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The aim of this review was to examine the mechanisms by which physical activity and inactivity modify muscle fatigue. It is well known that acute or chronic increases in physical activity result in structural, metabolic, hormonal, neural, and molecular adaptations that increase the level of force or power that can be sustained by a muscle. These adaptations depend on the type, intensity, and volume of the exercise stimulus, but recent studies have highlighted the role of high intensity, short-duration exercise as a time-efficient method to achieve both anaerobic and aerobic/endurance type adaptations. The factors that determine the fatigue profile of a muscle during intense exercise include muscle fiber composition, neuromuscular characteristics, high energy metabolite stores, buffering capacity, ionic regulation, capillarization, and mitochondrial density. Muscle fiber-type transformation during exercise training is usually toward the intermediate type IIA at the expense of both type I and IIx myosin heavy-chain isoforms. High-intensity training results in increases of both glycolytic and oxidative enzymes, muscle capillarization, improved phosphocreatine resynthesis and regulation of K(+), H(+), and lactate ions. Decreases of the habitual activity level due to injury or sedentary lifestyle result in partial or even compete reversal of the adaptations due to previous training, manifested by reductions in fiber cross-sectional area, decreased oxidative capacity, and capillarization. Complete immobilization due to injury results in markedly decreased force output and fatigue resistance. Muscle unloading reduces electromyographic activity and causes muscle atrophy and significant decreases in capillarization and oxidative enzymes activity. The last part of the review discusses the beneficial effects of intermittent high-intensity exercise training in patients with different health conditions to demonstrate the powerful effect of exercise on health and well being.
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REVIEW ARTICLE
published: 18 May 2012
doi: 10.3389/fphys.2012.00142
Effects of physical activity and inactivity on muscle fatigue
Gregory C. Bogdanis*
Department of Physical Education and Sports Science, University of Athens, Athens, Greece
Edited by:
Christina Karatzaferi, University of
Thessaly, Greece
Reviewed by:
Bruno Bastide, University of Lille Nord
de France, University of Lille 1, France
Norbert Maassen, University
Hannover/Medical School Hannover,
Germany
*Correspondence:
Gregory C. Bogdanis, Department of
Physical Education and Sports
Science, University of Athens, 41
Ethnikis Antistasis Street, Dafne, 172
37 Athens, Greece.
e-mail: gbogdanis@phed.uoa.gr
The aim of this review was to examine the mechanisms by which physical activity and
inactivity modify muscle fatigue. It is well known that acute or chronic increases in phys-
ical activity result in structural, metabolic, hormonal, neural, and molecular adaptations
that increase the level of force or power that can be sustained by a muscle. These adap-
tations depend on the type, intensity, and volume of the exercise stimulus, but recent
studies have highlighted the role of high intensity, short-duration exercise as a time-efficient
method to achieve both anaerobic and aerobic/endurance type adaptations.The factors that
determine the fatigue profile of a muscle during intense exercise include muscle fiber com-
position, neuromuscular characteristics, high energy metabolite stores, buffering capacity,
ionic regulation, capillarization, and mitochondrial density. Muscle fiber-type transformation
during exercise training is usually toward the intermediate type IIA at the expense of both
type I and IIx myosin heavy-chain isoforms. High-intensity training results in increases of
both glycolytic and oxidative enzymes, muscle capillarization, improved phosphocreatine
resynthesis and regulation of K+,H
+, and lactate ions. Decreases of the habitual activ-
ity level due to injury or sedentary lifestyle result in partial or even compete reversal of
the adaptations due to previous training, manifested by reductions in fiber cross-sectional
area, decreased oxidative capacity, and capillarization. Complete immobilization due to
injury results in markedly decreased force output and fatigue resistance. Muscle unloading
reduces electromyographic activity and causes muscle atrophy and significant decreases
in capillarization and oxidative enzymes activity. The last part of the review discusses the
beneficial effects of intermittent high-intensity exercise training in patients with different
health conditions to demonstrate the powerful effect of exercise on health and well being.
Keywords: high-intensity exercise, training, repeated sprints, aerobic training
INTRODUCTION
Muscle fatigue can be defined as the inability to maintain the
required or expected force or power output (Edwards, 1981;Fitts,
1994). Due to the fact that a decrease in muscle performance may
ensue even during a submaximal activity,a more appropriate defi-
nition of fatigue for any population may be:“any decline in muscle
performance associated with muscle activity at the original inten-
sity (Simonson and Weiser, 1976;Bigland-Ritchie et al., 1986).
Muscle fatigue is a common symptom during sport and exercise
activities, but is also increasingly observed as a secondary outcome
in many diseases and health conditions during performance of
everyday activities (Rimmer et al., 2012). In many of these health
conditions, physical inactivity is a major contributing factor to
the increased fatigability of the patient. Deconditioning as a result
of restricted physical activity results in large decreases in muscle
mass and strength, as well as increased fatigability due to changes
in muscle metabolism (Bloomfield, 1997;Rimmer et al., 2012). On
the other end of the physical activity spectrum, chronic exercise
training increases muscle strength and function, and enhances
the ability of the muscles to resist fatigue in healthy individu-
als and patients of all ages (Bishop et al., 2011;Hurley et al.,
2011).
The aim of the present review is to investigate and explain the
differences in muscle fatigue between individuals with different
physical activity levels histories. The effects of different types of
training will be evaluated and compared, while the factors that
contribute to muscle fatigue in healthy individuals will be ana-
lyzed. Also, the outcomes of an acute or chronic decrease in
physical activity due to injury, immobilization, or illness will be
examined. Finally, the beneficial effects of exercise in patients
with different health conditions will be presented in an attempt
to demonstrate the powerful effect of exercise training not only on
sport performance, but also on health and well being.
MUSCLE FATIGUE IN INDIVIDUALS WITH DIFFERENT
TRAINING BACKGROUNDS
Training history has an impact on muscle fatigue profile during
high-intensity exercise. It is well known that power trained athletes
are stronger and faster than both endurance athletes and untrained
individuals. Previous studies have shown that power trained ath-
letes have 25–35% higher maximal voluntary contraction (MVC)
force and maximal rate of force development (RFD), as well as
peak and mean power compared to endurance athletes (Paasuke
et al., 1999;Calbet et al., 2003). When comparing the fatigue pro-
files of those athletes, a lower peak power but a slower rate of
muscle power decline is observed in endurance athletes than in
power athletes. This is due to the ability of endurance trained ath-
letes to better maintain their performance during the test as shown
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Bogdanis Physical activity and muscle fatigue
by their lower fatigue index, calculated as the rate of drop from
peak to end power output.
The differences in fatigue between power and endurance
trained athletes are more evident when repeated bouts of maximal
exercise are performed with short recovery intervals. A common
method to examine fatigue in maximal repeated muscle perfor-
mance is to calculate fatigue during a protocol of short-duration
sprints, interspersed with brief recoveries (Bishop et al., 2011). In
that case, fatigue index is expressed as the drop of peak or mean
power from the first to the last sprint (Hamilton et al., 1991), or
preferably as the average decrement of power in all sprints rel-
ative to the first sprint (Fitzsimons et al., 1993). According to
the later calculation of fatigue, endurance runners had a 37%
smaller power decrement over five6 s maximal sprints interspersed
with 24 s rest, compared with team sports players (Bishop and
Spencer, 2004). This was accompanied by smaller disturbances in
blood homeostasis as reflected by lower post-exercise blood lac-
tate concentration (Bishop and Spencer, 2004). One important
factor that may contribute to the slower rate of fatigue and the
smaller metabolic disturbances of endurance trained individuals
is their higher aerobic fitness. It has been shown that endurance
athletes have higher oxygen uptake during a repeated sprint test,
indicating a greater contribution of aerobic metabolism to energy
supply (Hamilton et al., 1991). The comparison of fatigue profiles
between athletes with different training background reveals some
possible mechanisms that determine the ability of the muscle to
maintain high performance. It is now accepted that the factors
causing fatigue may range from central (e.g., inadequate genera-
tion of motor command in the motor cortex) to peripheral (e.g.,
accumulation of metabolites within the muscle fibers (Girard et al.,
2011). High-intensity exercise, usually in the form of repeated
bouts interspersed with a short interval, can be used as a model
to examine muscle fatigue both in health and disease. The recent
use of intense interval exercise as a time-efficient and highly effec-
tive strategy for training healthy individuals (Burgomaster et al.,
2008) and patients with various health conditions (e.g., chronic
obstructive pulmonary disease, COPD patients; Vogiatzis, 2011),
necessitates understanding of the factors that cause muscle fatigue
in this type of exercise.
FACTORS MODIFYING FATIGUE IN PHYSICALLY ACTIVE
INDIVIDUALS
MUSCLE FIBER COMPOSITION
It is known for many decades that muscle fiber composition differs
between sprint/power trained and endurance trained athletes and
untrained individuals (Costill et al., 1976). The traditional distinc-
tion between slow and fast muscle fibers based on myosin ATPase,
has been replaced by the characterization according to the expres-
sion of myosin heavy-chain (MHC) isoforms. The classification of
fibers according to MHC can provide an informative picture about
functional characteristics such as strength, power,and fatigue resis-
tance (Bottinelli, 2001;Malisoux et al., 2007). Based on the major
MHC isoforms, three pure fiber types can be identified: slow
type I and fast type IIA and IIX (Sargeant, 2007). Although these
fiber types have similar force per unit cross-sectional area (CSA),
they differ considerably in maximum shortening velocity (type I
about four to five times slower than IIX) and power generating
capacity (Sargeant, 2007). Furthermore, type IIX fibers have an
enzymatic profile that favors anaerobic metabolism, namely, high
resting phosphocreatine (PCr) content (Casey et al., 1996) and
high concentration and activity of key glycolytic enzymes such as
glycogen phosphorylase and phosphofructokinase (Pette, 1985).
This profile makes the fiber more vulnerable to fatigue due to
energy depletion or accumulation of metabolites (Fitts, 2008). On
the other hand, type I fibers have a higher content and activity
of oxidative enzymes that favor aerobic metabolism and fatigue
resistance (Pette, 1985). Thus, muscles with a greater proportion
of type I fibers would be more fatigue resistant compared with
muscles with a greater proportion of type IIA and type IIX fibers.
In this context, endurance trained individuals have a higher per-
centage of type I slow/fatigue resistant fibers (about 65% type I
fibers in the gastrocnemius muscle; Harber and Trappe, 2008),
compared with sprinters (about 40% type I fibers in the quadri-
ceps; Korhonen et al., 2006), and recreationally active individuals
(about 50% type I fibers in the gastrocnemius muscle; Harber and
Trappe, 2008).
The greater fatigability of individuals whose muscles have a
high percentage of type II fibers was demonstrated in several
studies. For example, Hamada et al. (2003) reported a more than
twofold greater decrease in force during repeated maximal volun-
tary isometric contractions of the quadriceps, in individuals with
a high percentage of type II fibers (72%) compared with individ-
uals with much lower (39%) type II fibers. Similar findings were
reported by Colliander et al. (1988) using repeated bouts of isoki-
netic exercise. An interesting finding in that investigation was that
when blood flow to the leg was occluded using a pneumatic cuff,
the decrease in peak force was fivefold greater in the group of sub-
jects with higher percentage of type I muscle fibers. This indicates
the reliance of these fibers on blood flow, oxygen availability, and
aerobic metabolism (Colliander et al., 1988).
Single fiber studies show that there is a selective recruitment
and selective fatigue of the fast fibers containing the IIX MHC
isoform, as shown by a large (70%) decrease of single fiber ATP
within 10 s of sprint exercise (Karatzaferi et al., 2001b). At the same
time, type I fibers showed no change in ATP. This may suggest
that the contribution of the faster and powerful fibers that con-
tain the IIX isoform may be decreased after the first few seconds
of high-intensity exercise (Sargeant, 2007). The greater metabolic
disturbances in type II compared to type I fibers may be due to the
faster rate of PCr degradation and anaerobic glycolysis and thus
lactate and H+accumulation (Greenhaff et al., 1994).
IONIC REGULATION
During high-intensity exercise large changes in metabolites and
ions are observed within the working muscles (Juel et al., 2004;
Mohr et al., 2007;Cairns and Lindinger, 2008). Disturbances in
the concentration of muscle lactate, hydrogen (H+), potassium
(K+), and calcium (Ca2+) ions are linked with fatigue (McKenna
et al., 2008) and thus ionic regulation becomes critical for muscle
membrane excitation, contraction, and energy metabolism (Allen
et al., 2008).
The extensive activation of glycogenolysis and anaerobic glycol-
ysis result in H+accumulation that decreases muscle pH by about
0.5 unit (McCully et al.,1994;Bogdanis et al., 1995). The ability of
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Bogdanis Physical activity and muscle fatigue
the muscle to regulate H+and lactate homeostasis during high-
intensity exercise may play an important role in the fatigue process
(Juel, 2008). Several mechanisms contribute to muscle pH regula-
tion, including release of H+to the blood via different transport
systems and buffering of H+within the muscle (Juel, 2008). The
most important membrane transport systems involved in pH reg-
ulation are the Na+/H+exchange, which is considered as the most
important, the Na+/bicarbonate co-transport, and the lactate/H+
co-transport (Juel, 2008).
Although removal of H+and lactate out of the muscle cell are
considered important for the restoration of muscle performance
following intense contractions, there is evidence to suggest that low
pH and high lactate have far less inhibitory effects on the activation
of the contractile apparatus than previously assumed (Allen et al.,
2008). This evidence comes mainly from isolated animal mus-
cle and single fiber experiments and suggests that a small part of
fatigue is due to increased inorganic phosphate (Pi), that reduces
force output, and K+accumulation inside the t-tubules, that
affects action potential (Allen et al., 2008). According to this evi-
dence, the greatest part of fatigue, is due to reduced sarcoplasmic
reticulum calcium (Ca2+) release and decreased Ca2+sensitivity
of the contractile proteins (Allen et al., 2008). An increasing body
of data shows that oxidative stress may influence Ca2+sensitivity
and Ca2+reuptake by the sarcoplasmic reticulum and therefore
muscle function and fatigue (Westerblad and Allen, 2011).
