Experimental Physiology Email Content Delivery
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Experimental Physiology 92.2 pp 323-331
DOI: 10.1113/expphysiol.2006.034322
© The Physiological Society 2007
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
92/2/323    most recent
expphysiol.2006.034322v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Sargeant, A. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Sargeant, A. J.
Related Collections
Right arrow Symposia Papers

Symposium Reports

Muscle-energetic and cardio-pulmonary determinants of exercise tolerance in humans

Structural and functional determinants of human muscle power

 Anthony J. Sargeant1,2

1 Institute for Biophysical and Clinical Research into Human Movement, Manchester Metropolitan University, Manchester, UK 2 Institute for Fundamental and Clinical Human Movement Science, Vrije University, Amsterdam, The Netherlands

Abstract

Measurements of human power need to be interpreted in relation to the movement frequency, since that will determine the velocity of contraction of the active muscle and hence the power available according to the power–velocity relationship. Techniques are described which enable movement frequency to be kept constant during human exercise under different conditions. Combined with microdissection and analysis of muscle fibre fragments from needle biopsies obtained pre- and postexercise we have been able ‘to take the muscle apart’, having measured the power output, including the effect of fatigue, under conditions of constant movement frequency. We have shown that fatigue may be the consequence of a metabolic challenge to a relatively small population of fast fatigue-sensitive fibres, as indicated by [ATP] depletion to ~30% of resting values in those fibres expressing myosin heavy chain isoform IIX after just 10 s of maximal dynamic exercise. Since these same fibres will have a high maximal velocity of contraction, they also make a disproportionate contribution to power output in relation to their number, especially at faster movement rates. The microdissection technique can also be used to measure phosphocreatine concentration ([PCr]), which is an exquisitely sensitive indicator of muscle fibre activity; thus, in just seven brief maximal contractions [PCr] is depleted to levels < 50% of rest in all muscle fibre types. The technique has been applied to study exercise at different intensities, and to compare recruitment in lengthening, shortening and isometric contractions, thus yielding new information on patterns of recruitment, energy turnover and efficiency.

(Received 18 December 2006; accepted after revision 12 January 2007; first published online 7 March 2007)
Corresponding author A. J. Sargeant: Institute for Biophysical and Clinical Research into Human Movement, Manchester Metropolitan University, Hassall Road, Alsager, Cheshire ST7 2HL, UK. Email: a.j.sargeant{at}mmu.ac.uk

Human muscle power is as important to an elderly person who wants to walk to the shops or climb the stairs to bed as it is to an Olympic cyclist, a prima ballerina, or a child with cerebral palsy. The ability to generate muscle power is, however, dependent on the speed of movement, since this will determine the velocity of contraction of the active muscles, hence the power available as determined by the power–velocity relationship of skeletal muscle schematically represented in Fig. 1.


Figure 1
View larger version (14K):
[in this window]
[in a new window]

  		Figure 1.  Schematic illustration of force–velocity relationship of muscle, as shown by the contiunous line
The mathematical consequence of this relationship is that power in relation to velocity is of the form shown by the dashed line, where maximum power is reached at optimal velocity (Vopt). At a power ouput, X, delivered at a slow velocity, point A, 100% of the maximum power available is required, with no reserve of power-generating capability. At the optimal velocity for maximum power, point B, only 50% of the available power is required.

 
If speed of movement is limited, for example, by osteo-arthritis in the elderly or muscle contractures in cerebral palsy, then, even if the individual has adequate muscle mass, the power generated in dynamic tasks may be very limited and this may lead to instability of body posture and gait. Furthermore the ‘reserve’ of power-generating capability, hence the ability to resist fatigue, will be reduced at slow movement speed. At a power requirement X shown in Fig. 1 only 50% of the muscle power-generating capability is needed at optimum velocity (point B), but 100% is required at the slower speed (point A).

Speed of movement may also be constrained by the nature of the task itself, including the external forces that need to be overcome and the equipment being used; for example, gears on bicycles, the design of wheelchairs for spinal cord-injured people, or the body mass that needs to be moved in a ballerina's grande jetée.

