Europ. J. appl. Physiol. 34, 269--278 (1975) 9 by Springer-Verlag 1975

Maximal Steady State Versus State of Conditioning Ben R. Londeree and Stephen A. Ames Human Performance Laboratory, University of Missouri, Columbia, .~Iissouri 65210 :Received June 30,1975

Abstract. Criteria for the identification of maximal steady state as related to state of conditioning were evaluated, t3 volunteers walked and/or ran during a series of 15 rain tests on a treadmill. The speeds ranged from mild to exhaustive. Heart rate was monitored continuously; ~oz was determined from 6 rain to 9 rain; and venous blood was obtained at 10 rain and t5 rain for lactate analyses. Max 17o2was established for each subject. Subjects were classified on level of conditioning according to the quantity and quality of their activity record for the previous 6 months. The 10 rain heart rate associated with a blood lactate level of 2.2 mM/L (MSSHR) was the best predictor of conditioning. The relative Fo2 ( % of max 17o~) found with a 10 rain blood lactate concentration of 2.2 m~/L (I~MSSFo~) was almost as accurate as MSSHR in predicting state of conditioning. Changes in blood lactate levels between t0 rain and 15 rain were not significantly related to conditioning. Key words: Maximal steady state - - Steady state oxygen consumption - - State of Cardiorespiratory fitness - - Anaerobic threshold. There are m a n y tests of circulorespiratory endurance. Typically the criterion is the ability to run distance races and probably the measurement found to correlate the highest with this ability is m a x ~2 in m l / k g , rain (Costill, 1968). Max Fo~ often is used as the criterion for simpler tests of eireulorespiratory endurance. However, it has been shown t h a t max I?o2 is largely a function of heredity (Astrand and Rodahl, ~970, p. 280; Klissouras, ~962) even though its magnitude can be increased b y training. For a given 1?o2it is impossible to know whether the subject has a lot of ability and is "out of shape", if he has little ability and is in "good shape", or if he possesses an intermediate level of ability and is in "moderately good shape". Consequently, no test presently exists which can differentiate levels of conditioning; only changes in conditioning can be determined during longitudinal studies. I n prescribing exercise knowledge of the subject's present state of conditioning would be of value. The training threshold m a y be related to the state of conditioning (Gledhill, 1968). I f the subject is already in " p r e t t y good shape" he should not expect much improvement. I n addition, the coach of endurance atheletes could intelligently decide which athletes need more conditioning and which ones should be placed on a maintenance program. Several investigators have reported t h a t highly conditioned endurance runners were able to maintain a greater relative (% of m a x Vo2) maximal steady state oxygen consumption (RMSSI?o2) than low-fit subjects (Astrand and Rodahl, i970, p. 38i; Costill, i968; Costill et al., ~971; ttermansen and Saltin, 1967; Williams

