Goodall et al., 2010). Moreover, during exer-cise with a small muscle mass in severe acute hypoxia,pulmonary gas exchange is less perturbed and consequently,brain oxygenation is less altered than during exercise with alarge muscle mass (Amann and Calbet, 2008; Calbet andLundby, 2009; Calbet et al., 2009). The energy charge of the

cell is less reduced during submaximal cycling at the samerelative intensity in hypoxia (FIo2 = 0.115; 72% of Vo2max)than in normoxia (73% of Vo2max) (Wadley et al., 2006),implying a similar or milder alteration of muscle metabolismin hypoxia. The reduction in muscle activation at the samerelative intensity in hypoxia compared to normoxia, observedin the present investigation, could originate from both dif-ferences in muscle metabolism and changes in corticospinaldrive. On the other hand, the potential effects due to differ-ences in pedaling rate can be ruled out, since pedaling rateswere similar between the two conditions when compared atthe same relative intensities. It should be taken also intoconsideration that, in severe acute hypoxia, the absolute in-tensity is much lower than in normoxia, when exercising atthe same relative intensity.

In summary, muscle activation during whole body exerciseincreases almost linearly with exercise intensity, following amuscle-specific pattern, which is modulated depending onFIo2 and the relative intensity of exercise. In general, at agiven absolute intensity, muscle activation is higher in hyp-oxia than in normoxia. Conversely, at a given relative in-tensity muscle activation is reduced in severe acute hypoxia.Median and mean frequencies remain at the same level orincrease slightly with exercise intensity, following also amuscle specific pattern modulated by FIo2. Since both theduration of VL and VM bursts and RMS increase with ex-ercise intensity, it can be inferred that these two muscles areincreasingly involved in power output generation as the ex-ercise intensity is elevated, an effect that is accentuated inhypoxia.

Acknowledgments

Special thanks are given to Jose Navarro de Tuero for hisexcellent technical assistance. Thanks are also expressed toLorena Rodrıguez-Garcıa and Jesus Gustavo Ponce Gonzalezwho helped occasionally during the execution of the exper-iments.

Author Disclosure Statement

The authors have no conflict of interest to disclose. Thisstudy was supported by a grant from the Ministerio de Edu-cacion y Ciencia of Spain (DEP2009-11638 and FEDER).

References

Albertus-Kajee Y, Tucker R, Derman W, and Lambert M.(2010). Alternative methods of normalising EMG duringcycling. J Electromyogr Kinesiol 20:1036–1043.

Amann M, and Calbet JA. (2008). Convective oxygen transportand fatigue. J Appl Physiol 104:861–870.

Amann M, Proctor LT, Sebranek JJ, Pegelow DF, and DempseyJA. (2009). Opioid-mediated muscle afferents inhibit centralmotor drive and limit peripheral muscle fatigue developmentin humans. J Physiol 587:271–283.

Amann M, Romer LM, Pegelow DF, Jacques AJ, Hess CJ, andDempsey JA. (2006). Effects of arterial oxygen content onperipheral locomotor muscle fatigue. J Appl Physiol 101:119–127.

Amann M, Romer LM, Subudhi AW, Pegelow DF, andDempsey JA. (2007). Severity of arterial hypoxaemia affectsthe relative contributions of peripheral muscle fatigue to ex-ercise performance in healthy humans. J Physiol 581:389–403.


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https://www.researchgate.net/publication/6798824_Muscle_activation_during_cycling_at_different_cadences_effect_of_maximal_strength_capacity?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

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https://www.researchgate.net/publication/10950511_Influence_of_cycling_cadence_on_neuromuscular_activity_of_the_knee_extensors_in_humans?el=1_x_8&enrichId=rgreq-d94836d6-5d87-40ee-a12f-153be08253a4&enrichSource=Y292ZXJQYWdlOzI2NTY5MjY3NTtBUzoxNDUxOTI0MDEyNDgyNTZAMTQxMTYyNzk3NDA3Mg==

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Address correspondence to:Dr. Jose A L Calbet

Departamento de Educacion FısicaCampus Universitario de Tafira,

35017 Las Palmas de Gran CanariaCanary Island 35017

Spain

E-mail:[email protected]

Received March 18, 2014;accepted in final form June 23, 2014.




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Task failure during exercise toexhaustion in normoxia and hypoxia isdue to reduced muscle activation causedby central mechanisms while musclemetaboreflex does limit performance

Rafael Torres-Peralta1, David Morales-Alamo1, Miriam Gonzalez-Izal2, JOSE ANTONIO L.

CALBET1*, José Losa Reyna1, Ismael Pérez Suárez1, Mikel Izquierdo2

1Physical Education and Research Institute of Biomedical and Health Sciences (IUIBS), University of Las

Palmas de Gran Canaria, Spain, 2Department of Health Sciences, Public University of Navarra, PublicUniversity of Navarra, Spain

Submitted to Journal:

Frontiers in Physiology

Specialty Section:

Exercise Physiology

Article type:

Original Research Article

Manuscript ID:

174203

Received on:

27 Oct 2015

Frontiers website link: www.frontiersin.org

In review

http://www.frontiersin.org/

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financialrelationships that could be construed as a potential conflict of interest

Author contribution statement

Conception and design of the experiments: JAC; pre-testing, experimental preparation, data collection and analysis: RTP, DMA, JLR,IPS, and JAC; EMG analysis: RTP, MGI, and MI. The first version of the manuscript was written by RTP and JAC. All co-authors read,contributed comments and approved the final version of the manuscript.

Keywords

Fatigue, Electromyography, exhaustion, EMG, Lactate, high-intensity, hypoxia, performance

Abstract

Word count: 349

To determine whether task failure during incremental exercise to exhaustion (IE) is principally due to reduced neural drive andincreased metaboreflex activation eleven men (22±2 years) performed a 10s control isokinetic sprint (IS; 80 rpm) after a shortwarm-up. This was immediately followed by an IE in normoxia (Nx, PIO2:143 mmHg) and hypoxia (Hyp, PIO2:73 mmHg) in randomorder an separated by a 120 min resting period. At exhaustion, the circulation of both legs was occluded instantaneously (300mmHg) during 10 or 60s to impede recovery and increase metaboreflex activation. This was immediately followed by and IS withopen circulation. Electromyographic recordings were obtained from the vastus medialis and lateralis. Muscle biopsies and bloodgases were obtained in separate experiments. During the last 10s of the IE, pulmonary ventilation, VO2, power output and muscleactivation were lower in hypoxia than in normoxia, while pedaling rate was similar. Compared to the control sprint,performance (IS-Wpeak) was reduced to a greater extent after the IE-Nx (11% lower P<0.05) than IE-Hyp. The root mean square(EMGRMS) was reduced by 38 and 27% during IS performed after IE-Nx and IE-Hyp, respectively (Nx vs. Hyp: P<0.05). Post-ischemiaIS-EMGRMS values were higher than during the last 10s of IE. Sprint exercise mean (IS-MPF) and median (IS-MdPF) powerfrequencies, and burst duration, were more reduced after IE-Nx than IE-Hyp (P<0.05). Despite increased muscle lactateaccumulation, acidification, and metaboreflex activation from 10 to 60s of ischemia, IS-Wmean (+23%) and burst duration (+10%)increased, while IS-EMGRMS decreased (-24%, P<0.05), with IS-MPF and IS-MdPF remaining unchanged. In conclusion, close to taskfailure, muscle activation is lower in hypoxia than in normoxia. Task failure is predominantly caused by central mechanisms, whichrecover to great extent within one minute even when the legs remain ischemic. There is dissociation between the recovery ofEMGRMS and performance. The reduction of surface electromyogram MPF, MdPF and burst duration due to fatigue is associated butnot caused by muscle acidification and lactate accumulation. Despite metaboreflex stimulation, muscle activation and power outputrecovers partly in ischemia indicating metaboreflex activation has a minor impact on sprint performance.

Funding statement

This study was supported by a grant from the Ministerio de Educación y Ciencia of Spain (DEP2009-11638 and FEDER) and VIIConvocatoria de Ayudas a la Investigación Cátedra Real Madrid-Universidad Europea de Madrid (2015/04RM)

Ethics statement

(Authors are required to state the ethical considerations of their study in the manuscript including for caseswhere the study was exempt from ethical approval procedures.)

Did the study presented in the manuscript involve human or animal subjects: Yes

Please state the full name of the ethics committee that approved the study. If the study was exempt from this requirementplease state the reason below.

Comité Ética de Experimentación Humana de la Universidad de Las Palmas de Gran Canaria

Please detail the consent procedure used for human participants or for animal owners. If not applicable, please state this.

Before volunteering, subjects received full oral and written information about the experiments and possible risks associated withparticipation. Written consent was obtained from each subject. The study was performed by the Helsinki Declaration.

In review

Please detail any additional considerations of the study in cases where vulnerable populations were involved, for exampleminors, persons with disabilities or endangered animal species. If not applicable, please state this.

Not applicable

In review

Task failure during exercise to exhaustion in normoxia and hypoxia is due to reduced muscle activation caused by central mechanisms while muscle metaboreflex does limit performance Rafael Torres-‐Peralta1,2, David Morales-‐Alamo1, 2, Miriam González-‐Izal3, José Losa-‐Reyna1,2; Ismael Pérez-‐Suárez1,2, Mikel Izquierdo3, José A.L. Calbet1,2. 1 Department of Physical Education, University of Las Palmas de Gran Canaria, Campus Universitario de Tafira s/n, Las Palmas de Gran Canaria, 35017, Spain.

2 Research Institute of Biomedical and Health Sciences (IUIBS), Las Palmas de Gran Canaria, Canary Islands, Spain.

3 Department of Health Sciences, Public University of Navarra, Tudela, Navarra 31500, Spain.

Running title: Metaboreflex activation and fatigue in normoxia and severe acute hypoxia Correspondence to: José A L Calbet

Departamento de Educación Física, Campus Universitario de Tafira,

35017 Las Palmas de Gran Canaria, Canary Island, Spain.

Tel: 0034 928 458 896

Fax: 0034 928 458 867

email: [email protected]

In review

2

Abstract 1

To determine whether task failure during incremental exercise to exhaustion (IE) 2

is principally due to reduced neural drive and increased metaboreflex activation 3

eleven men (22±2 years) performed a 10s control isokinetic sprint (IS; 80 rpm) 4

after a short warm-‐up. This was immediately followed by an IE in normoxia (Nx, 5

PIO2:143 mmHg) and hypoxia (Hyp, PIO2:73 mmHg) in random order an separated 6

by a 120 min resting period. At exhaustion, the circulation of both legs was 7

occluded instantaneously (300 mmHg) during 10 or 60s to impede recovery and 8

increase metaboreflex activation. This was immediately followed by and IS with 9

open circulation. Electromyographic recordings were obtained from the vastus 10

medialis and lateralis. Muscle biopsies and blood gases were obtained in separate 11

experiments. During the last 10s of the IE, pulmonary ventilation, VO2, power 12

output and muscle activation were lower in hypoxia than in normoxia, while 13

pedaling rate was similar. Compared to the control sprint, performance (IS-‐14

Wpeak) was reduced to a greater extent after the IE-‐Nx (11% lower P<0.05) than 15

IE-‐Hyp. The root mean square (EMGRMS) was reduced by 38 and 27% during IS 16

performed after IE-‐Nx and IE-‐Hyp, respectively (Nx vs. Hyp: P<0.05). Post-‐17

ischemia IS-‐EMGRMS values were higher than during the last 10s of IE. Sprint 18

exercise mean (IS-‐MPF) and median (IS-‐MdPF) power frequencies, and burst 19

duration, were more reduced after IE-‐Nx than IE-‐Hyp (P<0.05). Despite increased 20

muscle lactate accumulation, acidification, and metaboreflex activation from 10 to 21

60s of ischemia, IS-‐Wmean (+23%) and burst duration (+10%) increased, while IS-‐22

EMGRMS decreased (-‐24%, P<0.05), with IS-‐MPF and IS-‐MdPF remaining 23

unchanged. In conclusion, close to task failure, muscle activation is lower in 24

In review

3

hypoxia than in normoxia. Task failure is predominantly caused by central 25

mechanisms, which recover to great extent within one minute even when the legs 26

remain ischemic. There is dissociation between the recovery of EMGRMS and 27

performance. The reduction of surface electromyogram MPF, MdPF and burst 28

duration due to fatigue is associated but not caused by muscle acidification and 29

lactate accumulation. Despite metaboreflex stimulation, muscle activation and 30

power output recovers partly in ischemia indicating metaboreflex activation has a 31

minor impact on sprint performance. 32

33

34

Keywords: Fatigue, electromyography, exhaustion, EMG, lactate, high-‐intensity, 35

hypoxia, performance 36

In review

4

Abbreviations. 37

ADP: Adenosine diphosphate 38

ATP: Adenosine triphosphate 39

CNS; Central nervous system 40

d.w.: Dry weight 41

DEXA: Dual-‐energy x-‐ray absorptiometry 42

EMG: Surface electromyogram 43

EMGRMS: Root mean square of the EMG 44

FIO2: Inspired oxygen fraction 45

HR: Heart rate 46

HRmax: Maximal heart rate 47

Hyp: Hypoxia 48

Hypb: session in hypoxia with biopsies taken 49

IE: Incremental exercise to exhaustion 50

MPF: Mean power frequency 51

MdPF: Median power frequency 52

MVC: Maximal voluntary contraction 53

Nx: Normoxia 54

Nxb: Session in normoxia with biopsies taken 55

PaO2: Arterial oxygen pressure 56

PCr: Phosphocreatine 57

PIO2: Inspired O2 pressure 58

RMS: root mean square 59

RMSNz: Normalized root mean square 60

VE: Minute ventilation 61

In review

5

VO2: Oxygen consumption 62

VO2max: Maximal oxygen uptake 63

VO2peak: Peak oxygen uptake 64

Wpeak-‐i: Instantaneous peak power output 65

Wmax: Peak power output at exhaustion during the incremental exercise test 66

Wmean: mean power output during the 10s sprints 67

w.w.: wet weight 68

TAI: Total activation index 69

In review

6

Introduction 70

Muscle fatigue has been defined as “any exercise-‐induced reduction in the ability 71

to exert muscle force or power, regardless of whether the task can be sustained 72