Thus, understanding the capability for generating and sustaining muscle power in the performance of ‘whole-body’ tasks, including human locomotion, crucially requires information on the speed of movement interpreted in relation to the optimum speed for maximum power for that movement. Curiously, although the optimum velocity for maximum power is a frequently used reference point in isolated muscle research, its significance in studies of human locomotion has been less widely recognized (despite, for example, Hill, 1922).

Characterizing the power–velocity relationship in human whole-body exercise

In 1981 we developed an isokinetic cycle ergometer, which allowed us to characterize the relationship between maximum power and movement frequency in human whole-body exercise (Sargeant et al. 1981). The parabolic relationship between maximum power and pedalling rate globally reflects the power–velocity relationship of the contributing muscles, as described for isolated muscle by A. V. Hill and others. In cycling exercise, the optimum velocity for maximum power in healthy young adults was identified as ~120 pedal revolutions min–1 (see Fig. 2).


Figure 2
View larger version (16K):
[in this window]
[in a new window]

  		Figure 2.  Maximal peak power in relation to pedalling rate
A, relationship of maximum peak power to the pedalling rate (in r.p.m.) for 5 subjects on an isokinetic cycle ergometer. B, the same data as in A except that the maximum peak power has been normalized for the size of the active muscle mass. Reprinted with permission from Sargeant et al. (1981).

 
The power–movement frequency relationship described is the product of many factors in whole-body exercise, but must ultimately depend upon the power–velocity relationship of the contributing muscle fibres in the active muscles. We have previously presented a simplified two-compartment model to explain how the power output from the two main fibre types present in human muscle might summate in maximal cycling exercise (Sargent & Beelen, 1993; and Fig. 3).


Figure 3
View larger version (11K):
[in this window]
[in a new window]

  		Figure 3.  Schematic model of the component and combined power–velocity relationship for a whole muscle comprised of equally proportions of type I and type II muscle fibres
The superimposed pedalling rates are derived by reference to the data shown in Fig. 2. It will be noted that the relative contribution of the type II fibre population increases from ~30% of the total power at 60 r.p.m. to ~70% at 120 r.p.m. (see Sargeant & Jones, 1995).

 
In reality, muscle fibres show a continuum of contractile and metabolic properties, most notably determined by the main ‘molecular motor’, the myosin heavy chain isoform (MyHC) expressed. In healthy adult human muscle fibres, three isoforms, type I, IIA and IIX, predominate, with many fibres coexpressing varying proportions of both IIA and IIX isoforms (Sant'ana Pereira et al. 1995). The continuum at the molecular level can be expected to result in a family of power–velocity relationships with an increasing maximum velocity of shortening and maximum power from type I to IIA to fibres coexpressing an increasing proportion of IIX, to the rather rarely observed fibre which only expresses the IIX isoform (see Fig. 4).


Figure 4
View larger version (16K):
[in this window]
[in a new window]

  		Figure 4.  Schematic representation of the power available from the continuum of muscle fibre populations as determined by the principal‘molecular motor’; that is, the myosin heavy chain isoform expressed and coexpressed
In this schematic diagram, the maximum velocity of shortening of the mean type II fibre population is assumed to be 4 times that of the type I fibres (see, e.g. Faulkner et al. 1980; Larsson & Moss, 1993). The superimposed ‘anchor points’ for pedalling rates in cycling exercise are derived from Figs 2 and 3.

 
The effect of muscle fatigue on human power output

In a series of studies, we characterized the fatiguing effect of prior exercise on the maximum power output (Sargeant & Dolan, 1987; Beelen & Sargeant, 1991; Beelen et al. 1995) and were able to demonstrate that 6 min of prior exercise at ~90% of maximum oxygen uptake Formula reduced maximum power by ~30% when measured at the optimal pedalling rate for maximum power on the isokinetic cycle ergometer (Fig. 5). In combination with data on the effect of different durations of prior exercise and the time course of recovery (Figs 6 and 7), the changes in maximum power would have been closely associated with the availability of high-energy phosphate in the muscle, as suggested in 1933 by Margaria, Edwards & Dill for the ‘anaerobic alactic’ component of energy supply (Margaria et al. 1933).