270

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et al., 1967 ; W y n d h a m et al., t965). G e n e r a l l y these i n v e s t i g a t o r s r e p o r t e d t h a t a n increase in blood lactic acid occurred a t a higher p e r c e n t o f m a x i m a l o x y g e n c o n s u m p t i o n in t h e m o r e h i g h l y c o n d i t i o n e d subjects. I n a d d i t i o n , a t all r e l a t i v e w o r k l o a d s b e t w e e n this a n a e r o b i c t h r e s h o l d a n d m a x i m a l o x y g e n consumption, t h e b l o o d l a c t a t e s were lower in t h e c o n d i t i o n e d subjects. S u b s e q u e n t l o n g i t u d i n a l studies showed t h a t a t least p a r t of t h e differences f o u n d in t h e cross-sectional i n v e s t i g a t i o n s was due t o t r a i n i n g ( E k b l o m , i 9 6 9 ; t t e r m a n s e n , et al. i967; W i l l i a m s et al., ~967). P r e v i o u s w o r k m e n t i o n e d a b o v e d i d n o t clearly e l u c i d a t e t h e criteria for I~MSSI?od. A l t h o u g h differences in t h e b l o o d l a c t a t e versus r e l a t i v e o x y g e n c o n s u m p t i o n curves were n o t e d b e t w e e n high a n d low-fit subjects, no a t t e m p t to d e t e r m i n e t h e s t r e n g t h of t h e r e l a t i o n s h i p b e t w e e n s t a t e of conditioning a n d RMSSI?oz was f o u n d in t h e l i t e r a t u r e . I t was felt t h a t some f o r m of a m a x i m a l s t e a d y s t a t e t e s t m i g h t be precise enough to i d e n t i f y levels of conditioning. Therefore this p r o j e c t was u n d e r t a k e n to d e t e r m i n e which one of several m a x i m a l s t e a d y s t a t e criteria was t h e b e s t p r e d i c t o r of level of conditioning. Procedures 13, volunteer, adult males were administered a series of treadmill tests. Characteristics of the subjects are presented in Table 1. Each day that a subject reported to the Laboratory he was tested at two speeds; the first was relatively mild and the second was moderate to vigorous. Each test lasted 15 rnin and a rest period of l0 to t5 min was provided between the workbouts. This testing procedure was repeated on subsequent days until a series of speeds from mild to maximal was completed. Most of the subjects were tested at 5 or 6 workloads, although the range was 2 to 8 tests. Finally a max l?o, determination was made by the method described by Astrand and Rodahl {1970, pp. 283, 616--617). During the tests the subjects ventilated through a low resistance valve (E. P. Associates) and the expired air was collected in three meteorological balloons for I min each (6--9 rain). Gas analyses were performed immediately on calibrated, electronic analyzers (Capnograph for C02 and Beckman E2 for 02) and volume was determined with a calibrated dry gas meter (American l~eter Co.). Barometric pressure, gas temperature and vapor tension were determined and oxygen consumption was calculated by procedures outlined by Consolazio et al. (1963, pp. 5--9). Blood samples were obtained from an arm vein at 10 and 15 min with an I.V. set. This system was flushed continuously between samples with a 1% heparin saline solution. Prior to each sample, 5 ml of blood were drawn and discarded. Then 7 ml of blood were taken and immediately mixed in a tube containing sodium fluoride. After mixing, the tube of blood was placed in ice until deproteinization (usually within 5 - - t 0 rain). Preparation for lactate analyses was made in duplicate utilizing an enzymatic kit (Sigma Chemical Co.) by the method of Marbach and Well (1967) and red on a Bechman D.U.2 direct reading speetrophotometer. One subject ran only 10 rain at each speed and blood samples were obtained immediately after each run via standard venipuncture with sodium fluoride vacutainers.

Table 1. Subject characteristics. X +_ S.D. Fitness

n

Low 4 Medium 6 High 3

Age (yrs)

Height (em)

Weight (kg)

Max l?o~ ml/kg/min

24.8 +_3.3 23.7 • 2.3 32.3 • 8.0

179.8 _+2.0 18i.8 +_7.2 180.3 • 6.1

74.8 _+ 6.7 77.0 • ~4.6 72.3 • 7.1

46.8 + 3.6 56.8 • 12.5 68.7 • 11.7

Maximal Steady State

271

/ E uJ t--

t-

4

iiiiiiiiiii I

40

I 50

1 60

PERCENT

L

i w

70

r

80

~ " --.I90

VO 2 MAX

:Fig. 1. The determination of R/~{SSI?o~ utilizing the criteria of lactate level of 2.2 mM/L or 4.4 mM/L. In this case the RMSS Vo~ (2.2 raM/L) is 75 % of max I?o~and RMSS I'{~z (4.4 m~'l-/L)is 85 % of max ~ . MSSHR is determined in a similar manner