EFFECTS OF REACTIVE OXYGEN SPECIES ON SKELETAL MUSCLE MASS
AND FUNCTION
There is growing evidence that reactive oxygen species (ROS) and
reactive nitrogen species (RNS) are produced in skeletal mus-
cles under physiological (exercise) as well as under pathological
conditions (Lamb and Westerblad, 2011;Pellegrino et al., 2011;
Westerblad and Allen, 2011). The most important ROS are: (a)
the superoxide anion that is mainly produced in the mitochondria
as a by-product of oxidative phosphorylation and by NADPH and
xanthine oxidases (b) hydrogen peroxide (H2O2) and (c) hydroxyl
radicals (Allen et al., 2008). Although increased ROS are implicated
in muscle fatigue, it is becoming increasingly clear that ROS are
important components in normal cellular signaling and adapta-
tion (Westerblad and Allen, 2011). ROS can cause muscle fatigue by
decreasing maximum Ca2+activated force, Ca2+sensitivity, and
Ca2+release, and this was demonstrated by experiments where
administration of ROS scavengers/antioxidants delayed fatigue
development (Lamb and Westerblad, 2011). From all the admin-
istered antioxidant supplements (e.g., ubiquinone-10, vitamins
C and E), the antioxidant N-acetylcysteine (NAC) has proven
to be the most effective (Hernandez et al., 2012). NAC easily
enters cells and contains a thiol group that can interact with ROS
and their derivatives (Ferreira and Reid, 2008). Also, as a thiol
donor,NAC also supports resynthesis of one of the major endoge-
nous antioxidant systems, glutathione (Hernandez et al., 2012).
The endogenous ROS scavenging pathways, such as glutathione
peroxidase (GPX) and superoxide dismutase (SOD) activities
are substantially up-regulated by exercise training (Allen et al.,
2008).
Reactive oxygen species have also been implicated in damage
of cell proteins, DNA, and lipids through oxidation and thus have
been related with muscle damage and muscle wasting observed in
heavy exercise, disuse, and various pathological conditions (Pel-
legrino et al., 2011). In models of disuse muscle atrophy using
hindlimb unloading and limb immobilization, the potential role
of oxidative stress in determining muscle wasting has been man-
ifested as an increase in oxidative stress (free iron, xanthine oxi-
dase activity, lipid peroxidation, and oxidized/reduced glutathione
ratio), together with an impairment in antioxidant defense sys-
tems (decreased catalase and GPX activities) and other protective
proteins such as heat shock proteins (Lawler et al., 2003, 2006;
Pellegrino et al., 2011). However, the co-existence of oxidative
stress and muscle atrophy does not necessarily imply a cause and
effect relationship for the hindlimb unloading model. Similarly,
data from the few human bed rest studies suggest a decrease in
protein synthesis, suggesting anabolic resistance, and not mainly
protein breakdown due to oxidative stress (for a review see Pel-
legrino et al., 2011). However, in respiratory, kidney, and cardiac
disease and muscular dystrophy the pivotal role of oxidative stress
and increased proteolysis has been suggested (Moylan and Reid,
2007).
CONTRIBUTION OF OXIDATIVE METABOLISM TO ENERGY SUPPLY
In recent years, data have been accumulated showing the signif-
icant contribution or oxidative metabolism to the energy supply
during short bouts of all-out exercise, such as sprinting (Bogdanis
et al., 1996, 1998;Spencer et al., 2005). An early study by Gaitanos
et al. (1993) noted that although the decrease in mean power dur-
ing 10 ×6 s sprints with 30 s rest was 27%, anaerobic energy supply
was reduced by almost threefold (70%), due to diminished con-
tribution of glycolysis to anaerobic ATP turnover. They were the
first to suggest that power output during the last sprints was prob-
ably sustained by increased contribution of oxidative metabolism.
The enhanced contribution of oxidative metabolism to repeated
all-out exercise was quantified in a later study using a protocol
of two 30 s sprints separated by 4 min of passive rest (Bogdanis
et al., 1996). Aerobic energy contribution during the first 30 s
sprint was about 29% and this increased to 43% during the sec-
ond 30 s sprint performed 4 min later (Figure 1). Interestingly,
aerobic contribution was further increased to 65% of the energy
during the last 20 s of the second sprint, at which point 85 ±3%
of VO2max was attained (Bogdanis et al., 1996 and unpublished
calculations from biopsy and oxygen uptake data). An increased
aerobic contribution to energy supply during repeated bouts of
high-intensity exercise has been reported for endurance trained
individuals (Hamilton et al., 1991;Tomlin and Wenger, 2002;Cal-
bet et al., 2003). It is noteworthy that oxygen uptake increases very
fast during repeated short-duration sprints (15 m ×40 m with 25 s
rest), reaching 80–100% VO2max during the last sprints (Dupont
et al., 2005).
RATE OF PHOSPHOCREATINE RESYNTHESIS
Phosphocreatine degradation provides the most immediate and
faster source of ATP resynthesis during high-intensity exercise
(Sahlin et al., 1998). However, due to the relatively low intra-
muscular stores, PCr is exhausted early during a single bout
of high-intensity exercise. However, PCr is rapidly resynthesized
during the recovery following exercise and thus the rate of PCr
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Bogdanis Physical activity and muscle fatigue
FIGURE 1 | Calculated ATP turnover (percent contribution) from ATP +PCr degradation, anaerobic glycolysis, and aerobic metabolism during two 30 s
sprints separated by 4min of recovery Redrawn using data from Bogdanis et al. (1996).
resynthesis determines its availability for the next exercise bout.
Consequently,individuals with fast PCr resynthesis exhibit greater
fatigue resistance during repeated bouts of high-intensity exercise
(Bogdanis et al., 1996;Casey et al., 1996;Johansen and Quis-
torff, 2003). PCr resynthesis depends highly on oxygen availability
(Haseler et al., 1999, 2007). The rate of PCr resynthesis mea-
sured by phosphorus nuclear magnetic resonance spectroscopy
has been widely used as an index of muscle oxidative capac-
ity (Haseler et al., 2004). Johansen and Quistorff (2003) have
examined the differences in PCr resynthesis and performance
recovery between endurance trained, sprint trained, and untrained
individuals using phosphorus nuclear magnetic resonance spec-
troscopy. Participants performed four maximal isometric con-
tractions of 30 s duration, interspersed by 60 s recovery intervals.
Endurance trained athletes showed almost twice as fast PCr resyn-
thesis rate compared to sprint trained and untrained participants
(half time, t1/2 : 12.5 ±1.5 vs. 22.5 ±2.5 vs. 26.4 ±2.8 s, respec-
tively). This resulted in almost complete restoration of PCr stores
prior to each contraction for the endurance athletes, whereas the
untrained and the sprinters started the subsequent contractions
with a PCr level of about 80% of baseline. There is evidence to
suggest that the faster rate of PCr resynthesis in endurance ath-
letes is probably not related to VO2max. The relationship between
VO2max and PCr resynthesis has been questioned, since it has been
shown that individuals with high and low VO2max (64.4 ±1.4 vs.
46.6 ±1.1 ml kg1min1,P<0.01) have similar PCr resynthesis
rates (Cooke et al., 1997). Furthermore, individuals with equal
VO2max levels may have remarkably different endurance capac-
ity because of differences in “peripheral” or muscle characteristics
such as muscle capillary density and onset of blood lactate accu-
mulation (Coyle et al., 1988). Thus, it may be suggested that the
faster rate of PCr resynthesis in endurance trained individuals is
most probably related with adaptations that favor blood flow and
oxygen delivery and utilization in the muscle, such as increased
mitochondrial content, capillary density and oxidative enzyme
content and activity (Andersen and Henriksson, 1977;Tesch and
Wright, 1983;Tesch et al., 1985;Karatzaferi et al., 2001a). The
role of peripheral adaptations on PCr resynthesis has also been
indirectly demonstrated by the high positive correlation (r =0.89,
P<0.01) between the percent PCr resynthesis 4min after a 30-s
sprint and endurance fitness as determined from the percent-
age of VO2max corresponding to a blood lactate concentration of
4 mmol l1(Bogdanis et al., 1996).
NEURAL FACTORS
The level and the type of physical activity have an impact on
the functional organization of the neuromuscular system. Power
trained athletes have been shown to be more affected by fatigu-
ing exercise than endurance athletes (Paasuke et al., 1999). Elec-
tromyographic (EMG) activity of the agonist and antagonist mus-
cles and the level of voluntary activation of motor units have been
traditionally used to examine the contribution of neural factors
on muscle fatigue. A failure to fully activate the muscles that con-
tribute to force or power output would imply the importance of
neural factors in affecting the rate of muscle fatigue.
Changes in the normalized EMG amplitude (root mean square,
RMS) of the vastus lateralis muscle during 10 ×6s sprints inter-
spersed by 30 s rest explained 97% of the total work done, suggest-
ing that fatigue is accompanied by reductions in neural drive and
muscle activation (Mendez-Villanueva et al., 2008). However, the
parallel decrease of EMG activity and power output may imply
that the decreased neural drive may be the consequence and not
the cause of the decreased performance. Amann and Dempsey
(2008) demonstrated that feedback from group III/IV muscle
afferents exerts an inhibitory influence on central motor drive, so
that to avoid excessive development of peripheral fatigue beyond
a sensory tolerance limit associated with potential muscle tissue
damage.
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Bogdanis Physical activity and muscle fatigue
A common finding in many studies assessing neuromuscular
activity is that fatigue in high-intensity exercise is characterized by
a shift in the EMG power spectrum of the muscles involved, pos-
sibly indicating selective fatigue of fast-twitch fibers (Kupa et al.,
1995;Billaut et al., 2006). This selective fatigue of the fast-twitch
fibers may be related with increased fatigue in individuals with a
high percentage of fast fibers.
Another neuromuscular characteristic that may be affected by
physical activity level is voluntary activation. Voluntary activation
of a muscle during an MVC can range from 80 to 100% (Behm
et al., 2002). When a muscle is sub maximally activated during an
MVC (e.g., 70% of its full capacity), fatigue is likely to develop at a
slower rate than if it was fully activated. Sub-optimal muscle acti-
vation during maximal effort is commonly observed in children
performing high-intensity exercise and is one of the reasons that
young individuals fatigue less compared with adults (Ratel et al.,
2003). However, sub-optimal muscle activation is not uncommon
in adults. Nordlund et al. (2004) reported a wide range of vol-
untary activation (67.9–99.9%) for the plantar flexors of healthy
habitually active males. A novel finding of that study was that a
large percentage (58%) of the variance in fatigue during repeated
short maximal isometric contractions was explained by the mag-
nitude of MVC torque and the initial percent voluntary activation.
This finding provides support to the suggestion that individuals
who cannot fully activate their muscles fatigue less but are able to
generate much less force and muscle power. This may be related
with a failure to recruit all fast-twitch fibers results, which,in turn,
results in less metabolic disturbances and less fatigue during high-
intensity exercise. It must be noted that the level of voluntary
activation is reduced with fatigue, as shown by a study by Racinais
et al. (2007), who reported a decrease in voluntary activation from
95 to 91.5% (P<0.02), along with a 10% decrease in peak power
and an about 17% decrease in MVC following ten 6 s sprints.
Fatigue during high-intensity dynamic exercise may become
greater due to the loss of synchronization between agonist and
antagonist muscles and the increased level of co-contraction of
the antagonists muscles. This would decrease the effective force
or power generated by a joint, especially during faster movements
where neuromuscular coordination is more important. Garrandes
et al. (2007) reported that the co-activation level of the antago-
nist muscles during knee extension was increased by 31% after
fatigue only in power trained and not in endurance athletes. Ear-
lier findings by Osternig et al. (1986) showed a four times higher
hamstrings co-activation during isokinetic knee extensions in
sprinters compared with distance runners (57 vs. 14%), probably
indicating a sport-specific adaptation. The higher antagonist co-
activation in sprint/power trained individuals may partly explain
their greater fatigue during dynamic exercise, since part of the
agonist force/power is lost to overcome antagonist muscle activity.
However, Hautier et al. (2000) reported that the lower activation
of the antagonist knee flexor muscled due to fatigue appeared to
be an efficient adaptation of the inter-muscular coordination to
modulate the net force generated by the fatigued agonists and
maintain the force applied on the pedals.
INFLUENCE OF INITIAL FORCE OR POWER ON MUSCLE FATIGUE
Fatigue is traditionally calculated as the drop of force or power
from an initial value to the lowest or end value. A common
observation when examining fatigue is that individuals who can
generate high force or power per kg body or muscle mass, usually
fatigue quicker (Girard et al., 2011). Previous studies have reported
that initial sprint performance is strongly correlated with fatigue
during a repeated sprint test (Hamilton et al., 1991;Bishop et al.,
2003) and inversely related to maximal oxygen uptake (Bogda-
nis et al., 1996). In fact, when comparing endurance and sprint
trained athletes, relative power output (per kg body mass) is only
different at the initial part of the exercise bout and thereafter per-
formance is similar or even greater in endurance athletes (Calbet
et al., 2003). A high force or power output (per kg body mass) dur-
ing the first part of a high intensity bout may imply high reliance
on fast-twitch fibers and anaerobic metabolism and thus greater
metabolic disturbances. Thus, the greater fatigue of more pow-
erful athletes may be more related to differences in fiber-type
contribution and energy metabolism than a greater initial force
or power.
