Jared R. Fletcher

Economy of running: beyond the measurement of oxygen uptake

The purpose of this study was to compare running economy across three submaximal speeds expressed as both oxygen cost (mlxkg(-1)xkm(-1)) and the energy required to cover a given distance (kcalxkg(-1)xkm(-1)) in a group of trained male distance runners. It was hypothesized that expressing running economy in terms of caloric unit cost would be more sensitive to changes in speed than oxygen cost by accounting for differences associated with substrate utilization. Sixteen highly trained male distance runners [maximal oxygen uptake (Vo(2max)) 66.5 +/- 5.6 mlxkg(-1)xmin(-1), body mass 67.9 +/- 7.3 kg, height 177.6 +/- 7.0 cm, age 24.6 +/- 5.0 yr] ran on a motorized treadmill for 5 min with a gradient of 0% at speeds corresponding to 75%, 85%, and 95% of speed at lactate threshold with 5-min rest between stages. Oxygen uptake was measured via open-circuit calorimetry. Average oxygen cost was 221 +/- 19, 217 +/- 15, and 221 +/- 13 mlxkg(-1)xkm(-1), respectively. Caloric unit cost was 1.05 +/- 0.09, 1.07 +/- 0.08, and 1.11 +/- 0.07 kcalxkg(-1)xkm(-1) at the three trial speeds, respectively. There was no difference in oxygen cost with respect to speed (P = 0.657); however, caloric unit cost significantly increased with speed (P < 0.001). It was concluded that expression of running economy in terms of caloric unit cost is more sensitive to changes in speed and is a more valuable expression of running economy than oxygen uptake, even when normalized per distance traveled.

Energy cost of running and Achilles tendon stiffness in man and woman trained runners

The energy cost of running (Erun), a key determinant of distance running performance, is influenced by several factors. Although it is important to express Erun as energy cost, no study has used this approach to compare similarly trained men and women. Furthermore, the relationship between Achilles tendon (AT) stiffness and Erun has not been compared between men and women. Therefore, our purpose was to determine if sex‐specific differences in Erun and/or AT stiffness existed. Erun (kcal kg−1 km−1) was determined by indirect calorimetry at 75%, 85%, and 95% of the speed at lactate threshold (sLT) on 11 man (mean ± SEM, 35 ± 1 years, 177 ± 1 cm, 78 ± 1 kg, V˙O2max = 56 ± 1 mL kg−1 min−1) and 18 woman (33 ± 1 years, 165 ± 1 cm, 58 ± 1 kg, V˙O2max = 50 ± 0.3 mL kg−1 min−1) runners. AT stiffness was measured using ultrasound with dynamometry. Man Erun was 1.01 ± 0.06, 1.04 ± 0.07, and 1.07 ± 0.07 kcal kg−1 km−1. Woman Erun was 1.05 ± 0.10, 1.07 ± 0.09, and 1.09 ± 0.10 kcal kg−1 km−1. There was no significant sex effect for Erun or RER, but both increased with speed (P < 0.01) expressed relative to sLT. High‐range AT stiffness was 191 ± 5.1 N mm−1 for men and 125 ± 5.5 N mm−1, for women (P < 0.001). The relationship between low‐range AT stiffness and Erun was significant at all measured speeds for women (r2 = 0.198, P < 0.05), but not for the men. These results indicate that when Erun is measured at the same relative intensity, there are no sex‐specific differences in Erun or substrate use. Furthermore, differences in Erun cannot be explained solely by differences in AT stiffness.