Heart rate was monitored continuously with a cardiotachometer (The Waters Co.). The ECG signal (modified V~) was obtained from three liquid column silver-silver chloride electrodes (Industrial-Medical Instruments, Inc.). The level of conditioning was inferred from an activity recall record of the previous 6 months. Individuals who seldom exercised were classified as low.fit; exercise (game type activities) approximately three times per week resulted in a rating of medium-fitness; and those who exercised (long distance running) at least five times per week were considered highly-fit. Therefore this classification scheme considered frequency, quantity, and intensity of recent exercise. The use of the terms; low-fit, medium-fit, and high-fit; were used in this paper on the charts, tables, and some discussion to conserve space but should be interpreted as levels of conditioning. One medium-fit subject was a highly regarded distance runner who had just returned to serious training after 5 weeks of light workouts due to a hip injury. In order to facilitate statistical analyses the conditioning classifications were assigned values of t, 2, and 3 for the low, medium, and high-fit subjects, respectively. Charts were prepared for each subject plotting blood lactate concentration against heart rate and against relative Fo2 (:Fig. I) at both 10 rain and i5 min. Utilization of these charts permitted estimation of the heart rate and relative I?o~needed to achieve a lactate level of 2.2 mM/L or 4.4 mM/L I n our laboratory resting blood lactates range from 0.6 mM/L to 2.2 raM/L, usually from 0.9 m ~ / n to i.6 mM/L. Costill (personal communication) suggested that long-d/stance runners could run quite comfortably as long as their lactate concentration was below 4.4 mM/L. In addition, the relative Vo2 at which the lactic acid concentration at i5 rain exceeded the 10 rain value was determined. I t was felt that the latter would identify the point of continuing anaerobic contribution to the metabolic requirement. All of the parameters listed in the previous paragraph were correlated with level of conditioning utilizing triserial procedures adjusted for coarse grouping (Wert et el., qt954). Correlation ratios were calculated, also, but were not included because the values were almost identical to the triserial correlations. Corrected multiple triserial correlations between conditioning and RMSSI?o2 and maximal steady state heart rate (MSSHR) were calculated (Wert et el., 1954). Regression equations were developed for variables significantly related to conditioning. In addition, Pearson product-moment correlations were run among selected steadystate parameters as well as max l?o~.Analyses of variance were run on each of the parameters

272

B. 1%.Londeree and S. A. Ames

with the level of conditioning serving as the independent variable; significant "F" ratios were followed by multiple comparisons utilizing the Scheff6 procedures. Results Relative l?o2 and heart rate were plotted separately against blood lactate concentrations for each subject. The data from the resulting ~[0 min curves were averaged b y conditioning level and are shown in Figs, 2 and 3 for relative ~2 and heart rates, respectively. I t was apparent t h a t as the conditioning level increased, lactate accumulation occurred at a higher relative workload. Relative fTo2 and heart rate values corresponding to blood l~ctate concentrations of 2.2 mM/L and 4.4 mM/L were determined from the ch~rts of individual subjects. The resulting data were averaged b y conditioning group and are presented in Table 2. Comparisons among the three levels of conditioning were made for e~ch of the above criteria. The differences ~mong heart rates associated with 2.2 raM/L-lactate for the three conditioning groups were ~ll significant. Relative 17o2 for lactate concentrations of 2.2 mM/L produced significant differences between only the low-vs high-fitness comparisons both at ]0 rain and 15 rain. The changes in heart rate occurring between lactate concentrations of 2.2 mM/L gnd 4.4 mM/n were less for the high-fit than either the low-fit or medium-fit, Increases in relative Vos associated with increases of lactate frorfl 2.2 mM/l. to 4.4 1nM/L were less for the high-fit t h a n the low- or medium-fit. Neither relative ~ nor heart rates

/ 9 LOW

. /

9 Meo,uM

!1 t / /

8

i

A

6~

: Zg,oM i

I

2~ =

3'o

~o

5'o

60

7o

PERCENT ~'02 MAx

Fig. 2

80

9'o

i

0L~120

1

150

160

170

180

HEART RATE

Fig. 3

Fig. 2. Lactate concentrations versus relative lYo~values for the three levels of conditioning. l~elative l?o~values were rounded to the nearest 10 % to reduce clutter :Fig. 3. Lactate concentrations versus heart rates for the three levels of conditioning. Heart rates were rounded to the nearest 10 bpm to reduce clutter

190

Maximal Steady State

273

Table 2. Heart rates ~nd relative l?o2levels associated with lactate concentrations of 2.2 rm~i/L and 4.4 mM/L at 10 min and 15 rain of exercise. X: _+S.E. 2.2 mM/r. 10 rain

High-fit Medium-fit Low-fit

High-fit 5Iedium-fi~ Low-fit

t68.3 • 1.2 154.5 • 3.7 t30.8 _+3.7

t5 rain I-Ieart rates (bpm) t74.5 _+3.5 t58.3 _+2.9 t36.3 • 6.9

Relative ~ ( % of max ~2) 74.0 • t.5 73.0 • 2.0 59.8 • 4.5 60.8 • 4.6 46.5 • 1.0 47.8 _+3.t