Tomlin and Wenger (2002) and later Bishop and Edge (2006)
investigated the influence of the initial power output on fatigue
during high-intensity exercise, by comparing two groups of female
team sports athletes who had similar peak and mean power out-
put in a 6-s cycle ergometer sprint, but different maximal oxygen
uptake values (low VO2max: 34–36 vs. moderate VO2max: 47–
50 ml kg1min1). These athletes were required to perform five
6 s sprints with 24 s recovery (Bishop and Edge, 2006)orten6s
sprints with 30 s recovery (Tomlin and Wenger, 2002). Even though
the two groups were matched for initial sprint performance, the
moderate VO2max group had a smaller power decrement across the
10 (low vs. moderate: 18.0 ±7.6 vs. 8.8 ±3.7%, P=0.02) or the
5 sprints (low vs. moderate: 11.1 ±2.5 vs. 7.6 ±3.4, P=0.045).
These results point to an important role of aerobic fitness on the
ability to resist fatigue.
Mendez-Villanueva et al. (2008) investigated this issue by cal-
culating the anaerobic power reserve of each individual. This
was quantified as the difference between the maximal anaero-
bic power measured during a 6-s sprint and the maximal aerobic
power determined during a graded test to exhaustion. Individuals
with a lower anaerobic power reserve, who had less reliance on
anaerobic metabolism, showed a greater resistance to fatigue. This
suggests that the relative contribution of the aerobic and anaer-
obic pathways to energy supply and not the initial power per se,
provide a better explanation for fatigue during repeated bouts of
high-intensity exercise (Mendez-Villanueva et al., 2008).
CHANGES IN FATIGABILITY FOLLOWING EXERCISE
TRAINING
A systematic change in functional demands posed on skeletal mus-
cle will result in adaptations that increase performance toward
the characteristics of the exercise stimulus. Depending on the
stimulus, skeletal muscle can increase its size (D’Antona et al.,
2006), alter muscle fiber-type composition (Malisoux et al.,2007),
increase enzyme activities (Green and Pette, 1997), and modify
muscle activation (Bishop et al., 2011). The adaptations that may
reduce muscle fatigue during high-intensity exercise depend on
the characteristics of the training program, i.e., type, intensity,
frequency,and duration. Muscle fatigue will be reduced by appro-
priate shifts in fiber type, enhanced enzyme activity, regulation of
ionic balance, and changes in muscle activation.
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Bogdanis Physical activity and muscle fatigue
SKELETAL MUSCLE FIBER-TYPE SHIFTING DUE TO TRAINING
Differences in muscle fiber-type distribution between athletes of
various sports reflect a combination of two factors: (a) natural
selection, i.e., individuals with a high percentage of fast-twitch
fibers follow and excel in a sport that requires speed and power,and
(b) training-induced fiber-type transformation, i.e., small changes
in muscle fiber-type distribution due to long term sport-specific
training. Training studies show that it is possible to attain some
degree of MHC transformation even with shorter term train-
ing (Malisoux et al., 2007). Transitions between MHC isoforms
are done in a sequential, reversible order from type I type
IIA type IIX and vice versa (Pette and Staron, 1997;Stevens
et al., 1999). This shifting is determined by the neural impulse pat-
terns, the mechanical loading characteristics, and by alterations in
the metabolic homeostasis (Pette, 1998). In addition to the pure
fiber types there are hybrid fibers co-expressing I and IIA or IIA
and IIX MHC isoforms. There is evidence to suggest that the rel-
ative proportion of hybrid fibers may increase with training, so
that the functional characteristics of the muscle are improved. For
example, endurance training may increase the percentage of type
I fibers co-expressing fast and slow isoforms, making them faster
without losing fatigue resistance (Fitts and Widrick, 1996;Fitts,
2003).
The typical response following high-intensity sprint or heavy
resistance training is a shifting of the faster (type IIX) fibers toward
the intermediate type IIA fibers, with the percentage of type I
fibers either decreasing or remaining unchanged (Esbjörnsson
et al., 1993;Ross and Leveritt, 2001;Andersen and Aagaard, 2010).
Most data from sprint training studies show that the MHC IIX
isoforms are down-regulated and there is usually a bidirectional
change toward IIA at the expense of both I and IIX MHC isoforms
(Esbjörnsson et al., 1993;Andersen et al., 1994;Ross and Leveritt,
2001). However, an increase in slow twitch at the expense of the
fast-twitch fibers has been reported following 7 weeks of sprint
training (Linossier et al., 1993). It should be noted that there are
very few pure type IIX fibers in skeletal muscles of healthy indi-
viduals, while most of the MHC IIX protein is found together with
MHC IIA protein in hybrid fibers (Andersen et al., 1994;Malisoux
et al., 2007). As will be discussed later in this review, pure type IIX
fibers appear most often in disused muscles.
The functional adaptations of muscle fibers following sprint
and strength training depend mainly on increases in fiber CSA,
with the force per unit of CSA remaining unchanged in most
(Widrick et al., 2002;Malisoux et al., 2007), but not in all stud-
ies (D’Antona et al., 2006). Maximal shortening velocity of single
fibers also seems to be unchanged after resistance (Widrick et al.,
2002) or sprint training (Harridge et al., 1998) in healthy young
individuals, but there is some evidence that plyometric train-
ing may increase maximal shortening velocity in single fibers
(Malisoux et al., 2007).
Training the muscle with lower intensity and longer duration
stimuli, as used in endurance training, brings about different adap-
tations. Studies preformed over the last four decades by Pette and
colleagues demonstrated the remarkable degree of transformation
of fast, fatigable muscles toward slower, fatigue resistant in terms
of both fiber type and metabolism using chronic low-frequency
stimulation (Pette and Vrbova, 1999). Although this situation is
not realistic, it demonstrated that activity may have a large impact
on the phenotype and fatigue profile of skeletal muscle. Similar,
but to a much lesser degree, effects on muscle fiber compositionare
seen during endurance training. Trappe et al. (2006) trained recre-
ational runners so that they could compete in a Marathon after
16 weeks (13weeks training and 3 weeks tapering). They reported
a decrease in slow (MHC I) and fast (MHC IIA) fiber CSA by
about 20%, but an increase in the percentage of MHC I fibers
(from 48 ±6to56±6%, P<0.05),while the percentage of MHC
IIA fibers remained unchanged (30 ±5%,). A significant finding
of that study was that single fiber muscle power expressed per
unit fiber volume as measured in vitro, was increased by >70%
in both MHC I and IIA fibers. These increases of power demon-
strate that high-volume endurance training (30–60 km running
per week) can modify the functional profile of the fibers that are
most involved.
It seems therefore that fiber-type profile can be affected to
some extent by both high intensity (sprint, strength, power) and
endurance training in healthy individuals. The bidirectional shifts
of the fast (type IIX) and slow (type I) fiber types toward the
intermediate IIA isoform do not guarantee that fatigability will
be improved. Factors such as changes in the metabolic properties
(e.g., oxidative capacity) of all fiber types with training (Fitts and
Widrick, 1996) as well as neural activation patterns of the contract-
ing muscle may play an important role in fatigue resistance and
should also be considered together with fiber type shifts. There
is growing evidence suggesting that the functional properties of
muscle fibers can change in several physiological and pathologi-
cal conditions with no significant shift in myosin isoforms. This
does not negate the important role of muscle fiber composition
on fatigue, but rather shows that a “fine tuning” of one or more
characteristics of a given fiber may be done according to functional
demands (Malisoux et al., 2007).
INCREASES IN ENZYME ACTIVITIES
The metabolic profile of each muscle fiber is sensitive to train-
ing, even when no fiber-type transformation occurs (Pette, 1998).
The majority of investigations have reported increases in the activ-
ity of key enzymes of glycolysis, such as glycogen phosphorylase,
phosphofructokinase (PFK), and lactate dehydrogenase (LDH)
following sprint training (Linossier et al., 1993, 1997;Dawson
et al., 1998). Linossier et al. (1993) trained young students with
repeated short sprints (5 s sprint 55 s rest) for 7 weeks with four
sessions per week. The number of sprints per session was increased
every week from 16 to 26 sprints per session. This program resulted
in increased energy production from anaerobic glycolysis, as indi-
cated by the increased muscle lactate accumulation after compared
to before training (Δlactate 37.2 ±17.9 vs. 52.8 ±13.5 mmol kg1
dry weight P<0.01) and the 20% higher PFK and LDH activ-
ity. A similar training study by Dawson et al. (1998) involving
short running sprints of comparable duration to the previous
study (30–60 m) found a 40% increase in glycogen phosphory-
lase, but no increase in PFK. A common finding of these two
studies involving short sprints was that the activities of key oxida-
tive enzymes involved in carbohydrate metabolism, e.g., citrate
synthase (CS) or lipid oxidation, e.g., 3-hydroxyacyl-CoA dehy-
drogenase (HAD), were either unchanged (Linossier et al., 1993,
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Bogdanis Physical activity and muscle fatigue
1997) or decreased (Dawson et al., 1998) with this type of repeated
short sprint exercise.
However, data from sprint training studies using longer sprint
durations such as 30 s sprints, showed increases in oxidative
enzymes. For example, MacDougall et al. (1998) trained their
subjects three times per week for 7 weeks using repeated 30 s
sprints with 3–4 min rest in each session. The number of sprints
increased progressively from 4 to 10 per session. This training
program resulted in a significant increase in the total work done
during the last three of the 4 ×30s sprint test protocol. This was
accompanied by a 49% increase in PFK activity (P<0.05) and
36 and 65% increases in CS and succinate dehydrogenase (SDH,
P<0.05). Also an increase in VO2max from 51.0 ±1.8 to 54.5 ±1.5
(P<0.05) was reported, suggesting that repeated long sprints
(30 s) constitute a powerful aerobic stimulus. In a similar training
study with repeated 30 s cycle ergometer sprints, there was a 7.1%
increase in mean power over a 30-s sprint and an 8% increase in
VO2max (Barnett et al., 2004). Interestingly, these authors reported
a 42% increase in CS activity but no increase in PFK or anaerobic
energy provision from PCr or glycolysis. They suggested that the
improvement in 30 s sprint performance was probably mediated
by increased energy provision from oxidative metabolism.
HIGH-INTENSITY TRAINING: A POWERFUL AND
TIME-EFFICIENT EXERCISE STIMULUS
The adaptations caused by high-intensity exercise training have
first been examined by Dudley et al. (1982), who reported that
fast-twitch fibers respond to training by increasing cytochrome c,
only when intensity was high. A decade later, McKenna and his
research group started investigating the effects of sprint training
on ionic balance (McKenna et al., 1993). As discussed in a previ-
ous section of this review, Bogdanis et al. (1996) were the first to
demonstrate a large increase in oxidative metabolism coupled by
a decrease in anaerobic glycolysis when a 30-s sprint was repeated
after 4 min or recovery. The increase in aerobic metabolism and
the decrease in glycolysis were possibly mediated by changes in
key enzyme activities, such as glycogen phosphorylase, PFK, and
pyruvate dehydrogenase (PDH). Parolin et al. (1999) reported an
inhibition of glycogen phosphorylase transformation to the more
active form due to increased H+concentration at the last of three
30 s sprints performed with a 4-min rest. At the same time PDH
activity was enhanced possibly due to the increased H+concentra-
tion, resulting in a better matching between pyruvate production
and oxidation and minimal muscle lactate accumulation. Repeated
high-intensity bouts lasting from 30 s (Stepto et al., 1999)to4min
(Helgerud et al., 2001) are used since then to improve endurance
performance in several sports. These early studies indicated that
repeated bouts of intense exercise rely heavily on aerobic energy
supply and formed the bases for the increasingly popular high-
intensity exercise interval training (high-intensity training, HIT)
concept.
A series of more recent studies by Burgomaster et al. (2005,
2006, 2008) have shown that training with repeated 30 s sprints
results in large increases in oxidative enzymes such as CS (by
38%), cytochrome coxidase (COX), and HAD. These adapta-
tions were achieved with only six training sessions performed
over 2 weeks with 1–2 days rest (four to seven sprints 30s sprints
per session with 4 min rest) and were accompanied by a remark-
able 100% increase in endurance capacity as defined by time to
exhaustion at 80% VO2max (from 26 ±5to51±11 min, P<0.05).
The authors have proposed the repeated 30s sprint method as a
time-efficient training strategy to simultaneously improve aero-
bic and anaerobic fitness and reduce fatigue. The extremely low
time commitment (2.5 min per session for 5×30 s sprints, or less
than 20 min including the 4-min rest intervals) makes this method
attractive and further research is warranted to examine its possible
applications in health and disease. The basis for the usefulness of
this exercise scheme in both sports and clinical settings is that the
exercise stimulus induces rapid phenotypic changes that resem-
ble traditional endurance training and promotes mitochondrial
biogenesis (Gibala, 2009) which appear to stimulate other healthy
metabolic adaptations in skeletal muscle, such as improved insulin
action, improved lipoprotein lipase activity and greater clearance
of plasma triglycerides (Coyle, 2005).
Following the pioneering study by Burgomaster et al. (2005),
Gibala et al. (2006) compared the typical HIT protocol (i.e.,
4–6 ×30 s sprints with 4 min rest) with traditional endurance
exercise (90–120 min of continuous cycling at 65% VO2max )
performed three times per week for 2 weeks. The two proto-
cols resulted in similar increases in muscle oxidative capacity as
reflected by the activity of COX and a similar improvement in
an endurance time trial (by 10.1 and 7.5%). The key role the
increase of the active form of pyruvate dehydrogenase (PDH) after
this type of training was highlighted in the study of Burgomas-
ter et al. (2006) who also reported a concomitant reduction in
glycogenolysis (from 139 ±11 to 100±16 mmol kg1dry weight,
P=0.03) and lower lactate accumulation possibly due to greater
mitochondrial pyruvate oxidation. The lower level of acidification
due to decreased glycogenolysis may have contributed to reduced
fatigability following this type of training.
It should also be stressed that this type of repeated sprint exer-
cise also increases VO2max and improves cardiovascular function.
