The effects of resistance training on denervated myofibers, senescent cells, and associated protein markers in middle-aged adults.

Denervated myofibers and senescent cells are hallmarks of skeletal muscle aging. However, sparse research has examined how resistance training affects these outcomes. We investigated the effects of unilateral leg extensor resistance training (2 days/week for 8 weeks) on denervated myofibers, senescent cells, and associated protein markers in apparently healthy middle-aged participants (MA, 55 ± 8 years old, 17 females, 9 males). We obtained dual-leg vastus lateralis (VL) muscle cross-sectional area (mCSA), VL biopsies, and strength assessments before and after training. Fiber cross-sectional area (fCSA), satellite cells (Pax7+), denervated myofibers (NCAM+), senescent cells (p16+ or p21+), proteins associated with denervation and senescence, and senescence-associated secretory phenotype (SASP) proteins were analyzed from biopsy specimens. Leg extensor peak torque increased after training (p < .001), while VL mCSA trended upward (interaction p = .082). No significant changes were observed for Type I/II fCSAs, NCAM+ myofibers, or senescent (p16+ or p21+) cells, albeit satellite cells increased after training (p = .037). While >90% satellite cells were not p16+ or p21+, most p16+ and p21+ cells were Pax7+ (>90% on average). Training altered 13 out of 46 proteins related to muscle-nerve communication (all upregulated, p < .05) and 10 out of 19 proteins related to cellular senescence (9 upregulated, p < .05). Only 1 out of 17 SASP protein increased with training (IGFBP-3, p = .031). In conclusion, resistance training upregulates proteins associated with muscle-nerve communication in MA participants but does not alter NCAM+ myofibers. Moreover, while training increased senescence-related proteins, this coincided with an increase in satellite cells but not alterations in senescent cell content or SASP proteins. These latter findings suggest shorter term resistance training is an unlikely inducer of cellular senescence in apparently healthy middle-aged participants. However, similar study designs are needed in older and diseased populations before definitive conclusions can be drawn.

The effects of a sugar-free amino acid-containing electrolyte beverage on 5-kilometer performance, blood electrolytes, and post-exercise cramping versus a conventional carbohydrate-electrolyte sports beverage and water.

OBJECTIVE: The purpose of this study was to examine the acute effects of a multi-ingredient, low calorie dietary supplement (MIDS, XTEND® Healthy Hydration) on 5-kilometer (5-km) time trial performance and blood electrolyte concentrations compared to a carbohydrate-electrolyte beverage (CE, GATORADE® Thirst Quencher) and distilled water (W). METHODS: During visit 1 (V1), participants (10 men and 10 women, 20-35 years old, BMI ≤ 29 kg/m2, recreationally active) reported to the laboratory whereby the following tests were performed: i) height and weight measurements, ii) body composition analysis, iii) treadmill testing to measure maximal aerobic capacity, and iv) 5-km time trial familiarization. The second visit (V2) was one week after V1 in the morning (0600 - 0900) and participants arrived 12-14 h fasted (no food or drink). The first battery of assessments (V2-T1) included nude body mass, urine specific gravity (USG), a profile of mood states (POMS) questionnaire, and the completion of a visual analogue scale (VAS) questionnaire to quantify cramping. Then heart rate (HR), blood pressure (BP), total body hydration (via bioelectrical impedance spectroscopy [BIS]) were examined. Finally, a measurement of blood markers via finger stick was performed. Participants consumed a randomized beverage (16 fl. oz. of MIDS, 16 fl. oz. of W, or 16 fl. oz. of CE) within 3 min followed by a 45-min rest. Following the rest period, a second battery (V2-T2) was performed whereby participants' USG was assessed and they completed the POMS and VAS questionnaires, and HR, BP, and blood markers were measured. The participants then performed a 5-km treadmill time trial. Immediately following the 5-km time trial, participants completed a third testing battery (V2-T3) that began with blood markers, HR and BP assessments, followed by nude body weight assessment, and the POMS and VAS questionnaires. After 60 min, a fourth battery (V2-T4) was performed that included HR, BP, and blood markers. After sitting quietly for another 60 min a fifth battery assessment was performed (V2-T5) that included participants' USG, POMS and VAS questionnaires, HR, BP, blood markers, and total body hydration. Visits 3 (V3) and 4 (V4) followed the same protocol except a different randomized drink (16 oz. of CE, MIDS, or W) was consumed; all of which were separated by approximately one week. RESULTS: No differences occurred between conditions for 5-km time trial completion, indirect calorimetry outcomes during 5-km time trials, USG, or nude mass measurements (p > 0.05 for all relevant statistical tests). However, blood potassium and the sodium/potassium ratio displayed significant interactions (p < 0.05), and post hoc testing indicated these values were better maintained in the MIDS versus other conditions. Post-exercise cramp prevalence was greater in the CE (p < 0.05) and trended higher with W (p = 0.083) compared to the MIDS condition. Post-exercise cramp severity was also elevated with the W and CE beverages (p < 0.05) but not the MIDS (p = 0.211). CONCLUSIONS: The MIDS did not affect 5-km time trial performance but exhibited favorable effects on blood electrolyte and post-exercise self-reporting cramp outcomes compared to the CE and W drinks.

A novel deep proteomic approach in human skeletal muscle unveils distinct molecular signatures affected by aging and resistance training.

The skeletal muscle proteome alterations to aging and resistance training have been reported in prior studies. However, conventional proteomics in skeletal muscle typically yields wide protein abundance ranges that mask the detection of lowly expressed proteins. Thus, we adopted a novel deep proteomics approach whereby myofibril (MyoF) and non-MyoF fractions were separately subjected to protein corona nanoparticle complex formation prior to digestion and Liquid Chromatography Mass Spectrometry (LC-MS). Specifically, we investigated MyoF and non-MyoF proteomic profiles of the vastus lateralis muscle of younger (Y, 22±2 years old; n=5) and middle-aged participants (MA, 56±8 years old; n=6). Additionally, MA muscle was analyzed following eight weeks of resistance training (RT, 2d/week). Across all participants, the number of non-MyoF proteins detected averaged to be 5,645±266 (range: 4,888-5,987) and the number of MyoF proteins detected averaged to be 2,611±326 (range: 1,944-3,101). Differences in the non-MyoF (8.4%) and MyoF (2.5%) proteomes were evident between age cohorts, and most differentially expressed non-MyoF proteins (447/543) were more enriched in MA versus Y. Biological processes in the non-MyoF fraction were predicted to be operative in MA versus Y including increased cellular stress, mRNA splicing, translation elongation, and ubiquitin-mediated proteolysis. RT in MA participants only altered ~0.3% of MyoF and ~1.0% of non-MyoF proteomes. In summary, aging and RT predominantly affect non-contractile proteins in skeletal muscle. Additionally, marginal proteome adaptations with RT suggest more rigorous training may stimulate more robust effects or that RT, regardless of age, subtly alters basal state skeletal muscle protein abundances.

Extracellular matrix content and remodeling markers do not differ in college-aged men classified as higher and lower responders to resistance training.

We determined if skeletal muscle extracellular matrix (ECM) content and remodeling markers adapted with resistance training or were associated with hypertrophic outcomes. Thirty-eight untrained males (21 ± 3 yr) participated in whole body resistance training (10 wk, 2 × weekly). Participants completed testing [ultrasound, peripheral quantitative computed tomography (pQCT)] and donated a vastus lateralis (VL) biopsy 1 wk before training and 72 h following the last training bout. Higher responders (HR, n = 10) and lower responders (LR, n = 10) were stratified based on a composite score considering changes in pQCT-derived mid-thigh cross-sectional area (mCSA), ultrasound-derived VL thickness, and mean fiber cross-sectional area (fCSA). In all participants, training reduced matrix metalloprotease (MMP)-14 protein (P < 0.001) and increased satellite cell abundance (P < 0.001); however, VL fascial thickness, ECM protein content per myofiber, MMP-2/-9 protein content, tissue inhibitor of metalloproteinase (TIMP)-1/-2 protein content, collagen-1/-4 protein content, macrophage abundance, or fibroadipogenic progenitor cell abundance were not altered. Regarding responder analysis, MMP-14 exhibited an interaction (P = 0.007), and post hoc analysis revealed higher protein content in HR versus LR before training (P = 0.026) and a significant decrease from pre to posttraining in HR only (P = 0.002). In summary, basal skeletal muscle ECM markers are minimally affected with 10 wk of resistance training, and these findings could be related to not capturing more dynamic alterations in the assayed markers earlier in training. However, the downregulation in MMP-14 in college-aged men classified as HR is a novel finding and warrants continued investigation, and further research is needed to delineate muscle connective tissue strength attributes between HR and LR.NEW & NOTEWORTHY Although past studies have examined aspects of extracellular matrix remodeling in relation to mechanical overload or resistance training, this study serves to expand our knowledge on a multitude of extracellular matrix markers and whether these markers adapt to resistance training or are associated with differential hypertrophic responses.

A novel deep proteomic approach in human skeletal muscle unveils distinct molecular signatures affected by aging and resistance training.

We examined the myofibrillar (MyoF) and non-myofibrillar (non-MyoF) proteomic profiles of the vastus lateralis (VL) muscle of younger (Y, 22±2 years old; n=5) and middle-aged participants (MA, 56±8 years old; n=6), and MA following eight weeks of knee extensor resistance training (RT, 2d/week). Shotgun/bottom-up proteomics in skeletal muscle typically yields wide protein abundance ranges that mask lowly expressed proteins. Thus, we adopted a novel approach whereby the MyoF and non-MyoF fractions were separately subjected to protein corona nanoparticle complex formation prior to digestion and Liquid Chromatography Mass Spectrometry (LC-MS) analysis. A total of 10,866 proteins (4,421 MyoF and 6,445 non-MyoF) were identified. Across all participants, the number of non-MyoF proteins detected averaged to be 5,645±266 (range: 4,888-5,987) and the number of MyoF proteins detected averaged to be 2,611±326 (range: 1,944-3,101). Differences in the non-MyoF (8.4%) and MyoF (2.5%) proteome were evident between age cohorts. Further, most of these age-related non-MyoF proteins (447/543) were more enriched in MA versus Y. Several biological processes in the non-MyoF fraction were predicted to be operative in MA versus Y including (but not limited to) increased cellular stress, mRNA splicing, translation elongation, and ubiquitin-mediated proteolysis. Non-MyoF proteins associated with splicing and proteostasis were further interrogated, and in agreement with bioinformatics, alternative protein variants, spliceosome-associated proteins (snRNPs), and proteolysis-related targets were more abundant in MA versus Y. RT in MA non-significantly increased VL muscle cross-sectional area (+6.5%, p=0.066) and significantly increased knee extensor strength (+8.7%, p=0.048). However, RT modestly altered the MyoF (~0.3%, 11 upregulated and two downregulated proteins) and non-MyoF proteomes (~1.0%, 56 upregulated and eight downregulated proteins, p<0.01). Further, RT did not affect predicted biological processes in either fraction. Although participant numbers were limited, these preliminary results using a novel deep proteomic approach in skeletal muscle suggest that aging and RT predominantly affects protein abundances in the non-contractile protein pool. However, the marginal proteome adaptations occurring with RT suggest either: a) this may be an aging-associated phenomenon, b) more rigorous RT may stimulate more robust effects, or c) RT, regardless of age, subtly affects skeletal muscle protein abundances in the basal state.

Resistance training in humans and mechanical overload in rodents do not elevate muscle protein lactylation.

Although several reports have hypothesized that exercise may increase skeletal muscle protein lactylation, empirical evidence in humans is lacking. Thus, we adopted a multi-faceted approach to examine if acute and subchronic resistance training (RT) altered skeletal muscle protein lactylation levels. In mice, we also sought to examine if surgical ablation-induced plantaris hypertrophy coincided with increases in muscle protein lactylation. To examine acute responses, participants' blood lactate concentrations were assessed before, during, and after eight sets of an exhaustive lower body RT bout (n = 10 trained college-aged men). Vastus lateralis biopsies were also taken before, 3-h post, and 6-h post-exercise to assess muscle protein lactylation. To identify training responses, another cohort of trained college-aged men (n = 14) partook in 6 weeks of lower-body RT (3x/week) and biopsies were obtained before and following the intervention. Five-month-old C57BL/6 mice were subjected to 10 days of plantaris overload (OV, n = 8) or served as age-matched sham surgery controls (Sham, n = 8). Although acute resistance training significantly increased blood lactate responses ∼7.2-fold (p < 0.001), cytoplasmic and nuclear protein lactylation levels were not significantly altered at the post-exercise time points, and no putative lactylation-dependent mRNA was altered following exercise. Six weeks of RT did not alter cytoplasmic protein lactylation (p = 0.800) despite significantly increasing VL muscle size (+3.5%, p = 0.037), and again, no putative lactylation-dependent mRNA was significantly affected by training. Plantaris muscles were larger in OV versus Sham mice (+43.7%, p < 0.001). However, cytoplasmic protein lactylation was similar between groups (p = 0.369), and nuclear protein lactylation was significantly lower in OV versus Sham mice (p < 0.001). The current null findings, along with other recent null findings in the literature, challenge the thesis that lactate has an appreciable role in promoting skeletal muscle hypertrophy.

The effects of resistance training to near failure on strength, hypertrophy, and motor unit adaptations in previously trained adults.

Limited research exists examining how resistance training to failure affects applied outcomes and single motor unit characteristics in previously trained individuals. Herein, resistance-trained adults (24 ± 3 years old, self-reported resistance training experience was 6 ± 4 years, 11 men and 8 women) were randomly assigned to either a low-repetitions-in-reserve (RIR; i.e., training near failure, n = 10) or high-RIR (i.e., not training near failure, n = 9) group. All participants implemented progressive overload during 5 weeks where low-RIR performed squat, bench press, and deadlift twice weekly and were instructed to end each training set with 0-1 RIR. high-RIR performed identical training except for being instructed to maintain 4-6 RIR after each set. During week 6, participants performed a reduced volume-load. The following were assessed prior to and following the intervention: (i) vastus lateralis (VL) muscle cross-sectional area (mCSA) at multiple sites; (ii) squat, bench press, and deadlift one-repetition maximums (1RMs); and (iii) maximal isometric knee extensor torque and VL motor unit firing rates during an 80% maximal voluntary contraction. Although RIR was lower in the low- versus high-RIR group during the intervention (p < 0.001), total training volume did not significantly differ between groups (p = 0.222). There were main effects of time for squat, bench press, and deadlift 1RMs (all p-values < 0.05), but no significant condition × time interactions existed for these or proximal/middle/distal VL mCSA data. There were significant interactions for the slope and y-intercept of the motor unit mean firing rate versus recruitment threshold relationship. Post hoc analyses indicated low-RIR group slope values decreased and y-intercept values increased after training suggesting low-RIR training increased lower-threshold motor unit firing rates. This study provides insight into how resistance training in proximity to failure affects strength, hypertrophy, and single motor unit characteristics, and may inform those who aim to program for resistance-trained individuals.

Skeletal Muscle DNA Methylation and mRNA Responses to a Bout of Higher versus Lower Load Resistance Exercise in Previously Trained Men.

We sought to determine the skeletal muscle genome-wide DNA methylation and mRNA responses to one bout of lower load (LL) versus higher load (HL) resistance exercise. Trained college-aged males (n = 11, 23 ± 4 years old, 4 ± 3 years self-reported training) performed LL or HL bouts to failure separated by one week. The HL bout (i.e., 80 Fail) consisted of four sets of back squats and four sets of leg extensions to failure using 80% of participants estimated one-repetition maximum (i.e., est. 1-RM). The LL bout (i.e., 30 Fail) implemented the same paradigm with 30% of est. 1-RM. Vastus lateralis muscle biopsies were collected before, 3 h, and 6 h after each bout. Muscle DNA and RNA were batch-isolated and analyzed using the 850k Illumina MethylationEPIC array and Clariom S mRNA microarray, respectively. Performed repetitions were significantly greater during the 30 Fail versus 80 Fail (p < 0.001), although total training volume (sets × reps × load) was not significantly different between bouts (p = 0.571). Regardless of bout, more CpG site methylation changes were observed at 3 h versus 6 h post exercise (239,951 versus 12,419, respectively; p < 0.01), and nuclear global ten-eleven translocation (TET) activity, but not global DNA methyltransferase activity, increased 3 h and 6 h following exercise regardless of bout. The percentage of genes significantly altered at the mRNA level that demonstrated opposite DNA methylation patterns was greater 3 h versus 6 h following exercise (~75% versus ~15%, respectively). Moreover, high percentages of genes that were up- or downregulated 6 h following exercise also demonstrated significantly inversed DNA methylation patterns across one or more CpG sites 3 h following exercise (65% and 82%, respectively). While 30 Fail decreased DNA methylation across various promoter regions versus 80 Fail, transcriptome-wide mRNA and bioinformatics indicated that gene expression signatures were largely similar between bouts. Bioinformatics overlay of DNA methylation and mRNA expression data indicated that genes related to "Focal adhesion," "MAPK signaling," and "PI3K-Akt signaling" were significantly affected at the 3 h and 6 h time points, and again this was regardless of bout. In conclusion, extensive molecular profiling suggests that post-exercise alterations in the skeletal muscle DNA methylome and mRNA transcriptome elicited by LL and HL training bouts to failure are largely similar, and this could be related to equal volumes performed between bouts.

Hip thrust and back squat training elicit similar gluteus muscle hypertrophy and transfer similarly to the deadlift.

Purpose: We examined how set-volume equated resistance training using either the back squat (SQ) or hip thrust (HT) affected hypertrophy and various strength outcomes. Methods: Untrained college-aged participants were randomized into HT or SQ groups. Surface electromyograms (sEMG) from the right gluteus maximus and medius muscles were obtained during the first training session. Participants completed nine weeks of supervised training (15-17 sessions), before and after which we assessed muscle cross-sectional area (mCSA) via magnetic resonance imaging and strength via three-repetition maximum (3RM) testing and an isometric wall push test. Results: Glutei mCSA growth was similar across both groups. Estimates [(-) favors HT; (+) favors SQ] modestly favored the HT compared to SQ for lower [effect ± SE, -1.6 ± 2.1 cm2], mid [-0.5± 1.7 cm2], and upper [-0.5 ± 2.6 cm2], but with appreciable variance. Gluteus medius+minimus [-1.8 ± 1.5 cm2] and hamstrings [0.1 ± 0.6 cm2] mCSA demonstrated little to no growth with small differences between groups. Thigh mCSA changes were greater in SQ for the quadriceps [3.6 ± 1.5 cm2] and adductors [2.5 ± 0.7 cm2]. Squat 3RM increases favored SQ [14 ± 2.5 kg] and hip thrust 3RM favored HT [-26 ± 5 kg]. 3RM deadlift [0 ± 2 kg] and wall push strength [-7 ± 13 N] similarly improved. All measured gluteal sites showed greater mean sEMG amplitudes during the first bout hip thrust versus squat set, but this did not consistently predict gluteal hypertrophy outcomes. Conclusion: Nine weeks of squat versus hip thrust training elicited similar gluteal hypertrophy, greater thigh hypertrophy in SQ, strength increases that favored exercise allocation, and similar strength transfers to the deadlift and wall push.

Hip thrust and back squat training elicit similar gluteus muscle hypertrophy and transfer similarly to the deadlift.

We examined how set-volume equated resistance training using either the back squat (SQ) or hip thrust (HT) affected hypertrophy and various strength outcomes. Untrained college-aged participants were randomized into HT (n = 18) or SQ (n = 16) groups. Surface electromyograms (sEMG) from the right gluteus maximus and medius muscles were obtained during the first training session. Participants completed 9 weeks of supervised training (15-17 sessions), before and after which gluteus and leg muscle cross-sectional area (mCSA) was assessed via magnetic resonance imaging. Strength was also assessed prior to and after the training intervention via three-repetition maximum (3RM) testing and an isometric wall push test. Gluteus mCSA increases were similar across both groups. Specifically, estimates [(-) favors HT (+) favors SQ] modestly favored the HT versus SQ for lower [effect ±SE, -1.6 ± 2.1 cm2; CI95% (-6.1, 2.0)], mid [-0.5 ± 1.7 cm2; CI95% (-4.0, 2.6)], and upper [-0.5 ± 2.6 cm2; CI95% (-5.8, 4.1)] gluteal mCSAs but with appreciable variance. Gluteus medius + minimus [-1.8 ± 1.5 cm2; CI95% (-4.6, 1.4)] and hamstrings [0.1 ± 0.6 cm2; CI95% (-0.9, 1.4)] mCSA demonstrated little to no growth with small differences between groups. mCSA changes were greater in SQ for the quadriceps [3.6 ± 1.5 cm2; CI95% (0.7, 6.4)] and adductors [2.5 ± 0.7 cm2; CI95% (1.2, 3.9)]. Squat 3RM increases favored SQ [14 ± 2 kg; CI95% (9, 18),] and hip thrust 3RM favored HT [-26 ± 5 kg; CI95% (-34, -16)]. 3RM deadlift [0 ± 2 kg; CI95% (-4, 3)] and wall push strength [-7 ± 12N; CI95% (-32, 17)] similarly improved. All measured gluteal sites showed greater mean sEMG amplitudes during the first bout hip thrust versus squat set, but this did not consistently predict gluteal hypertrophy outcomes. Squat and hip thrust training elicited similar gluteal hypertrophy, greater thigh hypertrophy in SQ, strength increases that favored exercise allocation, and similar deadlift and wall push strength increases.

Antidepressant treatment in bipolar versus unipolar depression.

OBJECTIVE: Antidepressant responses were compared in DSM-IV bipolar and unipolar depression. METHOD: The authors analyzed clinical records for outcomes of antidepressant trials for 41 patients with bipolar depression and 37 with unipolar depression, similar in age and sex distribution. RESULTS: Short-term nonresponse was more frequent in bipolar (51.3%) than unipolar (31.6%) depression. Manic switching occurred only in bipolar depression but happened less in patients taking mood stabilizers (31.6% versus 84.2%). Cycle acceleration occurred only in bipolar depression (25.6%), with new rapid cycling in 32.1%. Late response loss (tolerance) was 3.4 times as frequent, and withdrawal relapse into depression was 4.7 times less frequent, in bipolar as in unipolar depression. Mood stabilizers did not prevent cycle acceleration, rapid cycling, or response loss. Modern antidepressants, in general, did not have lower rates of negative outcomes than tricyclic antidepressants. CONCLUSIONS: The findings suggest an unfavorable cost/benefit ratio for antidepressant treatment of bipolar depression.

Bipolar spectrum disorder: a pilot study.

OBJECTIVE: To assess depressive features of a proposed definition of bipolar spectrum disorder (BSD). METHODS: Thirty-six patients with bipolar disorder type I or II were compared to 37 patients with unipolar major depressive disorder through patient interview and chart review. RESULTS: Univariate analysis suggests that 7 of 12 (recurrent major depressive episodes, brief major depressive episodes, atypical depressive symptoms, early age of onset, family history of bipolar disorder, antidepressant tolerance, and antidepressant-induced mania) features of major depressive episodes were more likely to occur in bipolar versus unipolar patients. After adjustment in a multivariable regression model, however, the five most powerful predictors of bipolar disorder were brief major depressive episodes, early age of onset, antidepressant- induced mania, postpartum depression, and atypical depressive symptoms. CONCLUSIONS: This preliminary study supports the idea that bipolar disorder is characterized by some depressive features less likely to be found in unipolar depression. Further prospective study needs to be conducted comparing BSD with unipolar depression.