Figure 5
View larger version (12K):
[in this window]
[in a new window]

  		Figure 5.  Maximum peak power measured at optimal velocity (expressed as a percentage of control) after 6 min of prior exercise performed at different intensities
Data for 5 subjects, each represented by a different symbol, showing a reduction to 30–40% after prior exercise at 90% Figure 5. Adapted with permission from Sargeant & Dolan (1987).

 

Figure 6
View larger version (9K):
[in this window]
[in a new window]

  		Figure 6.  Maximum peak power determined in a series of experiments after different durations of prior exercise performed at 98% of Figure 6
Data for two subjects, each represented by a different symbol. Adapted with permission from Sargeant & Dolan (1987).

 

Figure 7
View larger version (8K):
[in this window]
[in a new window]

  		Figure 7.  Recovery in maximum peak power after 6 min of prior exercise performed at 90% Figure 7
The graph indicates full recovery of power within 2 min, with subsequent potentiation which may be related to an increase in muscle temperature (see Sargeant, 1987). Mean ± S.D. data for 4 subjects. Adapted with permission from Sargeant & Dolan (1987).

 
In a subsequent paper, the effect of prior exercise on the maximum power generated at different pedalling rates was studied (Beelen & Sargeant, 1991). Surprisingly, when subjects pedalled at 60 r.p.m. no significant fatigue effect was observed on performance of the subsequent 25 s maximum effort (Fig. 8A). In contrast, at 120 r.p.m. there was a reduction of ~25% in the maximum power generated at the beginning of the 25 s maximum test (Fig. 8B).


Figure 8
View larger version (8K):
[in this window]
[in a new window]

  		Figure 8.  Peak power generated by 1 subject during 25 maximal efforts performed on the isokinetic cycle ergometer under rested control conditions ({circ}) or following 6 min of prior fatiguing exercise performed at 90% of Figure 8 (•)
Data points are for each revolution in both conditions, cycling at 60 r.p.m. pedal rate (A) and 120 r.p.m. (B). Reprinted with permission from Beelen & Sargeant (1991).

 
The group data are shown in Fig. 9, where it can be seen that the effect of prior exercise is highly velocity dependent. However, while Fig. 8B indicates a reduction of ~25% in power at the beginning of the maximum effort, it also shows that the rate of fatigue was actually less over the 25 s test; that is, the fatiguing prior exercise seemed to have made the active muscles fatigue resistant. The result was that after about 18 s there was no difference in the power generated between the fatigued and control conditions. We suggested that both the velocity-dependent effect of fatigue on maximum power and the paradox of a lower rate of fatigue following prior exercise at 120 r.p.m. could be explained by selective fatigue of the more powerful type II muscle fibre populations. These fibres, which are also more fatigue sensitive, might be expected to make a proportionately greater contribution to the whole-muscle power as pedalling rate increased as indicated in Fig. 3. Furthermore, because the fatigue-sensitive fibres were already fatigued at the beginning of the 25 s exercise, the power would have been mainly generated by more fatigue-resistant fibres, which fatigue at a relatively slow rate. In contrast, the fatigue-sensitive fibres were still available to be rapidly fatigued in the control condition with no prior exercise, hence the rate of fatigue was much greater.


Figure 9
View larger version (10K):
[in this window]
[in a new window]

  		Figure 9.  Group data for human maximum peak power when cycling at 5 different pedalling rates in the rested control condition ({circ}) and following 6 min of prior fatiguing exercise (•)
Mean ± S.E.M. data for 6 subjects. There was no significant effect of prior exercise at 60 or 80 r.p.m., but differences of ~25% were significant at the higher pedal rates, demonstrating the velocity-dependent effect of fatigue. *Significance P < 0.05 Reprinted with permission from Beelen & Sargeant (1991).

 
The significance of fibre type variability and selective fatigue

In order to investigate the metabolic status of different muscle fibre types present in human locomotory muscle, we developed a microdissection technique. Muscle fibre fragments were isolated from needle biopsy of human quadriceps pre- and postexercise and during recovery. Part of each fragment was used to characterize the fibre according to the proportion and type of myosin heavy chain isoform expressed, as shown in Fig. 10, while the remaining part was analysed for high-energy phosphate concentrations using HPLC (Sant'ana Pereira et al. 1995, 1996; Karatzaferi et al. 1999).