Astorino et al. (2012) reported a 6% increase in VO2max, oxygen
pulse and power output, in only six sessions of HIT involving
repeated 30 s sprints over 2–3 weeks. However, in athletic popu-
lations, the importance of lower intensity–high-volume training
should not be overlooked. Laursen (2010) in a critical review of low
and high volume and intensity training suggested that training for
sports performance should have an appropriate blend of both HIT
and high-volume training, otherwise performance ability can stag-
nate. A polarized approach for optimal intensity distribution for
the training of elite athletes of intense events (rowing, swimming,
track running, and cycling) was suggested by Laursen (2010),
whereby 75% of total training volume should be performed at
low intensities, and 10–15% should be performed at very high
intensities.
Another form of high-intensity interval training is called “aero-
bic interval training” and usually consists of four exercise bouts of
4 min each, at an intensity corresponding to 90–95% of peak heart
rate or 85–90% VO2max, with 2–3 min or rest in between (Wisloff
et al., 2007). This type of training is commonly used in soccer in
the form of running or small sided games and has been proved
to be very effective in delaying soccer specific or game fatigue.
A comparison between the effectiveness of this training protocol
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Bogdanis Physical activity and muscle fatigue
with a repeated sprint protocol has been performed by Ferrari
Bravo et al. (2008). They compared the effects of training with a
4×4 min running at 90–95% of maximal heart rate, with 3 min
active recovery vs. a repeated sprint training protocol that included
three sets of six 40 m all-out “shuttle” sprints with 20 s passive
recovery between sprints and 4 min between sets. The repeated
sprint group, compared with the aerobic interval training group,
showed a greater improvement not only in repeated sprint perfor-
mance, but also in the soccer specific“Yo–Yo” intermittent recovery
test (28.1 vs. 12.5%, P<0.01). A similar improvement in VO2max
(6%) was found for the two groups. As noted above, the adap-
tations and improvements following HIT of either form (aerobic
interval and repeated sprints) are far superior and time-efficient
compared with longer duration continuous training. As will be dis-
cussed later,the benefits of high-intensity interval exercise of both
forms (30 s–4min high-intensity bouts) extend to health promo-
tion and are currently proposed for improving health and reducing
fatigue in many diseases (COPD and cardiac patients).
MOLECULAR BASES FOR ADAPTATIONS TO HIT
Understanding the multiple benefits of HIT requires investigation
of the molecular signals that cause adaptations at the level of the
skeletal muscle fiber.According to Coffey and Hawley (2007), there
are at least four primary signals, as well as a number of secondary
messengers, that are related with mitochondrial adaptations and
glucose transport capacity across the sarcolemma:
(1) Mechanical tension or stretch,
(2) Oxidative stress manifested by an increase in ROS.
(3) Increase in intracellular calcium with each contraction.
(4) Altered energy status, as reflected by a lower ATP concentra-
tion.
Some putative signaling cascades promoting skeletal muscle
mitochondrial biogenesis in response to high-intensity interval
training may be as follows (Gibala et al., 2012): during intense
muscle contractions, the rise in intracellular calcium activates the
mitochondrial biogenesis messenger calmodulin kinase. At the
same time, the “energy crisis” that results in decreased ATP and
increased adenosine mono phosphate (AMP) activates the AMP-
activated protein kinase (Gibala, 2009;Laursen, 2010). Activation
of p38 mitogen-activated protein kinase (MAPK), possibly via
increase generation of ROS may also be involved (Gibala et al.,
2012). These signals can increase a key transcriptional coacti-
vator, namely the peroxisome proliferator-activated receptor-γ
coactivator-1α(PGC-1α), which is a key regulator of oxidative
enzyme expression in skeletal muscle. PGC-1αhas been described
as a “master switch” that coordinates mitochondrial biogenesis
by interacting with various nuclear genes encoding for mito-
chondrial proteins (Gibala, 2009;Gibala et al., 2012). Previous
work has shown that an increased expression of PGC-1αin the
muscle results in the conversion of the muscle from glycolytic
to oxidative with a dramatic up-regulation of typical oxidative
genes/proteins like COX. This results in a shift of the functional
capacity of the muscle toward a more fatigue resistance profile
found in the endurance trained state. Calvo et al. (2008) demon-
strated that up-regulation of PGC-1αin transgenic mice, results
in far superior exercise performance and 20% higher peak oxygen
uptake compared with wild-type control mice. It is noteworthy
that in the study of Burgomaster et al. (2008) which compared
typical endurance training with HIT, PGC-1αprotein content of
the quadriceps muscle was equally increased in both protocols,
demonstrating the large potential of the repeated sprint protocol to
produce rapid mitochondrial adaptations. As suggested by Coyle
(2005), one of the advantages of the repeated sprint protocol over
the traditional endurance exercise, lays on the high level of type
II muscle fiber recruitment that is not achieved in the traditional
low intensity endurance exercise. Thus, HIT results in mitochon-
drial adaptations also in type II fibers that are absent when lower
intensity/high-volume endurance training is performed. These
adaptations of type II fibers would also increase their fatigue
resistance and this is beneficial for high-intensity performance.
CHANGES IN MUSCLE FIBER CAPILLARY SUPPLY AND REGULATION OF
IONIC BALANCE
As noted in the previous sections, the improvement in fatigue resis-
tance is partly due to an increase in the enzymes that favor oxidative
metabolism. However, a proliferation of capillary supply to muscle
fibers would cause an additional improvement in fatigue resis-
tance by enhanced lactate and H+elimination and oxygen supply
(Tesch and Wright, 1983). Additional to the role of the different
lactate and H+transport mechanisms out of the exercising mus-
cle, improved perfusion contributes to the increased release from
muscle to the blood (Juel, 2008). HIT training with intense leg
extension exercise three to five times per week for 7 weeks (1 min
exercise, 3min rest for 1 h at 150% of leg VO2max) resulted in an
increase of capillary-to-fiber ratio from 1.74 ±0.10 to 2.37 ±0.12
capillaries per fiber, and a 17% increase in capillary density (Jensen
et al., 2004). These adaptations would increase oxygen extraction
and facilitate aerobic metabolism during exercise as well as the rate
of PCr resynthesis during the recovery intervals (McCully et al.,
1991).
Inarecentreview,Iaia and Bangsbo (2010) presented the bene-
fits of “speed endurance”training, which is a form of repeated HIT.
The characteristics of this type of training are as follows: The form
or exercise is running and the intensity is between 70 and 100% of
the maximum running speed, which corresponds to a cardiores-
piratory load very close or well above VO2max. The number of
repetitions is between 3 and 12 repetitions and the duration of
each bout is 10–40 s (usually 30s) with a recovery interval greater
than five times the exercise duration (usually 2–4min). In well
trained athletes, this type of training causes adaptations that do
not appear to depend on changes in VO2max, muscle substrate lev-
els, glycolytic and oxidative enzymes activity. Instead they appear
to be related to improved running economy, and a higher expres-
sion of muscle Na+,K
+pump α-subunits, which may delay fatigue
during intense exercise by increasing Na+–K+pump activity and
a reduced contraction-induced net loss of K+, thus preserving
muscle excitability (Iaia and Bangsbo, 2010). These conclusions
were based on previous studies that compared the effects of two
different intense training regimens on changes in muscle ATPase
subunits and fatigue.
Mohr et al. (2007) divided participants into a sprint training
group (15 ×6 s sprints with 1 min rest) and a speed endurance
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Bogdanis Physical activity and muscle fatigue
group (8 ×30 s runs at 130% VO2max, with 1.5 min rest). Train-
ing was performed three to five times per week and lasted for
8 weeks. The fatigue index during a 5 m ×30 m sprint running test
with 25 s active recovery, was reduced by 54% only in the speed
endurance group, and remained unchanged in the sprint group.
The reduction in fatigue was accompanied by a 68% increase in
Na+–K+ATPase isoform α2 and a 31% increase in the amount
of the Na+/H+exchanger isoform, only in the speed endurance
group. These adaptations are possibly related with the meta-
bolic responses (and thus metabolic load) during each session
of speed endurance training, where peak blood lactate (14.5–
16.5 mmol l1) and plasma K+(about 6.4 mmol l1) were higher
compared to the sprint training responses (blood lactate: 8.5 and
K+:5.5 mmol l1).
The marked increases in extracellular K+that are commonly
observed during high-intensity exercise contribute to muscle
fatigue by causing depolarization of the sarcolemmal and t-tubular
membranes (McKenna et al., 2008). A training-induced increase
in Na–K+ATPase activity has been shown to contribute to the
control of K+homeostasis and reduce fatigue (Mohr et al., 2007).
However, the importance of pH regulation, especially in less
trained and non-athletic populations and patients with various
diseases should not be overlooked. It is well established that the
pH regulating systems in skeletal muscles are very responsive to
HIT (Juel, 2008). During high-intensity exercise and the subse-
quent recovery period, muscle pH is regulated by three systems:
(1) lactate/H+co-transport by two important monocarboxylate
transporter proteins: MCT1 and MCT4, (2) Na+/H+exchange by
a specific exchanger protein,and (3) Na+/bicarbonate transporters
(Juel, 2008). The MCT1 and MCT4 transporters are considered as
the most important during exercise and thus their changes follow-
ing training have been extensively studied in animal and human
muscle. Animal studies have shown that HIT in rats for 5weeks
results in 30 and 85% in the MCT1 and Na+/bicarbonate trans-
porter, respectively, while MCT4 remained unchanged (Thomas
et al., 2007). In humans, changes in the Na+/H+exchanger pro-
tein levels by 30% have been reported in the 4-week high-intensity
sprint training study of Iaia et al. (2008). Moreover, significant
increases in MCT1 and Na+/H+exchanger protein densities have
been found after HIT, especially when training bouts cause a sig-
nificant accumulation of H+in the muscle (Mohr et al., 2007).
Increased expression of lactate and H+transporters results in
faster H+and lactate release. Juel et al. (2004) used the one-legged
knee extensor exercise model to examine changes in muscle pH
regulating systems following intense training. Following 7 weeks of
training with 15 ×1min bouts of single knee extensions at 150%
VO2max per day,time to exhaustion was improved by 29%. The rate
of lactate release at exhaustion was almost double (19.4 ±3.6 vs.
10.6 ±2.0 mmol min1,P<0.05) and the rate of H+release was
50% higher (36.9 ±3.1 vs. 24.2 ±1.5 mmol min1,P<0.05) for
the trained than for the untrained leg. The membrane contents
of the MCT1 lactate/H+co-transporter and Na+/H+exchanger
proteins were increased by 15 and 16%, while blood flow was also
increased by 16% in the trained compared to the untrained leg.
This study demonstrated that when muscle is stressed with training
stimuli that cause high intramuscular lactate and H+concentra-
tion, it adapts by increasing the rate of lactate and H+transport out
of the muscle. These adaptations are done by both changes in spe-
cific membrane proteins and structural changes, such as increased
capillary density (Jensen et al., 2004), that enhance blood flow and
thus transport of lactate and H+away from the working muscle.
Within the muscle cell, the ability to buffer the build-up of
free H+in the muscle during high-intensity exercise is an impor-
tant determinant of fatigue resistance and may be improved by
training. To test this hypothesis, Edge et al. (2006) trained recre-
ationally active female team sport players for 3 days per week for
5 weeks, using two protocols with matched for total work but dif-
ferent intensity. The high-intensity group performed six to ten
2-min bouts of cycling with 1 min rest at an intensity that was
120–140% of that corresponding to the 4-mmol l1blood lactate
threshold. The moderate-intensity group performed continuous
exercise at 80–95% of that corresponding to the lactate thresh-
old for 20–30 min, so that the total work was the same with the
high-intensity group. Blood lactate at the end of a typical train-
ing session was 16.1 ±4.0 mmol l1for the high-intensity group
and only 5.1 ±3.0 mmol l1for the moderate-intensity exercise
group. VO2max and the intensity corresponding to lactate thresh-
old were equally improved (by 10–14%) in both groups, but only
the high-intensity group showed a significant increase in buffer-
ing capacity by 25% (from 123 ±5to153±7μmol H+gdry
muscle1pH1,P<0.05), coupled with a greater improvement
in a repeated sprint exercise performance compared with the low
intensity group (13.0 vs. 8.5%, P<0.05, Edge et al., 2005). Taken
collectively, the above results emphasize the importance of exercise
intensity for achieving the most favorable adaptations that delay
muscle acidification and increase fatigue resistance. A reduced
rate of H+accumulation, by transporting more H+out of the
muscle and/or by intracellular buffering, would allow a greater
contribution of glycolysis to energy supply and thus higher muscle
performance.
EFFECTS OF PHYSICAL INACTIVITY ON MUSCLE FATIGUE
DETRAINING
Detraining is a period of insufficient or reduced training stimu-
lus that causes reversal of adaptations at rates depending on the
magnitude of physical activity reduction and by the length of the
deconditioning period. Muscular and neural adaptations may be
reversed at different rates, while muscle fiber phenotype is altered
toward an increased expression of the fast MHC IIX phenotype
(Andersen and Aagaard, 2000).