4.4 m~/L 10 min

t5 rain

177.7• 3.3 177.6• 3.7 171.5_+3.0

481.0 177.0 + 2.5 176.8• 2.8

81.3 • 4.5 78.8 _+5.0 70.0 • 6.0

74.0 76.2 _+4.9 72.3 • 6.1

associated with lactates of 4.4 mM/L discriminated between levels of conditioning as attested by insignificant " 2 " ' ratios. The relative l?o~ values where the blood lactate concentration at 15 rain first exceeded the 10 rain level were determined. 4 of the I2 subjects never demonstrated this phenomenon; therefore, the highest relative Vo2which these subjects completed was utilized for calculation purposes. The mean relative ~z 4- S.E. values by conditioning group where the 15 rain lactate exceeded the t0 rain level were: low-fit, 85.8 4- 6.3 ; medium-fit, 81.2 i 3.5; and high-fit, 76.0 4- 2.0. There were no significant differences among these values. The triserial correlations between the various steady-state criteria and level of conditioning are presented in Table 3. The significant relationships were consistent with the results of the preceding ANOVA's. Regression equations and their associated standard errors of the estimate appear next to the discriminating parameters. The 1 0 m i n equations appeared to estimate conditioning more precisely than the ;[5 rain equations. Also MSSHR appeared to be a slightly more precise predictor of state of condition t h a n RMSSI?o~. Combining RMSSI?o2 and MSSHR (2.2 mM/~-laetate) improved predictions slightly over the bivariate estimates. However, statistical tests showed t h a t there were no significant differences among the various prediction equations. Note the moderate relationship between m a x l?o= and state of condition. The correlation between RMSSI?o2 and MSSHR (2.2 raM/L-lactate) was 0.80 for the ~0 rain data and 0.76 for the 15 rain values. Max l?o~ was correlated with MSSHR (2.2 raM/L-lactate) at i0 rain, 0.65, with RMSSVo~ (2.2 raM/L-lactate) at t0 rain, 0.46, and with conditioning, 0.62.

Discussion As mentioned previously, several investigators reported t h a t trained endurance athletes could perform at higher relative workloads without lactate production than sedentary subjects; the present data were consistent with these studies. Saltin (i97t) discussed a study by Runseon in which it was found t h a t when the

274

B.R. Londeree and S. A. Ames

Table 3. Correlations and regression equations for level of conditioning versus RMSStII~, RMSS~2, and max 17o2 Variable

Correlation with fitness

Regression with fitness

Standard error of the estimate

10 rain determinations I~MSSI?o2for 2.2 mM/L ~MSS~2 for 4.4 mM/I, MSSHR for 2.2 m~/[/L MSSHR for 4.4 mM/L R M S S ~ and MSSHR for 2.2 mM/L

0.82** 0.34 0.90** 0.33 0.94**

0.049 Xi, - 0.972

0.4726

0.043 X 2 - 4.543

0.3599

0.0t92 X i + 0.0411 X2 - 5.3136

0.3236

t5 rain determinations I~SSI?o2 for 2.2 mM/L RMSS~2 for 4.4 m~I/L MSSItl~ for 2.2 mM/L NSSttI~ for 4.4 ml~/L R M S S ~ and MSSHt~ for 2.2 ml~/L

0.75** 0A9 0.84** 0.20 0.88**

0.043 X i - 0.682

0.5200

0.036 X 2 - 3.699

0.4266

0.0180 X i + 0.0369 X~ - 4.7233

0.3734

Relative level that i5 rain L > 10 rain L ?~[aximal oxygen consumption (ml/kg 9 rain) * P < 0.05.

** P < 0.01.

- 0.38 0.62* ,X i = R~SSI?o2; X~ = MSSHR.

criterion of time to exhaustion was used, there were only small differences between unfit and fit subjects working at the same relative workload ( 6 0 % - - 1 0 0 % of m a x l?o~). Other studies have found r a t h e r small differences between the relative workloads t h a t could be maintained in steady state b y trained versus untrained subjects (Hermansen et al., 1967) or subjects before and after training (Saltin st al., 1968). Unfortunately, in these studies the level of fitness was inferred from m a x 1)o2 and the present d a t a showed t h a t conditioning and m a x I?o~should not be equated. Runseon's results appear incompatible with theory, most of the scientific literature, and personal experiences and suggest a need for a replication of the s t u d y using a measure of "level of fitness" other t h a n m a x 17o2, e.g., activity level. The use of activity levels, considering frequency, quantity, and quality, during the previous 6 m o n t h s as criteria of conditioning was necessary because no measure of the state of conditioning per se exists at the present time. The subjects were l a b o r a t o r y personnel and their personal acquaintances. The close associations provided considerable insight into the activity level of each subject. Classification errors would mitigate against significant differences among conditioning groups and tend to reduce the size of the correlations between conditioning and the predictor variables. Actually, the largest errors in prediction of state of condition of individuals occurred for subjects in the medium-fit group. The extreme groups were more homogeneous.

Maximal Steady State

275

The low correlation between state of conditioning and max %~ supported the contention that the latter was confounded by at least one other factor. Astrand and Rodahl (1970, p. 280) and Klissouras (t972) proposed that this factor was heredity. Considering the size of the relationship (0.62) it appeared that conditioning accounted for less than 40 % of the variability found in max %~ in the present group of subjects. The moderate correlations between max ~o2 and MSSttl% (0.65) and RMSSITo,~ (0.46) were consistent with such an interpretation. The remaining variance in max IYo~(60 %) probably can be attributed to at least three factors: 1) measurement errors, 2) years of endurance type training, and 3) heredity. Measurement errors probably accounted for about 3 to 5 % of the total variability in max ?a~ (Astrand and Saltin, t961). Errors in conditioning classification as well as the coarse grouping utilized undoubtably added additional random variance. No evidence was available regarding the residual influence of past (not recent) training; however, it was reasonable to expect some effect. Since the extent of the influence of past training and errors of conditioning classification were unknown, it was impossible to estimate the amount of contribution that heredity made on max ~ . The important conclusion from the data was that max Po~ was not a valid measure of state of conditioning. This does not preclude the fact that changes in max 17o~resulting from regular exercise m a y serve well as an index of change in conditioning. There are two other alternative explanations for the low correlation between state of conditioning and max ~ : l) the small number of subjects, and 2) the uniqueness of the sample. The former is unlikely since other correlations were high. The latter is a distinct possibility. The mean age of the high-fit subjects was greater than the other two groups. One of the medium-fit subjects had the largest max Pc2, but his quantity of training was quite low because he had just recovered from a slow healing injury. One of the high-fit subjects had a moderate max Po~, but his training consisted of running l0 miles daily. The single best predictor of state of condition was the MSSHR at i0 rain utilizing 2.2 raM/L-blood lactate concentration as the upper limit of steady state. Although there were no differences in average predictive precision based on the statistical tests among the significant correlation coefficients, the ANOVA tests demonstrated that MSSHR for 2.2 raM/L-lactate at both i0 rain and 15 rain discriminated among all three levels of conditioning and the corresponding RMSS [?o~only discriminated between the high- and low-fitness groups. Combining these two factors did not improve level of conditioning prediction significantly. For practical reasons it is fortunate that the i0 rain heart rate associated with a lactate concentration of 2.2 mM/L (MSSHR2.~) was a good predictor of conditioning. This test is submaximaI and requires no gas analyses. The low stress would be particularly valuable for testing poorly conditioned subjects and unhealthy individuals (if future work permits generalization to various unhealthy populations). On the other hand, all of the tests, including the MSSHR~.2 test, are time consuming and require blood sampling. Quizzing the subject regarding his activity level will enable the investigator to make an intelligent guess of MSSI-IR~.~ and thereby keep the number of workbouts to a minimum. Since serial blood sampling is not necessary, blood could be obtained immediately postexercise by standard venipuncture or finger prick.

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The size of the correlations between the steady-state tests and conditioning suggested that these tests might be relatively free from heredity. Substantiation of this hypothesis must await long-term training studies with initially very low-fit subjects (RMSSVo2 = 40 %). If the state of conditioning of these subjects can be elevated to levels comparable with very high-fit individuals (RMSS~2 = 85%) the proof would be more compelling. Preliminary study along these lines in our laboratory has been encouraging. Williams et al. (i967) utilizing an upturn in excess lactate as the criterion found RMSSVo~ to increase from 46% to 62% as a result of 4 to 16 weeks of training. Ekblom 0969) reported an increase in I%MSSI?o2 to about 75 % in 2 subjects who trained for 52 months. A blood lactate concentration of 2.2 mM/L consistently was a superior criterion of steady-state (as related to conditioning) than either a lactate level of 4.4 mM/L or continuing accumulation of lactate between i0 rain and i5 rain. A lactate level of 2.2 mM/L indicated that essentially all of the energy was supplied aerobically. The low-fit subjects were able to maintain an aerobic state only at relatively mild work levels. Increased intensity was accompanied by accumulating lactate and the associated discomfort. However, since low-fit subiects met their increasing energy needs both aerobically and anaerobically, there probably was no critical threshold pace, i.e., a point such that a further increase in intensity caused a great lactate production. The high-fit subjects worked very close to a maximal effort under aerobic conditions. These individuals, with their small aerobic reserve, produced energy needs above steady-state level primarily from anaerobic sources. The net effect was that high-fit subjects delayed the onset of anaerobic metabolism, but once steady-state was exceeded the production of lactic acid increased rapidly with additional work. This would make the identification of the RMSS ~2 workload very important for high-fit distance runners. Bang (i936) and Saiki et al. (1967) attributed the increased blood lactate during submaximal work to the lag in aerobic metabolism at the beginning of exercise. With continued exercise the lactate concentration tended to return to the resting level. The rate of decline in lactate concentration appeared to be a function of work intensity and fitness (Saiki et al., i967). In the present data the change in blood lactate from the i0th rain to the tSth rain tended to decrease slightly (not significantly) when the i0 rain lactate was below 2.8 mM/L and tended to increase (not significantly) when the i0 rain lactate was above 3.9 mM/L. Most of the exceptions to these trends were in the low-fit group. These results suggested that below maximal steady state workloads the blood lactate elevation was due to the initial lag in adjustment of the aerobic mechanisms. However, at loads in excess of steadystate there may have been a continuing anaerobic contribution. Several factors m a y be operative in permitting fit subjects to perform at a high RMSS~o2. Trained muscles contain a greater supply of ATP (Karlsson et al., i972) and myoglobin (Whipple, 1962) ; this would increase the alactic capacity. Training may improve distribution of blood flow to the muscles (Elsner and Carlson, i962; Rother et al., i963) and capiUarization of the muscles (Petren, i936). The capacity of trained muscles to utilize oxygen at a higher rate probably results from the increase supply of aerobic enzymes and capacity to oxidize pyruvate (I-Iolloszy, 1967) and palmitate (Mole and I-Iolloszy, t970), more tightly coupled oxidative