(Bigland-‐Ritchie & Woods, 1984), that can be reversed by rest” (Gandevia, 2001). 73

The mechanisms leading to task failure may involve physiological processes at 74

neural (central fatigue) or muscular levels (peripheral fatigue), with failure at the 75

neuromuscular junction included in the “peripheral” component (Gandevia, 2001). 76

It has been suggested that the rate of muscle fatigue development is regulated by 77

the central nervous system (CNS) with feedback from the type III and IV muscle 78

afferents (Amann & Dempsey, 2008), which sense metabolite accumulation, 79

particularly H+, lactate and ATP (Light et al., 2008). Type III/IV muscle afferents 80

have been reported to inhibit corticospinal drive (Amann & Dempsey, 2008; 81

Rossman et al., 2012; Kennedy et al., 2015), with greater inhibitory effect on 82

extensor than flexor muscles (Martin et al., 2006). However, whether metabolite 83

accumulation and the expected metaboreflex stimulation impair muscle activation 84

and limit peak power during whole body sprint exercise remains unknown. 85

During whole-‐body exercise in severe acute hypoxia the level of peripheral 86

fatigue at exhaustion seems lower, indicating that central mechanisms, likely 87

linked to reduced brain oxygenation (Rasmussen et al., 2010), predominate over 88

local mechanisms in determining the cessation of exercise (Amann et al., 2007). In 89

agreement with this hypothesis, an instantaneous increase of the inspired O2 90

fraction (FIO2) from 0.21 to 1.00 does not eliminate muscle fatigue at the end of an 91

incremental exercise test performed at sea level (Calbet et al., 2003a). In contrast, 92

during constant-‐intensity or incremental exercise to exhaustion in severe hypoxia 93

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(PIO2 ≈75 mmHg), muscle fatigue is swiftly relieved by mild hyperoxic gas or room 94

air (Amann et al., 2007; Calbet et al., 2003a; Calbet et al., 2003b; Kayser et al., 95

1994). These findings led to the concept that during incremental exercise to 96

exhaustion in normoxia, task failure is most likely caused by peripheral 97

mechanisms while central mechanisms prevail in severe hypoxia (Amann et al., 98

2007; Calbet et al., 2003a). In support, peripheral fatigue, as assessed via decreases 99

in potentiated quadriceps twitch force two minutes after constant-‐intensity 100

exercise to exhaustion, was lower when the exercise was performed in severe 101

hypoxia than in normoxia (Amann et al., 2007). Nevertheless, this observation was 102

not accompanied by an assessment of muscle metabolites and obviates the fact 103

that reduced potentiated quadriceps twitch force may occur without reduction of 104

peak power output (Hureau et al., 2014; Fernandez-‐del-‐Olmo et al., 2013). 105

Moreover, the recovery process starts as early as muscle contraction ceases, and 106

given the fast kinetics of phosphocreatine re-‐synthesis at the end of exercise 107

(Bogdanis et al., 1996; Yoshida et al., 2013; Dawson et al., 1997), most of the 108

recovery has already occurred within the first two minutes post-‐exercise (Sargeant 109

& Dolan, 1987). Also, muscle fatigue is task-‐specific (Gandevia, 2001), implying 110

that a procedure using a similar pattern of movement, and hence recruitment of 111

neural pathways, is expected to be more sensitive to detect fatigue. 112

It is assumed that central fatigue occurs when the force elicited during a 113

maximal isometric contraction can be increased by superimposing a direct 114

(electrical or magnetic) stimulation of the muscle, nerve or motor cortex 115

(Rasmussen et al., 2010; Fernandez-‐del-‐Olmo et al., 2013; Goodall et al., 2012; 116

Goodall et al., 2010). However, if the superimposed stimulation does not elicit a 117

higher level of force, then it is assumed that the mechanism causing muscle fatigue 118

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is primarily peripheral if accompanied by a reduced potentiated twitch force. 119

Nevertheless, few minutes after a 30 s all out sprint exercise (Wingate test) 120

potentiated quadriceps twitches indicate substantial peripheral fatigue, when at 121

the same time peak power output has completely recovered (Fernandez-‐del-‐Olmo 122

et al., 2013). Moreover, every possible combination of effects and interpretation of 123

results has been reported in regard to the contribution of central and peripheral 124

mechanisms to muscle fatigue after dynamic contractions in normoxia (Fernandez-‐125

del-‐Olmo et al., 2013; Sidhu et al., 2012; Sidhu et al., 2009; Marcora & Staiano, 126

2010) and hypoxia (Amann et al., 2007; Goodall et al., 2010; Millet et al., 2012). 127

Some of these discrepancies can be attributed to the facts that neural mechanisms 128

of muscle fatigue are task-‐specific (Sidhu et al., 2012), and to different levels of 129

input from type III and IV muscle afferents (Sidhu et al., 2012). Although the 130

inhibition of type III and IV muscle afferents has been shown to attenuate muscle 131

fatigue in certain exercise models (Sidhu et al., 2014), whether type III and IV 132

muscle afferent input contributes to reduce exercise performance by a central 133

mechanism remains controversial (Kennedy et al., 2015; Millet et al., 2012; Millet 134

et al., 2009; Marcora, 2010; Amann et al., 2013). Part of the discrepancies may be 135

due to the fact that type III and IV muscle afferent discharge cannot be directly 136

measured during whole-‐body exercise in humans, combined with the difficulty in 137

interpreting the effects intrathecal fentanyl when this drug differently alters 138

ventilation, arterial O2 content, arterial PaCO2, heart rate and mean arterial blood 139

pressure, depending on the exercise intensity, exercise duration, and the study 140

population (Poon & Song, 2015; Olson et al., 2014; Dempsey et al., 2014). Thus, we 141

decided to explore the role of III/IV muscle afferents on exercise performance 142

(peak power output) using a completely different experimental approach. 143

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9

Therefore, the main aim of this investigation was to determine whether task 144

failure during an incremental exercise to exhaustion is principally due to central 145

mechanisms that cause a reduction in neural activation, modulated by the level of 146

oxygenation. Another aim was to determine if increased afferent feedback from 147

metabolite accumulation in an exhausted muscle has a negative influence on sprint 148

performance by reducing neural activation, as assessed through electromyogram 149

(EMG) recordings. 150

We aimed to test these two hypotheses: i) task failure during incremental 151

exercise to exhaustion in hypoxia occurs with lower levels of muscle activation 152

compared to normoxia, and ii) increased afferent feedback from III and IV muscle 153

afferents impairs sprint performance. 154

155

Methods 156

Subjects 157

Eleven healthy men (age: 21.5±2.0 years, height: 174±8 cm, body mass: 72.3±9.3 158

kg, body fat: 16.1±4.9%, VO2max: 51±5 mL.kg-‐1.min-‐1) agreed to participate in this 159

investigation. Before volunteering, subjects received full oral and written 160

information about the experiments and possible risks associated with 161

participation. Written consent was obtained from each subject. The study was 162

performed by the Helsinki Declaration and was approved by the Ethical Committee 163

of the University of Las Palmas de Gran Canaria (CEIH-‐2010-‐01 and CEIH-‐2009-‐164

01). 165

166

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General overview 167

This study was a part of a larger project that included several experiments 168

designed to address the mechanisms limiting whole body exercise performance in 169

humans. The results focusing on O2 transport and muscle metabolism have been 170

published (Morales-‐Alamo et al., 2015; Calbet et al., 2015). Body composition was 171

determined by dual-‐energy x-‐ray absorptiometry (DEXA) (Hologic QDR-‐1500, 172

Hologic Corp., software version 7.10, Waltham, MA) (Calbet et al., 1997), during the 173

familiarization sessions. The leg muscle mass was calculated from the DEXA scans 174

using Wang's et al. model (Wang et al., 1999). 175

The experimental protocol is summarized in Figure 1, and an example of the 176

electromyographic recordings from one subject is given in Figure 2. On the 177

experimental days, subjects reported to the laboratory at 08.00 h. after an 178

overnight fast from 22.00 h. The subjects performed an incremental exercise test 179

to exhaustion in normoxia (PIO2: ~143 mmHg) or acute hypoxia (PIO2: ~73 mmHg, 180

Altitrainer200, SMTEC, Switzerland), in random order and separated by a 120 min 181

rest. Before the exercise test, bilateral cuffs were placed around the thighs and 182

connected to a rapid cuff inflator (SCD10, Hokanson E20 AG101, Bellevue, USA). 183

The test started with a warm-‐up (2 min at 50 W + 2 min 100 W + 1 min at 160 W) 184

followed by 4.5 min of slow unloaded pedaling. This was followed by a 30 s rest 185

period while the subjects became ready to sprint at the 5th minute after the end of 186

the warm-‐up. The volunteers were requested to sprint as hard and fast as possible 187

during 10 s with the ergometer set in isokinetic mode and at 80 rpm (Excalibur 188

Sport 925900, Lode, Groningen, The Netherlands). This sprint was used as a 189

control sprint and was always performed in normoxia. Five minutes later, the 190

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11

incremental exercise began. For the test in normoxia, the load was increased by 30 191

W every 2 min until exhaustion, starting from an initial load of 80 W. In hypoxia, 192

the incremental test started from 60 W, and the load was increased by 20 W every 193

2 min until exhaustion. Exhaustion during the incremental exercise tests was 194

defined by the subject stopping pedaling or dropping pedaling rate below 50 rpm 195

during 5 s, despite strong verbal encouragement. At exhaustion, the cuffs were 196

inflated at maximal speed and pressure (i.e., 300 mmHg) to completely and 197

instantaneously occlude the circulation (ischemia). This prevented any increase of 198

oxygenation during the recovery and caused anoxia within 3-‐5s of the application 199

of the occlusion as reported elsewhere (Morales-‐Alamo et al., 2015). A limitation of 200

previous studies was that the impact of the early recovery could not be accounted 201

for (Marcora & Staiano, 2010; Coelho et al., 2015), and certainly some recovery 202

occurs during the time elapsed between the end of the exercise and the start of the 203

sprint. To circumvent this limitation we applied complete ischemia during the 204

recovery and we used short (10 s) and long (60 s) ischemia periods. We surmised 205

that peripheral fatigue would be exacerbated by the prolonged ischemia at the end 206

of an incremental exercise to exhaustion. 207

The incremental exercise test in normoxia and hypoxia ended with two 208

different periods of ischemia of 10 or 60s. Following a countdown, the subject 209

performed a 10 s isokinetic sprint as hard and fast as possible while the ergometer 210

was set at 80 rpm. The cuffs were always instantaneously deflated at the beginning 211

of the post-‐ischemia sprints. In the unfatigued state, peak power increases with 212

pedaling rate, but peak power is less affected by pedaling rate in the fatigued state 213

(Beelen & Sargeant, 1991). Importantly, the difference in peak power between the 214

fatigued and unfatigued state increases the higher the pedaling rate used in the 215

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12

control sprint (unfatigued) (Beelen & Sargeant, 1991). Thus to avoid the 216

limitations associated with varying pedaling rates sprints were performed in 217

isokinetic mode at 80 rpm, a pedaling rate that allows maximal power output in 218

the fatigued state (Beelen & Sargeant, 1991). 219

A few weeks later, the IEs were repeated in two additional experimental 220

sessions; one day in normoxia (Nxb, PIO2: ~143 mmHg) and the other in hypoxia 221

(Hypb, PIO2: ~73 mmHg; “b” indicates biopsy session). In the Nxb session, after 10 222

min rest in the supine position, a muscle biopsy was obtained from the m. vastus 223

lateralis with local anesthesia (lidocaine 2%, 2 ml), using the Bergstrom technique 224

with suction (Bergstrom, 1962). This biopsy was obtained with the needle pointing 225

distally with 45° inclination (Guerra et al., 2011). An additional incision was 226

performed before the beginning of the exercise in the contralateral leg. Afterward, 227

the incisions were covered with a transient plaster, and a cuff was placed around 228

the left leg. The subjects then sat on the cycle ergometer and resting 229

measurements were performed. Two minutes later, the IE was begun as described 230

above. At exhaustion, the cuff was inflated instantaneously at 300 mmHg, and a 231

biopsy was taken exactly 10 s after the end of the incremental exercise test. The 232

biopsy needle was introduced perpendicular to the thigh. This biopsy was followed 233

by a final biopsy at 60 s with the needle pointing proximally (45° inclination). In 234

the Hypb session, essentially the same procedures were applied. All biopsies were 235

immediately frozen in liquid nitrogen and stored at -‐80 °C. Hypb and Nxb sessions 236

were performed in random order. 237

238

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13

Power output and oxygen uptake 239

Power output during the sprint was reported as instantaneous peak power output 240

(Wpeak-‐i) and mean power output (Wmean) during the 10 s duration of the sprint. 241