A common practice in detraining studies is to train the par-
ticipants for a short or longer period and then remove the train-
ing stimulus and measure the detraining adaptations. Andersen
et al. (2005) trained sedentary young males using knee exten-
sion exercises three times per week for 3months using mod-
erate to heavy resistances (from 10 to 6 repetition maximum,
RM). Testing was performed before the start of training, after
3 months of training and again 3 months after detraining. Follow-
ing 3 months of training, the CSA of quadriceps and EMG activity
both increased by 10%. Also, isokinetic muscle strength at 30 and
240˚ s1, was increased by 18% (P<0.01) and 10% (P<0.05),but
power, velocity, and acceleration of unloaded knee extension was
unchanged. The proportion of MHC IIX decreased from 5.6 ±0.8
to 0.8 ±0.3% (P<0.001), with a corresponding increase of MHC
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Bogdanis Physical activity and muscle fatigue
IIA proportion from 34.0 ±2.5 to 39.4 ±2.0% (P<0.001). After
3 months of detraining isokinetic CSA, EMG and muscle strength
and power at 30 and 240˚ s1returned to pre-training levels. How-
ever, unloaded knee extension angular velocity and power were
increased remarkably by 14 and 44% in relation to pre and post
training. This was accompanied by an increase in MHC IIX iso-
form from 0.8 ±0.3 to 7.7±1.1%, which was significantly higher
compared with both pre and post training levels (P<0.001). This
phenomenon, i.e., an increase of the fast MHC IIX isoform is
a typical adaptation to detraining following systematic training
and has been observed in even greater extent (from 2.0 ±0.8 to
17.2 ±3.2%, P<0.01), after a similar protocol of training and
detraining (Andersen and Aagaard, 2000). However, this is accom-
panied by a reduction in type II fiber CSA, which would actually
make the muscle weaker when higher loads than only the weight
of the limb are to be moved (e.g., body weight).
From a metabolic point of view, detraining results in a marked
decrease in muscle oxidative capacity, as indicated by a large
decrease in mitochondrial enzyme activities. In the 10-week train-
ing study of Linossier et al. (1997) presented earlier in this
review, the increased activities of the glycolytic enzymes were
not reversed after 7 weeks of detraining. However, VO2max and
oxidative enzymes (CS and HAD) were decreased at or below the
pre-training values. Simoneau et al. (1987) reported similar results
of no significant change in glycolytic enzymes, but a significant
reduction of oxidative enzymes after 7 weeks of detraining. In a
more recent study (Burgomaster et al., 2007), cytochrome coxi-
dase subunit, a marker of oxidative capacity, remained elevated
even after 6 weeks of detraining following 6 weeks of HIT. How-
ever, some studies have reported decreases in glycolytic enzymes
in highly trained athletes who stop training for 4–8 weeks (Mujika
and Padilla, 2001).
As discussed earlier in the review, exercise-induced angiogene-
sis (increased capillarization) is an important adaptation to HIT
that is possibly mediated by the increased expression of PGC-
1α(Tadaishi et al., 2011). Earlier studies reported that a short
period of detraining does not seem to significantly decrease cap-
illary density of the previously trained muscle, possibly due to the
concomitant decrease in muscle fiber area (Klausen et al., 1981;
Coyle et al., 1984). However, more recent data suggest that only a
short period of detraining is adequate to reverse training-induced
angiogenic remodeling, as seen by the regression of capillary con-
tacts and individual capillary-to-fiber ratio in the plantaris and
soleus muscles of rats (Malek et al., 2010). These authors sug-
gested that this was modulated by vascular endothelial growth
factor (VEGF).
The reductions in oxidative enzyme activities together with
the shifting of muscle fiber type to the fast fatigable MHC
IIX isoform would increase fatigue during high-intensity exer-
cise following a period of detraining. However, short (2 week)
“tapering” period of decreased training volume (by 40–60%) with-
out changes in training intensity and frequency is commonly
used by athletes to maximize performance gains (Bosquet et al.,
2007). This short period of reduced training volume, would take
advantage of the positive adaptations of detraining, while at the
same time would avoid the negative long term effects of reduced
activity.
IMMOBILIZATION AND DISUSE
Athletes and physically active individuals may be forced to short
term immobilization of a limb or even to bed rest due to acute
injury or illness. The consequences of gravitational unloading have
been extensively investigated in recent years (Ohira et al., 2002;
Urso, 2009). One of the most typical adaptations to immobiliza-
tion is muscle atrophy, accompanied with decreases in functional
capacity. Antigravity muscles (e.g., gastrocnemius and soleus) are
most susceptible to atrophy following bed rest (Clark, 2009). The
loss of muscle strength during a period of 4–6 weeks of unload-
ing has been largely attributed to the loss of contractile proteins
(Degens and Always, 2006;Urso, 2009), but it exceeds the loss of
muscle mass due to neurological factors (Clark, 2009). Disuse-
induced deficits in central activation may account for about 50%
of the between – person variability in the loss of knee exten-
sor strength after 3 weeks of bed rest (Kawakami et al., 2001).
Deschenes et al. (2002) hypothesized that the loss of strength
resulting from a 2-week unilateral lower limb unloading, was due
to impaired neural activation of the affected muscle. In that study
they immobilized the lower limb of healthy young college students
in a light weight orthopedic knee brace at an angle of 70˚, with
the purpose to eliminate weight bearing activity. After 2weeks
of immobilization, peak isokinetic torque of the knee extensors
across a range of velocities was reduced by an average of 17.2% with
greater losses in slow than in fast contraction velocities. The reduc-
tion in torque was coupled by reduced EMG activity, but the ratio
of total torque/EMG was unchanged. Muscle fiber composition
remained unchanged in the 2-week unloading period.
Studies performed using animal models of hindlimb unload-
ing showed that there is a shift of MHC isoforms from slow to
fast, accompanied by significant muscle atrophy (Leterme and
Falempin, 1994;Picquet and Falempin, 2003). It is noteworthy
that chronic electrostimulation prevented the shift in fiber types,
but failed to counteract the loss of muscle mass and force output
(Leterme and Falempin, 1994). Similarly, tendon vibration applied
daily on the unloaded hindlimb significantly attenuated, but did
not prevent the loss of muscle mass and the changes in fiber type
(Falempin and In-Albon, 1999).
A decrease in capillary supply and blood flow during rest
and exercise is common in unloaded muscle. Degens and Always
(2006) reported that the capillary loss and reduction in maximal
blood flow are largely proportional to the loss of muscle mass,
maintaining blood flow per unit muscle mass. However, a recent
investigation looking at the effects of a 9-day hind limb unloading
on both capillarization and expression of angio-adaptive mole-
cules reported differences in capillary regression between fast and
slow rat skeletal muscles (Roudier et al., 2010). In that experi-
ment, both soleus and plantaris muscles were atrophied similarly,
but capillary regression occurred only in the soleus, which is a slow
twitch and oxidative postural muscle. Conversely, capillarization
was preserved in the plantaris, a fast twitch, glycolytic muscle. The
authors reported that the key pro- and anti-angiogenic signals
(various types of VEGF) play a determinant role in regulating this
process.
The muscle fatigue profile following muscle disuse atrophy
involve both the loss of strength, transition from slow to fast
myosin, a shift toward glycolysis and a decreased capacity for fat
Frontiers in Physiology | Striated Muscle Physiology May 2012 | Volume 3 | Article 142 | 10
Bogdanis Physical activity and muscle fatigue
oxidation (Stein and Wade, 2005). However, caution should be
exercised when measuring fatigue on a disused muscle. In the
immobilization study of Deschenes et al. (2002), fatigue resistance
was assessed during a 30 repetition set of isokinetic knee extensions
at 3.14 rad s1, as the difference in total work produced during
the first 10 repetitions compared with the last 10 repetitions. By
calculating this percent decrease of work, fatigue resistance was
enhanced instead of decreased following immobilization (drop in
total work 29.8 ±2.5 vs. 20.6 ±6.5%, pre vs. post immobiliza-
tion; P<0.05). However, the total work generated over the 30
contractions was 15% less after immobilization (2735.3 ±207.6
vs. 2339.0 ±163.3 J, P<0.05). This artifact, i.e., an improvement
rather than a reduction of fatigue resistance should be interpreted
with caution because this is simply due to the lower total work in
the first 10 repetitions after immobilization.
The length of immobilization plays an important role in the
negative adaptations resulting from muscle unloading. When
immobilization is longer than 4 weeks, there is a large increase
in fatigability linked with reductions in oxidative capacity due to
decreases in CS and PDH. Indeed, Ward et al. (1986), showed
that after 5 weeks of immobilization, the proportion of PDH in
the active form was only 52%, compared with 98% after train-
ing 5 months training. This results in greater lactate and H+
accumulation during exercise after the immobilization period.
USE OF HIGH-INTENSITY INTERMITTENT EXERCISE
TRAINING IN PATIENT POPULATIONS
Many chronic diseases, such as coronary artery disease (CAD),
COPD result in a progressively reduced exercise capacity due to
both biochemical and morphological changes in skeletal mus-
cles. Abnormal fiber-type proportions have been found in COPD
patients, with markedly lower type I oxidative fibers (16 vs. 42%)
compared to controls (Gosker et al., 2002). Also, oxidative capac-
ity of type I, as well as of type IIA fibers was lower than normal,
thus making those patients more susceptible to peripheral mus-
cle fatigue. The reduced exercise capacity and increased muscle
fatigue of those patients is not only due to intolerable sensations
of breathlessness, but also due to peripheral muscle discomfort
(Vogiatzis, 2011). The inability of those patients to be physically
active reduces even more their exercise capacity and this vicious
circle increases the risk of negative health outcomes due to the
sedentary lifestyle (Rimmer et al., 2012). COPD patients have
a reduced tolerance of continuous exercise and different reha-
bilitative strategies and training modalities have been proposed
to optimize exercise tolerance. Several recent investigations have
shown that the greater physiological benefits can be obtained
through high-intensity intermittent, compared with moderate-
intensity continuous training. Vogiatzis (2011) has shown that
using interval exercise in the form of 30 s on and 30 s off, at an
intensity of 100% of maximum work rate, COPD patients can
almost triple the total exercise duration (30 vs. 12 min), with signif-
icantly lower and more stable metabolic and ventilator responses
compared with continuous exercise. Patients with severe COPD
can endure high-intensity interval training in a rehabilitation set-
ting for long periods of time with lower symptoms of dyspnea and
leg discomfort compared with the conventionally implemented
continuous training (Kortianou et al., 2010). This is due to the
beneficial effects of the recovery intervals that allow PCr resynthe-
sis and lactate removal. The increased availability of PCr in each
short exercise bout and its short-duration result in a decreased
reliance on anaerobic glycolysis that results in less lactate accumu-
lation and allows more intense exercise stimuli to the peripheral
muscle with less cardiac and respiratory strain. A recent study
showed that this type of training performed by severe COPD
patients allowed them to exercise at a sufficiently high intensity to
obtain true physiological training effects manifested by improve-
ments in muscle fiber size, type, and capillarization (Vogiatzis et al.,
2011).
High-intensity interval training in the form of four repeated
4 min bouts at 90–95% of peak heart rate, separated by 2–3 min or
active recovery at 60–70% of peak heart rate, has been used suc-
cessfully in cardiac patients (Wisloff et al., 2009). In those patients
fatigue occurs not only because of reduced cardiac function but
also due to skeletal muscle fatigue (Downing and Balady, 2011).
Decreased muscle mass and capillarization, shifting of slow to
fast-twitch fibers that rely more on glycolysis, as well as reduced
mitochondrial size and oxidative enzymes are typically found in
heart failure patients and cannot be explained by decondition-
ing alone (Downing and Balady, 2011). The role of inflammatory
mediators, such as tumor necrosis factor and interleukin-6, in the
pathogenesis of skeletal muscle wasting and fatigue in numer-
ous clinical settings including heart failure, is an area of active
investigation. Interestingly, inflammatory cytokines are reduced
following exercise training, in parallel with the improved fatigue
resistance (Downing and Balady, 2011). Supervised high-intensity
intermittent training can be safely prescribed as a time-efficient
strategy in those patients because it results in far superior adapta-
tions compared with conventional low intensity exercise training
(Moholdt et al., 2012). This type of exercise not only reduces mus-
cle fatigue but also improves cardiorespiratory fitness, endothelial
function, left ventricle morphology and function (e.g., ejection
fraction) in all cardiac patients, with no adverse or other life-
threatening events occurring secondary to exercise participation
(Cornish et al., 2011).
This type of aerobic interval training has also been used for the
treatment of metabolic syndrome (Tjonna et al., 2008). Patients
exercised three times per week for 16weeks and compared to the
traditional low intensity training group, the high-intensity exer-
cise group demonstrated a larger improvement in VO2max (35 vs.
16%, P<0.01), endothelial function (9 vs. 5%, P<0.001), insulin
signaling in fat and skeletal muscle, fasting blood glucose, and
lipogenesis in adipose tissue. Furthermore, both the continuous
and the intermittent exercise programs were equally effective in
reducing mean arterial blood pressure and body weight and fat.
The use of high-intensity interval training in the form of short
cycle ergometer sprints lasting 10–20 s has been recently used as a
time-efficient alternative to traditional cardiorespiratory training
with a target to improve metabolic health (Metcalfe et al., 2011).
The subjects were healthy but sedentary men and women who
trained three times per week for 6 weeks, with sessions lasting only
10 min, including only one or two 10–20 s sprints and a warm-up
and cool-down. Insulin sensitivity in the male training group was
increased by 28%, while VO2peak was increased by 15 and 12% in
the males and females, respectively.
www.frontiersin.org May 2012 | Volume 3 | Article 142 | 11
Bogdanis Physical activity and muscle fatigue
CONCLUSION AND FUTURE PERSPECTIVES
Muscle fatigue is not only important for sports settings but
may be vital during everyday life because it may pose a bar-
rier to normal physical activity. Deconditioning due to seden-
tary lifestyle and/or cardiovascular and pulmonary diseases may
limit exercise capacity and increase fatigability, resulting in fur-
ther deterioration of health and well being. However, the adverse
effects of physical inactivity can be reversed by exercise train-
ing and the extended use of high-intensity interval training
as a time-efficient strategy for improving both sports perfor-
mance and health-related fitness requires further investigation.
Since exercise intensity and duration are key variables for adap-
tations, more research is needed to reveal the best combina-
tion of those variables for each population group. Also, the
safety of this type of training in the short and longer term
and the possibility of overtraining should be examined in larger
patient cohorts as well as in different age groups of healthy
individuals.
REFERENCES
Allen, D., Lamb, G. D., and Westerblad,
H. (2008). Skeletal muscle fatigue:
cellular mechanisms. Physiol. Rev.
88, 287–332.
Amann, M., and Dempsey, J. A. (2008).
Locomotor muscle fatigue modi-
fies central motor drive in healthy
humans and imposes a limitation
to exercise performance. J. Physiol.
(Lond.) 586, 161–173.
Andersen, J. L., and Aagaard, P. (2000).
Myosin heavy chainIIX overshoot in
human skeletal muscle. Muscle Nerve
2, 1095–1104.
Andersen, J. L., and Aagaard, P. (2010).
Effects of strength training on mus-
cle fiber types and size; conse-
quences for athletes training for
high-intensity sport. Scand. J. Med.
Sci. Sports 20(Suppl. 2), 32–38.
Andersen, J. L., Klitgaard, H., and Saltin,
B. (1994). Myosin heavy chain iso-
forms in single fibres from m. vas-
tus lateralis of sprinters: influence
of training. Acta Physiol. Scand. 151,
135–142.
Andersen, L. L., Andersen, J. L., Mag-
nusson, S. P., Suetta, C., Madsen, J.
L., Christensen, L. R., and Aagaard,
P. (2005). Changes in the human
muscle force-velocity relationship in
response to resistance training and
subsequent detraining. J. Appl. Phy s-
iol. 99, 87–94.
Andersen, P., and Henriksson, J. (1977).
Capillary supply of the quadri-
ceps femoris muscle of man: adap-
tive response to exercise. J. Physiol.
(Lond.) 270, 677–690.
Astorino, T. A., Allen, R. P., Roberson, D.
W., and Jurancich, M. (2012). Effect
of high-intensity interval training on
cardiovascular function, VO2max,
and muscular force. J. Strength Cond.
Res. 26, 138–145.
Barnett, C., Carey,M., Proietto, J., Cerin,
E., Febbraio, M. A., and Jenkins, D.
(2004). Muscle metabolism during
sprint exercise in man: influence of
sprint training. J. Sci. Med. Sport 7,
314–22.
Behm, D. G., Whittle, J.,Button, D., and
Power, K. (2002). Intermuscle differ-
ences in activation. Muscle Nerve 25,
236–243.
Bigland-Ritchie, B., Cafarelli, E., and
Vøllestad, N. K. (1986). Fatigue
of submaximal static contractions.
Acta Physiol. Scand. 556, 137–148.
Billaut, F., Basset, F. A., Giacomoni,
M., Lemaitre, F., Tricot, V., and Fal-
gairette, G. (2006). Effect of high-
intensity intermittent cycling sprints
on neuromuscular activity. Int. J.
Sports Med. 27, 25–30.
Bishop, D., and Edge, J. (2006). Deter-
minants of repeated-sprint ability
in females matched for single-sprint
performance. Eur. J. Appl. Physiol.
97, 373–379.
Bishop, D., Girard, O., and Mendez-
Villanueva, A. (2011). Repeated-
sprint ability – part II: recommen-
dations for training. Sports Med. 41,
741–756.
Bishop, D., Lawrence, S., and Spencer,
M. (2003) Predictors of repeated-
sprint ability in elite female hockey
players. J. Sci. Med. Sport 6, 199–209.
Bishop, D., and Spencer, M. (2004).
Determinants of repeated-sprint
ability in well-trained team-sport
athletes and endurance-trained ath-
letes. J. Sports Med. Phys. Fitness 44,
1–7.
Bloomfield, S. A. (1997). Changes in
musculoskeletal structure and func-
tion with prolonged bed rest. Med.
Sci. Sports Exerc. 29, 197–206.
Bogdanis, G. C., Nevill, M. E., Boobis, L.
H., and Lakomy, H. K. (1996). Con-
tribution of phosphocreatine and
aerobic metabolism to energy sup-
ply during repeated sprint exercise.
J. Appl. Physiol. 80, 876–884.
Bogdanis, G. C., Nevill, M. E., Boobis,
L. H., Lakomy, H. K., and Nevill, A.
M. (1995). Recovery of power out-
put and muscle metabolites follow-
ing 30 s of maximal sprint cycling
in man. J. Physiol. (Lond.) 482,
467–480.
Bogdanis, G. C., Nevill, M. E., Lakomy,
H. K., and Boobis, L. H. (1998).
Power output and muscle metabo-
lism during and following recovery
from 10 and 20 s of maximal sprint
exercise in humans. Acta Physiol.
Scand. 163, 261–272.
Bosquet, L., Montpetit, J., Arvisais, D.,
and Mujika, I. (2007). Effects of
tapering on performance: a meta-
analysis. Med. Sci. Sports Exerc. 39,
1358–1365.
Bottinelli, R. (2001). Functional hetero-
geneity of mammalian single muscle
fibres: do myosin isoforms tell the
whole story? Pflugers Arch. 443,6–17.
Burgomaster, K. A., Cermak, N. M.,
Phillips, S. M., Benton, C. R., Bonen,
A., and Gibala, M. J. (2007). Diver-
gent response of metabolite trans-
port proteins in human skeletal
muscle after sprint interval training
and detraining. Am. J. Physiol. 292,
R1970–R1976.
Burgomaster, K. A., Heigenhauser, G.
J., and Gibala, M. J. (2006). Effect
of short-term sprint interval train-
ing on human skeletal muscle carbo-
hydrate metabolism during exercise
and time-trial performance. J. Appl.
Physiol. 100, 2041–2047.
Burgomaster, K. A., Howarth, K. R.,
Phillips, S. M., Rakobowchuk, M.,
Macdonald, M. J., McGee, S. L.,
and Gibala, M. J. (2008). Similar
metabolic adaptations during exer-
cise after low volume sprint interval
and traditional endurance training
in humans. J. Physiol. (Lond.) 586,
151–160.
Burgomaster, K. A., Hughes, S. C.,
Heigenhauser, G. J., Bradwell, S. N.,
and Gibala, M. J. (2005). Six sessions
of sprint interval training increases
muscle oxidative potential and cycle
endurance capacity in humans. J.
Appl. Physiol. 98, 1985–1990.
Cairns, S. P., and Lindinger, M. I.
(2008). Do multiple ionic interac-
tions contribute to skeletal mus-
cle fatigue? J. Physiol. (Lond.) 586,
4039–4054.
Calbet, J. A., De Paz, J. A., Garatachea,
N., Cabeza de Vaca, S., and Chavar-
ren, J. (2003). Anaerobic energy
provision does not limit Wingate
exercise performance in endurance-
trained cyclists. J. Appl. Physiol. 94,
668–676.
Calvo, J. A., Daniels, T. G., Wang, X.,
Paul, A., Lin, J., Spiegelman, B. M.,
Stevenson, S. C., and Rangwala, S. M.
(2008). Muscle-specific expression
of PPARgamma coactivator-1alpha
improves exercise performance and
increases peak oxygen uptake. J.
Appl. Physiol. 104, 1304–1312.
Casey, A., Constantin-Teodosiu, D.,
Howell, S., Hultman, E., and Green-
haff, P. L. (1996). Metabolic response
of type I and II muscle fibres dur-
ing repeated bouts of maximal exer-
cise in humans. Am. J. Physiol. 271,
E38–E43.
Clark, B. C. (2009). In vivo alterations
in skeletal muscle form and function
after disuse atrophy. Med. Sci. Sports
Exerc. 41, 1869–1875.
Coffey, V. G., and Hawley, J. A. (2007).
The molecular bases of training
adaptation. Sports Med. 37, 737–763.
Colliander, E. B., Dudley, G. A., and
Tesch, P. A. (1988). Skeletal mus-
cle fibre type composition and per-
formance during repeated bouts
of maximal, concentric contrac-
tions. Eur. J. Appl. Physiol. 58,
81–86.
Cooke, S. R., Petersen, S. R., and Quin-
ney, H. A. (1997). The influence of
maximal aerobic power on recovery
of skeletal muscle following anaero-
bic exercise. Eur. J. Appl. Physiol. 75,
512–519.
Cornish, A. K., Broadbent, S., and
Cheema, B. S. (2011). Interval train-
ing for patients with coronary artery
disease: a systematic review. Eur. J.
Appl. Physiol. 111, 579–589.
Costill, D. L., Daniels, J., Evans, W.,
Fink, W., Krahenbuhl, G., and Saltin,
B. (1976). Skeletal muscle enzymes
and fibre composition in male and
female track athletes. J. Appl. Physiol.
40, 149–154.
Coyle, E. F. (2005). Very intense
exercise-training is extremely potent
and time efficient: a reminder. J.
Appl. Physiol. 98, 1983–1984.
Coyle, E. F., Coggan, A. R., Hopper,
M. K., and Walters, T. J. (1988).
Determinants of endurance in well-
trained cyclists. J. Appl. Physiol. 64,
2622–2630.
Coyle, E. F., Martin, W. H. III, Sina-
core, D. R., Joyner, M. J., Hagberg,
J. M., and Holloszy, J. O. (1984).
Time course of loss of adaptations
after stopping prolonged intense
endurance training. J. Appl. Physiol.
57, 1857–1864.
Frontiers in Physiology | Striated Muscle Physiology May 2012 | Volume 3 | Article 142 | 12
Bogdanis Physical activity and muscle fatigue
D’Antona, G., Lanfranconi, F., Pelle-
grino, M. A., Brocca, L., Adami,
R., Rossi, R., Moro, G., Miotti,
D., Canepari, M., and Bottinelli,
R. (2006). Skeletal muscle hyper-
trophy and structure and function
of skeletal muscle fibres in male
body builders. J. Physiol. (Lond.) 570,
611–627.
Dawson, B., Fitzsimons, M., Green, S.,
Goodman, C., Carey, M., and Cole,
K. (1998). Changes in performance,
muscle metabolites, enzymes and
fibre types after short sprint training.
Eur. J. Appl. Physiol. 78, 163–169.
Degens, H., and Always, S. E. (2006).
Control of muscle size during dis-
use, disease, and aging. Int. J. Sports
Med. 27, 94–99.
Deschenes, M. R., Giles, J. A., McCoy,
R. W., Volek, J. S., Gomez, A. L.,
and Kraemer, W. J. (2002). Neural
factors account for strength decre-
ments observed after short-term
muscle unloading. Am. J. Physiol.
282, R578–R583.
Downing, J., and Balady, G. J. (2011).
The role of exercise training in heart
failure. J. Am. Coll. Cardiol. 58,
561–569.
Dudley, G. A., Abraham, W. M., and
Terjung, R. L. (1982). Influence of
exercise intensity and duration on
biochemical adaptations in skeletal
muscle. J. Appl. Physiol. 53, 844–850.
Dupont, G., Millet, G. P., Guinhouya,C.,
and Berthoin, S. (2005). Relation-
ship between oxygen uptake kinetics
and performance in repeated run-
ning sprints. Eur. J. Appl. Physiol. 95,
27–34.
Edge, J., Bishop, D., and Goodman, C.
(2006). The effects of training inten-
sity on muscle buffer capacity in
females. Eur. J. Appl. Physiol. 96,
97–105.
Edge, J., Bishop, D., Goodman, C.,
and Dawson, B. (2005). Effects of
high- and moderate-intensity train-
ing on metabolism and repeated
sprints. Med. Sci. Sports Exerc. 37,
1975–1982.
Edwards, R. H. (1981). “Human mus-
cle function and fatigue,” in Human
Muscle Fatigue: Physiological Mecha-
nisms, eds R. Porter and J. Whelan
(London: Pitman Medical), 1–18.
Esbjörnsson, M., Hellsten-Westing, Y.,
Balsom, P. D., Sjödin, B., and Jans-
son, E. (1993). Muscle fibre type
changes with sprint training: effect
of training pattern. Acta Physiol.
Scand. 149, 245–246.
Falempin, M., and In-Albon, S. F.
(1999). Influence of brief daily ten-
don vibration on rat soleus muscle
in non-weight-bearing situation. J.
Appl. Physiol. 87, 3–9.
Ferrari Bravo, D., Impellizzeri, F. M.,
Rampinini, E., Castagna, C., Bishop,
D., and Wisloff, U. (2008). Sprint vs.
interval training in football. Int. J.
Sports Med. 29, 668–674.
Ferreira, L. F., and Reid, M. B. (2008).
Muscle-derived ROS and thiol reg-
ulation in muscle fatigue. J. Appl.
Physiol. 104, 853–860.
Fitts, R. H. (1994). Cellular mechanisms
of muscle fatigue. Physiol. Rev. 74,
49–94.
Fitts, R. H. (2003). Effects of regular
exercise training on skeletal mus-
cle contractile function. Am.J.Phys.
Med. Rehabil. 82, 320–331.
Fitts, R. H. (2008). The cross-bridge
cycle and skeletal muscle fatigue. J.
Appl. Physiol. 104, 551–558.
Fitts, R. H., and Widrick, J. J. (1996).
Muscle mechanics: adaptations with
exercise-training. Exerc. Sport Sci.
Rev. 24, 427–473.
Fitzsimons, M., Dawson, B., Ward, D.,
and Wilkinson, A. (1993). Cycling
and running tests of repeated sprint
ability. Aust. J. Sci. Med. Sport 25,
82–87.
Gaitanos, G. C., Williams, C., Boobis, L.
H., and Brooks, S. (1993). Human
muscle metabolism during intermit-
tent maximal exercise. J. Appl. Phys-
iol. 75, 712–719.
Garrandes, F., Colson, S. S., Pensini,
M., Seynnes, O., and Legros, P.
(2007). Neuromuscular fatigue pro-
file in endurance-trained and power-
trained athletes. Med. Sci. Sports
Exerc. 39, 149–158.
Gibala, M. J. (2009). Molecular
responses to high-intensity interval
exercise. Appl. Physiol. Nutr. Metab.