The parabolic power–velocity relationship does apply to fatigued states

There is a relatively flat power–cadence relationship between 60 and 100 rpm in fatigued subjects (Beelen and Sargeant 1991). Does this mean power output measured at 80–100 rpm can be compared with power output at 40 rpm? Burnley (2010) says no, but Marcora and Staiano would argue that this is acceptable. There is published support for Burnley’s point. Acceleration at the end of a Wingate test yields a linear torque– angular velocity relationship, which predicts a parabolic power–cadence relationship in these fatigued subjects (MacIntosh et al. 2004). In fatigue, power output would be greater when measured at 75 rpm than when measured at 40 rpm. We would argue that the results of Beelen and Sargeant (1991), which are remarkably similar to the results of Marcora and Staiano (2010a, b), are consistent with those of MacIntosh et al. (2004). The actual power output for the corresponding torque–cadence relationship has been added to Fig. 1, and these demonstrate that there is variation across a broad range of cadences. If you were to test at discreet cadences from 60 to 120 rpm, on separate days, as Beelen and Sargeant (1991) did, you would obtain power outputs distributed around the lines presented. The results shown in Fig. 1 illustrate that this range of cadences will yield similar power outputs: they exist on the plateau of the fatigued parabolic power–cadence relationship. Clearly, if you were to test at 40 rpm, the power drops off considerably. Marcora and Staiano (2010a, b) would have us believe that their subjects with a maximal power output of just over 1,000 W were capable of generating a power output over 700 W at 40 rpm, in the fatigued state. Note that the maximal predicted power in the non-fatigued state at 40 rpm for our subject (maximal power output of 1,248 W) is 740 W. It should also be pointed out that the parabolic power–cadence relationship overestimates power at 40 rpm because the maximum (isometric) torque that can be generated (while seated) is body weight (in Newton) times crank length. For a 175 mm crank and 82 kg subject, the maximum (isometric) torque would be 140 Nm, so maximum power (non-fatigued) at 40 rpm would be considerably less than 590 W. It seems highly unlikely that the subjects of Marcora and Staiano would have been able to Fig. 1 The linear torque–cadence relationship is plotted with solid symbols and the straight lines represent the regression lines, with r = 0.9777 in the non-fatigued state and r = 0.9784 in the fatigued state. Open symbols represent calculated power (on right axis) corresponding to the same measures as the torque values. Clearly, there is a parabolic power–cadence relationship

Pacing Strategy, Muscle Fatigue, and Technique in 1500-m Speed-Skating and Cycling Time Trials

PURPOSE To evaluate pacing behavior and peripheral and central contributions to muscle fatigue in 1500-m speed-skating and cycling time trials when a faster or slower start is instructed. METHODS Nine speed skaters and 9 cyclists, all competing at regional or national level, performed two 1500-m time trials in their sport. Athletes were instructed to start faster than usual in 1 trial and slower in the other. Mean velocity was measured per 100 m. Blood lactate concentrations were measured. Maximal voluntary contraction (MVC), voluntary activation (VA), and potentiated twitch (PT) of the quadriceps muscles were measured to estimate central and peripheral contributions to muscle fatigue. In speed skating, knee, hip, and trunk angles were measured to evaluate technique. RESULTS Cyclists showed a more explosive start than speed skaters in the fast-start time trial (cyclists performed first 300 m in 24.70 ± 1.73 s, speed skaters in 26.18 ± 0.79 s). Both trials resulted in reduced MVC (12.0% ± 14.5%), VA (2.4% ± 5.0%), and PT (25.4% ± 15.2%). Blood lactate concentrations after the time trial and the decrease in PT were greater in the fast-start than in the slow-start trial. Speed skaters showed higher trunk angles in the fast-start than in the slow-start trial, while knee angles remained similar. CONCLUSIONS Despite similar instructions, behavioral adaptations in pacing differed between the 2 sports, resulting in equal central and peripheral contributions to muscle fatigue in both sports. This provides evidence for the importance of neurophysiological aspects in the regulation of pacing. It also stresses the notion that optimal pacing needs to be studied sport specifically, and coaches should be aware of this.

ACHILLES TENDON STRAIN ENERGY IN DISTANCE RUNNING: CONSIDER THE MUSCLE ENERGY COST

The return of tendon strain energy is thought to contribute to reducing the energy cost of running (Erun). However, this may not be consistent with the notion that increased Achilles tendon (AT) stiffness is associated with a lower Erun. Therefore, the purpose of this study was to quantify the potential for AT strain energy return relative to Erun for male and female runners of different abilities. A total of 46 long distance runners [18 elite male (EM), 12 trained male (TM), and 16 trained female (TF)] participated in this study. Erun was determined by indirect calorimetry at 75, 85, and 95% of the speed at lactate threshold (sLT), and energy cost per stride at each speed was estimated from previously reported stride length (SL)-speed relationships. AT force during running was estimated from reported vertical ground reaction force (Fz)-speed relationships, assuming an AT:ground reaction force moment arm ratio of 1.5. AT elongation was quantified during a maximal voluntary isometric contraction using ultrasound. Muscle energy cost was conservatively estimated on the basis of AT force and estimated cross-bridge mechanics and energetics. Significant group differences existed in sLT (EM > TM > TF; P < 0.001). A significant group × speed interaction was found in the energy storage/release per stride (TM > TF > EM; P < 0.001), the latter ranging from 10 to 70 J/stride. At all speeds and in all groups, estimated muscle energy cost exceeded energy return (P < 0.001). These results show that during distance running the muscle energy cost is substantially higher than the strain energy release from the AT.