Figure 10
View larger version (53K):
[in this window]
[in a new window]

  		Figure 10.  SDS-PAGE and histochemistry
Histochemical and electrophoretic characterization of 6 single human skeletal muscle fibres. Fibres were classified (from left to right): type IIA, IIaX, IIX, IIAx, IIA and I (capital letters indicate predominance of one type of MyHC type). On the extreme left is a reference gel for whole-muscle homogenate showing the position of the type I, IIA and IIX isoforms. Reprinted with permission from Sant'Ana Pereira et al. (1996).

 
These techniques were applied in a series of studies in which subjects were asked to generate maximum power on the isokinetic cycle ergometer in exercise bouts lasting for 10 or 25 s. Pedalling at 120 r.p.m. power was reduced by ~20 and ~40%, respectively (Sant'Ana Pereira et al. 1996; Karatzaferi et al. 2001). In the type I fibre population there is no change in [ATP] after 10 s and only a modest decrease after 25 s. In type IIA fibres there is already a significant decrease to 60% of resting values after 10 s and a further inexorable decline to ~40% after 25 s. The remainder of the type II fibres coexpressed varying proportions of both IIA and IIX isoforms. We divided these into two groups based on the predominant MyHC isoform, hence type IIAx or IIXa. In both of the groups which expressed IIX MyHC isoform, [ATP] was reduced to ~30% of resting values after only 10 s of maximal exercise, which is probably close to the maximal level of ATP depletion possible (Fig. 11). Not surprisingly, there is no further reduction in [ATP] at the end of the 25 s exercise.


Figure 11
View larger version (10K):
[in this window]
[in a new window]

  		Figure 11.  Mean decline in [ATP] for type I ({square}), IIA ({circ}),IIAx ({triangleup}) and IIXa ({nabla}) muscle fibres
Biopsies were obtained at 10 and 25 s in separate experiments. A typical power profile is shown for one subject for the whole 25 s. Reprinted with permission from Karatzaferi et al. (2001).

 
It seems probable that the fastest fatigue-sensitive fibres on the continuum of metabolic and contractile properties would have fatigued very early in this maximal dynamic exercise, and we would propose that the sequential metabolic challenge might be schematically represented as illustrated in Fig. 12, which shows a family of fibre populations, from pure IIX (which will be the first to fatigue) through IIXa to IIAx to IIA to type I.


Figure 12
View larger version (14K):
[in this window]
[in a new window]

  		Figure 12.  Schematic suggestion of the probable decline in [ATP] for the continuum of fibre properties
Very few pure type IIX fibres are seen in healthy adult muscle, but if the IIAx fibres are already around the minimal possible levels after 10 s, it might be assumed that the IIX fibres would be at that level even earlier. The measured data points from Fig. 11 are included as anchor points for the schematic.

 
Selective fatigue and recruitment

What is apparent from the above studies of muscle power generated in maximal short-term exercise lasting ~25 s is that fatigue characterized as a loss of power from a whole muscle or groups of muscle may be due to metabolic challenge and reduced mechanical output from a relatively small group of fast and therefore powerful muscle fibres. Accordingly, care needs to be exercised in interpreting the levels of metabolites and substrates derived from whole-muscle homogenates (whether analysed biochemically or with magnetic resonance spectroscopy (MRS) techniques). Furthermore, and self-evidently, the extent to which any fibre population will fatigue will depend on its intrinsic fatigue sensitivity in combination with the pattern and level of recruitment of that particular population depending upon the type and intensity of exercise.

The microdissection technique and associated analyses enable us to measure changes in phosphocreatine concentration [PCr], which is an exquisitely sensitive indicator of fibre activity. After only four 1 s maximal isometric contractions, [PCr] was reduced to ~75, 65 and 53% of resting values in type I, IIA and IIAX fibres, respectively, with further reductions after seven and 10 contractions (Fig. 13).


Figure 13
View larger version (9K):
[in this window]
[in a new window]

  		Figure 13.  Changes in phosphocreatine (PCr) content expressed as PCr/Cr ratio at rest and following 4, 7 and 10 maximal isometric contractions of the knee extensors
Drawn from data in Beltman et al. (2004b).