34, 428–432.
Gibala, M. J., Little, J. P., Macdonald, M.
J., and Hawley, J. A. (2012). Physi-
ological adaptations to low-volume,
high-intensity interval training in
health and disease. J. Physiol. (Lond.)
590, 1077–1084.
Gibala, M. J., Little, J. P., van Essen,
M., Wilkin, G. P., Burgomaster,
K. A., Safdar, A., Raha, S., and
Tarnopolsky, M. A. (2006). Short-
term sprint interval versus tradi-
tional endurance training: similar
initial adaptations in human skeletal
muscle and exercise performance. J.
Physiol. (Lond.) 575, 901–911.
Girard, O., Mendez-Villanueva, A., and
Bishop, D. (2011). Repeated-sprint
ability – part I: factors contributing
to fatigue. Sports Med. 41, 673–694.
Gosker, H. R., van Mameren, H., van
Dijk, P. J., Engelen, M. P., van der
Vusse, G. J., Wouters, E. F., and
Schols, A. M. (2002). Skeletal mus-
cle fibre-type shifting and meta-
bolic profile in patients with chronic
obstructive pulmonary disease. Eur.
Respir. J. 19, 617–625.
Green, H. J., and Pette, D. (1997).
Early metabolic adaptations of rab-
bit fast-twitch muscle to chronic
low-frequency stimulation. Eur. J.
Appl. Physiol. 75, 418–424.
Greenhaff, P. L., Nevill, M. E., Soder-
lund, K., Bodin, K., Boobis, L.
H., Williams, C., and Hultman, E.
(1994). The metabolic responses of
human type I and II muscle fibres
during maximal treadmill sprinting.
J. Physiol. (Lond.) 478, 149–155.
Hamada, T., Sale, D. G., MacDougall,
J. D., and Tarnopolsky, M. A.
(2003). Interaction of fibre type,
potentiation and fatigue in human
knee extensor muscles. Acta Physiol.
Scand. 178, 165–173.
Hamilton, A. L., Nevill, M. E.,
Brooks, S., and Williams, C. (1991).
Physiological responses to maxi-
mal intermittent exercise: differ-
ences between endurance-trained
runners and games players. J. Sports
Sci. 9, 371–382.
Harber, M., and Trappe, S. (2008). Sin-
gle muscle fiber contractile prop-
erties of young competitive dis-
tance runners. J. Appl. Physiol. 105,
629–636.
Harridge, S. D., Bottinelli, R., Canepari,
M., Pellegrino, M., Reggiani,C., Esb-
jornsson, M., Balsom, P. D., and
Saltin, B. (1998). Sprint training,
in vitro and in vivo muscle function,
and myosin heavy chain expression.
J. Appl. Physiol. 84, 442–449.
Haseler, L. J., Hogan, M. C., and
Richardson, R. S. (1999). Skeletal
muscle phosphocreatine recovery in
exercise-trained humans is depen-
dent on O2 availability. J. Appl. Phys-
iol. 86, 2013–2018.
Haseler, L. J., Lin, A., Hoff, J., and
Richardson, R. S. (2007). Oxygen
availability and PCr recovery rate in
untrained human calf muscle: evi-
dence of metabolic limitation in nor-
moxia. Am. J. Physiol. 293, R2046–
R2051.
Haseler, L. J., Lin, A. P., and Richard-
son, R. S. (2004). Skeletal mus-
cle oxidative metabolism in seden-
tary humans: 31P-MRS assess-
ment of O2 supply and demand
limitations. J. Appl. Physiol. 97,
1077–1081.
Hautier, C. A., Arsac, L. M., Deghdegh,
K., Souquet, J., Belli, A., and Lacour,
J. R. (2000). Influence of fatigue on
EMG/force ratio and cocontraction
in cycling. Med. Sci. Sports Exerc. 32,
839–843.
Helgerud, J., Engen, L. C., Wisloff,
U., and Hoff, J. (2001). Aerobic
endurance training improves soccer
performance. Med. Sci. Sports Exerc.
33, 1925–1931.
Hernandez, A., Cheng, A., and West-
erblad, H. (2012). Antioxidants and
skeletal muscle performance: “com-
mon knowledge” vs. experimen-
tal evidence. Front. Physiol. 3:46.
doi:10.3389/fphys.2012.00046
Hurley, B. F., Hanson, E. D., and Sheaff,
A. K. (2011). Strength training as
a countermeasure to aging muscle
and chronic disease. Sports Med. 41,
289–306.
Iaia, F. M., and Bangsbo, J. (2010).
Speed endurance training is a power-
ful stimulus for physiological adap-
tations and performance improve-
ments of athletes. Scand. J. Med. Sci.
Sports 20, 11–23.
Iaia, F. M., Thomassen, M., Kolding,
H., Gunnarsson, T., Wendell, J., Ros-
tgaard, T., Nordsborg, N., Krus-
trup, P., Nybo, L., Hellsten, Y., and
Bangsbo, J. (2008). Reduced vol-
ume but increased training inten-
sity elevates muscle Na+-K+pump
α1-subunit and NHE1 expression
as well as short-term work capac-
ity in humans. Am. J. Physiol. 294,
R966–R974.
Jensen, L., Bangsbo, J., and Hellsten,
Y. (2004). Effect of high intensity
training on capillarization and pres-
ence of angiogenic factors in human
skeletal muscle. J. Physiol. (Lond.)
557, 571–582.
Johansen, L., and Quistorff, B. (2003).
31P-MRS characterization of sprint
and endurance trained athletes. Int.
J. Sports Med. 24, 183–189.
Juel, C. (2008). Regulation of pH in
human skeletal muscle: adaptations
to physical activity. Acta Physiol.
(Oxf.) 193, 17–24.
Juel, C., Klarskov, C., Nielsen, J. J., Krus-
trup, P., Mohr, M., and Bangsbo,
J. (2004). Effect of high-intensity
intermittent training on lactate and
H+release from human skeletal
muscle. Am. J. Physiol. 286, E245–
E251.
Karatzaferi, C.,de Haan, A., Ferguson,R.
A., van Mechelen, W., and Sargeant,
A. J. (2001a). Phosphocreatine and
ATP content in human single mus-
cle fibres before and after maximum
dynamic exercise. Pflugers Arch. 442,
467–474.
Karatzaferi, C., de Haan, A., van Meche-
len, W., and Sargeant, A. J. (2001b).
Metabolic changes in single human
fibres during brief maximal exercise.
Exp. Physiol. 86, 411–415.
Kawakami, Y., Akima, H., Kubo, K.,
Muraoka,Y., Hasegawa, H., Kouzaki,
M., Imai, M., Suzuki, Y., Gunji,
A., Kanehisa, H., and Fukunaga,
T. (2001). Changes in muscle size,
www.frontiersin.org May 2012 | Volume 3 | Article 142 | 13
Bogdanis Physical activity and muscle fatigue
architecture, and neural activation
after 20 days of bed rest with and
without resistance exercise. Eur. J.
Appl. Physiol. 84, 7–12.
Klausen, K., Andersen, L. B., and Pelle,
I. (1981). Adaptive changes in work
capacity, skeletal muscle capillariza-
tion and enzyme levels during train-
ing and detraining. Acta Physiol.
Scand. 113, 9–16.
Korhonen, M. T., Cristea, A., Alen,
M., Hakkinen, K., Sipila, S., Mero,
A., Viitasalo, J. T., Larsson, L., and
Suominen, H. (2006). Aging, muscle
fiber type, and contractile function
in sprint-trained athletes. J. Appl.
Physiol. 101, 906–917.
Kortianou, E. A., Nasis, I. G., Spetsi-
oti, S. T., Daskalakis, A. M., and
Vogiatzis, I. (2010). Effectiveness of
interval exercise training in patients
with COPD. Cardiopulm. Phys. Ther.
J. 21, 12–19.
Kupa, E. J., Roy, S. H., Kandarian, S. C.,
and De Luca, C. J. (1995). Effects of
muscle fibre type and size on EMG
median frequency and conduction
velocity. J. Appl. Physiol. 79, 23–32.
Lamb, G. D., and Westerblad, H. (2011).
Acute effects of reactive oxygen and
nitrogen species on the contractile
function of skeletal muscle. J. Phys-
iol. (Lond.) 589, 2119–2127.
Laursen, P. B. (2010). Training for
intense exercise performance: high-
intensity or high-volume training?
Scand. J. Med. Sci. Sports 20, 1–10.
Lawler, J. M., Song, W., and Demaree,
S. R. (2003). Hindlimb unloading
increases oxidative stress and dis-
rupts antioxidant capacity in skeletal
muscle. Free Radic. Biol. Med. 35,
9–16.
Lawler, J. M., Song, W., and Kwak, H. B.
(2006). Differential response of heat
shock proteins to hindlimb unload-
ing and reloading in the soleus.
Muscle Nerve 33, 200–207.
Leterme, D., and Falempin, M. (1994).
Compensatory effects of chronic
electrostimulation on unweighted
rat soleus muscle. Pflugers Arch. 426,
155–160.
Linossier, M. T., Denis, C., Dormois,
D., Geyssant, A., and Lacour, J. R.
(1993). Ergometric and metabolic
adaptation to a 5-s sprint training
programme. Eur. J. Appl. Physiol. 67,
408–414.
Linossier, M. T., Dormois, D., Perier,
C., Frey, J., Geyssant, A., and
Denis, C. (1997). Enzyme adapta-
tions of human skeletal muscle dur-
ing bicycle short-sprint training and
detraining. Acta Physiol. Scand. 161,
439–445.
MacDougall, J. D., Hicks, A. L., Mac-
Donald, J. R., McKelvie, R. S., Green,
H. J., and Smith, K. M. (1998).
Muscle performance and enzymatic
adaptations to sprint interval train-
ing. J. Appl. Physiol. 84, 2138–2142.
Malek, M. H., Olfert, I. M., and Espos-
ito, F. (2010). Detraining losses of
skeletal muscle capillarization are
associated with vascular endothelial
growth factor protein expression in
rats. Exp. Physiol. 95, 359–368.
Malisoux, L., Francaux, M., and
Theisen, D. (2007). What do single-
fibre studies tell us about exercise
training? Med. Sci. Sports Exerc. 39,
1051–1060.
McCully, K. K., Iotti, S., Kendrick, K.,
Wang, Z., Posner, J. D., Leigh, J.,
and Chance, B. (1994). Simultane-
ous in vivo measurements of HbO2
saturation and PCr kinetics after
exercise in normal humans. J. Appl.
Physiol. 77, 5–10.
McCully, K. K., Kakihira, H., Van-
denborne, K., and Kent-Braun, J.
(1991). Noninvasive measurements
of activity-induced changes in mus-
cle metabolism. J. Biomech. 24,
153–161.
McKenna, M. J., Bangsbo, J., and
Renaud, J. M. (2008). Muscle K+,
Na+, and Cl disturbances and Na+-
K+pump inactivation: implications
for fatigue. J. Appl. Physiol. 104,
288–295.
McKenna, M. J., Schmidt, T. A., Harg-
reaves, M., Cameron, L., Skinner, S.
L., and Kjeldsen, K. (1993). Sprint
training increases human skeletal
muscle Na+-K+-ATPase concentra-
tion and improves K+regulation. J.
Appl. Physiol. 75, 173–180.
Mendez-Villanueva, A., Hamer, P.,
and Bishop, D. (2008). Fatigue in
repeated-sprint exercise is related to
muscle power factors and reduced
neuromuscular activity. Eur. J. Appl.
Physiol. 103, 411–419.
Metcalfe, R. S., Babraj, J. A., Fawkner,
S. G., and Vollaard, N. B. (2011).
Towards the minimal amount of
exercise for improving metabolic
health: beneficial effects of reduced-
exertion high-intensity interval
training. Eur. J. Appl. Physiol.
doi:10.1007/s00421-011-2254-z
Moholdt, T., Aamot, I. L., Granøien, I.,
Gjerde, L., Myklebust, G., Walder-
haug, L., Brattbakk, L., Hole, T.,
Graven, T., Stolen, T. O., Amund-
sen, B. H., Molmen-Hansen, H. E.,
Stoylen, A., Wisloff, U., and Slor-
dahl, S. A. (2012). Aerobic inter-
val training increases peak oxygen
uptake more than usual care exer-
cise training in myocardial infarc-
tion patients: a randomized, con-
trolled study. Clin. Rehabil. 26,
33–44.
Mohr, M., Krustrup, P., Nielsen, J. J.,
Nybo, L., Rasmussen, M. K., Juel, C.,
and Bangsbo, J. (2007). Effect of two
different intense training regimens
on skeletal muscle ion transport pro-
teins and fatigue development. Am.
J. Physiol. 292, R1594–R1602.
Moylan, J. S., and Reid, M. B. (2007).
Oxidative stress,chronic disease, and
muscle wasting. Muscle Nerve 35,
411–429.
Mujika, I., and Padilla, S. (2001). Mus-
cular characteristics of detraining in
humans. Med. Sci. Sports Exerc. 33,
1297–1303.
Nordlund, M. M., Thorstensson, A.,
and Cresswell, A. G. (2004). Cen-
tral and peripheral contributions to
fatigue in relation to level of activa-
tion during repeated maximal vol-
untary isometric plantar flexions. J.
Appl. Physiol. 96, 218–225.
Ohira, Y., Yoshinaga, T., Nomura, T.,
Kawano, F., Ishihara, A., Nonaka,
I., Roy, R. R., and Edgerton, V.
R. (2002). Gravitational unloading
effects on muscle fiber size, pheno-
type and myonuclear number. Adv.
Space Res. 30, 777–781.
Osternig, L. R., Hamill, J., Lander, J.
E., and Robertson, R. (1986). Co-
activation of sprinter and distance
runner muscles in isokinetic exer-
cise. Med. Sci. Sports Exerc. 18,
431–435.