Oxygen uptake was measured with a metabolic cart (Vmax N29; Sensormedics, 242

Yorba Linda, California, USA), calibrated before each test according to the 243

manufacturer instructions, with high-‐grade calibration gasses (Carburos Metálicos, 244

Las Palmas de Gran Canaria, Spain). Respiratory variables were analyzed breath-‐245

by-‐breath and averaged every 20 s during the incremental exercise tests. The 246

highest 20-‐s averaged VO2 recorded in normoxia was taken as the VO2max. The 247

same criterion was applied to determine the VO2peak in hypoxia. 248

249

Muscle metabolites 250

From each muscle biopsy, 30 mg of wet tissue were freeze-‐dried, cleaned and 251

powdered with a manual mortar on ice. Subsequently, the samples were 252

suspended in 0.5 M HClO4 and centrifuged at 15000 g at 4 °C for 15 min. The 253

supernatant was neutralized with KHCO3 2.1M. ATP, phosphocreatine (PCr), 254

creatine, pyruvate and lactate concentrations were enzymatically determined in 255

neutralized extracts by fluorometric analysis (Lowry & Passonneau, 1972; 256

Morales-‐Alamo et al., 2013). 257

258

Electromyography 259

Electrical muscle activation was monitored using surface electromyography 260

(EMG). EMG signals were continuously recorded from the vastus medialis and 261

vastus lateralis. Before the application of the EMG electrodes the skin surface was 262

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14

carefully shaved and wiped with alcohol to reduce skin impedance. Bipolar single 263

differential electrodes were placed longitudinally on the muscles following the 264

SENIAM recommendations (Merletti & Hermens, 2000) and taped to the skin to 265

minimize movement artifacts. The reference electrode was placed on the skin over 266

the acromion. The position of the electrodes was marked on the skin with indelible 267

ink, and these references were used for precise electrode placement on repeated 268

experiments. 269

The EMG signals were acquired using a 16-‐channel recording system 270

(Myomonitor IV, Delsys Inc., Boston, MA) at a sampling rate of 1000 Hz using 271

rectangular shaped (19.8 mm wide and 35 mm long) bipolar surface electrodes 272

with 1 x 10 mm 99.9% Ag conductors, and with an inter-‐conductor distance of 10 273

mm (DE-‐2.3 Delsys Inc). The EMG data were filtered with a high-‐pass filter of 20 274

Hz and a low-‐pass filter of 450 Hz using a fifth-‐order Butterworth filter. The 275

system has an input impedance of >1015Ω per 0.2pF of input capacitance, a 276

common mode rejection ratio of >80 dB, signal-‐to-‐noise ratio < 1.2 μV, and a pre-‐277

amplifier gain 1000 V/V ±1%. Each pedal revolution was detected using an 278

electrogoniometer (Goniometer Biosignal Sensor S700 Joint Angle Shape Sensor; 279

Delsys Inc. Boston) fixed on the left knee and sampled at 500 Hz. EMG and joint 280

movement were simultaneously recorded by a portable device (Myomonitor IV, 281

Delsys Inc. Boston) and wirelessly transmitted to a computer (EMGWorks Wireless 282

application and EMGWorks Acquisition 3.7.1.3; Delsys, Inc. Boston). 283

The EMG signal corresponding to each muscle contraction was analyzed 284

using code developed ‘in house’ (Matlab R2012b, MathWorks, Natick, MA, USA). 285

The EMG recordings were full-‐wave rectified and to provide an index of muscle 286

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15

activation, the amplitude characteristics were analyzed via average RMS of a 25-‐287

ms moving window for the duration of the burst. Burst onset and offset detection 288

were determined using 20% of the maximal EMGRMS activity of each burst as a 289

reference (Hug & Dorel, 2009; Baum & Li, 2003; Torres-‐Peralta et al., 2014), rather 290

than a mean threshold value from 15 consecutive bursts (Ozgunen et al., 2010). 291

This approach yielded the same result as direct, simple visual discrimination, with 292

100% detection of all bursts. The EMGRMS recorded during the last minute of a 2 293

min 80 W load (in normoxia) was used to normalize the remaining EMGRMS data. 294

Besides, we defined a total activity index during the sprint (TAI) as TAI = EMGRMS x 295

burst duration (ms) x number of pedal strokes during the sprint. The total activity 296

index is similar to the integrated EMG signal, but was computed separately for 297

each burst and excluded the baseline EMG between burst (Torres-‐Peralta et al., 298

2014). The TAI recorded during the last minute of a 2 min 80 W load (in normoxia) 299

was used to normalize the rest of the TAI values. 300

The mean (MPF) and median (MdPF) power spectrum frequencies were 301

calculated using Fast Fourier Transform (Solomonow et al., 1990). All variables 302

were reported as the mean values of the pedal strokes recorded during the last 10 303

s of the incremental exercise or the 10 s sprints. EMG variables responded 304

similarly during the four control sprints. Therefore, to reduce EMG variability the 305

four control sprints were averaged. EMG data are reported separately for vastus 306

medialis and lateralis, and also as the average of the two muscles. Since the 307

incremental exercise tests in normoxia and hypoxia were repeated, the mean of 308

each pair was used in further analysis to represent either normoxia or hypoxia. 309

310

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16

Statistics 311

Normal distribution of variables was checked with the Shapiro-‐Wilks test. A 312

repeated-‐measures ANOVA with FIO2 condition (normoxia vs. hypoxia) and 313

occlusion duration (10 vs. 60 s) was used to analyze the responses observed 314

during the sprints. Pairwise comparisons at specific time points were performed 315

with Student t-‐tests, and adjusted for multiple comparisons using the Holm–316

Bonferroni method. Values are reported as the mean ± standard deviation (unless 317

otherwise stated). P ≤ 0.05 was considered statistically significant. All statistical 318

analyses were performed using SPSS v.15.0 for Windows (SPSS Inc., Chicago, IL) 319

and Excel 2011 (Microsoft, Redmond, WA, USA). 320

321

Results 322

Incremental exercise 323

Compared to normoxia, Wmax, pulmonary ventilation, respiratory rate, heart rate 324

and VO2peak were reduced during the last 10 s of exercise in hypoxia. Additional 325

information regarding the respiratory and cardiovascular responses to the IE can 326

be found elsewhere (Morales-‐Alamo et al., 2015; Calbet et al., 2015). The 327

ergospirometric variables corresponding to the last 10 s of incremental exercise 328

are reported in Table 1, together with the corresponding electromyographic 329

responses. 330

331

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17

Muscle fatigue 332

Sprint performance was reduced at the end of the IEs (Fig. 3), as previously 333

reported (Morales-‐Alamo et al., 2015). Compared to the control sprints, post-‐IE 334

sprint performance was reduced (32-‐46%, P<0.05). Sprint Wpeak-‐i was 11% 335

lower following post-‐IE in normoxia than hypoxia. Similar effects were observed in 336

Wmean. Sprint performance was improved after ischemic recovery. Wpeak-‐I and 337

Wmean were 11 and 23% higher, respectively, following 60 than 10 s of occlusion 338

(P<0.05), as previously reported (Morales-‐Alamo et al., 2015). 339

340

EMG responses 341

Vastus lateralis EMGs. Figure 2 depicts an example of the EMG recordings during 342

one experimental day. During the last 10 s of the incremental exercise to 343

exhaustion the raw (average of the two muscles) and normalized RMS was 16% 344

lower in hypoxia than in normoxia, respectively (P<0.05) (Table 1). The average 345

normalized TAI was also lower (23%) in hypoxia than in normoxia (P<0.001). The 346

median frequency was 6% lower in normoxia than hypoxia (P<0.05). The mean 347

and median frequencies during the last 10s of the IE remained at the same level 348

during the subsequent sprints. 349

The average RMS, RMSNz, and TAINz were 1.6, 1.7 and 2.9-‐fold higher 350

during the sprints post-‐IE than during the last 10s of the IE (all, P<0.05). Compared 351

to the control sprints, the RMSraw and the normalized RMSNz were reduced by 36 352

and 35%, respectively, in the sprints performed after the IE (Table 2). Although the 353

60s occlusion caused a 14% lower RMSNz compared to the 10s occlusion, this 354

difference did not reach statistical significance (Main effect P=0.059). Compared to 355

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18

the control sprints the TAINz was reduced by 42 and 34% after the incremental 356

test in normoxia and hypoxia, respectively (P<0.05). 357

Compared to the control sprint, the median frequency was reduced by 18 358

and 9% following the IEs in normoxia and hypoxia, respectively (both, P<0.05) 359

(Table 3). Thus, the median frequency was 9% lower in the sprints following IE in 360

normoxia than in hypoxia (Main effect P=0.011). MPF changes were essentially 361

similar to MdPF (Tables 1, 2, 3, and 4). 362

Compared to the control sprints, the duration of the bursts was reduced by 363

9% in the sprints performed after 10s occlusions. Nevertheless, after 60 s of 364

occlusion, the duration of burst in the following sprints achieved the same value as 365

in the control sprints (331.9±24.6 and 331.0±29.7 ms, control and 60s after IE, 366

respectively, P=0.91). The duration of the bursts was 3% longer in the sprints that 367

followed an IE in hypoxia than normoxia (P=0.03). The average contraction time 368

(i.e., burst duration x pedaling rate) was 15% lower during the last 10 s of IE than 369

during the post-‐IE sprints (P<0.001). 370

Vastus medialis EMGs. The vastus medialis EMG responses to incremental (Tables 371

1) and sprint exercise (Table 3) were similar to those described for the vastus 372

lateralis. Therefore, we combined both vastus EMGs responses to reduce variability 373

(Table 4). The combined response was similar to that reported for vastus lateralis 374

and medialis, but with lower variability, confirming some of the effects that did not 375

reach statistical significance when only analysed using a single muscle EMG 376

recordings. 377

378

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19

Muscle metabolites 379

Muscle metabolites and the aerobic and anaerobic energy yield during the sprints 380

have been reported elsewhere (Morales-‐Alamo et al., 2015). Briefly, ATP and PCr 381

concentrations were reduced to a similar extent both in normoxia and hypoxia 382

(ANOVA time effect: P<0.05). From the 10th to 60th s of ischemic recovery ATP 383

concentration remained unchanged while PCr declined an additional ~5% (ANOVA 384

time effect: P<0.05 compared to Post and P<0.001, compared to PRE). Muscle 385

lactate concentration was increased to similar values 10 s after both incremental 386

exercise tests (93.5±24.3 and 88.3±26.6 mmol kg d.w.-‐1, in normoxia and hypoxia, 387

respectively (ANOVA time effect: P<0.001). From the 10th to 60th s of ischemia 388

muscle lactate was increased by 24.0±20.7 and 21.6±24.5 mmol kg d.w.-‐1, and 389

muscle pH reduced by 0.102±0.040 and 0.109±0.041 units, after the IE in 390

normoxia and hypoxia, respectively (ANOVA time effect: P<0.01). 391

392

Discussion 393

This investigation confirms, in agreement with previous studies using constant 394

intensity (Marcora & Staiano, 2010) and incremental exercise to exhaustion in 395

normoxia (Coelho et al., 2015), that task failure during incremental exercise in 396

normoxia is not caused by muscle fatigue. The present study extends these 397

findings to whole-‐body incremental exercise in severe hypoxia. We have also 398

shown that muscle activation during the last 10 s of an incremental exercise to 399

exhaustion is lower in severe hypoxia than in normoxia. This reduction in muscle 400

activation cannot be explained by differences in metabolite accumulation between 401

hypoxia and normoxia, and likely reflects central mechanisms of fatigue, which 402

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20

recovered, at least partly, during the next 10 or 60s of ischemia, as reflected by the 403

greater activation of the muscles during the subsequent sprint. The latter occurred 404

despite the lower energy availability and the greater accumulation of metabolites 405

after the ischemic recoveries. We have shown that muscle fatigue, as assessed 406

through sprint performance, at the end of an incremental exercise to exhaustion, is 407

lower when the exercise is performed in severe acute hypoxia than in normoxia 408

despite similar muscle metabolite accumulation. This is also compatible with the 409

incremental exercise in hypoxia ending by central mechanism/s acting earlier, i.e., 410

with a lower amount of peripheral fatigue in hypoxia than in normoxia. This 411

reduction in sprint performance is accompanied by a greater reduction in muscle 412

activation (as reflected by the EMGRMS changes) in the sprints carried out after IE 413

in normoxia than hypoxia. This could be interpreted as indicative of slower 414

recovery of central fatigue after the IE performed in normoxia than hypoxia. 415

Strikingly, following 60 s of recovery with complete occlusion of the circulation 416

sprint performance was higher than that observed immediately following 10 s of 417

occlusion, as previously reported (Morales-‐Alamo et al., 2015). This improvement 418

in performance was achieved with lower EMGRMS compared to the sprints executed 419

after 10s of ischemia. Thus, this investigation demonstrates dissociation between 420

the recovery of the EMGRMS and the recovery of power output. Since occlusion 421

resulted in an increase of muscle lactate and H+ accumulation from 10 s to 60 s of 422

occlusion (Morales-‐Alamo et al., 2015), the present experiments support the 423

concept that muscle acidification reduces the EMGRMS without necessarily 424

reflecting increased muscle fatigue or reduced muscle activation by the central 425

nervous system. In addition, we have demonstrated that despite similar muscle 426

concentrations of lactate and H+ at the beginning of the respective sprints, the MPF 427

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21

and MdPF during sprint exercise are reduced by muscle fatigue when the sprint is 428

performed after an incremental exercise in normoxia, but not in hypoxia. MPF and 429

MdPF did not recover from the end of the incremental exercise to the start of the 430

sprints, or from the 10th to the 60th second of ischemia, despite cessation of neural 431

activation and appropriate oxygenation of the brain. These results point to 432

peripheral mechanisms being primarily responsible for the reduction of MPF and 433

MdPF during the sprints post-‐IE (Brody et al., 1991; Juel, 1988). Moreover, despite 434

greater lactate and H+ accumulation after 60 s of ischemic recovery, sprint exercise 435

MPF and MdPF were not further reduced; therefore these two metabolites do not 436

seem to account for the observed reduction of MPF and MdPF with muscle fatigue 437

(Vestergaard-‐Poulsen et al., 1995). We have also shown that the duration of the 438

bursts is reduced in fatigued muscles contracting under isokinetic conditions, 439

recovering to non-‐fatigued levels within 60 s, regardless of the muscular 440

concentrations of lactate and H+. We lastly provided evidence for a minor impact, if 441

any, of increased group III/IV afferent feedback on sprint exercise performance. 442

443

Surface EMG changes are more sensitive to central than peripheral fatigue 444

To demonstrate the existence of central fatigue it is necessary to show that during 445

a maximal voluntary contraction, direct stimulation of motor neural pathways or 446

cortical motoneurons results in greater levels of force than elicited voluntarily 447

(Gandevia et al., 1996; Merton, 1954). These procedures have several constraints 448

limiting their application to complex tasks, such as pedaling. To circumvent these 449

problems, a commonly used approach has been to carry out potentiated and 450

interpolated twitch assessments at exhaustion as fast as possible, i.e., 1-‐2 minutes 451

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22

after the task failure, when most of the reduction in power output has already been 452

recovered (Fernandez-‐del-‐Olmo et al., 2013; Sargeant & Dolan, 1987; Coelho et al., 453

2015). Another limitation of stimulation techniques is that muscle fatigue is task-‐454

specific (Gandevia, 2001). Stimulation techniques cannot reproduce the 455

complexity of motor orders involving thousands of motor units from different 456

muscles firing at different rates, which are recruited with specific timings to 457

achieve a coordinated movement. Also, in fatigued muscles, the increase in force 458

elicited by an interpolated twitch may be due in part to intracellular mechanisms 459

(i.e., a peripheral mechanism that is likely related to the force/[Ca2+]i relationship 460

(Gandevia et al., 2013), not necessarily reflecting increased central fatigue. 461

An alternative approach for assessing muscle fatigue is to measure the 462

maximal power that can be generated during the task that elicits muscle fatigue 463

(Marcora & Staiano, 2010; Coelho et al., 2015; Cairns et al., 2005). However, during 464

whole-‐body exercise on the cycle ergometer, pedaling frequency slows down close 465

to task failure (Torres-‐Peralta et al., 2014). Given the dependency of power on 466

muscle contraction velocity, fatigue should ideally be tested under similar muscle 467

contraction velocities as during isokinetic pedaling (Sargeant & Dolan, 1987). 468

In the present experiments, the sprints were performed in isokinetic 469

conditions, i.e., the duration of each pedaling cycle was always the same, regardless 470

of the state of muscle fatigue (Fig 2). This isokinetic approach was possible 471

because the cycle ergometer servo-‐control instantaneously varied the resistance 472

applied to the pedals depending on the force exerted resulting in a constant 473

pedaling rate of 80 rpm. These conditions allowed us to examine the impact of 474

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23

fatigue on certain components of the EMG signal without the variability induced by 475

the speed of movement. 476

At a given pedaling rate, the duration of contraction bursts increases with 477

the intensity of exercise, reaching maximal values at intensities close to Wmax 478

(Torres-‐Peralta et al., 2014). In all conditions and every subject, the mean intensity 479

achieved during the 10 s sprints was above the intensity reached at exhaustion 480

during the IEs. This result implies that concerning intensity, burst duration should 481

be maximal during all sprints. However, burst duration during the sprints 482

performed after 10 s of ischemic recovery was reduced, meaning that muscles 483

were activated during a shorter fraction of the pedaling cycle. This effect might 484

have been caused by reduced sarcolemmal excitability as a consequence of fatigue 485

(Sidhu et al., 2012; Sejersted & Sjogaard, 2000), but sarcolemmal excitability 486

appears to recover in less than 60 s after a fatiguing whole-‐body sprint exercise 487

(Fernandez-‐del-‐Olmo et al., 2013). In agreement, burst duration recovered within 488

the 60 s of ischemic rest after both IEs. Despite the observed recovery of burst 489

duration, the EMGRMS was further reduced following 60 s of ischemia. Since the 490

reduction in EMGRMS was accompanied by increased power output and normal 491

burst duration, it seems unlikely that the lower sprint EMGRMS after 60 s of 492

ischemia originates from a failure of the muscle cells to respond to neural 493

activation. 494

During high-‐intensity contractions, the myosin ATPase and ion pumps 495

account for most of the energy expenditure in muscles because no energy can be 496

diverted to biosynthetic processes as the required enzymes are blocked. In our 497

experimental conditions, upon cessation of incremental exercise the ion pumps are 498

In review

24

expected to be maximally activated, particularly the Na+-‐K+ pump, which has a 499

critical role in restoring sarcolemmal excitability (Pedersen et al., 2003; Hostrup et 500

al., 2014). During ischemia, the energy needed to maintain the activity of the ion 501

pumps was provided by the glycolysis and to a lesser extent by the small amount 502

of remaining PCr (Morales-‐Alamo et al., 2015). Any small amount of O2 bound to 503

myoglobin was rapidly used upon occlusion due to the strong activation of 504

mitochondrial respiration by the increased ADP concentration at task failure 505

(Morales-‐Alamo et al., 2015). Femoral vein and mean capillary PO2 was lower at 506

exhaustion after the incremental exercise test in severe hypoxia than in normoxia 507

(Calbet et al., 2015). Therefore, the potential contribution of the small amount of 508

O2 trapped in the occluded leg (or remaining bound to myoglobin) to ATP re-‐509

synthesis should have been lower in hypoxia than in normoxia. However, although 510

more O2 was available at exhaustion for the initial recovery in normoxia, i.e., within 511

the first 10 s of occlusion, performance was more impaired in the sprint performed 512

after 10 s of ischemic recovery that followed the normoxic rather than the hypoxic 513

IEs. This result concurs with task failure occurring with a lower level of peripheral 514

fatigue during IE in hypoxia than normoxia, as our results indicate. Studies in cats 515

(Hill et al., 1992; Lagier-‐Tessonnier et al., 1993) and rabbits (Arbogast et al., 2000) 516

have shown increased baseline discharge frequency of group III and IV muscle 517

afferents by PO2 close to the values observed in the femoral vein in the present 518

investigation (Calbet et al., 2015). Thus, lower interstitial PO2 values in hypoxia 519

than normoxia could have enhanced III/IV afferent feedback to cause increased 520

inhibition of the corticospinal drive during exercise in severe acute hypoxia, as 521

previously suggested (Calbet et al., 2015). Muscle III and IV afferent, and perhaps 522

other sensory endings in joints and tendons, have been postulated to contribute to 523

In review

25

central fatigue (Amann et al., 2013; 1996; Reid, 1927; Garland, 1991; Amann et al., 524

2008; Bigland-‐Ritchie et al., 1986). Animal studies have shown that when 525

motoneurons are stimulated repetitively many neurons reduce their discharge 526

frequency or stop firing (Kernell & Monster, 1982a; Kernell & Monster, 1982b; 527

Spielmann et al., 1993). This phenomenon is likely accentuated by hypoxia. 528

Consequently, reduced responsiveness of some motoneurons pools (central 529

fatigue) combined with increased III/IV muscle afferent feedback and increased 530

ventilatory demand might have increased the perception of effort (Marcora, 2009), 531

leading to task failure at the end of IE in hypoxia with a lower level of peripheral 532

fatigue than in normoxia (Pierrefiche et al., 1997). Oxygenation upon exhaustion 533

might have restored faster central fatigue at the end of the IE in hypoxia than 534

normoxia, by restoring within seconds normoxic interstitial PO2 levels in the 535

central nervous system. 536

537

Group III and IV muscle afferent stimulation does not limit peak power output during 538

whole body sprint exercise in healthy humans. 539

Group III/IV muscle afferent neurons include a complex family of afferent endings 540

some of which act as nociceptors while others respond to thermal, mechanical or 541

chemical stimulation (Light et al., 2008; Jankowski et al., 2013; McCord & Kaufman, 542

2010). Metabolic products of muscle contraction like H+ (Light et al., 2008; Rotto & 543

Kaufman, 1988), lactate (Light et al., 2008), adenosine (Middlekauff et al., 1997), 544

ATP (Light et al., 2008), nitric oxide (Arbogast et al., 2001), and inflammation 545

mediators may also increase III/IV muscle afferent discharge (Light et al., 2008; 546

McCord & Kaufman, 2010). It is particularly important that the response to the 547

In review

26

isolated increase of H+, ATP and lactate is much lower than observed to the 548

combination of the three (Light et al., 2008). Some metaboreceptive III and IV 549

muscle afferents seem specialized in detecting innocuous levels of metabolites, 550

while others respond to noxious levels and contribute to muscle pain (Kniffki et al., 551

1978; Mense, 1996). It is thought that both low and high concentration 552

responding-‐endings could contribute to sympathetic reflexes and to increase the 553

perception of effort (Light et al., 2008). 554

Using lumbar intrathecal fentanyl administration before exercise to block μ-‐555

opioid receptor-‐sensitive group, Amann and co-‐workers (Amann et al., 2011; 556

Amann et al., 2009) studied the influence of group III and IV afferents on voluntary 557

activation (assessed by the twitch-‐interpolation technique) after constant-‐558

intensity bicycling exercise. After 3 min of recovery, voluntary activation was 559

reduced by 1.2% during the placebo trial (non-‐significant) and 1.7% during the 560

fentanyl trial (Amann et al., 2011). Moreover, 3 min after a time trial that caused 561

fatigue in 7.5 min, voluntary activation was reduced by 1.6% (compared to 0.8% in 562

the placebo trial) (Amann et al., 2009). These results further emphasize that any 563

potentially negative influence of III and IV muscle afferents on voluntary activation 564

is likely small after whole-‐body exercise or that voluntary activation capacity 565

recovers rather quickly (Kennedy et al., 2015; Bigland-‐Ritchie et al., 1986; Pageaux 566

et al., 2015). 567

Amann et al. (2011) reported that despite the inhibition of III and IV 568

afferents, fentanyl markedly reduced performance (from 8.7 to 6.8 min) during a 569

constant-‐intensity trial to exhaustion. In another study by the same group (Amann 570

et al., 2009), where the subjects performed a time trial, performance was similar in 571

In review

27

the fentanyl and placebo experiments. The reason for these discrepant effects of 572

III/IV muscle afferents inhibition on performance is not clear (Marcora, 2010). In 573

the case of the constant-‐intensity trial, there was a substantial impairment in O2 574

transport in the fentanyl trial, an effect caused by reduced ventilation, leading to 575

lower hemoglobin saturation and VO2 with fentanyl than placebo. A slightly lower 576

impairment of O2 transport was reported in the time trial experiments, which 577

could have been compensated for by increased involvement of the anaerobic 578

metabolism (Amann et al., 2009). Marcora et al. (2010) have suggested that during 579

the time trial, the “belief effect” induced by reducing leg muscle pain with fentanyl-‐580

induced a fast start, which compensated for the negative effect of fentanyl on 581

cardiorespiratory responses. As a result, exercise performance was unchanged 582

during the time trial. During the constant-‐intensity trial, the “belief effect” could 583

not induce a fast start and consequently exercise performance was reduced. 584

Interestingly, in both experiments with fentanyl the reduction of quadriceps 585

potentiated twitch forces elicited by magnetic neural stimulation were greater 586

than in the control trials (Amann et al., 2011; Amann et al., 2009). Assuming that a 587

reduction in the force elicited by potentiated twitches indicates a greater level of 588

peripheral fatigue and that the subjects exercised to their limits in all trials, Amann 589

and co-‐workers studies give support to the concept that III/IV afferent feedback is 590

used to set the limit of peripheral fatigue that is permitted. However, these 591

experiments, combined with the present findings, show that task failure at the end 592

of an IE to exhaustion (current study), or at the end of constant-‐intensity (Marcora 593

& Staiano, 2010; Bosio et al., 2012) or a simulated time-‐trial competition (Amann 594

and co-‐workers studies) is not due to a peripheral failure. Both types of 595

experiments show that greater levels of peripheral fatigue are possible, but not 596

In review

28

reached because the exercise ends due to central mechanisms of fatigue (Kayser, 597

2003). The critical question is whether peripheral fatigue causes central fatigue 598

and task failure through a central mechanism by activating the metaboreflex. If the 599

latter is the main mechanism causing central fatigue and task failure a reduction in 600

sprint performance under conditions with increased metaboreflex activation will 601

be expected. However, our results show that this is not the case. 602

Metabolite accumulation at task failure and during ischemia should have 603

promoted a sustained discharge of III/IV muscle afferents (Light et al., 2008; 604

McCord & Kaufman, 2010; Darques & Jammes, 1997; Darques et al., 1998), an 605

effect that would be expected to be greater after 60 than 10 s occlusions in the 606

present investigation. Nevertheless, sprint exercise power output was higher after 607

60 than 10 s of ischemia. Increased metaboreflex activation should exacerbate the 608

ventilatory response to exercise (Amann et al., 2010), as observed during the 609

sprints performed following 60 s of ischemia in the present investigation (Morales-‐610

Alamo et al., 2015). Thus, despite increased metaboreflex activation during the 611

sprints after 60s of ischemia, and a theoretically worsened metabolic situation, 612

peak and mean power output was higher during the sprints after 60 than 10 s of 613

ischemia. Our finding appear to be at odds with the recent study by Kennedy et al. 614

(2015), in which the occlusion of the circulation during 2 min after a 2-‐min 615

sustained MVC of the knee extensors resulted in a progressive reduction of the 616

maximal voluntary contraction (MVC) (See Fig. 3A of Kennedy et al. 2015). This 617

effect was accompanied by a progressive reduction of maximal voluntary 618

activation indicative of increasing central fatigue (See Fig. 3B of Kennedy et al. 619

2015). In agreement with our results, Kennedy et al. (2015) observed a fast 620

recovery of voluntary activation upon release of the cuff, indicating that the 621

In review

29

negative influence of III/IV afferent discharge on voluntary activation was also 622

relieved very rapidly. This quick response could be due to (i) the release of the 623

direct compression on the femoral nerve, (ii) the washout of metabolites combined 624

with oxygenation due to reactive hyperemia, or (iii) the combination of these 625

effects. In our experimental conditions, the hyperemic response to the release of 626

the cuff was likely much greater than in Kennedy et al. (2015) as reflected by the 627

rapid increase of pulmonary VO2 and the elevated heart rate at the beginning of the 628

sprint (Morales-‐Alamo et al., 2015). Another interesting aspect of the study by 629

Kennedy et al (2015) is that the level of peripheral fatigue as assessed by 630

potentiated twitches remained at the same level during the 2 min of ischemia, 631

despite 5 x 2-‐s long MVC maneuvers (i.e., 10 s of maximal contractile activity with 632

occlusion of the circulation). Thus, the 2 min of post-‐exercise ischemia did not 633

worsen peripheral fatigue (Kennedy et al., 2015). Although Kennedy et al. (2015) 634

did not measure muscle metabolites, 10 s of maximal contractile activity during 635

the 2 min of ischemia, in combination with increased metabolic demand due to the 636

preceding MVC (sustained during 2 min), should have increased peripheral fatigue 637

according to the prevailing paradigm. 638

The present investigation strongly suggests that the inhibitory role of 639

muscle afferent discharge on the corticospinal motor drive during maximal 640

intensity whole-‐body exercise is either small or counteracted by a strong 641

corticospinal drive (central command). Otherwise, the III/IV muscle afferent 642

feedback due to ischemia (PO2 close to 0 mmHg in our experimental conditions) 643

and the metabolites accumulated during the IEs should have decreased Wpeak and 644

Wmean during the 10 or 60 s post-‐ischemia sprints below the Wmax achieved at 645

task failure in the IEs. This finding contrasts with experiments using single joint 646

In review

30

(Kennedy et al., 2015; Gandevia et al., 1996) or handgrip dynamic contractions 647

(Broxterman et al., 2015), where a clear inhibition of voluntary activation is 648

consistently shown. 649

In the present investigation, increased III/IV muscle afferent feedback could 650

explain why the observed EMGRMS were lower in the sprints performed after 60 s 651

than after 10 s of ischemia. Likewise, that MPF and MdPF remained at task failure 652

levels during the post-‐IE sprints is also consistent with an on-‐going negative 653

feedback reducing motoneurons firing frequencies (Broxterman et al., 2015). 654

However, the power output achieved during the sprints after 60 s of ischemia is 655

close to the maximal power attainable by our subjects without phosphagens 656

(Morales-‐Alamo et al., 2015), leaving little room for central mechanisms to limit 657

sprint performance after 60 s of ischemia. Thus, it seems that 60 s of ischemic 658

recovery allows for restoration of the central mechanisms of fatigue, despite the 659

discharge from the III/IV muscle afferents. The latter was likely counteracted by a 660

strong central command and a rapid reperfusion of the muscle upon the release of 661

the cuff during the post-‐IE sprints. In agreement with this interpretation, Amann et 662

al. (2009) reported no effect of intrathecal fentanyl on time trial performance, 663

although the power output profile was dramatically changed. 664

665

Reduced sprint EMGMRS but increased power output after 60 than 10 s post-‐exercise 666

ischemia 667

In vitro experiments have shown that lactate and H+ accumulation may facilitate 668

peripheral recovery by increasing chloride conductance (Pedersen et al., 2003; 669

Nielsen et al., 2001; Karelis et al., 2004). Thus, an elevated glycolytic rate combined 670

In review

31

with a progressive rise of muscle temperature due to flow arrest during ischemic 671

recovery could have exerted two opposing actions. Positively, increased glycolysis 672

may have facilitated peripheral recovery by enhancing sarcolemmal excitability 673

(Pedersen et al., 2003), which was likely depressed immediately after the IEs. 674

Negatively, increased glycolysis and the subsequent metabolite accumulation may 675

have increased III/IV muscle afferent discharge, interfering with muscle activation. 676

The combination of both mechanisms could explain the lower EMGRMS values 677

observed during the sprints performed 60 s compared to 10 s after the IEs. If we 678

assume that EMGRMS is a valid index of muscle activation and corticospinal motor 679

output, a greater reduction in sprint EMGRMS after prolonged (60 s) compared to 680

shorter (10 s) ischemia would lead to the untenable conclusion that all of the 681

improvement in Wpeak and Wmean observed from 10 to 60 s of ischemic recovery 682

is due to peripheral mechanisms. Moreover, this peripheral-‐based improvement 683

would have to be sufficient to counteract the reduced motor command. A more 684

plausible explanation is that for a given level of neural activation, EMGRMS is 685

reduced by metabolite accumulation; i.e., EMGRMS does not faithfully reflect the 686

level of neural activation (Vestergaard-‐Poulsen et al., 1995). In agreement with 687

this interpretation, it has been shown that central fatigue recovers rapidly upon 688

cessation of contractile activity, even when peripheral fatigue remains at the same 689

level (Gandevia et al., 1996; Bigland-‐Ritchie et al., 1986). Therefore, the observed 690

reduction in sprint EMGRMS after 60 s compared to 10 s of ischemic recovery is 691

unlikely to be caused by increased central fatigue. 692

693

In review

32

Fatigue reduces the duration of the burst during isokinetic sprints 694

The duration of the burst was similarly decreased in the sprints performed 10 s 695

after the incremental exercise in hypoxia and normoxia. However, sprint power 696

output was greater after the incremental exercise in hypoxia. To generate greater 697

power, more mechanical impulse must be produced. As the duration of the bursts 698

(a surrogate of contraction time) was similar in the sprints performed 10 s after 699

both IEs, the subjects must have applied a greater force on the pedals after the 700

hypoxic IE. Therefore, greater motor cortical drive was required in the sprint that 701

occurred after hypoxia. In agreement, with this conclusion, the MPF and MdPF 702

were higher in the sprints preceded by IE in hypoxia than normoxia, suggesting 703

greater firing rates (Solomonow et al., 1990; Sbriccoli et al., 2003; Gerdle & Fugl-‐704

Meyer, 1992) and a lower degree of central fatigue during the sprint 10 s after the 705

IE in hypoxia. Alternatively, central fatigue could have recovered more rapidly 706

after the IE in hypoxia, likely due to a direct effect of oxygenation on the central 707

nervous system, as previously postulated (Amann et al., 2007; Calbet et al., 2003a; 708

Calbet et al., 2003b; Kayser et al., 1994). 709

710

Perception of effort and psychological factors 711

In our experimental conditions, the perception of effort at exhaustion was always 712

maximal since the subjects exercised to their limits. At the end of the incremental 713

exercise, muscle activation was much lower than during the subsequent sprints, 714

despite the fact muscles remained ischemic. This finding indicates that task failure 715

was not due to muscle fatigue; it was caused by reduced muscle activation. Our 716

data indicate that the central component of fatigue recovered very fast. This 717

In review

33

observation is compatible with a perception of effort-‐mediated task failure 718

(Marcora & Staiano, 2010; Bosio et al., 2012). Subjects stopped because they felt 719

that the effort was unbearable despite strong verbal encouragement. The 10s rest 720

presumably eliminated the perception of effort negative feedback on the motor 721

drive, allowing our subjects to attain the actual amount of power they could 722

generate during the first seconds of the sprint. Thus, the peak power output during 723

the first seconds of the sprint reflects almost exclusively what the muscle and the 724

central nervous system can achieve, in absence of a strong negative feedback from 725

the perception of effort. This is supported by the fact that the peak power output 726

reached during 10 s post-‐IE sprints is close to that expectable in the case of no 727

availability of PCr. Furthermore, the greater power output during the first seconds 728

of the sprint after 60 than 10s of ischemia, can be explained by enhanced muscular 729

recovery facilitated by the glycolysis as recently reported (Morales-‐Alamo et al., 730

2015). 731

Although psychological factors were not analyzed in this study, these could 732

hardly explain the greater improvement of sprint performance observed after 60 733

compared to 10 s occlusions. In fact, all subjects expected to have a lower 734

contractile capacity after the longer occlusions, which were accompanied by more 735

unpleasant feelings than the 10 s occlusions. Our subjects knew that exercise in 736

hypoxia feels more difficult that in normoxia, and this could have affected more 737

their motivation. In the case of a type II error, metabolite accumulation will be 738

compatible with an earlier disengagement from the task during the incremental 739

exercise in hypoxia than normoxia. However, this investigation has shown that it is 740

not the level of muscle lactate or muscle acidification what causes task failure 741

(Morales-‐Alamo et al., 2015), since with much greater lactate accumulation and 742

In review

34

muscle acidification, performance was markedly higher after 60 than 10 s 743

occlusions. Thus, the greater sprint performance 10 s after the incremental 744

exercise in hypoxia compared to normoxia, cannot be attributed to the small 745

(statistically non-‐significant) differences in metabolite accumulation at the end of 746

the respective IE to exhaustion. It remains to be ascertained if task failure during 747

hypoxia is caused by altered corticospinal responsiveness to higher orders or is 748

the consequence of psychological factors, reducing the motivation to maintain a 749

maximal effort (Marcora & Staiano, 2010). 750

751

In summary, task failure at the end of an incremental exercise to exhaustion 752

depends more on central than peripheral mechanisms, as indicated by the fact that 753

the level of muscle activation observed during the last 10s of the incremental 754

exercise was much lower than that reached 10 s later during a 10s sprint, despite 755

the fact that muscle remained ischemic from the end of exercise to the start of the 756

sprint. The central component of fatigue appears to recover to a greater extent, 757

during the first 10 s following an incremental exercise to exhaustion in hypoxia 758

than in normoxia, concomitant with a rapid change to normoxic breathing during 759

the recovery. We have also shown that ischemic recovery after incremental 760

exercise to exhaustion allows for a partial restoration of power output despite 761

increased acidification and reduced EMGRMS. Moreover, this study demonstrates 762

that MPF, MdPF and the duration of the bursts during isokinetic sprints are 763

reduced with fatigue. Lastly, this investigation indicates that increased group III/IV 764

muscle afferent discharge has a minor, if any, negative impact on sprint exercise 765

performance in healthy humans. 766

In review

35

Acknowledgements 767

This study was supported by a grant from the Ministerio de Educación y Ciencia of 768

Spain (DEP2009-‐11638 and FEDER) and VII Convocatoria de Ayudas a la 769

Investigación Cátedra Real Madrid-‐Universidad Europea de Madrid (2015/04RM). 770

Especially thanks are given to José Navarro de Tuero for his excellent technical 771

assistance. 772

773

Author contributions. Conception and design of the experiments: JAC; pre-‐774

testing, experimental preparation, data collection and analysis: RTP, DMA, JLR, IPS, 775

and JAC; EMG analysis: RTP, MGI, and MI. The first version of the manuscript was 776

written by RTP and JAC. All co-‐authors read, contributed comments and approved 777

the final version of the manuscript. 778

779

Conflict of interest 780

None of the authors has any conflicts of interests. 781

782

In review

36

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S. Arbogast, J.L. Darques, F. Bregeon, and Y. Jammes (2001). Effects of endogenous 1003 nitric oxide in activation of group IV muscle afferents. Muscle Nerve 24, 247-‐1004 253. 1005

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S. Mense (1996). Group III and IV receptors in skeletal muscle: are they specific or 1009 polymodal? Prog. Brain Res. 113, 83-‐100. 1010

M. Amann, G.M. Blain, L.T. Proctor, J.J. Sebranek, D.F. Pegelow, and J.A. Dempsey 1011 (2011). Implications of group III and IV muscle afferents for high-‐intensity 1012 endurance exercise performance in humans. J. Physiol. 589, 5299-‐5309. 1013

M. Amann, L.T. Proctor, J.J. Sebranek, D.F. Pegelow, and J.A. Dempsey (2009). 1014 Opioid-‐mediated muscle afferents inhibit central motor drive and limit 1015 peripheral muscle fatigue development in humans. J. Physiol. 587, 271-‐283. 1016

B. Pageaux, L. Angius, J.G. Hopker, R. Lepers, and S.M. Marcora (2015). Central 1017 alterations of neuromuscular function and feedback from group III-‐IV muscle 1018 afferents following exhaustive high-‐intensity one-‐leg dynamic exercise. Am. J. 1019 Physiol. Regul. 308, R1008-‐1020. 1020

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B. Kayser (2003). Exercise starts and ends in the brain. Eur. J. Appl. 90, 411-‐419. 1024 J.L. Darques, and Y. Jammes (1997). Fatigue-‐induced changes in group IV muscle 1025

afferent activity: differences between high-‐ and low-‐frequency electrically 1026 induced fatigues. Brain Res. 750, 147-‐154. 1027

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M. Amann, G.M. Blain, L.T. Proctor, J.J. Sebranek, D.F. Pegelow, and J.A. Dempsey 1031 (2010). Group III and IV muscle afferents contribute to ventilatory and 1032 cardiovascular response to rhythmic exercise in humans. J. Appl. Physiol. 109, 1033 966-‐976. 1034

R.M. Broxterman, C.J. Ade, J.C. Craig, S.L. Wilcox, S.J. Schlup, and T.J. Barstow 1035 (2015). Influence of blood flow occlusion on muscle oxygenation 1036

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characteristics and the parameters of the power-‐duration relationship. J. 1037 Appl. Physiol. 118, 880-‐889. 1038

O.B. Nielsen, F. de Paoli, and K. Overgaard (2001). Protective effects of lactic acid 1039 on force production in rat skeletal muscle. J. Physiol. 536, 161-‐166. 1040

A.D. Karelis, M. Marcil, F. Peronnet, and P.F. Gardiner (2004). Effect of lactate 1041 infusion on M-‐wave characteristics and force in the rat plantaris muscle 1042 during repeated stimulation in situ. J. Appl. Physiol. 96, 2133-‐2138. 1043

P. Sbriccoli, I. Bazzucchi, A. Rosponi, M. Bernardi, G. De Vito, and F. Felici (2003). 1044 Amplitude and spectral characteristics of biceps Brachii sEMG depend upon 1045 speed of isometric force generation. J. Electromyogr. Kinesiol. 13, 139-‐147. 1046

B. Gerdle, and A.R. Fugl-‐Meyer (1992). Is the mean power frequency shift of the 1047 EMG a selective indicator of fatigue of the fast twitch motor units? Acta 1048 Physiol. Scand. 145, 129-‐138. 1049

1050 1051

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Figure Legends 1053

Figure 1. Experimental protocol. The experimental day started with a warm-‐up 1054

followed by 4.5 min of slow unloaded pedaling and a 30 s resting phase, while the 1055

subjects became ready to perform the first sprint (isokinetic, 10 s at 80 rpm) at the 1056

5th minute after the end of the warm-‐up. This sprint was used as a control sprint 1057

and was always performed in normoxia. Five minutes later, an incremental 1058

exercise to exhaustion began in normoxia (PIO2: ~143 mmHg) or acute hypoxia 1059

(PIO2: ~73 mmHg). The order of the incremental exercise test was randomized. 1060

Between the two incremental exercise tests, the subjects were allowed to rest 1061

during 120 min. At the end of the incremental exercise test, bilateral cuffs were 1062

inflated at maximal speed and pressure (i.e., 300 mmHg) to occlude completely 1063

and instantaneously the circulation (ischemia) of the legs. The incremental 1064

exercise test in normoxia and hypoxia ended with an ischemia period of 10 s on 1065

one experimental day and 60s on another day. The order of the duration of the 1066

ischemia period was randomized. At the end of the ischemia period, the subjects 1067

performed a 10 s isokinetic sprint as hard and fast as possible (80 rpm) while the 1068

cuffs were always instantaneously deflated at the beginning of the post-‐ischemia 1069

sprints. 1070

1071

Figure 2. Schematic representation of the power output (upper panels), raw EMG 1072

(2nd row), rectified EMG (3th row) and rectified and smoothed EMG (lower 1073

panels), during the control sprint, last 6 s of the incremental exercise (IE) in 1074

normoxia (Nx), subsequent 10-‐s isokinetic sprint at 80 rpm (normoxia), IE in 1075

hypoxia (Hyp) and subsequent 10-‐s isokinetic sprint at 80 rpm (normoxia). The 1076

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connected vertical arrows indicate the duration of the ischemia period, which in 1077

this example was 10s. 1078

1079

Figure 3. Peak (Wpeak-‐i) and mean (Wmean) power output during sprint exercise 1080

performed at the end of an incremental exercise to exhaustion in normoxia (PIO2 ≈ 1081

143 mmHg) and severe hypoxia (PIO2 ≈ 73 mmHg), after 10 or 60s of occlusion of 1082

the circulation. a P<0.05 compared with the other conditions; b P<0.05 compared 1083

with Nx10s; c P<0.05 compared with Nx60s. 1084

In review

45 Table 1. Ergospirometric and electromyographic responses during the last 10 s of the incremental exercise to exhaustion in normoxia (PIO2 ≈ 143 mmHg) and severe hypoxia (PIO2 ≈ 73 mmHg).

Normoxia Hypoxia P

FIO2 (%) 20.8 ± 0.1 10.8 ± 0.1 <0.001

SpO2 (%) 93.1 ± 4.4 64.6 ± 4.6 <0.001

Wmax (W) 259.2 ± 32.0 170.1 ± 21.0 <0.001

VO2peak (l.min-‐1) 3.62 ± 0.37 2.41 ± 0.29 <0.001

VE (l.min-‐1) 143.5 ± 19.5 123.8 ± 22.5 <0.001

RR (breaths.min-‐1) 60.2 ± 7.6 53.8 ± 7.0 <0.001

HR (beats.min-‐1) 185.4 ± 6.0 175.1 ± 9.0 <0.001

PETO2 (mmHg) 113.2 ± 2.3 52.4 ± 2.8 <0.001

PETCO2 (mmHg) 32.1 ± 2.6 27.5 ± 2.1 <0.001

RER 1.15 ± 0.03 1.35 ± 0.11 <0.001

VCO2 (l.min-‐1) 4.12 ± 0.49 3.23 ± 0.41 <0.001

RPM 56.7 ± 7.4 55.4 ± 5.9 0.5 VM RMSraw (µV) 134.2 ± 60.1 113.3 ± 48.9 <0.05

VL RMSraw (µV) 103.0 ± 30.9 88.9 ± 30.9 0.12

Average RMSraw (µV) 121.0 ± 37.7 101.1 ± 33.7 <0.01 VM RMSNz (A.U.) 219.1 ± 77.6 182.3 ± 45.5 <0.05

VL RMSNz (A.U.) 193.7 ± 76.4 165.0 ± 62.4 0.07

Average RMSNz (A.U.) 206.4 ± 61.2 173.7 ± 41.8 <0.05 VM TAINz (A.U.) 289.5 ± 109.6 222.6 ± 88.1 <0.001

VL TAINz (A.U.) 246.5 ± 102.2 187.5 ± 73.1 <0.05

Average TAINz (A.U.) 268.0 ± 80.1 205.0 ± 68.2 <0.001 VM MPF (Hz) 84.2 ± 18.4 89.6 ± 18.0 0.13

VL MPF (Hz) 84.1 ± 18.6 89.6 ± 17.8 0.13

Average MPF (Hz) 84.2 ± 18.5 89.6 ± 17.9 0.13 VM MdPF (Hz) 68.6 ± 12.3 73.3 ± 14.8 <0.05

VL MdPF (Hz) 68.5 ± 12.5 73.0 ± 14.6 <0.05

Average MdPF (Hz) 68.6 ± 12.4 73.1 ± 14.7 <0.05 VM Burst (ms) 401.9 ± 51.7 362.5 ± 55.9 0.12

VL Burst (ms) 401.4 ± 55.2 368.3 ± 55.7 0.10

Average Burst (ms) 401.7 ± 49.4 365.4 ± 52.8 0.10

FIO2: inspiratory oxygen fraction; SpO2: hemoglobin saturation in capillary blood measured by pulse oximetry; Wmax: power output at exhaustion; VO2: oxygen consumption; VE: pulmonary ventilation; RR: respiratory rate; HR: heart rate; PETO2: end-‐tidal O2 pressure; PETCO2: end-‐tidal CO2 pressure; RER: respiratory exchange ratio; VCO2: CO2 production; RPM: revolution per minute; VL: vastus lateralis; VM: vastus medialis; RMSraw: raw root mean square; RMSNz: normalized root mean square; TAINz: Normalized total activation index (arbitrary units, A.U.); MPF: mean power frequency; MdPF: median power frequency; Burst: burst duration; Average: mean of VM and VL.

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Table 2. Vastus lateralis electromyographic variables in response to sprint exercise performed at the end of an incremental exercise to exhaustion in normoxia (PIO2 ≈ 143 mmHg) and severe hypoxia (PIO2 ≈ 73 mmHg), after 10 or 60s of occlusion of the circulation.

Control sprint Nx10s Nx60s Hyp10s Hyp60s

Main Oxy (P)

Main Occ (P)

Interaction Oxy x Occ

(P)

RMSraw (µV)

238.1 ± 82.0 a 153.2 ± 64.7 137.1 ± 53.2 160.2 ± 68.7 161.8 ± 61.8 0.220 0.706 0.429

RMSNz (A.U.)

475.1 ± 155.2 a 317.3 ± 95.1 254.6 ± 110.0 344.2 ± 126.4 c 317.0 ± 172.4 0.112 0.059 0.436

Burst (ms) 331.9 ± 24.6 b,d 299.7 ± 22.7 c 324.6 ± 27.7 305.5 ± 23.8 c 337.3 ± 34.4 b,d 0.026 0.001 0.381

TAINz (A.U.) 1023.1 ± 340.6 a 600.8 ± 268.8 581.5 ± 244.2 642.9 ± 297.0 715.8 ± 288.2 0.12 0.729 0.326

MPF (Hz) 93.9 ± 9.7 b,c 81.9 ± 14.2 79.5 ± 16.4 86.3 ± 20.3 89.5 ± 17.2 0.006 0.837 0.212

MdPF (Hz) 80.2 ± 6.0 b,c,d 66.4 ± 9.4 e 67.0 ± 13.6 71.4 ± 16.6 74.7 ± 13.9 c 0.011 0.255 0.500

a P<0.05 compared with the other conditions; b P<0.05 compared with Nx10s; c P<0.05 compared with Nx60s; d P<0.05 compared with Hyp10s; RM ANOVA (2 X 2) Main Oxy: main oxygenation effect due to the conditions in which was performed the incremental exercise test (Nx: Normoxia; Hyp: hypoxia); RM ANOVA (2 X 2) Main Occ: Main Occlusion effect due to the duration of the occlusion (10s vs. 60s); Wpeak-‐i: instantaneous peak power in the sprint; Wmean: mean power in the 10s sprint; RMSraw: raw root mean square; RMSNz: Normalized root mean square; Burst: burst duration; TAINz: Normalized total activation index (arbitrary units, A.U.); MPF: mean power frequency; MdPF: median power frequency.

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Table 3. Vastus medialis electromyographic variables in response to sprint exercise performed at the end of an incremental exercise to exhaustion in normoxia and severe hypoxia (PIO2 ≈ 73 mmHg), after 10 or 60s of occlusion of the circulation.

Control sprint Nx10s Nx60s Hyp10s Hyp60s

Main Oxy (P)

Main Occ (P)


(P)

RMSraw (µV)

263.5 ± 115.7 b,c,e 177.4 ± 95.0 d 193.9 ± 121.3 204.2 ± 103.1 183.9 ± 81.1 0.333 0.943 0.038

RMSNz (A.U.)

410.4 ± 163.3 a 284.0 ± 97.1 d 276.4 ± 126.1 333.0 ± 143.1 279.7 ± 104.8 d 0.078 0.137 0.098

Burst (ms) 342.2 ± 27.7 b 309.4 ± 42.5 c, 355.2 ± 49.4 d 322.0 ± 53.1 347.8 ± 37.9 b 0.743 0.017 0.154

TAINz (A.U.) 1152.1 ± 463.3 a 701.1 ± 359.9 d 809.0 ± 498.6 829.7 ± 397.9 820.7 ± 335.6 0.118 0.638 0.119

MPF (Hz) 94.3 ± 9.9 b,c,d 81.9 ± 14.0 79.8 ± 15.8 85.8 ± 19.2 89.4 ± 17.4 0.008 0.703 0.241

MdPF (Hz) 80.8 ± 6.7 a 66.2 ± 9.2 67.1 ± 13.4 71.3 ± 16.6 74.6 ± 14.1 b,c 0.011 0.218 0.587

a P<0.05 compared with the other conditions; b P<0.05 compared with Nx10s; c P<0.05 compared with Nx60s; d P<0.05 compared with Hyp10s; RM ANOVA (2 X 2) Main Oxy: main oxygenation effect due to the conditions in which was performed the incremental exercise test (Nx: Normoxia; Hyp: hypoxia); RM ANOVA (2 X 2) Main Occ: Main Occlusion effect due to the duration of the occlusion (10s vs. 60s); RMSraw: raw root mean square; RMSNz: Normalized root mean square; Burst: burst duration; TAINz: Normalized total activation index (arbitrary units, A.U.); MPF: mean power frequency; MdPF: median power frequency.

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1090 Table 4. Electromyographic variables (average of vastus medialis and lateralis) in response to sprint exercise performed at the end of an incremental exercise to exhaustion in normoxia (PIO2 ≈ 143 mmHg) and severe hypoxia (PIO2 ≈ 73 mmHg), after 10 or 60s of occlusion of the circulation.

Control Nx10s Nx60s Hyp10s Hyp60s Main Oxy (P)

Main Occ (P)


(P)

RMSraw (µV)

250.8 ± 89.1 a 165.3 ± 69.6 d 165.5 ± 76.5 182.2 ± 79.8 172.9 ± 50.7 0.164 0.793 0.536

RMSNz (A.U.) 442.7 ± 141.9 a 300.6 ± 88.9 d 265.5 ± 93.9 d 338.6 ± 122.7 298.3 ± 117.7 d 0.042 0.043 0.835

Burst (ms)

337.1 ± 23.9 b,d 304.5 ± 29.8 c 339.9 ± 36.0 d 313.7 ± 36.0 342.6 ± 35.3 b,d 0.305 0.005 0.754

TAINz (A.U.)

1089.7 ± 355.0 653.1 ± 274.8 d 720.1 ± 323.5 739.6 ± 331.4 769.7 ± 238.9 0.082 0.510 0.575

MPF (Hz)

94.1 ± 9.8 b,c,d 81.9 ± 14.1 79.6 ± 16.1 86.0 ± 19.7 89.5 ± 17.3 b,c 0.007 0.769 0.221

MdPF (Hz) 80.5 ± 6.3 b,c,d 66.3 ± 9.2 67.0 ± 13.5 71.3 ± 16.6 74.6 ± 14.0 b,c 0.011 0.234 0.543

a P<0.05 compared with the other conditions; b P<0.05 compared with Nx10s; c P<0.05 compared with Nx60s; d P<0.05 compared with Hyp10s; RM ANOVA (2 X 2) Main Oxy: main oxygenation effect due to the conditions in which was performed the incremental exercise test (Nx: Normoxia; Hyp: hypoxia); RM ANOVA (2 X 2) Main Occ: Main Occlusion effect due to the duration of the occlusion (10s vs. 60s); RMSraw: raw root mean square; RMSNz: Normalized root mean square; Burst: burst duration; TAINz: Normalized total activation index (arbitrary units, A.U.); MPF: mean power frequency; MdPF: median power frequency.

In review

Figure 1.TIFF

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Figure 2.TIFF

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Figure 3.TIF

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1

Oxygenation at fatigue in hypoxia increases muscle activation and relieves fatigue:

influence of PIO2.

Rafael Torres-Peralta1,2, José Losa-Reyna1,2; David Morales-Alamo1, 2, Miriam González-Izal3, Ismael Pérez-Suárez1,2, Mikel Izquierdo3, José A.L. Calbet1,2.

1 Department of Physical Education, University of Las Palmas de Gran Canaria, Campus Universitario de Tafira s/n, Las Palmas de Gran Canaria, 35017, Spain.

2 Research Institute of Biomedical and Health Sciences (IUIBS), Las Palmas de Gran Canaria, Canary Islands, Spain.

3 Department of Health Sciences, Public University of Navarra, Tudela, Navarra 31500, Spain.

Running title: Oxygenation effects on muscle activation at fatigue

Correspondence to:

José A L Calbet

Departamento de Educación Física, Campus Universitario de Tafira,

35017 Las Palmas de Gran Canaria, Canary Island, Spain.

Tel: 0034 928 458 896

Fax: 0034 928 458 867

email: [email protected]

2

Abstract

The aims of this study were to determine whether maximal muscle activation during

incremental exercise to exhaustion is reduced in severe hypoxia compared to normoxia

and to determine the role played in this process by arterial oxygen pressure (PaO2) and

saturation (SpO2). To achieve these aims we recruited eleven voluntaries (22±2 years)

who performed an incremental exercise to exhaustion in severe acute hypoxia (PIO2: 73

mmHg). Upon exhaustion, subjects were requested to continue exercise when the

breathing gas mixture was swiftly changed to a higher level of oxygenation (PIO2 of 73

(placebo), 82, 92, 99 and 143 mm Hg, were tested in random order). After two minutes

at the same load that elicited exhaustion at each level of hypoxia, the incremental

exercise was pursued until a new exhaustion occurred. At this point, subjects were

requested again to keep exercising while the breathing gas was changed to room air

(normoxia). Electromyographic recordings were obtained from the vastus medialis

(VM) and lateralis (VL) Muscle activation, as reflected by VM and VL raw and

normalized root mean square (RMS, RMSNz), normalized total activation index

(TAINz) and burst duration was 8-20 % lower in hypoxia than normoxia (P<0.05). In

contrast, MPF was 5% lower in normoxia than hypoxia (P<0.001). Oxygenation

allowed for the continuation of exercise in all instances. VL and VM RMSraw were

increased by 6-8% when the PIO2 was increased from 73 to 99 or 92 mmHg (SpO2 from

63 to 78 or 70%, respectively). This was confirmed by similar responses of RMSNz and

TAINz. VM RMSNz increased by 6% when the PIO2 was increased from 73 to 82

mmHg (SpO2 from 63 to 67%). A similar response was observed for the VL and VM

TAINz in the transition from a PIO of 73 to 82 mmHg (P<0.05). MPF and MdPF

remained at the same level with oxygenation. Oxygenation had no significant effects on

muscle activation (VL and VM RMSraw, RMSNz and TAINz) in the transition from a

3

PIO2 of 92-99 to 142 mmHg (SpO2 from 70-78 to 94%, respectively). Nevertheless, the

raw and normalized VL and VM averaged RMS was increased by 5 and 9%,

respectively, with the transition from a PIO2 of 82 to 142 mmHg (SpO2 from 67 to 94%,

respectively, P<0.05). In conclusion, these findings indicate that one of the central

mechanisms by which severe hypoxia may cause central fatigue and task failure during

incremental exercise is by reducing the capacity for maximal muscle activation.

4

Introduction

Muscle activation, as reflected by the root mean square of the electromyographic signal

(EMGRMS), is higher in severe acute hypoxia than normoxia at the same absolute

intensity, but lower hypoxia than normoxia at the same relative intensity (Torres-Peralta

et al. 2014). Close to exhaustion, the surface integrated electromyographic (iEMG)

activity is higher during constant intensity exercise in hyperoxia FIO2=0.30 than severe

acute hypoxia (FIO2=0.10) (Amann et al. 2007). This could mean that hypoxia could

limit the motor drive output from the central nervous system (CNS) leading to reduced

muscle activation and task failure. In agreement, during exercise in severe hypoxia,

fatigue is rapidly relieved by oxygenation with normoxic (Calbet et al. 2003a) or

hyperoxic gas (Amann et al. 2007). If hypoxia depresses muscle activation, oxygenation

should be accompanied by an immediate increase of muscle activation at the same

absolute exercise intensity. However, there is no conclusive evidence in this regard. It

remains unknown whether the ergogenic effect of oxygenation requires an increase of

muscle activation.

During exercise in severe acute (Amann et al. 2007; Calbet et al. 2003a; Calbet

et al. 2015; Morales-Alamo et al. 2015) and chronic hypoxia (Calbet et al. 2003b;

Kayser et al. 1994) task failure is thought to be caused by predominantly central

mechanisms sensitive to reduced brain O2 delivery (Goodall et al. 2012) or interstitial

brain PO2 (Amann and Calbet 2008). An important difference between exercise in

severe and moderate hypoxia is the region of the hemoglobin oxygen dissociation curve

(ODC) at which the gas exchange occurs at the lungs. In severe hypoxia pulmonary gas

exchange occurs in the straight region of the ODC, implying that a small increase in

arterial oxygen pressure (PaO2) would result in a greater elevation of arterial

hemoglobin saturation (SaO2) (Calbet et al. 2003a; Calbet and Lundby 2009). In

5

moderate hypoxia, pulmonary gas exchange occurs at the upper and flatter region of the

ODC where an improvement in PaO2 translates into a smaller elevation of SaO2

(Amann et al. 2007). The fact that oxygenation only relieves fatigue when applied at

exhaustion in severe hypoxia could indicate that a substantial elevation of CaO2 is

required. However, the fact that oxygenation is not relieving fatigue during moderate

hypoxia could indicate that oxygenation is only relieving fatigue during exercise when a

certain level of hypoxia has been reached during exercise, implying that the increase in

PaO2 is even more critical than the elevation of CaO2. It remains unknown what level of

improvement in PaO2 and CaO2 are required to relief fatigue and enhance the neural

activation upon exhaustion in hypoxia.

Thus, our hypotheses are: (i) fatigue during exercise in severe acute hypoxia is

associated with lower muscle activation than in normoxia, (ii) oxygenation upon

exhaustion rapidly increases muscle activation depending on the level of hypoxia at

exhaustion and the inspiratory O2 pressure (PIO2) of the oxygenation gas, and (iii) the

ergogenic effect of oxygenation depends more on the improvement of SaO2 than on the

improvement in PaO2.

Therefore, the aims of this study were: a) to determine the influence of the level

hypoxia on the reduction of muscle activation at exhaustion in hypoxia; b) to determine

the minimal increase in (PaO2 and CaO2) needed to enhance muscle activation at

exhaustion in hypoxia; and c) to find out if the ergogenic effect of oxygenation is

always accompanied by enhanced muscle activation, as indication of a predominantly

central mechanism. To achieve these aims we recruited eleven voluntaries performed

incremental exercise to exhaustion in severe acute hypoxia (PIO2: 73-74 mmHg). Upon

exhaustion, subjects were requested to continue exercise when the breathing mixture

was swiftly changed to a higher level of oxygenation. After two minutes at the same

6

load that elicited exhaustion in severe hypoxia, the incremental exercise was pursued

until a new exhaustion occurred. At this point, subjects were requested again to keep

exercising while the breathing gas was changed to room air (normoxia). This created a

combination of conditions in which PaO2 and SaO2 increased in different proportions at

exhaustion.

Material and Methods

Subjects

Eleven healthy men (age: 21.5±2.0 years, height: 174±8 cm, body mass: 72.3±9.3 kg,

body fat: 16.1±4.9%, VO2max: 51±5 mL.kg-1.min-1) agreed to participate in this

investigation. Before volunteering, subjects received full oral and written information

about the experiments and possible risks associated with participation. Written consent

was obtained from each subject. The study was performed by the Helsinki Declaration

and was approved by the Ethical Committee of the University of Las Palmas de Gran

Canaria (CEIH-2010-01 and CEIH-2009-01).

General overview

This study was a part of a larger project that included several experiments designed to

address the mechanisms limiting whole body exercise performance in humans. The

results focusing on O2 transport and muscle metabolism have been published (Calbet et

al. 2015; Morales-Alamo et al. 2015). Body composition was determined by dual-

energy x-ray absorptiometry (DEXA) (Hologic QDR-1500, Hologic Corp., software

version 7.10, Waltham, MA) (Calbet et al. 1997), during the familiarization sessions.

The leg muscle mass was calculated from the DEXA scans using Wang's et al. model

(Wang et al. 1999). After that, subjects reported to the laboratory to familiarize with

7

maximal exercise tests in normoxia and normobaric hypoxia (Altitrainer200, SMTEC,

Switzerland) on separate days. For experimental purposes, subjects performed two sets

of incremental exercise tests, here called invasive and deception. On the first

experimental day, all subjects performed the invasive tests as previously described

(Calbet et al. 2015) and on the second and third day they completed the deception

protocol. The exercise tests were carried out on a cycle ergometer (Lode Excalibur

Sport 925900, Groningen, The Netherlands) and subjects were instructed to pedal at 80

revolutions per minute (rpm).

Exercise protocol

Deception protocol (non invasive). Subjects performed four incremental exercise tests

on two different days, separated by at least one week. A 90 min recovery period was

established between the two tests carried out on the same day (Fig. 1) (Calbet et al.

2003a). Each deception test was composed of an initial phase in severe hypoxia

(PIO2=73-74 mmHg) (HYP1), followed by a second phase with a similar or a less

severe level of hypoxia (HYP2), which continued with a final phase in normoxia (NX3).

HYP1 started with an intensity of 60 or 70 W which, after 2 min was increased by 20 or

30 W every 2 min until exhaustion (Exh1). At Exh1, the inspired gas mixture was

rapidly changed to one of four different gas mixtures (PIO2 = 73-74 (placebo), 82, 92

and 99 mmHg). This second phase of the exercise was named HYP2. These gas

mixtures were administered in random order and with a double-blind design. After 2

min (or exhaustion) at the load eliciting Exh1, the load was increased by 20 or 30 W

every two min until exhaustion (Exh2). At Exh2, the gas mixture was rapidly changed

to room air (PIO2 = 142-143 mmHg) while the subjects were strongly encouraged to

8

continue pedaling. After 2 min (or exhaustion) at the load eliciting Exh2, the load was

increased by 20 or 30 W every two min until exhaustion (Exh3).

Oxygen uptake and hemoglobin oxygen saturation

Oxygen uptake was measured with a metabolic cart (Vmax N29; Sensormedics,

California, USA), calibrated prior to each test according to the manufacturer

instructions. Respiratory variables were analyzed breath-by-breath and averaged every

10, 20 or 30 s for the analysis of transitions at exhaustion. The highest 20-s averaged

VO2 recorded in a given incremental exercise test was considered the VO2peak.

Hemoglobin oxygen saturation was estimated with a finger pulse oximeter (SpO2)

(OEM III module, 4549-000, Plymouth, MN) and transformed into SaO2 using the

equation SaO2 = (1.004 x SpO2) - 0.4543, (r2=0.99), which was derived from the

invasive tests.

Electromyography

Electrical muscle activation was monitored using surface electromyography (EMG).

EMG signals were continuously recorded from the vastus medialis and vastus lateralis.

Before the application of the EMG electrodes the skin surface was carefully shaved and

wiped with alcohol to reduce skin impedance. Bipolar single differential electrodes were

placed longitudinally on the muscles following the SENIAM recommendations

(Merletti and Hermens 2000) and taped to the skin to minimize movement artifacts. The

reference electrode was placed on the skin over the acromion. The position of the

electrodes was marked on the skin with indelible ink, and these references were used for

precise electrode placement on repeated experiments.