 
We therefore used this technique to examine the pattern of recruitment at different intensities of isometric contraction, viz. 39, 72 and 87% of maximal voluntary contraction (MVC; Beltman et al. 2004c). As expected and shown in Fig. 14, type I and IIA fibres showed a significant leftward shift in the cumulative distribution curves for [PCr] with increasing intensity of contraction compared with rest. In contrast, the IIAX fibre population showed no evidence of metabolic involvement even at 72% of MVC. It was not until the very highest intensity, 87%, that [PCr] was reduced, as shown by the significant leftward shift in the cumulative distribution. This finding is somewhat surprising when one considers that in dynamic exercise, studies based on glycogen depletion suggest an involvement of all muscle fibre types at ~90% Formula , which is an exercise intensity that would only require ~40% of the maximum force-generating capacity of the active muscles at the same velocity of contraction (Sargeant et al. 1985).


Figure 14
View larger version (18K):
[in this window]
[in a new window]

  		Figure 14.  Cumulative frequency distribution of single fibre PCr/Cr ratios in type I, IIA and IIAXfibres at rest and following 7 isometric contractions at 39, 72 and 87% of MVC
In general, the cumulative curves show a leftward shift as intensity increases except in the case of the IIAX fibres, which are only active at an intensity above 72%. *Significance P < 0.05 Adapted from Beltman et al. (2004a).

 
We have also used this technique to compare the pattern of metabolic activity during maximal lengthening, isometric and shortening contractions (Fig. 15; Beltman et al. 2004c). From these experiments, it is clear from the leftward shift of the cumulative distribution for [PCr] that there is no evidence for a ‘reversal’ of the normal pattern of recruitment during lengthening contractions, as has sometimes been proposed. Indeed, the observed shift in [PCr] indicates that type I fibres are more active in lengthening contractions than either IIA or IIAX; that is, the normal hierarchy of motor unit recruitment according to the size principle is preserved (Henneman & Mendell, 1981). In these maximal contractions, the data also showed that in all fibre types the greatest [PCr] reduction was seen in shortening contractions, somewhat less reduction in isometric, and the smallest reduction in the lengthening contraction.


Figure 15
View larger version (29K):
[in this window]
[in a new window]

  		Figure 15.  Cumulative distribution of single fibre PCr/Cr ratios in type I, IIA and IIAXfibres at rest, and after a series of 10 lengthening (long-dashed lines), isometric (short-dashed lines) or shortening contractions (dash-and-dotted lines)
The area between the cumulative distribution for rest and following lengthening contractions has been shaded to illustrate that, far from there being a selective activation of type II fibres during lengthening contractions as is sometimes proposed, the reverse seems to be the case, in that the shift in the distribution is less marked in the type IIAX fibres (shaded area) than in the type I and IIA fibres. Adapted from Beltman et al. (2004c).

 
Energy turnover and efficiency

It should be noted that the rate of energy turnover in different fibre populations will be affected by the efficiency at the fibre level and, just as power is velocity dependent, so too will be the efficiency of the muscle fibre. There are, however, almost no data on the mechanical efficiency–velocity relationships of different human muscle fibre types in relation to normal locomotory exercise. On the basis of animal muscle experiments, it has been proposed that maximal efficiency occurs at a velocity that is close to, but slightly below the optimum for maximum power (see, e.g. Goldspink, 1978; Lodder et al. 1991, Rome, 1993). Thus, on the basis of Fig. 3 it might be speculated that the efficiency–velocity relationship for type I and type II fibres would be of the form shown in Fig. 16, and that optimal velocity would occur at, respectively, ~50 and ~150 r.p.m. (Sargeant, 1999). As a consequence of this reciprocal change in efficiency, combined with changes in recruitment patterns with increasing intensity and velocity-dependent contributions, it can be modelled and predicted that the net efficiency in high-intensity cycling exercise should be largely independent of pedalling rate over a wide range (from ~60 to 110 r.p.m.; Sargeant & Rademaker, 1996), a prediction supported by experimental data (Zoladz et al. 2000). It should always be remembered, however, that this is a greatly simplified two-compartment model. The reality is that there will be a continuum of efficiency–velocity relationships reflecting the continuum of the expression of contractile protein isoforms and other modulators of energy turnover.