Running Economy from a Muscle Energetics Perspective

The economy of running has traditionally been quantified from the mass-specific oxygen uptake; however, because fuel substrate usage varies with exercise intensity, it is more accurate to express running economy in units of metabolic energy. Fundamentally, the understanding of the major factors that influence the energy cost of running (Erun) can be obtained with this approach. Erun is determined by the energy needed for skeletal muscle contraction. Here, we approach the study of Erun from that perspective. The amount of energy needed for skeletal muscle contraction is dependent on the force, duration, shortening, shortening velocity, and length of the muscle. These factors therefore dictate the energy cost of running. It is understood that some determinants of the energy cost of running are not trainable: environmental factors, surface characteristics, and certain anthropometric features. Other factors affecting Erun are altered by training: other anthropometric features, muscle and tendon properties, and running mechanics. Here, the key features that dictate the energy cost during distance running are reviewed in the context of skeletal muscle energetics.

Reply to: Reply to: The parabolic power–velocity relationship does apply to fatigued states

We are pleased that Marcora and Staiano (2011) can see that there is a parabolic relationship between power and velocity, and therefore that their argument that the relationship is Xat is not valid. However, we have two further concerns: (1) we suggest that it is not appropriate to use this example data to interpret their study, when in fact they should have obtained individualized data for each subject for such interpretation, and (2) we are concerned that Marcora and Staiano have not accepted that this information is evident in the published literature and that it was there long before they wrote their reply to Burnley (2010). We provided an example of this relationship using the data of a single subject, from a previously published study (MacIntosh et al. 2004). In that article, we presented linear torque– angular velocity relationships in fatigue, and we also showed corresponding parabolic power–angular velocity relationships. The key here is that a linear torque–angular velocity relationship is the basis for a parabolic power– velocity relationship. If Marcora and Staiano had recognized that a linear relationship between torque and angular velocity yielded a parabolic power–angular velocity relationship, they would have realized that others have also presented data similar to ours, demonstrating that there must be a parabolic relationship between power and velocity, and that relationship is sustained in fatigue. For example, Buttelli et al. (1996) have also shown that, after sequential sprints, the torque– velocity relationship remains linear. These investigators have also shown (Buttelli et al. 1997) that if they allowed subjects to ride to exhaustion at 80 or 60% of maximal power output and then re-evaluated the relationship between torque and angular velocity, there was still a linear relationship. Unfortunately, in this case, they allowed a full minute of recovery, so their data cannot be used to address the same question of interest here: Is there peripheral fatigue contributing to the limit of performance during predominantly aerobic exercise? Even if Marcora and Staiano could not recognize the importance of a linear torque–angular velocity relationship, they should have recognized the parabolic power–resistance relationship presented by Dotan and Bar-Or (1983). Considering that power is the product of velocity and resistance, if there is a parabolic power– resistance relationship, there must be a parabolic power– velocity relationship. Before we proceed to the issue of what factors might limit endurance, we would like to point out another problem with the initial Marcora and Staiano (2010) study. It has already been established that the criterion for ending the test should not have allowed the subjects to slow their cadence. This is just one of several problems with the study. The study was done with rugby players, performing endurance exercise on a cycle ergometer. These athletes were most likely not particularly trained in cycling. This is evident in the extremely short duration that these athletes were able to endure 80% of maximal oxygen uptake (10 min). Coyle et al. (1988) has reported that cyclists can ride at 88% of maximal oxygen uptake for 29 min, and that highly trained cyclists can persist at this intensity for 60 min. So where does this leave us with respect to the issue of central or peripheral limitations to endurance? We have recently proposed the existence of a peripheral governor, a local control system that regulates the intensity Communicated by Susan A. Ward.