9

The EMG signals were acquired using a 16-channel recording system

(Myomonitor IV, Delsys Inc., Boston, MA) at a sampling rate of 1000 Hz using

rectangular shaped (19.8 mm wide and 35 mm long) bipolar surface electrodes with 1 x

10 mm 99.9% Ag conductors, and with an inter-conductor distance of 10 mm (DE-2.3

Delsys Inc). The EMG data were filtered with a high-pass filter of 20 Hz and a low-pass

filter of 450 Hz using a fifth-order Butterworth filter. The system has an input

impedance of >1015Ω per 0.2pF of input capacitance, a common mode rejection ratio of

>80 dB, signal-to-noise ratio < 1.2 μV, and a pre-amplifier gain 1000 V/V ±1%. Each

pedal revolution was detected using an electrogoniometer (Goniometer Biosignal

Sensor S700 Joint Angle Shape Sensor; Delsys Inc. Boston) fixed on the left knee and

sampled at 500 Hz. EMG and joint movement were simultaneously recorded by a

portable device (Myomonitor IV, Delsys Inc. Boston) and wirelessly transmitted to a

computer (EMGWorks Wireless application and EMGWorks Acquisition 3.7.1.3;

Delsys, Inc. Boston).

The EMG signal corresponding to each muscle contraction was analyzed using

code developed ‘in house’ (Matlab R2012b, MathWorks, Natick, MA, USA). The EMG

recordings were full-wave rectified and to provide an index of muscle activation, the

amplitude characteristics were analyzed via average RMS of a 25-ms moving window

for the duration of the burst. Burst onset and offset detection were determined using

20% of the maximal EMGRMS activity of each burst as a reference (Baum and Li 2003;

Hug and Dorel 2009; Torres-Peralta et al. 2014), rather than a mean threshold value

from 15 consecutive bursts (Ozgunen et al. 2010). This approach yielded the same result

as direct, simple visual discrimination, with 100% detection of all bursts. The EMGRMS

recorded during the last minute of a 2 min 80 W load (in normoxia) was used to

normalize the remaining EMGRMS data. Besides, we defined a total activity index during

10

the sprint (TAI) as TAI = EMGRMS x burst duration (ms) x number of pedal strokes

during the sprint. The total activity index is similar to the integrated EMG signal, but

was computed separately for each burst and excluded the baseline EMG between burst

(Torres-Peralta et al. 2014). The TAI recorded during the last minute of a 2 min 80 W

load (in normoxia) was used to normalize the rest of the TAI values.

The mean (MPF) and median (MdPF) power spectrum frequencies were

calculated using Fast Fourier Transform (Solomonow et al. 1990). All variables were

reported as the mean values of the pedal strokes recorded during the last 10 s of the

incremental exercise or the 10 s sprints. EMG data are reported separately for vastus

medialis (VM) and lateralis (VL), and also as the average of the two muscles.

Statistics

Normal distribution of variables was checked with the Shapiro-Wilks test. Pairwise

comparisons at specific time points were performed with Student t-tests. Values are

reported as the mean ± standard deviation (unless otherwise stated). P ≤ 0.05 was

considered statistically significant. All statistical analyses were performed using SPSS

v.15.0 for Windows (SPSS Inc., Chicago, IL) and Excel 2011 (Microsoft, Redmond,

WA, USA).

11

Results

Maximal exercise in severe acute hypoxia (PIO2=73 mmHg) and normoxia PIO2=142

mmHg)

As shown in Table 1, SpO2, Wmax, VO2 peak, VEpeak, RR, HRpeak, PETO2, PETCO2,

and VCO2 were lower during the last 30 s of exercise in hypoxia than in normoxia,

while the RER was higher in hypoxia than in normoxia (all P≤0.05).

Muscle activation, as reflected by VM and VL raw and normalized RMS, total

activation index and burst duration was 8-20 % lower in hypoxia than normoxia

(P<0.05) (Table 1). In contrast, MPF was 5% lower in normoxia than hypoxia

(P<0.001) and a similar trend was observed MdPF (Table 1).

Effect of oxygenation on cardiorespiratory and EMG variables

Oxygenation allowed for the continuation of exercise in all instances. Compared to the

mean values observed during the last 30s of exercise in severe hypoxia (PIO2=73

mmHg), PETO2 and VO2 were increased, and RER reduced during the first 30s upon

oxygenation (Table 2 and 3). These effects were more accentuated the highest the

difference in PIO2 between the hypoxic and the oxygenation condition.

Transition from severe hypoxia (PIO2 of 73 mmHg) to higher levels of oxygenation. VL

and VM RMSraw, as well as the mean of the two, was increased by 6-8% when the

PIO2 was increased from 73 to 99 or 92 mmHg (SpO2 from 63 to 78 or 70%,

respectively) (Table 2). This was corroborated by similar responses of RMSNz and

TAINz. VM RMSNz increased by 6% when the PIO2 was increased from 73 to 82

mmHg (SpO2 from 63 to 67%). A similar response was observed for the VL and VM

TAINz in the transition from a PIO of 73 to 82 mmHg (P<0.05). MPF and MdPF

remained at the same level with oxygenation.

12

Transition to normoxia. As depicted in Table 3, oxygenation had no significant effects

on muscle activation (VL and VM RMSraw, RMSNz and TAINz) in the transition from

a PIO2 of 99 to 142 mmHg (SpO2 from 78 to 94%, respectively). This was also the case

for the transitions from a PIO2 of 92 to 142 mmHg (SpO2 from 70 and 94%,

respectively). Nevertheless, the raw and normalized VL and VM averaged RMS was

increased by 5 and 9%, respectively, with the transition from a PIO2 of 82 to 142 mmHg

(SpO2 from 67 to 94%, respectively) P<0.05). When the two conditions with a greater

level of hypoxia were combined (PIO2 of 73 and 82 mmHg; SpO2 of 63 and 67%),

oxygenation to normoxia significantly increased muscle activation (RMSraw and Nz;

but not the normalized TAI) (P<0.05). However, this was not the case for the combined

less hypoxic conditions (PIO2 of 92 and 99 mmHg; SpO2 of 70 and 78%), for which

oxygenation did not result in significantly greater muscle activation. MPF and MdPF

remained at the same level with oxygenation.

We also circumscribed the analysis to the 10s measured 5s after the start of the

transition and compared these 10s with the last 10 s of the preceding exercise phase.

The results were essentially similar, i.e. oxygenation resulted in increased muscle

activation (RMSraw and Nz) particularly when fatigue occurred with high levels of

hypoxia (PIO2 of 73 and 82 mmHg).

In general, the pedaling rate was increased with oxygenation in the transition

from different levels of hypoxia to normoxia, and consequently the duration of the burst

was reduced.

Placebo effects. In the placebo condition subjects believed that received hyperoxic gas

when exhausted in severe hypoxia, however, they were maintained at the same level of

hypoxia. Consequently, no significant changes were observed in muscle activation

(RMSNz and TAINz) (Table 2).

13

Discussion

This study shows that muscle activation is lower during the last 10-30s of an

incremental exercise to exhaustion in hypoxia than in normoxia. We have shown that

oxygenation at exhaustion relieves rapidly fatigue and allows for the continuation of

exercise. This effect is accompanied by increased muscle activation only when the level

of hypoxia was high, i.e., for PIO2 during the incremental exercise to exhaustion ≤ 82

mmHg (equivalent to altitudes above ~4300 m). However, our investigation has also

demonstrated that an increase of muscle activation upon oxygenation at fatigue in

hypoxia is not indispensable for the ergogenic effects of oxygenation.

Severe hypoxia reduces the level of muscle activation attainable during incremental

exercise to exhaustion

During whole body exercise in severe acute (Amann et al. 2007; Calbet et al. 2003a;

Calbet et al. 2015; Morales-Alamo et al. 2015) and chronic hypoxia (Calbet et al.

2003b; Kayser et al. 1994) task failure is thought to be caused by predominantly central

mechanisms sensitive to reduced brain O2 delivery (Goodall et al. 2012) or interstitial

brain PO2 (Amann and Calbet 2008). In support of a central predominance is the rapid

relief of fatigue upon oxygenation, i.e. when subjects upon exhaustion are requested to

continue the exercise when swiftly switched to breathe normoxic (Calbet et al. 2003a)

or hyperoxic gas (Amann et al. 2007). This concurs with a greater functional reserve at

task failure in severe acute hypoxia than normoxia (Amann et al. 2007; Morales-Alamo

et al. 2015). However, oxygenation does not relief fatigue when administered at

exhaustion during whole body exercise in moderate hypoxia (FIO2=0.15) (Amann et al.

2007) or during small muscle exercise in severe hypoxia (Calbet and Lundby 2009). It

has been reported that a greater level of supraspinal fatigue occurs at task failure during

14

whole body (Goodall et al. 2010) and knee extension exercise (Goodall et al. 2010) in

hypoxia than in normoxia. This effect is more accentuated the highest the severity of

hypoxia (Goodall et al. 2010). However, in contrast to our observation, quadriceps

muscle activation (EMGRMS) declined during repeated isometric muscle contractions

(60% of the maximal voluntary contraction, 5s/5s contraction/recovery) to similar levels

in severe hypoxia (FIO2=0.10) and normoxia (Goodall et al. 2010). A main difference

between whole body and small muscle (knee extension) exercise in hypoxia is that for a

given PIO2, pulmonary gas exchange is more perturbed during whole body than small

muscle exercise (Calbet et al. 2009). The latter combined with a greater right-shift of the

ODC in severe hypoxia causes a much greater degree of desaturation for a given PaO2

during whole body than small muscle exercise in severe hypoxia (Calbet et al. 2009).

Consequently, with an FIO2 close to 0.10, SpO2 at exhaustion was 78% during knee

extension exercise in Goodall et al. (2010) and 63% in the current investigation. In the

present investigation, a level of SpO2 of 78% was observed at exhaustion when the PIO2

was 99 mmHg, and oxygenation did not elicit increased in muscle activation. By

combining the present results with those of Goodall et al. (2010) it may suggest that

muscle activation is more reduced at exhaustion in hypoxia than normoxia when the

levels of SaO2 falls below ~70%.

Mechanisms by which hypoxia could reduce muscle activation capacity

Hypothetically, hypoxia could attenuate muscle activation through two main

mechanisms. Severe hypoxia could trigger inhibitory feedback at spinal and supraspinal

levels reducing the discharge rate of spinal motoneurons compared to normoxia.

Alternatively, severe hypoxia could limit or reduce the recruitment of high-threshold

motor units. Regarding the first mechanism, animal studies have shown that levels of

15

PaO2 similar to those observed in this investigation at exhaustion in severe acute

hypoxia (Calbet et al. 2015) increase the baseline discharge frequency of group III and

especially of group IV muscle afferents in resting cats (Hill et al. 1992; Lagier-

Tessonnier et al. 1993) and rabbits (Arbogast et al. 2000). Increased group III/IV muscle

afferents firing rate may cause reflex inhibition of the α-motoneuron pool (for review

see (Amann and Kayser 2009)) and hence, reduced muscle activation. Nevertheless, if

this were the case we should have seen a concomitant change in MPT of MdPF with

oxygenation in the current investigation, and this was not the case. In agreement with

our interpretation, no clear inhibitory effect on EMGRMS from increased metaboreflex

activation during ischemic intermittent isometric muscle contractions to exhaustion in

hypoxia compared to normoxia was observed during knee extension exercise (Millet et

al. 2009).

Regarding the second mechanism, hypoxia may reduce oxygenation of

prefrontal, premotor, and motor regions leading to a mismatch between energy demand

and aerobic ATP resynthesis, which could limit the corticospinal motor drive

(Rasmussen et al. 2007; Verges et al. 2012).

IEMG increases with increasing angular velocity during concentric contractions

(Amiridis et al. 1996; Westing et al. 1991). In the present investigation, oxygenation

was associated to an increase of pedaling rate in the transition from hypoxia to

normoxia, but not in the transition from severe hypoxia to a lower level of hypoxia.

Since in the latter muscle activation was increased this rules out the changes in pedaling

rate as the main mechanisms accounting for the increase in muscle activation with

oxygenation.

In summary, this investigation demonstrates that close to task failure, muscle

activation is lower during incremental exercise to exhaustion in severe acute hypoxia

16

than in normoxia. In addition, we have shown that oxygenation at exhaustion reduces

fatigue and allow the continuation of exercise in moderate and severe acute hypoxia,

regardless of the effects of oxygenation on muscle activation. In hypoxia, muscle

activation at task failure is increased within 10-30 s of oxygenation when task failure

occurred at levels of hypoxia equivalent to altitudes above ~4300 m (PIO2 ≤ 82 mmHg)

and when the PIO2 is increased to levels ≥ 82 mmHg and SaO2 ≥ 67%. Globally, these

findings indicate that one of the central mechanisms by which severe hypoxia may

cause central fatigue and task failure is by reducing the capacity for maximal muscle

activation.

17

Acknowledgements

This study was supported by a grant from the Ministerio de Educación y Ciencia of

Spain (DEP2009-11638 and FEDER). Especial thanks are given to José Navarro de

Tuero for his excellent technical assistance.

Author contributions. Conception and design of the experiments: JAC; pre-testing,

experimental preparation, data collection, and analysis: RTP, DMA, JLR, IPS, and JAC;

EMG analysis: RTP, MGI, and MI. The first version of the manuscript was written by

RTP and JAC. All co-authors read, contributed comments and approved the final

version of the manuscript.

Conflict of interest

None of the authors have any conflicts of interests.

18

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