Figure 16
View larger version (11K):
[in this window]
[in a new window]

  		Figure 16.  Schematic illustration of the possible form of the relationship between mechanical efficiency and velocity of contraction for type I muscle fibres and the mean for type II muscle fibres
The model is based on data and assumptions from Figs 2 and 3, including the ratio of 1:4 for the maximal velocity for shortening of type I and type II fibres. In the absence of systematic data, no relative difference is indicated in the maximum efficiency; each fibre type is normalized to the same maximum. Note the equal efficiency value at around the mid-range of normal locomotory cadence, at 90 r.p.m., and the reciprocal change in efficiency of type I and II fibre populations at 60 and 120 r.p.m.

 
Conclusion

Using a microdissection technique, we have been able ‘to take the muscle apart’, having characterized and measured the power output, including the effect of fatigue, under conditions of constant movement frequency. In so doing, we have shown that fatigue may be the consequence of a metabolic challenge to a relatively small population of fast fatigue-sensitive fibres. Since these fibres are predicted to have a high maximal velocity of contraction, they make a disproportionate contribution to power output in relation to their number, especially at faster movement rates. In addition, the microdissection technique can be used to provide an exquisitely sensitive marker of muscle fibre activity in a very few contractions, thus yielding new information on patterns of recruitment and energy turnover during human exercise.

References

Beelen A & Sargeant AJ (1991). Effect of fatigue on maximal power output at different contraction velocities in humans. J Appl Physiol 71, 2332–2337.[Abstract/Free Full Text]

Beelen A, Sargeant AJ, Jones DA & de Ruiter CJ (1995). Fatigue and recovery of voluntary and electrically elicited dynamic force in humans. J Physiol 484, 227–235.

Beltman JG, de Haan A, Haan H, Gerrits HL, van Mechelen W & Sargeant AJ (2004a). Metabolically assessed muscle fibre recruitment in brief isometric contractions at different intensities. Eur J Appl Physiol 92, 485–492.[Medline]

Beltman JG, Sargeant AJ, Haan H, van Mechelen W & de Haan A (2004b). Changes in PCr/Cr ratio in single characterized muscle fibre fragments after only a few maximal voluntary contractions in humans. Acta Physiol Scand 180, 187–193.[CrossRef][Medline]

Beltman JG, Sargeant AJ, van Mechelen W & de Haan A (2004c). Voluntary activation level and muscle fibre recruitment of human quadriceps during lengthening contractions. J Appl Physiol 97, 619–626.[Abstract/Free Full Text]

Faulkner JA, Jones DA, Round JM & Edwards RHT (1980). Dynamics of energetic processes in human muscle. In Exercise Bioenergetics and Gas Exchange, ed. Cerretelli P & Whipp BJ, pp. 81–90. Elsevier/North Holland Biomedical Press, Amsterdam.

Goldspink G (1978). Energy turnover during contractions of different types of muscle. Biomechanics VI-A, ed. Asmussen E & Jørgensen K, pp. 27–39. University Park Press, Baltimore.

Henneman E & Mendell LM (1981). Functional organization of motoneurone pool and its inputs. In Handbook of Physiology, section 1, The Nervous System, vol. II, Motor Control, ed. Brookhart JM, Mountcastle VB, Brooks VB & Geiger SR, pp. 423–507. American Physiological Society, Bethesda.

Hill AV (1922). The maximal work and mechanical efficiency of human muscles and their most economical speed. J Physiol 56, 19–30.[Free Full Text]

Karatzaferi C, de Haan A, Offringa C & Sargeant AJ (1999). Improved high-performance liquid chromatographic assay for the determination of "high-energy" phosphates in mammalian skeletal muscle. Application to a single-fibre study in man. J Chromatogr B Biomed Sci Appl 730, 183–191.[CrossRef][Medline]

Karatzaferi C, de Haan A, van Mechelen W & Sargeant AJ (2001). Metabolism changes in single human fibres during brief maximal exercise. Exp Physiol 86, 411–415.[Abstract]

Larsson L & Moss RL (1993). Maximum velocity of shortening in relation to myosin isoform composition in single fibres from human skeletal muscles. J Physiol 472, 595–614.