Procedures for Rat in situ Skeletal Muscle Contractile Properties

There are many circumstances where it is desirable to obtain the contractile response of skeletal muscle under physiological circumstances: normal circulation, intact whole muscle, at body temperature. This includes the study of contractile responses like posttetanic potentiation, staircase and fatigue. Furthermore, the consequences of disease, disuse, injury, training and drug treatment can be of interest. This video demonstrates appropriate procedures to set up and use this valuable muscle preparation. To set up this preparation, the animal must be anesthetized, and the medial gastrocnemius muscle is surgically isolated, with the origin intact. Care must be taken to maintain the blood and nerve supplies. A long section of the sciatic nerve is cleared of connective tissue, and severed proximally. All branches of the distal stump that do not innervate the medial gastrocnemius muscle are severed. The distal nerve stump is inserted into a cuff lined with stainless steel stimulating wires. The calcaneus is severed, leaving a small piece of bone still attached to the Achilles tendon. Sonometric crystals and/or electrodes for electromyography can be inserted. Immobilization by metal probes in the femur and tibia prevents movement of the muscle origin. The Achilles tendon is attached to the force transducer and the loosened skin is pulled up at the sides to form a container that is filled with warmed paraffin oil. The oil distributes heat evenly and minimizes evaporative heat loss. A heat lamp is directed on the muscle, and the muscle and rat are allowed to warm up to 37°C. While it is warming, maximal voltage and optimal length can be determined. These are important initial conditions for any experiment on intact whole muscle. The experiment may include determination of standard contractile properties, like the force-frequency relationship, force-length relationship, and force-velocity relationship. With care in surgical isolation, immobilization of the origin of the muscle and alignment of the muscle-tendon unit with the force transducer, and proper data analysis, high quality measurements can be obtained with this muscle preparation.

Quantification of the manifestations of fatigue during treadmill running

Abstract During whole-body exercise, fatigue is difficult to quantify; however, changes to mechanical, physiological and psychological systems during exercise are associated with the development of fatigue. To quantify fatigue, one must therefore assess changes occurring in these variables. The purpose of this study was to demonstrate a method to assign weightings to selected variables and to combine them into a single value quantifying changes occurring during exercise. Twelve female recreational runners performed one hour of treadmill running, during which heart rate, respiration rate, stride frequency and six selected psychological variables were collected at defined intervals throughout the run. Data were normalised and a principle component analysis was performed. The resulting first eigenvector was termed the “contribution vector” and indicated the weighting of each variable towards the global exercise-induced changes in the body. The projection of data onto the contribution vector resulted in a value described as the “fatigue index”. An assessment of the generalisation of the method to new data was performed using a leave-one-out cross-validation procedure and indicated that the index is accurate to within 3.01% of the maximum index value measured. The method developed here has the advantage over current methods due to its multifactorial, causal and customisable nature.

THEORETICAL CONSIDERATIONS FOR MUSCLE-ENERGY SAVINGS DURING DISTANCE RUNNING

We have recently demonstrated that the triceps surae muscles energy cost (ECTS) represents a substantial portion of the total metabolic cost of running (Erun). Therefore, it seems relevant to evaluate the factors which dictate ECTS, namely the amount and velocity of shortening, since it is likely these factors will dictate Erun. Erun and triceps surae morphological and AT mechanical properties were obtained in 46 trained and elite male and female distance runners using ultrasonography and dynamometry. ECTS (J·stride-1) at the speed of lactate threshold (sLT) was estimated from AT force and crossbridge mechanics and energetics. To estimate the relative impact of these factors on ECTS, mean values for running speed, body mass, resting fascicle length (Lf), Achilles tendon stiffness and moment arm and maximum isometric plantarflexion torque were obtained. ECTS was calculated across a range (mean ± 1 sd) of values for each independent factor. Average sLT was 233 m·min-1. At this speed, ECTS was 255 J·stride-1. Estimated fascicle shortening velocity was 0.08 Vmax and the level of muscle activation was 84.7% of maximum isometric torque. Compared to the ECTS calculated from the lowest range of values obtained for each independent factor, higher AT stiffness was associated with a 39% reduction in ECTS, 81% reduction in fascicle shortening velocity and a 31% reduction in muscle activation. Longer AT moment arms and elevated body masses were associated with an increase in ECTS of 18% and 23%, respectively. These results demonstrate that a low ECTS is achieved primarily from a high AT stiffness and low body mass, which is exemplified in elite distance runners.