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Human muscle fibers are generally classified by myosin heavy chain (MHC) isoforms characterized by slow to fast contractile speeds. Type I, or slow-twitch fibers, are seen in high abundance in elite endurance athletes, such as long-distance runners and cyclists. Alternatively, fast-twitch IIa and IIx fibers are abundant in elite power athletes, such as weightlifters and sprinters. While cross-sectional comparisons have shown marked differences between athletes, longitudinal data have not clearly converged on patterns in fiber type shifts over time, particularly between slow and fast fibers. However, not all fiber type identification techniques are created equal and, thus, may limit interpretation. Hybrid fibers, which express more than one MHC type (I/IIa, IIa/IIx, I/IIa/IIx), may make up a significant proportion of fibers. The measurement of the distribution of fibers would necessitate the ability to identify hybrid fibers, which is best done through single fiber analysis. Current evidence using the most appropriate techniques suggests a clear ability of fibers to shift between hybrid and pure fibers as well as between slow and fast fiber types. The context and extent to which this occurs, along with the limitations of current evidence, are discussed herein.

Here, Taber et al discuss the relationship between training-induced increases in muscle size (i.e., hypertrophy) and changes in strength. Recently, Buckner et al and Hornsby et al debated the contribution of hypertrophy to strength and the role hypertrophy plays in sports performance; however, this is not a new discussion. The exact contribution of hypertrophy to strength remains to be determined; yet, we feel certain considerations can provide clarity for future work. To provide these considerations, we begin by operationally defining both hypertrophy and strength. Thereafter, they address the strength-hypertrophy relationship through: (1) epistemological and statistical considerations, (2) molecular, mechanical, and single-fiber bases, and (3) exemplary training studies. They have presented theoretical and longitudinal evidence that strength acquisition in the long term is enhanced by hypertrophy. They have provided evidence that mechanical and molecular factors support the hypothesis that hypertrophy enhances strength.

We sought to identify biomarkers which delineated individual hypertrophic responses to resistance training. Untrained, college-aged males engaged in full-body resistance training (3 d/wk) for 12 weeks. Body composition via dual x-ray absorptiometry (DXA), vastus lateralis (VL) thickness via ultrasound, blood, VL muscle biopsies, and three-repetition maximum (3-RM) squat strength were obtained prior to (PRE) and following (POST) 12 weeks of training. K-means cluster analysis based on VL thickness changes identified LOW [n = 17; change (mean±SD) = +0.11±0.14 cm], modest (MOD; n = 29, +0.40±0.06 cm), and high (HI; n = 21, +0.69±0.14 cm) responders. Biomarkers related to histology, ribosome biogenesis, proteolysis, inflammation, and androgen signaling were analyzed between clusters. There were main effects of time (POST>PRE, p<0.05) but no cluster×time interactions for increases in DXA lean body mass, type I and II muscle fiber cross sectional area and myonuclear number, satellite cell number, and macronutrients consumed. Interestingly, PRE VL thickness was ~12% greater in LOW versus HI (p = 0.021), despite POST values being ~12% greater in HI versus LOW (p = 0.006). However there was only a weak correlation between PRE VL thickness scores and change in VL thickness (r2 = 0.114, p = 0.005). Forced post hoc analysis indicated that muscle total RNA levels (i.e., ribosome density) did not significantly increase in the LOW cluster (351±70 ng/mg to 380±62, p = 0.253), but increased in the MOD (369±115 to 429±92, p = 0.009) and HI clusters (356±77 to 470±134, p<0.001; POST HI>POST LOW, p = 0.013). Nonetheless, there was only a weak association between change in muscle total RNA and VL thickness (r2 = 0.079, p = 0.026). IL-1β mRNA levels decreased in the MOD and HI clusters following training (p<0.05), although associations between this marker and VL thickness changes were not significant (r2 = 0.0002, p = 0.919). In conclusion, individuals with lower pre-training VL thickness values and greater increases muscle total RNA levels following 12 weeks of resistance training experienced greater VL muscle growth, although these biomarkers individually explained only ~8-11% of the variance in hypertrophy.

Cellular adaptations that occur during skeletal muscle hypertrophy in response to high-volume resistance training are not well-characterized. Therefore, we sought to explore how actin, myosin, sarcoplasmic protein, mitochondrial, and glycogen concentrations were altered in individuals that exhibited mean skeletal muscle fiber cross-sectional area (fCSA) hypertrophy following 6 weeks of high-volume resistance training. Thirty previously resistance-trained, college-aged males (mean ± standard deviation: 21±2 years, 5±3 training years) had vastus lateralis (VL) muscle biopsies obtained prior to training (PRE), at week 3 (W3), and at week 6 (W6). Muscle tissue from 15 subjects exhibiting PRE to W6 VL mean fCSA increases ranging from 320-1600 μm2 was further interrogated using various biochemical and histological assays as well as proteomic analysis. Seven of these individuals donated a VL biopsy after refraining from training 8 days following the last training session (W7) to determine how deloading affected biomarkers. The 15 fCSA hypertrophic responders experienced a +23% increase in mean fCSA from PRE to W6 (p<0.001) and, while muscle glycogen concentrations remained unaltered, citrate synthase activity levels decreased by 24% (p<0.001) suggesting mitochondrial volume decreased. Interestingly, repeated measures ANOVAs indicated that p-values approached statistical significance for both myosin and actin (p = 0.052 and p = 0.055, respectively), and forced post hoc tests indicated concentrations for both proteins decreased ~30% from PRE to W6 (p<0.05 for each target). Phalloidin-actin staining similarly revealed actin concentrations per fiber decreased from PRE to W6. Proteomic analysis of the sarcoplasmic fraction from PRE to W6 indicated 40 proteins were up-regulated (p<0.05), KEGG analysis indicated that the glycolysis/gluconeogenesis pathway was upregulated (FDR sig. <0.001), and DAVID indicated that the following functionally-annotated pathways were upregulated (FDR value <0.05): a) glycolysis (8 proteins), b) acetylation (23 proteins), c) gluconeogenesis (5 proteins) and d) cytoplasm (20 proteins). At W7, sarcoplasmic protein concentrations remained higher than PRE (+66%, p<0.05), and both actin and myosin concentrations remained lower than PRE (~-50%, p<0.05). These data suggest that short-term high-volume resistance training may: a) reduce muscle fiber actin and myosin protein concentrations in spite of increasing fCSA, and b) promote sarcoplasmic expansion coincident with a coordinated up-regulation of sarcoplasmic proteins involved in glycolysis and other metabolic processes related to ATP generation. Interestingly, these effects seem to persist up to 8 days following training.

We sought to compare the effects of external pneumatic compression (EPC) and sham when used concurrently with resistance training on performance-related outcomes and molecular measures related to recovery. Twenty (N = 20) resistance-trained male participants (aged 21.6±2.4 years) were randomized to balanced sham or EPC intervention groups. The protocol consisted of 3 consecutive days of heavy, voluminous back squat exercise followed by EPC/sham treatment (Days2-4) and 3 consecutive days of recovery (Days5-7) with EPC/sham only on Days5-6. On Day1 (PRE), and Days3-7, venipuncture, flexibility and pressure-to-pain threshold (PPT) measures were performed. Vastsus lateralis muscle tissue was biopsied at PRE, 1-h post-EPC/sham treatment on Day2 (POST1) and 24-h post-EPC/sham treatment on Day7 (POST2). Isokinetic peak torque was assessed at PRE and POST2. Peak isokinetic strength did not change from PRE to POST2 in either group. The PPT was significantly lower on Days3-6 with sham, indicating greater muscle soreness, though this was largely abolished in the EPC group. A significant decrease in flexibility with sham was observed on Day3 (+16.2±4.6% knee joint angle; P<0.01) whereas there was no change with EPC (+2.8±3.8%; P>0.01). Vastus lateralis poly-ubiquitinated proteins significantly increased at the POST2 time point relative to PRE with sham (+66.6±24.6%; P<0.025) and were significantly greater (P<0.025) than those observed with EPC at the same time point (-18.6±8.5%). 4-hydroxynonenal values were significantly lower at POST2 relative to PRE with EPC (-16.2±5.6%; P<0.025) and were significantly lower (P<0.025) than those observed with sham at the same time point (+11.8±5.9%). EPC mitigated a reduction in flexibility and PPT that occurred with sham. Moreover, EPC reduced select skeletal muscle oxidative stress and proteolysis markers during recovery from heavy resistance exercise.

We sought to examine how 12 weeks of resistance exercise training (RET) affected skeletal muscle myofibrillar and sarcoplasmic protein levels along with markers of mitochondrial physiology in high versus low anabolic responders. Untrained college-aged males were classified as anabolic responders in the top 25th percentile (high-response cluster (HI); = 13, dual x-ray absorptiometry total body muscle mass change (Δ) = +3.1 ± 0.3 kg, Δ vastus lateralis (VL) thickness = +0.59 ± 0.05 cm, Δ muscle fiber cross sectional area = +1,426 ± 253 μm ) and bottom 25th percentile (low-response cluster (LO); = 12, +1.1 ± 0.2 kg, +0.24 ± 0.07 cm, +5 ± 209 μm ; < 0.001 for all Δ scores compared to HI). VL muscle prior to (PRE) and following RET (POST) was assayed for myofibrillar and sarcoplasmic protein concentrations, myosin and actin protein content, and markers of mitochondrial volume. Proteins related to myofibril formation, as well as whole lysate PGC1-α protein levels were assessed. Main effects of cluster (HI > LO, = 0.018, Cohen's = 0.737) and time (PRE > POST, = 0.037, Cohen's = -0.589) were observed for citrate synthase activity, although no significant interaction existed (LO PRE = 1.35 ± 0.07 mM/min/mg protein, LO POST = 1.12 ± 0.06, HI PRE = 1.53 ± 0.11, HI POST = 1.39 ± 0.10). POST myofibrillar myozenin-1 protein levels were up-regulated in the LO cluster (LO PRE = 0.96 ± 0.13 relative expression units, LO POST = 1.25 ± 0.16, HI PRE = 1.00 ± 0.11, HI POST = 0.85 ± 0.12; within-group LO increase = 0.025, Cohen's = 0.691). No interactions or main effects existed for other assayed markers. Our data suggest myofibrillar or sarcoplasmic protein concentrations do not differ between HI versus LO anabolic responders prior to or following a 12-week RET program. Greater mitochondrial volume in HI responders may have facilitated greater anabolism, and myofibril myozenin-1 protein levels may represent a biomarker that differentiates anabolic responses to RET. However, mechanistic research validating these hypotheses is needed.

Resistance training generally increases skeletal muscle hypertrophy, whereas aging is associated with a loss in muscle mass. Interestingly, select studies suggest that aging, as well as resistance training, may lead to a reduction in the abundance of skeletal muscle myofibrillar (or contractile) protein (per mg tissue). Proteomic interrogations have also demonstrated that aging, as well as weeks to months of resistance training, lead to appreciable alterations in the muscle proteome. Given this evidence, the purpose of this small pilot study was to examine total myofibrillar as well as total sarcoplasmic protein concentrations (per mg wet muscle) from the vastus lateralis muscle of males who were younger and resistance-trained (denoted as YT, n = 6, 25 ± 4 years old, 10 ± 3 self-reported years of training), younger and untrained (denoted as YU, n = 6, 21 ± 1 years old), and older and untrained (denoted as OU, n = 6, 62 ± 8 years old). The relative abundances of actin and myosin heavy chain (per mg tissue) were also examined using SDS-PAGE and Coomassie staining, and shotgun proteomics was used to interrogate the abundances of individual sarcoplasmic and myofibrillar proteins between cohorts. Whole-body fat-free mass (YT > YU = OU), VL thickness (YT > YU = OU), and leg extensor peak torque (YT > YU = OU) differed between groups (p < 0.05). Total myofibrillar protein concentrations were greater in YT versus OU (p = 0.005), but were not different between YT versus YU (p = 0.325). The abundances of actin and myosin heavy chain were greater in YT versus YU (p < 0.05) and OU (p < 0.001). Total sarcoplasmic protein concentrations were not different between groups. While proteomics indicated that marginal differences existed for individual myofibrillar and sarcoplasmic proteins between YT versus other groups, age-related differences were more prominent for myofibrillar proteins (YT = YU > OU, p < 0.05: 7 proteins; OU > YT = YU, p < 0.05: 11 proteins) and sarcoplasmic proteins (YT = YU > OU, p < 0.05: 8 proteins; OU > YT&YU, p < 0.05: 29 proteins). In summary, our data suggest that modest (~9%) myofibrillar protein packing (on a per mg muscle basis) was evident in the YT group. This study also provides further evidence to suggest that notable skeletal muscle proteome differences exist between younger and older humans. However, given that our n-sizes are low, these results only provide a preliminary phenotyping of the reported protein and proteomic variables.

The sequence of a meal's macronutrient consumption influences postprandial blood glucose, but it is unknown whether altering the order of macronutrient consumption before exercise affects glycemic and metabolic responses during exercise. Randomized controlled crossover trial. Physically active adults who self-reported being free of cardiometabolic disease (n = 18; 8 male, 10 female) fasted for ≥8 h and were randomized to a rice-first or rice-last condition for one visit and the opposite for a second visit. Participants were asked to consume 150 g broccoli and 100 g chicken combined and 150 g rice on its own. Post-meal, participants rested for 60 min before a 30-min run at 70 % of maximum heart rate. Blood glucose and respiratory exchange data were measured regularly during rest and exercise. There was a condition × time interaction for blood glucose (p < .001), with higher levels for rice-first than rice-last 30 min after eating (133 ± 20 vs. 106 ± 21; p < .001). Rice-first led to a larger reduction in blood glucose than rice-last from pre- to post-exercise (21.4 ± 22.1 vs. 4.6 ± 23.5 mg/dL; p = .035). There was a condition × time interaction for respiratory exchange ratio at rest (p < .001), with 5–6 % higher values with rice-first than rice-last from 40 to 55 min postprandial. During exercise, respiratory exchange ratio was approximately 2.5 % higher with rice-first than rice-last (p = .029). A rice-first meal pattern elicited a higher postprandial blood glucose shortly after eating and a larger blood glucose drop during exercise. Further, it led to a greater rise in respiratory exchange ratio at rest, which was maintained during exercise.

Background We sought to determine if a pre-workout supplement (PWS), containing multiple ingredients thought to enhance blood flow, increases hyperemia associated with resistance training compared to placebo (PBO). Given the potential interaction with training loads/time-under-tension, we evaluated the hyperemic response at two different loads to failure. Methods Thirty males participated in this double-blinded study. At visit 1, participants were randomly assigned to consume PWS (Reckless™) or PBO (maltodextrin and glycine) and performed four sets of leg extensions to failure at 30% or 80% of their 1-RM 45-min thereafter. 1-wk. later (visit 2), participants consumed the same supplement as before, but exercised at the alternate load. Heart rate (HR), blood pressure (BP), femoral artery blood flow, and plasma nitrate/nitrite (NOx) were assessed at baseline (BL), 45-min post-PWS/PBO consumption (PRE), and 5-min following the last set of leg extensions (POST). Vastus lateralis near infrared spectroscopy (NIRS) was employed during leg extension exercise. Repeated measures ANOVAs were performed with time, supplement, and load as independent variables and Bonferroni correction applied for multiple post-hoc comparisons. Data are reported as mean ± SD. Results With the 30% training load compared to 80%, significantly more repetitions were performed ( p  < 0.05), but there was no difference in total volume load ( p  > 0.05). NIRS derived minimum oxygenated hemoglobin (O 2 Hb) was lower in the 80% load condition compared to 30% for all rest intervals between sets of exercise ( p  < 0.0167). HR and BP did not vary as a function of supplement or load. Femoral artery blood flow at POST was higher independent of exercise load and treatment. However, a time*supplement*load interaction was observed revealing greater femoral artery blood flow with PWS compared to PBO at POST in the 80% (+56.8%; p  = 0.006) but not 30% load condition (+12.7%; p  = 0.476). Plasma NOx was ~3-fold higher with PWS compared to PBO at PRE and POST ( p  < 0.001). Conclusions Compared to PBO, the PWS consumed herein augmented hyperemia following multiple sets to failure at 80% of 1-RM, but not 30%. This specificity may be a product of interaction with local perturbations (e.g., reduced tissue oxygenation levels [minimum O 2 Hb] in the 80% load condition) and/or muscle fiber recruitment.

Background: We examined the acute effect of a red spinach extract (RSE) (1000 mg dose; ~90 mg nitrate (NO 3 − )) on performance markers during graded exercise testing (GXT). Methods: For this randomized, double-blind, placebo (PBO)-controlled, crossover study, 15 recreationally-active participants (aged 23.1 ± 3.3 years; BMI: 27.2 ± 3.7 kg/m2) reported >2 h post-prandial and performed GXT 65–75 min post-RSE or PBO ingestion. Blood samples were collected at baseline (BL), pre-GXT (65–75 min post-ingestion; PRE), and immediately post-GXT (POST). GXT commenced with continuous analysis of expired gases. Results: Plasma concentrations of NO 3 − increased PRE (+447 ± 294%; p < 0.001) and POST (+378 ± 179%; p < 0.001) GXT with RSE, but not with PBO (+3 ± 26%, −8 ± 24%, respectively; p > 0.05). No effect on circulating nitrite (NO 2 − ) was observed with RSE (+3.3 ± 7.5%, +7.7 ± 11.8% PRE and POST, respectively; p > 0.05) or PBO (−0.5 ± 7.9%, −0.2 ± 8.1% PRE and POST, respectively; p > 0.05). When compared to PBO, there was a moderate effect of RSE on plasma NO 2 − at PRE (g = 0.50 [−0.26, 1.24] and POST g = 0.71 [−0.05, 1.48]). During GXT, VO2 at the ventilatory threshold was significantly higher with RSE compared to PBO (+6.1 ± 7.3%; p < 0.05), though time-to-exhaustion (−4.0 ± 7.7%; p > 0.05) and maximal aerobic power (i.e., VO2 peak; −0.8 ± 5.6%; p > 0.05) were non-significantly lower with RSE. Conclusions: RSE as a nutritional supplement may elicit an ergogenic response by delaying the ventilatory threshold.