Maximal Steady State

277

p h o s p h o r y l a t i o n , a b i l i t y to f u n c t i o n a t a lower A T P / ( A D P + P ) (Holloszy, i967), a n d increased v o l u m e a n d n u m b e r o f m i t o e h o n d r i a (Gollnick et al., 197i). F i n a l l y , a n increased aerobic c a p a c i t y of r e d fibers (Kolloszy et al., t971) m i g h t d e l a y t h e r e c r u i t m e n t of a n a e r o b i c pale fibers. References Astrand, P. 0., Rodahl, K. : Textbook of work physiology. New York: McGraw.Hill 1970 Astrand, P. 0., Saltin, ]3. : Oxygen uptake during the first minutes of heavy muscular exercise. J. appl. Physiol. 16, 971--976 (1961) ]3ang, O. : The lactate content of the blood during and after muscular exercise in man. Skand. Arch. Physiol. 74 (Suppl. 10) (1936) Consolazio, D. J., Johnson, R. E., Pecora, L. J. : Physiological measurements of metabolic functions in man. New York: McGraw-Hill t963 Costill, D. L.: What research tells tile coach about distance running. Washington, D.C.: AAHPER 1968 Costill, D. L., ]3ranam, G., Eddy, D., Sparks, K. : Determinants of marathon running success. Int. Z. angew. Physiol. 29, 249--254 (1971) Ekblom, ]3. : Effect of physical training on oxygen transport system in man. Acta physiol. scan& 77 (Suppl. 328) (1969) Elsner, R. W., Carlson, L. D. : Postexercise hyperemia in trained and untrained subjects. J. appl. Physiol. 17, 436--440 (1962) Gledhill, N. : The effect of various training intensities on cardiorespiratory fitness. Unpublished master's thesis, University of Western Ontario (1968) Gollnick, P. 0., Ianuzzo, C. D., King, D. W. : Ultrastructure and enzyme changes in muscles with exercise. In: Muscle metabolism during exercise, ]3. Pernow, ]3. Saltin, eds., pp. 69-85. New York: Plenum Press 1971 Hermansen, L., Hultman, E., Saltin, 13. : ~[uscle glycogen during prolonged severe exercise. Acta physiol, scan& 71, t29--139 (t967) Hermansen, L., Saltin, ]3. : :Blood lactate concentration during exercise at acute exposure to altitude. In: Exercise at altitude, R. ~argaria, ed., pp. 48--53. Amsterdam: Excerpta Medica Foundation t967 Holloszy, J. 0.: Biochemical adaptations in muscle: Effects of exercise on mitochondrial oxygen uptake and respiratory enzyme activity in skeletal muscle. J. biol. Chem. 242, 2278--2282 (t967) Holloszy, J. O., Oscai, L. 13., MoI6, P. A., ])on, I. J. : :Biochemical adaptations to endurance exercise in skeletal muscle. In: Muscle metabolism during exercise, ]3. Pernow, ]3. Saltin, eds., pp. 51--61. New York: Plenum Press t971 Karlsson, J., Nordesjo, L. O., Jorfeldt, L., Saltin, ]3. : ~usele lactate, ATP and CP levels during exercise after physical training in man. J. appl. Physiol. 33, 199--208 (1972) Klissouras, V.: Genetic limit of functional adaptability. Int. Z. angew. Physiol. 80, 85--94 (1972) Marbach, E. P., Well, N. H. : Rapid enzymatic measurements of blood lactate and pyruvate. Clin. Chem. 13, 3t4--325 (1967) MoM, P. A., Holloszy, J. O. : Exercise-induced increase in the capacity of skeletal muscle to oxidize palmitate. Proe. Soc. exp. :Biol. (N.Y.) 134, 789--792 (t970) Petren, T., Sjostrant, T., Sylven, ]3. : Der EinfluB des Trainings auf die HEufigkeit der Capillaren in Herz- und Skelettmuskulatur. Arbeitsphysiologie 9, 376--386 (t936) Rohter, F. D., Rochelle, R. H., Human, D. : Exercise blood flow changes in the human forearm during physical training. J. appl. Physiol. 18, 789--793 (1963) Saiki, tI., Margaria, 1~., Currica, :F. : Lactic acid production in submaximal muscular exercise. In: Exercise at altitude, R. Margaria, ed., pp. 54--57. Amsterdam: Exeerpta Medica Foundation t967 Saltin, :B. : Guidelines for physical training. Scand. J. Rehab. Med. 8, 39--46 (1971) Saltin, 13., ]31omqvist, G., Mitchell, J. H., Johnson, R. L., Jr., Wildenthal, K., Chapman, C. ]3. : Response to exercise after bed rest and after training. Circulation 38 (Suppl. VII) (1968)

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Weft, J. E., Neidt, C. O., Ahmann, J. S.: Statistical methods in educational and psychological research. New York: Appleton-Century-Crofts 1954 Whipple, G. H.: The hemoglobin of striated muscle: ~t. V~riations due to age and exercise. Amer. J. Physiol. 7G, 693--707 (1962) Williams, C. G., Wyndham, C. H., Kok, R., yon Rahden,/eL J. E.: Effect on training on maximal oxygen intake and on anaerobic metabolism in man. Int. Z. angew. Physiol. 94, 18--23 (i967) Wyndham, C. H., Seftel, H. C., Williams, C. G., Wilson, V., 8trydom, ~q. B., Bredell, G. A. G., von Rahden, M. J. E. : Circulatory mechanism of anaerobic metabolism in working muscle. S. Aft. reed. Jo 89, t008--t01~ (1965) Dr. Ben R. Londeree Human Performance Laboratory University of Missouri Columbia, Missouri 65901, USA