Lodder MAN, de Haan A & Sargeant AJ (1991). Effect of shortening velocity on work output and energy cost during repeated contractions of the rat EDL muscle. Eur J Appl Physiol 62, 430–435.

Margaria R, Edwards HT & Dill DB (1933). The possible mechanism of contracting and paying the oxygen debt and the role of lactic acid in muscular contraction. Am J Physiol 106, 689–715.[Free Full Text]

Rome LC (1993). The design of the muscular system. In Neuromuscular Fatigue, ed. Sargeant AJ & Kernell D, pp. 129–136. North-Holland/Academy Press, Amsterdam.

Sant'Ana Pereira JA, Sargeant AJ, Rademaker AC, de Haan A & van Mechelen W (1996). Myosin heavy chain isoform expression and high energy phosphate content in human muscle fibres at rest and post-exercise. J Physiol 496, 583–588.

Sant'ana Pereira JA, Wessels A, Nijtmans L, Moormans AF & Sargeant AJ (1995). New method for the accurate characterization of single human skeletal muscle fibres demonstrates a relation between mATPase and MyHC expression in pure and hybrid fibre types. J Muscle Res Cell Motil 16, 21–34.[CrossRef][Medline]

Sargeant AJ (1987). Effect of muscle temperature on leg extension force and short-term power output in humans. Eur J Appl Physiol 56, 693–698.

Sargeant AJ (1999). Neuromuscular determinants of human performance. In Physiological Determinants of Human Exercise Tolerance, ed. Whipp BJ & Sargeant AJ, pp. 13–28. The Physiological Society/Portland Press, London.

Sargeant AJ & Beelen A (1993). Human muscle fatigue in dynamic exercise. In Neuromuscular Fatigue, ed. Sargeant AJ & Kernell D, pp. 81–92. Academy Series, Royal Netherlands Academy of Arts and Sciences, Amsterdam.

Sargeant AJ & Dolan P (1987). Effect of prior exercise on maximal short-term power output in man. J Appl Physiol 63, 1475–1482.[Abstract/Free Full Text]

Sargeant AJ, Greig CA & Vollestad NK (1985). Muscle force and fibre recruitment during dynamic exercise in man. J Physiol 371, 176P.

Sargeant AJ, Hoinville E & Young A (1981). Maximum leg force and power output during short-term dynamic exercise. J Appl Physiol 51, 1175–1182.[Abstract/Free Full Text]

Sargeant AJ & Jones DA (1995). The significance of motor unit variability in sustaining mechanical output of muscle. Adv Exp Med Biol 384, 323–338.[Medline]

Sargeant AJ & Rademaker A (1996). Human muscle fibre types and mechanical efficiency during cycling. In The Physiology and Pathophysiology of Exercise Tolerance, ed. Steinacker JM & Ward SA, pp. 247–251. Plenum, New York.

Zoladz JA, Rademaker AC & Sargeant AJ (2000). Human muscle power generating capabiity during cycling at different pedalling rates. Exp Physiol 85, 117–124.[Abstract]




This article has been cited by other articles:


Home page
 J. Physiol.Home page
S. Marcora
Is peripheral locomotor muscle fatigue during endurance exercise a variable carefully regulated by a negative feedback system?
J. Physiol., April 1, 2008; 586(7): 2027 - 2028.
[Full Text] [PDF]

Home page
 Am. J. Physiol. Regul. Integr. Comp. Physiol.Home page
S. M. Marcora, A. Bosio, and H. M. de Morree
Locomotor muscle fatigue increases cardiorespiratory responses and reduces performance during intense cycling exercise independently from metabolic stress
Am J Physiol Regulatory Integrative Comp Physiol, March 1, 2008; 294(3): R874 - R883.
[Abstract] [Full Text] [PDF]

Home page
 Exp PhysiolHome page
S. A. Ward
Muscle-energetic and cardio-pulmonary determinants of exercise tolerance in humans: Muscle-energetic and cardio-pulmonary determinants of exercise tolerance in humans
Exp Physiol, March 1, 2007; 92(2): 321 - 322.
[Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
92/2/323    most recent
expphysiol.2006.034322v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Sargeant, A. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Sargeant, A. J.
Related Collections
Right arrow Symposia Papers

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS