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BRIEF COMMUNICATION Skeletal muscle architectural adaptations to marathon run training Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by Bangor University on 12/30/14 For personal use only.
Kevin Murach, Cory Greever, and Nicholas D. Luden
Abstract: We assessed lateral gastrocnemius (LG) and vastus lateralis (VL) architecture in 16 recreational runners before and after 12 weeks of marathon training. LG fascicle length decreased 10% while pennation angle increased 17% (p < 0.05). There was a significant correlation between diminished blood lactate levels and LG pennation angle change (r = 0.90). No changes were observed in VL. This is the first evidence that run training can modify skeletal muscle architectural features. Key words: exercise, pennation angle, fascicle length, structure. Résumé : On évalue l’architecture du jumeau externe (« LG ») et du vaste externe (« VL ») chez 16 coureurs par loisir avant et après 12 semaines d’entraînement pour un marathon. La longueur des faisceaux du LG diminue de 10% et l’angle de pennation augmente de 17% (p < 0,05). On observe une corrélation significative entre la diminution du taux sanguin de lactate et la variation de l’angle de pennation du LG (r = 0,90). On n’observe aucune modification dans le VL. C’est la première démonstration selon laquelle l’entraînement a` la course peut modifier les caractéristiques de l’architecture musculaire. [Traduit par la Rédaction] Mots-clés : exercice physique, angle de pennation, longueur fasciculaire, structure.
Introduction Skeletal muscle architecture is the geometrical arrangement of muscle thickness, fascicle length (Lf), and pennation angle (Ap, often represented by fascicle angle, Af), and is a chief determinant of whole-muscle function (Wickiewicz et al. 1984). Resistance training alters thickness, Ap and Lf (Blazevich et al. 2007), which demonstrates that exercise can impact muscle architecture. However, insight into possible architectural changes with run training is limited to cross-sectional data (Abe et al. 2000). Distance runners possess shorter fascicles and larger Ap in vastus lateralis (VL) and gastrocnemii compared with sprinters (Abe et al. 2000). Shorter fascicles with potentially fewer sarcomeres in series presumably require less metabolic energy upon activation (Blazevich 2006) and large resting Ap may allow fascicles to work closer to optimal force-production lengths (Shin et al. 2009). These characteristics likely promote fatigue resistance and metabolic efficiency, which would benefit endurance exercise. While architectural changes were not observed in VL with cycle training (Farup et al. 2012), whether beneficial architectural features are developed with run training in VL or lateral gastrocnemius (LG) has not been examined. The aim of this study was to test the hypothesis that marathon training will alter VL and LG architecture to resemble that previously observed in distance runners (Abe et al. 2000).
Materials and methods Subjects Sixteen experimental subjects (EXP: 10 males; 6 females) were recruited from a James Madison University (JMU) marathon preparation class. EXP (age, 20 ± 1.4 years; height, 164 ± 7 cm; body mass, 64 ± 7 kg; maximal oxygen consumption (V˙O2max), 57.7 ± 9.6 mL·kg−1·min−1) were recreational runners with no competitive or marathon running history. EXP data were from 2 separate cohorts in consecutive years (EXP1, n = 9; EXP2, n = 7). We also investigated 7 recreationally active (n = 3 male/n = 4 female) con-
trols (CON; age, 21.4 ± 1.0 years; height, 170 ± 8.3 cm; body mass, 67 ± 17 kg) from JMU. CON and EXP inclusion criteria mandated that subjects be apparently healthy, normal weight, and physically active while CON were required to maintain physical activity habits until post-testing. Informed consent approved by JMU’s Institutional Review Board was completed prior to testing. All relevant training and testing time points were consistent across groups. Experimental design VL and LG muscle architecture (thickness, Lf and Af) and cardiovascular measurements were obtained before and 12 weeks after marathon training (Trappe et al. 2006). Briefly, the 12-week, 4-days·week–1 program progressively increased volume (distance) with 24 km during week 1 (8-km–long run) and ⬃60 km during week 12 (29-km–long run), all at a self-selected pace. Treadmill testing All EXP performed incremental treadmill tests to assess aerobic capacity (V˙O2max) and submaximal oxygen consumption (V˙O2) (Luden et al. 2012). Breath samples were monitored using a VMAX Sensormedics Spectra metabolic cart (Yorba Linda, Calif., USA), with data aggregated in 30-s intervals. Treadmill procedures were similar for EXP cohorts. However, EXP2 (n = 7) underwent a 2-phase protocol to facilitate blood lactate analysis (less 1 subject posttraining because of illness). During phase 1, the treadmill was set at an individualized velocity that approximated the subject’s speed that was typically performed during a 60-min training run. Speed was incrementally increased 24–32 s·km−1 in 3-min stages (while monitoring V˙O2) followed by 1 min of rest. Resting venous blood was obtained (finger stick) and submaximal blood lactate concentrations and lactate threshold (>3.5 mmol·L−1) was determined via YSI 2300 STAT glucose/lactate analyzer (Yellow Springs, Ohio, USA). Lactate threshold was fixed at 3.5-mmol·L−1 post hoc, as this was the highest value eclipsed by all subjects. The velocity during
Received 22 July 2014. Accepted 22 September 2014. K. Murach, C. Greever, and N.D. Luden. Human Performance Laboratory, James Madison University, Harrisonburg, VA 22807, USA. Corresponding author: Nicholas D. Luden (e-mail: [email protected]). Appl. Physiol. Nutr. Metab. 40: 1–4 (2015) dx.doi.org/10.1139/apnm-2014-0287
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the penultimate stage was selected for submaximal V˙O2 comparisons before and after training. Fifteen minutes passive recovery ensued once blood lactate exceeded 3.5 mmol·L−1. Subjects then completed a 3-min walking warm-up at 5.6 km·h−1 (3.5 miles per hour). Phase 2 began at a velocity corresponding with the penultimate stage of phase 1.
mal V˙O2 (42.4 ± 6.7 vs. 41.2 ± 7.5 mL·kg−1·min−1 and 2.7 ± 0.5 vs. 2.6 ± 0.5 L·min−1). Fractional oxygen utilization during submaximal running (11.6 ± 1.0 km·h−1) was reduced with training (73.9 ± 7.2 vs. 70.6% ± 8.3% V˙O2max) (P < 0.05). Similarly, post-training blood lactate levels (2.6 ± 0.4 vs. 1.8 ± 0.5 mmol·L−1) were lower (P < 0.05) at submaximal speed (12.0 ± 1.0 km·h−1; n = 6).
Ultrasound Resting VL and LG architecture was measured in EXP and CON. Ultrasonography was performed using a Shenzen Mindray DC-6 (Nanshan, Shenzen, China) in B-mode with a linear array transducer set at 7.5 MHz. Images were captured when probe was aligned for optimal image quality (Kwah et al 2013). Insonation sites were preliminarily identified and recorded for subsequent visits using adapted methods (Kumagai et al. 2000). Briefly, for VL, subjects sat upright with a hip angle of 90° and ankle affixed at 90° using a customized Styrofoam support device. Midpoint between the bony protuberance of the femur’s greater trochanter and the prominence of the lateral femoral condyle was measured. A line from this midway point was extended mediolaterally. A second line from the patella’s lateral border was extended superiorly. Halfway along the mediolateral line represented mid-muscle belly. Images were captured after 10 min in fixed position. Subjects then moved to prone position with ankle joint affixed at 90° against a wall. At one-third the distance from the knee between the lateral femoral condyle and the lateral bony protuberance of the anklebone a line was extended mediolaterally. A line at one-quarter the distance between the lateral and medial condyle of the femur (posterior over LG) was extended inferiorly. The intersection represented mid-muscle belly and images were captured after 5 min of rest.
Skeletal muscle architecture There were no group × time interactions for VL thickness (EXP – pre-training: 2.60 ± 0.30 vs. post-training: 2.59 ± 0.29 cm; CON – 2.53 ± 0.47 vs .2.44 ± 0.43 cm), Af (EXP: 17.1 ± 3.0° vs. 16.6 ± 2.6°; CON: 16.3 ± 2.9° vs. 16.2 ± 2.6°), or Lf (EXP: 9.2 ± 2.1 vs. 9.3 ± 1.8 cm; CON: 9.2 ± 2.4 vs. 8.9 ± 1.6 cm), or for LG thickness (EXP: 1.37 ± 0.29 vs. 1.40 ± 0.36 cm; CON: 1.30 ± 0.29 vs. 1.32 ± 0.30 cm). However, group × time interactions were observed for both LG Af and Lf (P < 0.05). No changes in LG Af (12.1 ± 2.0° vs. 12.0 ± 2.0°) or Lf (6.4 ± 1.8 vs. 6.6 ± 2.1 cm) were observed in CON, but Af increased 17% (12.9 ± 3.2° vs. 15.0 ± 3.9°) (P < 0.01) and Lf decreased 10% (6.6 ± 2.7 vs. 5.9 ± 2.4 cm) in EXP (P < 0.01). There was a correlation between changes in submaximal blood lactate levels and LG Af (r = 0.90; P < 0.05). No other significant correlations were identified. EXP and CON LG Lf and Af data are displayed in Figs. 1A and 1B.
Image analysis Images were analyzed using ImageJ64 software (National Institutes of Health, USA) on a Macintosh computer. Thickness was determined by the average distance between superficial and deep aponeuroses at 3 points along the muscle belly perpendicular to the aponeuroses. Af was measured between superficial and deep aponeuroses at 3 different muscle locations (superficial, middle, and deep) and aggregated. Lf was calculated using a prediction equation (Kumagai et al. 2000). Ultrasound methods similar to those described here have been validated in reference to cadavers (Kawakami et al. 1993) and magnetic resonance images (Walton et al. 1997; Miyatani et al. 2002). Further, current values and standard deviations obtained in both muscles and groups are in line with the literature (Abe et al. 2000). The coefficient of variation (CV) for repeated measurements separated by 7 days (5 pilot subjects) were VL Af = 2.8%, thickness = 3.2%, and Lf = 5.1%; LG Af = 4.0%, thickness = 5.4%, and Lf = 8.7%. The control group also endorses the reproducibility of our measures. Statistical analysis The effects of training on skeletal muscle architecture was analyzed with 2 × 2 (time × group) repeated-measures ANOVAs. Pairwise comparisons (time × group interaction; P < 0.05) between pre- and post-training, within EXP, were analyzed using paired t tests with Bonferroni correction. Effects of training on cardiovascular physiology and blood lactate levels were assessed with paired t tests (pre- vs. post-training). Relationships between changes (raw score) in architecture and changes in V˙O2max, submaximal V˙O2, and submaximal lactate levels were calculated with Pearson correlation coefficients. All data were checked for normality and significance was set at P < 0.05. Data displayed as means ± SD.
Results Treadmill testing Training did not influence body weight (pre-training: 63.8 ± 6.6 vs. post-training: 63.3 ± 6.3 kg), V˙O2max (57.4 ± 6.6 vs. 58.6 ± 8.8 mL·kg−1·min−1 and 3.6 ± 0.5 vs. 3.7 ± 0.6 L·min−1), and submaxi-
Discussion This is the first evidence for skeletal muscle architectural adaptations to endurance run training. Increased LG Af and reduced Lf, without a change in thickness, agree with the distinct architecture of distance runners noted in previous investigations (Abe et al. 2000; Karamanidis and Arampatzis 2006). Physiological significance of this architecture arrangement is uncertain and beyond the scope of this brief report. However, it is conceivable that increasing Af and shortening Lf suits specific demands of endurance running by allowing LG to operate under more favorable energetic conditions. Lf partly determines peak muscle contractile velocity because of summation of serial sarcomeres (Bodine et al. 1982). Indeed, crosssectional data suggests resting Lf has a rank order effect on peak running velocity (fastest sprinters > sprinters > distance runners) (Abe et al. 2000). Though short fascicles compromise peak shortening velocity, increased Af and reduced Lf may confer potential advantages for endurance activity. Specifically, shorter fascicles likely require less energy for contraction as a result of less serial contractile material (Blazevich 2006; Lichtwark and Wilson 2008) and also possess greater mechanical stiffness (length-stiffness is inversely related). Since endurance run training does not affect Achilles tendon mechanical properties (Hansen et al. 2003), more compliant tendon relative to a stiffer muscle may store more energy and augment whole-muscle power output and efficiency during running (Wilson and Lichtwark 2011). This is supported by recent reports that greater calf muscle stiffness is related to better speed-specific running economy (Dumke et al. 2010) and that training-induced alterations in triceps surae muscle-tendon unit force production accompany running economy improvements (Albracht and Arampatzis 2013), similar in magnitude to the nonsignificant change in running economy observed here (⬃3%). Finally, larger resting Af should augment fascicle rotation during concentric activity and facilitate smaller changes in Lf for any given change in muscle length (Shin et al. 2009). This would theoretically enable fascicles to work closer to optimal functional range, thereby requiring less active muscle to accomplish submaximal tasks. The strong relationship between changes in Af and submaximal blood lactate level reduction (r = 0.90) could reflect this. Whether this association is physiologically relevant or rather the result of parallel adaptions is difficult to determine, particularly considering the markedly low sample size (n = 6). Regardless, potential for cause and effect remains and this relationship should be more closely examined. Published by NRC Research Press
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Fig. 1. Pre- and post-training lateral gastrocnemius (LG) fascicle angle (A) and fascicle length (B) for experimental subjects (EXP) and control subjects (CON). Solid line represents identical values before and after training. Data points above the line of identity indicate larger values after training and vice versa for a given individual.
We did not examine mechanisms of decreased LG Lf but a possible explanation is sarcomere loss. Serial sarcomere number can change according to muscle environment in animals. Sarcomere loss using direct counting procedures has been documented in animals following chronic periods of joint immobilization with muscle in a shortened position (Tabary et al. 1972; Williams and Goldspink 1973) and following chronic electrical stimulation (Tabary et al. 1981). While not directly assessed in humans, prolonged unloading can reduce estimated Lf (de Boer et al. 2007) whereas chronic static- (Holly et al. 1980) and active-muscle lengthening can elongate fascicles (Franchi et al. 2014). Thus, reduction in LG Lf may result from sarcomere reduction in response to repetitive LG shortening that accompanies endurance run training. However, resting Lf changes in humans (including the current investigation) may at least partially be a consequence of changes in muscle stiffness relative to tendon, a potential factor that warrants future inquiry. Absence of VL architecture adaptations in the current study is surprising when contextualized with reports that chronic loading induces considerable increases in VL Lf and Ap (Blazevich et al. 2003; Butterfield et al. 2005; Franchi et al. 2014; Noorkoiv et al. 2014). However, our combined data conform with Karamanidis’ work that demonstrates differences in gastrocnemius but not VL architecture between young distance runners and nonrunners (Karamanidis and Arampatzis 2006). Furthermore, in contrast with LG, VL single-fiber function and size did not change substantially and fiber-type did not shift to a more fatigue-resistant (slow-twitch) phenotype in response to the same marathon training used here (Luden et al. 2012; Trappe et al. 2006). This points to a reciprocal relationship between cellular and architectural adaptations. Since VL thickness and Ap do not adapt to relatively low-volume cycle training (Farup et al. 2012), it could be that a more robust and targeted endurance exercise stimulus is required to induce architectural adaptation of upper leg musculature. Our results provide initial evidence that architectural characteristics of endurance athletes are not solely dictated by genetic predisposition and likely involve training adaptation. We acknowledge that skeletal muscle architectural arrangements are dynamic and manifest differently depending on joint angle, activation status, and tendon compliance. While this may limit interpretation of our data, it does appear that resting architectural measures
of predominantly linear fascicles in leg muscles (Muramatsu et al. 2002) are representative of Ap (Maganaris and Baltzopoulos 1999), fascicle curvature (Muramatsu et al. 2002), and muscle length changes occurring with contraction (Kawakami et al. 1998). Although it remains unclear to what extent changes in static LG architecture may influence whole-muscle function during prolonged running, our study demonstrates that modest marathon training induces targeted architectural adaptations. Considering that architectural factors such as muscle-fiber length can be as important as myosin heavy chain isoform composition in determining shortening velocity of a muscle (Lieber and Friden 2000), future investigations may explore how architectural plasticity (within the LG as well as other active leg muscles) with endurance exercise may occur in relation to training paradigms or genetic factors to optimize running performance.
Acknowledgements We wish to thank the subjects for participating and congratulate them for successful marathon completion.
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BRIEF COMMUNICATION Skeletal muscle architectural adaptations to marathon run training Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by Bangor University on 12/30/14 For personal use only.
Kevin Murach, Cory Greever, and Nicholas D. Luden
Abstract: We assessed lateral gastrocnemius (LG) and vastus lateralis (VL) architecture in 16 recreational runners before and after 12 weeks of marathon training. LG fascicle length decreased 10% while pennation angle increased 17% (p < 0.05). There was a significant correlation between diminished blood lactate levels and LG pennation angle change (r = 0.90). No changes were observed in VL. This is the first evidence that run training can modify skeletal muscle architectural features. Key words: exercise, pennation angle, fascicle length, structure. Résumé : On évalue l’architecture du jumeau externe (« LG ») et du vaste externe (« VL ») chez 16 coureurs par loisir avant et après 12 semaines d’entraînement pour un marathon. La longueur des faisceaux du LG diminue de 10% et l’angle de pennation augmente de 17% (p < 0,05). On observe une corrélation significative entre la diminution du taux sanguin de lactate et la variation de l’angle de pennation du LG (r = 0,90). On n’observe aucune modification dans le VL. C’est la première démonstration selon laquelle l’entraînement a` la course peut modifier les caractéristiques de l’architecture musculaire. [Traduit par la Rédaction] Mots-clés : exercice physique, angle de pennation, longueur fasciculaire, structure.
Introduction Skeletal muscle architecture is the geometrical arrangement of muscle thickness, fascicle length (Lf), and pennation angle (Ap, often represented by fascicle angle, Af), and is a chief determinant of whole-muscle function (Wickiewicz et al. 1984). Resistance training alters thickness, Ap and Lf (Blazevich et al. 2007), which demonstrates that exercise can impact muscle architecture. However, insight into possible architectural changes with run training is limited to cross-sectional data (Abe et al. 2000). Distance runners possess shorter fascicles and larger Ap in vastus lateralis (VL) and gastrocnemii compared with sprinters (Abe et al. 2000). Shorter fascicles with potentially fewer sarcomeres in series presumably require less metabolic energy upon activation (Blazevich 2006) and large resting Ap may allow fascicles to work closer to optimal force-production lengths (Shin et al. 2009). These characteristics likely promote fatigue resistance and metabolic efficiency, which would benefit endurance exercise. While architectural changes were not observed in VL with cycle training (Farup et al. 2012), whether beneficial architectural features are developed with run training in VL or lateral gastrocnemius (LG) has not been examined. The aim of this study was to test the hypothesis that marathon training will alter VL and LG architecture to resemble that previously observed in distance runners (Abe et al. 2000).
Materials and methods Subjects Sixteen experimental subjects (EXP: 10 males; 6 females) were recruited from a James Madison University (JMU) marathon preparation class. EXP (age, 20 ± 1.4 years; height, 164 ± 7 cm; body mass, 64 ± 7 kg; maximal oxygen consumption (V˙O2max), 57.7 ± 9.6 mL·kg−1·min−1) were recreational runners with no competitive or marathon running history. EXP data were from 2 separate cohorts in consecutive years (EXP1, n = 9; EXP2, n = 7). We also investigated 7 recreationally active (n = 3 male/n = 4 female) con-
trols (CON; age, 21.4 ± 1.0 years; height, 170 ± 8.3 cm; body mass, 67 ± 17 kg) from JMU. CON and EXP inclusion criteria mandated that subjects be apparently healthy, normal weight, and physically active while CON were required to maintain physical activity habits until post-testing. Informed consent approved by JMU’s Institutional Review Board was completed prior to testing. All relevant training and testing time points were consistent across groups. Experimental design VL and LG muscle architecture (thickness, Lf and Af) and cardiovascular measurements were obtained before and 12 weeks after marathon training (Trappe et al. 2006). Briefly, the 12-week, 4-days·week–1 program progressively increased volume (distance) with 24 km during week 1 (8-km–long run) and ⬃60 km during week 12 (29-km–long run), all at a self-selected pace. Treadmill testing All EXP performed incremental treadmill tests to assess aerobic capacity (V˙O2max) and submaximal oxygen consumption (V˙O2) (Luden et al. 2012). Breath samples were monitored using a VMAX Sensormedics Spectra metabolic cart (Yorba Linda, Calif., USA), with data aggregated in 30-s intervals. Treadmill procedures were similar for EXP cohorts. However, EXP2 (n = 7) underwent a 2-phase protocol to facilitate blood lactate analysis (less 1 subject posttraining because of illness). During phase 1, the treadmill was set at an individualized velocity that approximated the subject’s speed that was typically performed during a 60-min training run. Speed was incrementally increased 24–32 s·km−1 in 3-min stages (while monitoring V˙O2) followed by 1 min of rest. Resting venous blood was obtained (finger stick) and submaximal blood lactate concentrations and lactate threshold (>3.5 mmol·L−1) was determined via YSI 2300 STAT glucose/lactate analyzer (Yellow Springs, Ohio, USA). Lactate threshold was fixed at 3.5-mmol·L−1 post hoc, as this was the highest value eclipsed by all subjects. The velocity during
Received 22 July 2014. Accepted 22 September 2014. K. Murach, C. Greever, and N.D. Luden. Human Performance Laboratory, James Madison University, Harrisonburg, VA 22807, USA. Corresponding author: Nicholas D. Luden (e-mail: [email protected]). Appl. Physiol. Nutr. Metab. 40: 1–4 (2015) dx.doi.org/10.1139/apnm-2014-0287
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the penultimate stage was selected for submaximal V˙O2 comparisons before and after training. Fifteen minutes passive recovery ensued once blood lactate exceeded 3.5 mmol·L−1. Subjects then completed a 3-min walking warm-up at 5.6 km·h−1 (3.5 miles per hour). Phase 2 began at a velocity corresponding with the penultimate stage of phase 1.
mal V˙O2 (42.4 ± 6.7 vs. 41.2 ± 7.5 mL·kg−1·min−1 and 2.7 ± 0.5 vs. 2.6 ± 0.5 L·min−1). Fractional oxygen utilization during submaximal running (11.6 ± 1.0 km·h−1) was reduced with training (73.9 ± 7.2 vs. 70.6% ± 8.3% V˙O2max) (P < 0.05). Similarly, post-training blood lactate levels (2.6 ± 0.4 vs. 1.8 ± 0.5 mmol·L−1) were lower (P < 0.05) at submaximal speed (12.0 ± 1.0 km·h−1; n = 6).
Ultrasound Resting VL and LG architecture was measured in EXP and CON. Ultrasonography was performed using a Shenzen Mindray DC-6 (Nanshan, Shenzen, China) in B-mode with a linear array transducer set at 7.5 MHz. Images were captured when probe was aligned for optimal image quality (Kwah et al 2013). Insonation sites were preliminarily identified and recorded for subsequent visits using adapted methods (Kumagai et al. 2000). Briefly, for VL, subjects sat upright with a hip angle of 90° and ankle affixed at 90° using a customized Styrofoam support device. Midpoint between the bony protuberance of the femur’s greater trochanter and the prominence of the lateral femoral condyle was measured. A line from this midway point was extended mediolaterally. A second line from the patella’s lateral border was extended superiorly. Halfway along the mediolateral line represented mid-muscle belly. Images were captured after 10 min in fixed position. Subjects then moved to prone position with ankle joint affixed at 90° against a wall. At one-third the distance from the knee between the lateral femoral condyle and the lateral bony protuberance of the anklebone a line was extended mediolaterally. A line at one-quarter the distance between the lateral and medial condyle of the femur (posterior over LG) was extended inferiorly. The intersection represented mid-muscle belly and images were captured after 5 min of rest.
Skeletal muscle architecture There were no group × time interactions for VL thickness (EXP – pre-training: 2.60 ± 0.30 vs. post-training: 2.59 ± 0.29 cm; CON – 2.53 ± 0.47 vs .2.44 ± 0.43 cm), Af (EXP: 17.1 ± 3.0° vs. 16.6 ± 2.6°; CON: 16.3 ± 2.9° vs. 16.2 ± 2.6°), or Lf (EXP: 9.2 ± 2.1 vs. 9.3 ± 1.8 cm; CON: 9.2 ± 2.4 vs. 8.9 ± 1.6 cm), or for LG thickness (EXP: 1.37 ± 0.29 vs. 1.40 ± 0.36 cm; CON: 1.30 ± 0.29 vs. 1.32 ± 0.30 cm). However, group × time interactions were observed for both LG Af and Lf (P < 0.05). No changes in LG Af (12.1 ± 2.0° vs. 12.0 ± 2.0°) or Lf (6.4 ± 1.8 vs. 6.6 ± 2.1 cm) were observed in CON, but Af increased 17% (12.9 ± 3.2° vs. 15.0 ± 3.9°) (P < 0.01) and Lf decreased 10% (6.6 ± 2.7 vs. 5.9 ± 2.4 cm) in EXP (P < 0.01). There was a correlation between changes in submaximal blood lactate levels and LG Af (r = 0.90; P < 0.05). No other significant correlations were identified. EXP and CON LG Lf and Af data are displayed in Figs. 1A and 1B.
Image analysis Images were analyzed using ImageJ64 software (National Institutes of Health, USA) on a Macintosh computer. Thickness was determined by the average distance between superficial and deep aponeuroses at 3 points along the muscle belly perpendicular to the aponeuroses. Af was measured between superficial and deep aponeuroses at 3 different muscle locations (superficial, middle, and deep) and aggregated. Lf was calculated using a prediction equation (Kumagai et al. 2000). Ultrasound methods similar to those described here have been validated in reference to cadavers (Kawakami et al. 1993) and magnetic resonance images (Walton et al. 1997; Miyatani et al. 2002). Further, current values and standard deviations obtained in both muscles and groups are in line with the literature (Abe et al. 2000). The coefficient of variation (CV) for repeated measurements separated by 7 days (5 pilot subjects) were VL Af = 2.8%, thickness = 3.2%, and Lf = 5.1%; LG Af = 4.0%, thickness = 5.4%, and Lf = 8.7%. The control group also endorses the reproducibility of our measures. Statistical analysis The effects of training on skeletal muscle architecture was analyzed with 2 × 2 (time × group) repeated-measures ANOVAs. Pairwise comparisons (time × group interaction; P < 0.05) between pre- and post-training, within EXP, were analyzed using paired t tests with Bonferroni correction. Effects of training on cardiovascular physiology and blood lactate levels were assessed with paired t tests (pre- vs. post-training). Relationships between changes (raw score) in architecture and changes in V˙O2max, submaximal V˙O2, and submaximal lactate levels were calculated with Pearson correlation coefficients. All data were checked for normality and significance was set at P < 0.05. Data displayed as means ± SD.
Results Treadmill testing Training did not influence body weight (pre-training: 63.8 ± 6.6 vs. post-training: 63.3 ± 6.3 kg), V˙O2max (57.4 ± 6.6 vs. 58.6 ± 8.8 mL·kg−1·min−1 and 3.6 ± 0.5 vs. 3.7 ± 0.6 L·min−1), and submaxi-
Discussion This is the first evidence for skeletal muscle architectural adaptations to endurance run training. Increased LG Af and reduced Lf, without a change in thickness, agree with the distinct architecture of distance runners noted in previous investigations (Abe et al. 2000; Karamanidis and Arampatzis 2006). Physiological significance of this architecture arrangement is uncertain and beyond the scope of this brief report. However, it is conceivable that increasing Af and shortening Lf suits specific demands of endurance running by allowing LG to operate under more favorable energetic conditions. Lf partly determines peak muscle contractile velocity because of summation of serial sarcomeres (Bodine et al. 1982). Indeed, crosssectional data suggests resting Lf has a rank order effect on peak running velocity (fastest sprinters > sprinters > distance runners) (Abe et al. 2000). Though short fascicles compromise peak shortening velocity, increased Af and reduced Lf may confer potential advantages for endurance activity. Specifically, shorter fascicles likely require less energy for contraction as a result of less serial contractile material (Blazevich 2006; Lichtwark and Wilson 2008) and also possess greater mechanical stiffness (length-stiffness is inversely related). Since endurance run training does not affect Achilles tendon mechanical properties (Hansen et al. 2003), more compliant tendon relative to a stiffer muscle may store more energy and augment whole-muscle power output and efficiency during running (Wilson and Lichtwark 2011). This is supported by recent reports that greater calf muscle stiffness is related to better speed-specific running economy (Dumke et al. 2010) and that training-induced alterations in triceps surae muscle-tendon unit force production accompany running economy improvements (Albracht and Arampatzis 2013), similar in magnitude to the nonsignificant change in running economy observed here (⬃3%). Finally, larger resting Af should augment fascicle rotation during concentric activity and facilitate smaller changes in Lf for any given change in muscle length (Shin et al. 2009). This would theoretically enable fascicles to work closer to optimal functional range, thereby requiring less active muscle to accomplish submaximal tasks. The strong relationship between changes in Af and submaximal blood lactate level reduction (r = 0.90) could reflect this. Whether this association is physiologically relevant or rather the result of parallel adaptions is difficult to determine, particularly considering the markedly low sample size (n = 6). Regardless, potential for cause and effect remains and this relationship should be more closely examined. Published by NRC Research Press
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Fig. 1. Pre- and post-training lateral gastrocnemius (LG) fascicle angle (A) and fascicle length (B) for experimental subjects (EXP) and control subjects (CON). Solid line represents identical values before and after training. Data points above the line of identity indicate larger values after training and vice versa for a given individual.
We did not examine mechanisms of decreased LG Lf but a possible explanation is sarcomere loss. Serial sarcomere number can change according to muscle environment in animals. Sarcomere loss using direct counting procedures has been documented in animals following chronic periods of joint immobilization with muscle in a shortened position (Tabary et al. 1972; Williams and Goldspink 1973) and following chronic electrical stimulation (Tabary et al. 1981). While not directly assessed in humans, prolonged unloading can reduce estimated Lf (de Boer et al. 2007) whereas chronic static- (Holly et al. 1980) and active-muscle lengthening can elongate fascicles (Franchi et al. 2014). Thus, reduction in LG Lf may result from sarcomere reduction in response to repetitive LG shortening that accompanies endurance run training. However, resting Lf changes in humans (including the current investigation) may at least partially be a consequence of changes in muscle stiffness relative to tendon, a potential factor that warrants future inquiry. Absence of VL architecture adaptations in the current study is surprising when contextualized with reports that chronic loading induces considerable increases in VL Lf and Ap (Blazevich et al. 2003; Butterfield et al. 2005; Franchi et al. 2014; Noorkoiv et al. 2014). However, our combined data conform with Karamanidis’ work that demonstrates differences in gastrocnemius but not VL architecture between young distance runners and nonrunners (Karamanidis and Arampatzis 2006). Furthermore, in contrast with LG, VL single-fiber function and size did not change substantially and fiber-type did not shift to a more fatigue-resistant (slow-twitch) phenotype in response to the same marathon training used here (Luden et al. 2012; Trappe et al. 2006). This points to a reciprocal relationship between cellular and architectural adaptations. Since VL thickness and Ap do not adapt to relatively low-volume cycle training (Farup et al. 2012), it could be that a more robust and targeted endurance exercise stimulus is required to induce architectural adaptation of upper leg musculature. Our results provide initial evidence that architectural characteristics of endurance athletes are not solely dictated by genetic predisposition and likely involve training adaptation. We acknowledge that skeletal muscle architectural arrangements are dynamic and manifest differently depending on joint angle, activation status, and tendon compliance. While this may limit interpretation of our data, it does appear that resting architectural measures
of predominantly linear fascicles in leg muscles (Muramatsu et al. 2002) are representative of Ap (Maganaris and Baltzopoulos 1999), fascicle curvature (Muramatsu et al. 2002), and muscle length changes occurring with contraction (Kawakami et al. 1998). Although it remains unclear to what extent changes in static LG architecture may influence whole-muscle function during prolonged running, our study demonstrates that modest marathon training induces targeted architectural adaptations. Considering that architectural factors such as muscle-fiber length can be as important as myosin heavy chain isoform composition in determining shortening velocity of a muscle (Lieber and Friden 2000), future investigations may explore how architectural plasticity (within the LG as well as other active leg muscles) with endurance exercise may occur in relation to training paradigms or genetic factors to optimize running performance.
Acknowledgements We wish to thank the subjects for participating and congratulate them for successful marathon completion.
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