Paasuke, M., Ereline, J., and Gapeyeva,
H. (1999). Twitch contractile prop-
erties of plantar flexor muscles
in power and endurance trained
athletes. Eur. J. Appl. Physiol. 80,
448–451.
Parolin,M. L., Chesley,A., Matsos, M. P.,
Spriet, L. L.,Jones, N. L., and Heigen-
hauser, G. J. (1999). Regulation of
skeletal muscle glycogen phosphory-
lase and PDH during maximal inter-
mittent exercise. Am. J. Physiol. 277,
E890–E900.
Pellegrino, M. A., Desaphy, J. F., Brocca,
L., Pierno, S., Camerino, D. C., and
Bottinelli, R. (2011). Redox home-
ostasis, oxidative stress and disuse
muscle atrophy. J. Physiol. (Lond.)
589, 2147–2160.
Pette, D. (1985). Metabolic heterogene-
ity of muscle fibres. J. Exp. Biol. 115,
179–189.
Pette, D. (1998). Training effects on the
contractile apparatus. Acta Physiol.
Scand. 162, 367–376.
Pette, D., and Staron, R. S. (1997).
Mammalian skeletal muscle fiber
type transitions. Int. Rev. Cytol. 170,
143–223.
Pette, D., and Vrbova, G. (1999). What
does chronic electrical stimulation
teach us about muscle plasticity?
Muscle Nerve 22, 666–677.
Picquet, F., and Falempin, M. (2003).
Compared effects of hindlimb
unloading versus terrestrial deaf-
ferentation on muscular properties
of the rat soleus. Exp. Neurol. 182,
186–194.
Racinais, S., Bishop, D., Denis, R., Lat-
tier, G., Mendez-Villaneuva, A., and
Perrey,S. (2007). Muscle deoxygena-
tion and neural drive to the muscle
during repeated sprint cycling. Med.
Sci. Sports Exerc. 39, 268–274.
Ratel, S., Lazaar, N., Williams, C. A.,
Bedu, M., and Duche, P. (2003). Age
differences in human skeletal muscle
fatigue during high-intensity inter-
mittent exercise. Acta Paediatr. 92,
1248–1254.
Rimmer, J. H., Schiller, W., and Chen,
M. D. (2012). Effects of disability-
associated low energy expenditure
deconditioning syndrome. Exerc.
SportSci.Rev.40, 22–29.
Ross, A., and Leveritt, M. (2001). Long-
term metabolic and skeletal mus-
cle adaptations to short-sprint train-
ing: implications for sprint train-
ing and tapering. Sports Med. 31,
1063–1082.
Roudier, E., Gineste, C., Wazna, A.,
Dehghan, K., Desplanches, D., and
Birot, O. (2010). Angio-adaptation
in unloaded skeletal muscle: new
insights into an early and mus-
cle type-specific dynamic process. J.
Physiol. (Lond.) 588, 4579–4591.
Sahlin, K., Tonkonogi, M., and Söder-
lund, K. (1998). Energy supply and
muscle fatigue in humans. Acta
Physiol. Scand. 162, 261–266.
Sargeant, A. J. (2007). Structural and
functional determinants of human
muscle power. Exp. Physiol. 92,
323–331.
Simoneau, J.A., Lortie, G., Boulay,M. R.,
Marcotte, M., Thibault, M. C., and
Bouchard, C. (1987). Effects of two
high-intensity intermittent training
programs interspaced by detrain-
ing on human skeletal muscle and
performance. Eur. J. Appl. Physiol.
56, 516–521.
Simonson, E., and Weiser, P. (1976).
Physiological Aspects and Physiolog-
ical Correlates of Work Capacity and
Fatigue. Springfield, IL: CC Thomas,
336–405.
Spencer, M., Bishop, D., Dawson,
B., and Goodman, C. (2005).
Physiological and metabolic
responses of repeated-sprint
activities: specific to field-based
team sports. Sports Med. 35,
1025–1044.
Stein, T. P., and Wade, C. E. (2005).
Metabolic consequences of muscle
disuse atrophy. J. Nutr. 135, 1824S–
1828S.
Frontiers in Physiology | Striated Muscle Physiology May 2012 | Volume 3 | Article 142 | 14
Bogdanis Physical activity and muscle fatigue
Stepto, N. K., Hawley, J. A., Dennis, S.
C., Hopkins, W. G. (1999). Effects
of different interval-training pro-
grams on cycling time-trial perfor-
mance. Med. Sci. Sports Exerc. 31,
736–741.
Stevens, L., Sultan, K. R., Peuker, H.,
Gohlsch, B., Mounier, Y., and Pette,
D. (1999). Time-dependent changes
in myosin heavy chain mRNA and
protein isoforms in unloaded soleus
muscle of rat. Am. J. Physiol. 277,
C1044–C1049.
Tadaishi, M., Miura, S., Kai, Y., Kano,
Y., Oishi, Y., and Ezaki, O. (2011).
Skeletal muscle-specific expression
of PGC-1a-b, an exercise-responsive
isoform, increases exercise capac-
ity and peak oxygen uptake. PLoS
ONE 6, e28290. doi:10.1371/jour-
nal.pone.0028290
Tesch, P. A., and Wright, J. E. (1983).
Recovery from short term intense
exercise: its relation to capillary sup-
ply and blood lactate concentration.
Eur. J. Appl. Physiol. 52, 98–103.
Tesch, P. A., Wright, J. E., Vogel, J. A.,
Daniels, W. L., Sharp, D. S., and
Sjodin, B. (1985). The influence of
muscle metabolic characteristics on
physical performance. Eur. J. Appl.
Physiol. 54, 237–243.
Thomas, C., Bishop, D., Moore-Morris,
T., and Mercier, J. (2007). Effects
of high-intensity training on MCT1,
MCT4, and NBC expressions in
rat skeletal muscles: influence of
chronic metabolic alkalosis. Am. J.
Physiol. 293, E916–E22.
Tjonna, A. E., Lee, S. J., Rognmo, O.,
Stolen, T. O., Bye, A., Haram, P. M.,
Loennechen, J. P., Al-Share, Q. Y.,
Skogvoll, E., Slørdahl, S. A., Kemi,
O. J., Najjar, S. M., and Wisloff, U.
(2008). Aerobicinter val training ver-
sus continuous moderate exercise as
a treatment for the metabolic syn-
drome: a pilot study.Circulation 118,
346–354.
Tomlin, D. L., and Wenger,H. A. (2002).
The relationships between aerobic
fitness, power maintenance and oxy-
gen consumption during intense
intermittent exercise. J. Sci. Med.
Sport 5, 194–203.
Trappe, S., Harber, M., Creer, A.,
Gallagher, P., Slivka, D., Minchev,
K., and Whitsett, D. (2006). Sin-
gle muscle fiber adaptations with
marathon training. J. Appl. Physiol.
101, 721–727.
Urso, M. L. (2009). Disuse atrophy of
human skeletal muscle: cell signaling
and potential interventions. Med.
Sci. Sports Exerc. 41, 1860–1868.
Vogiatzis, I. (2011). Strategies of mus-
cle training in very severe COPD
patients. Eur. Respir. J. 38, 971–975.
Vogiatzis, I., Terzis, G., Stratakos, G.,
Cherouveim,E., Athanasopoulos, D.,
Spetsioti, S., Nasis, I., Manta, P.,
Roussos, C., and Zakynthinos, S.
(2011). Effect of pulmonary reha-
bilitation on peripheral muscle fiber
remodeling in patients with COPD
in GOLD stages II to IV. Chest 140,
744–752.
Ward, G. R., MacDougall, J. D., Sutton,
J. R., Toews, C. J., and Jones, N. L.
(1986). Activation of human muscle
pyruvate dehydrogenase with activ-
ity and immobilization. Clin. Sci. 70,
207–210.
Westerblad, H., and Allen, D. G. (2011).
Emerging roles of ROS/RNS in mus-
cle function and fatigue. Antioxid.
Redox Signal. 15, 2487–2499.
Widrick, J. J., Stelzer, J. E., Shoepe, T.
C., and Garner, D. P. (2002). Func-
tional properties of human mus-
cle fibres after short-term resistance
exercise training. Am. J. Physiol. 283,
R408–R416.
Wisloff, U., Ellingsen, O., and Kemi,
O. J. (2009). High-intensity interval
training to maximize cardiac bene-
fits of exercise training? Exerc. Sport
Sci. Rev. 37, 139–146.
Wisloff, U., Støylen, A., Loennechen,
J. P., Bruvold, M., Rognmo, O.,
Haram, P. M., Tjonna, A. E., Hel-
gerud, J., Slørdahl, S. A., Lee, S.
J., Videm, V., Bye, A., Smith, G.
L., Najjar, S. M., Ellingsen, O., and
Skjaerpe, T. (2007). Superior car-
diovascular effect of aerobic interval
training versus moderate continu-
ous training in heart failure patients:
a randomized study. Circulation 115,
3086–3094.
Conflict of Interest Statement: The
author declares that the research was
conducted in the absence of any com-
mercial or financial relationships that
could be construed as a potential con-
flict of interest.
Received: 20 January 2012; accepted: 27
April 2012; published online: 18 May
2012.
Citation: Bogdanis GC (2012) Effects of
physical activity and inactivity on mus-
cle fatigue. Front. Physio. 3:142. doi:
10.3389/fphys.2012.00142
This article was submitted to Frontiers in
Striated Muscle Physiology, a specialty of
Frontiers in Physiology.
Copyright © 2012 Bogdanis. This is an
open-access article distributed under the
terms of the Creative Commons Attribu-
tion Non Commercial License, which per-
mits non-commercial use, distribution,
and reproduction in other forums, pro-
vided the original authors and source are
credited.
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Limited information is available regarding the role of anaerobic metabolism capacity on GOLD 1 and 2 COPD patients during upper limb exercise. We aimed to compare the upper limb anaerobic power capacity, blood lactate concentration, cardiovascular and respiratory responses, in male COPD patients versus healthy subjects during the 30-s Wingate anaerobic test (WAnT). The rate of fatigue and time constant of the power output decay (τ, tau) were also calculated and a regression analysis model was built to assess the predictors of τ in these patients. Twenty-four male COPD patients (post-bronchodilator FEV1 73.2 ± 15.3% of predicted) and 17 healthy subjects (FEV1 103.5 ± 10.1% of predicted) underwent the WAnT. Measurements were performed at rest, at the end of the WAnT, and during 3' and 5' of recovery time. Peak power (p = 0.04), low power (p = 0.002), and mean power output (p = 0.008) were significantly lower in COPD patients than in healthy subjects. Power output decreased exponentially in both groups, but at a significantly faster rate (p = 0.007) in COPD patients. The time constant of power decay was associated with resistance (in ohms) and fat-free mass (r2 = 0.604, adjusted r2 = 0.555, and p = 0.002). Blood lactate concentration was significantly higher in healthy subjects at the end of the test, as well as during 3' and 5' of recovery time (p < 0.01). Compared with healthy subjects, COPD patients with GOLD 1 and 2 presented lower upper limb anaerobic capacity and a faster rate of power output decrease during a maximal intensity exercise. Also, the WAnT proved to be a valid tool to measure the upper limb anaerobic capacity in these patients.
... Izquierdo et al. [61] observed that after a period of short-term strength training, exercise-induced loss of functional capacity occurred in athletes. The review of Bogdanis [62] reported that muscle can react in different ways to be adapted to exercise demands, such as increasing size, variations in fiber composition, increased enzyme activity, and altered muscle activation. If appropriate adaptations occur, muscle fatigue is reduced during exercise. ...
Several aspects of systemic alterations caused by the SARS-CoV-2 virus and the resultant COVID-19 disease have been currently explored in the general population. However, very little is known about these particular aspects in sportsmen and sportswomen. We believe that the most important element to take into account is the neuromuscular aspect, due to the implications that this system entails in motion execution and coordination. In this context, deficient neuromuscular control when performing dynamic actions can be an important risk factor for injury. Therefore, data in this review refer mainly to problems derived in the short term from athletes who have suffered this pathology, taking into account that COVID-19 is a very new disease and the presented data are still not conclusive. The review addresses two key aspects: performance alteration and the return to regular professional physical activity. COVID-19 causes metabolic-respiratory, muscular, cardiac, and neurological alterations that are accompanied by a situation of stress. All of these have a clear influence on performance but at the same time in the strategy of returning to optimal conditions to train and compete again after infection. From the clinical evidence, the resumption of physical training and sports activity should be carried out progressively, both in terms of time and intensity.
... In many of the previously mentioned health conditions, physical inactivity is a contributing factor to the increased fatigue of the patient [30]. Deconditioning, as a result of restricted physical activity, results in large decreases in muscle mass and strength, as well as increased fatigue due to changes in muscle metabolism [31,32]. ...
Chapter
Energy and fatigue carry important implications for vitality and overall quality of life. Lacking energy and experiencing fatigue can be both burdensome as well as adaptive. This chapter first classifies energy and fatigue and then reviews their measurement. This chapter closes with opportunities for future directions. Energy and fatigue are present under varying conditions including in daily performance, during and after acute physical or mental strain (capacity), and in the context of chronic conditions. Energy and fatigue have been measured both subjectively and objectively. Subjective outcomes can be derived from self-reported scales and prompts; objective outcomes may be derived from performance and capacity tasks and technology-reported physiological, biological, and behavioural markers. The scales and tasks employed to measure energy have been traditionally validated but may lack daily life context and ecological validity. Prompts and behavioural monitoring methods are emerging as promising alternatives. Energy and fatigue have also been routinely monitored for specific diseases and occupations. However, fewer studies monitor healthy individuals through consumer technology in daily life contexts. More research is needed for an objective, unobtrusive, longitudinal, and contextual measurement of energy and fatigue in the healthy general population, in service of improving health, wellbeing, and quality of life.