Explore the vast range of titles available.

Concurrent resistance and endurance exercise training (CET) has well‐studied benefits; however, inherent hormonal and genetic differences alter adaptive responses to exercise between sexes. Extracellular vesicles (EVs) are factors that contribute to adaptive signaling. Our purpose was to test if EV characteristics differ between men and women following CET. 18 young healthy participants underwent 12‐weeks of CET. Prior to and following CET, subjects performed an acute bout of heavy resistance exercise (AHRET) consisting of 6 × 10 back squats at 75% 1RM. At rest and following AHRET, EVs were isolated from plasma and characteristics and miRNA contents were analyzed. AHRET elevated EV abundance in trained men only (+51%) and AHRET‐induced changes were observed for muscle‐derived EVs and microvesicles. There were considerable sex‐specific effects of CET on EV miRNAs, highlighted by larger variation following the 12‐week program in men compared to women at rest. Pathway analysis based on differentially expressed EV miRNAs predicted that AHRET and 12 weeks of CET in men positively regulates hypertrophy and growth pathways more so than in women. This report highlights sex‐based differences in the EV response to resistance and concurrent exercise training and suggests that EVs may be important adaptive signaling factors altered by exercise training.

Extracellular vesicles (EVs) transport biological content between cells to mediate physiological processes. The association between EVs and resilience, the ability to cope with stress, is unknown. Using unbiased machine learning approaches, we aimed to identify a biological profile of resilience. Twenty servicemen (27.8 ± 5.9 years) completed the Connor Davidson Resilience (CD‐RISC) questionnaire and were exposed to daily physical and cognitive exertion with 48‐hr sleep and caloric restriction. Blood samples from baseline and the second day of stress were analyzed for neuroendocrine biomarkers impacted by military stress. EVs were isolated from plasma and stained with antibodies associated with exosomes (CD63), microvesicles (VAMP3), and apoptotic bodies (THSD1). Individuals were separated into high (n = 10, CD‐RISC > 90) and low (n = 10, CD‐RISC < 79) resilience. EV features were stratified by size, then down‐selected using regression trees and compared between groups. Diagnostic accuracy was assessed using receiver operating characteristic curves. Compared to low resilience, high resilience demonstrated a greater increase in variability of THSD1 local bright spot intensities among large‐sized EVs in response to stress (p = 0.002, Hedges’ g = 1.59). Among medium‐sized EVs, high resilience exhibited a greater decrease in side scatter intensity (p = 0.014, Hedges’ g = 1.17). Both features demonstrated high to moderate diagnostic accuracy for high resilience (AUC = 0.90 and 0.79). In contrast, neuroendocrine biomarker concentrations were similar between groups. The increase in variability among THSD1 + EVs in high, but not low, resilient individuals following stress may suggest high resilience is accompanied by stress‐triggered apoptotic adaptations to the environment that are not detected in neuroendocrine biomarkers. Individuals with high self‐report resilience demonstrated extracellular vesicle adaptations during a multifactorial stress environment that were not observed in low‐resilient individuals. Extracellular vesicles may be more sensitive than circulating neuroendocrine biomarkers, as no differences were observed between groups at the hormone/peptide level.

The purpose of this study was to determine the difference between estimated energy expenditure (EE) and self-reported dietary intake (EI), and factors associated with energy balance in deployed U.S. Army Special Operations Forces (SOF) Soldiers. Methods: Forty-six SOF Soldiers (age: 30.1 ± 3.5 yrs, body mass index: 27.7 ± 4.1 kg/m2) completed surveys on demographic data, mission activity characteristics, gastrointestinal issues, ration consumption, resilience, mood state, and dietary intake using a 127-question food frequency questionnaire at the end of a six-month deployment. EE was estimated using a SOF-specific prediction equation with a physical activity factor of 2.1. A paired t-test compared reported energy intake (EI) with estimated energy expenditure (EE). Pearson correlations identified significant variables associated with energy balance, which were then incorporated into a multiple linear regression model. The regression analysis included Profile of Mood States (POMS) anger and POMS depression as predictor variables to determine their influence on energy balance. Results: Reported mean EI was 2512 ± 1059 kcal·d−1, while estimated mean EE was 5272 ± 525 kcal·d−1. The mean energy imbalance was −2854 kcal/d (95% CI: −2655 to −3055, p < 0.001), with all participants in negative energy balance (range: −492 to −3813 kcal/d). POMS depression (r = 0.517, p < 0.01) and POMS anger (r = 0.363, p = 0.020) were associated with energy balance. The regression model was significant (R2 = 0.23, F (2, 38) = 7.02, p < 0.01), with POMS depression significantly predicting energy balance (β = 50.76, p = 0.011). Conclusions: Deployed SOF Soldiers reported high EE and limited EI, which may negatively impact performance. Higher POMS depression scores were associated with lower energy deficits. Future studies should investigate the relationship between mood and energy balance, using direct measures of EI and EE.

Technologies supporting the continuous, real-time measurement of blood oxygen saturation and plasma glucose levels have improved our ability to monitor performance status. Our ability to monitor other molecular markers of performance, however, including the hormones known to indicate overtraining and general health, has lagged. That is, although a number of other molecular markers of performance status have been identified, we have struggled to develop viable technologies supporting their real-time monitoring in the body. Here we review biosensor approaches that may support such measurements, as well as the molecules potentially of greatest interest to monitor. Narrative literature review. Literature review. Significant effort has been made to harness the specificity, affinity, and generalizability of biomolecular recognition in a platform technology supporting continuous in vivo molecular measurements. Most biosensor approaches, however, are either not generalizable to most targets, or fail when challenged in the complex environments found in vivo. Electrochemical aptamer-based sensors, in contrast, are the first technology to simultaneously achieve both of these critical attributes. In an effort to illustrate the potential of this platform technology, we both critically review the literature describing it and briefly survey some of the molecular performance markers we believe will prove advantageous to monitor using it. Electrochemical aptamer-based sensors may be the first truly generalizable technology for monitoring specific molecules in situ in the body and how adaptation of the platform to subcutaneous microneedles will enable the real-time monitoring of performance markers via a wearable, minimally invasive device

Abstract Study Objectives Within-subject stability of certain sleep features across multiple nights is thought to reflect the trait-like behavior of sleep. However, to be considered a trait, a parameter must be both stable and robust. Here, we examined the stability (i.e. across the same sleep opportunity periods) and robustness (i.e. across sleep opportunity periods that varied in duration and timing) of different sleep parameters. Methods Sixty-eight military personnel (14 W) spent 5 nights in the sleep laboratory during a simulated military operational stress protocol. After an adaptation night, participants had an 8-hour sleep opportunity (23:00–07:00) followed by 2 consecutive nights of sleep restriction and disruption which included two 2-hour sleep opportunities (01:00–03:00; 05:00–07:00) and, lastly, another 8-hour sleep opportunity (23:00–07:00). Intra-class correlation coefficients were calculated to examine differences in stability and robustness across different sleep parameters. Results Sleep architecture parameters were less stable and robust than absolute and relative spectral activity parameters. Further, relative spectral activity parameters were less robust than absolute spectral activity. Absolute alpha and sigma activity demonstrated the highest levels of stability that were also robust across sleep opportunities of varying duration and timing. Conclusions Stability and robustness varied across different sleep parameters, but absolute NREM alpha and sigma activity demonstrated robust trait-like behavior across variable sleep opportunities. Reduced stability of other sleep architecture and spectral parameters during shorter sleep episodes as well as across different sleep opportunities has important implications for study design and interpretation.

To investigate tactically-related physical performance and body composition recovery following U.S. Army Ranger training. Prospective cohort. Physical performance was comprehensively assessed using a tactically-related performance battery (i.e., Ranger Athlete Warrior assessment) in 10 male Soldiers at baseline (BL) two-weeks (P1), and six-weeks (P2) post-Ranger School. Body composition was determined using DXA. A one-way repeated measures ANOVA was used followed by Bonferroni-adjusted pairwise comparisons when group differences existed (p≤0.05). Pearson correlation coefficients were used to establish associations between changes in fitness and body composition. All performance domains except the bench press and deadlift worsened following training. Speed/mobility (Illinois agility test, seconds – BL: 16.20±0.86 vs. P2: 18.66±2.09), anaerobic capacity (300-yard shuttle run, seconds – BL: 62.95±6.17 vs. P2: 67.23±5.91), core strength (heel clap, repetitions – BL: 15.80±4.08 vs. P2: 11.50±4.95), and aerobic endurance (beep test, stage – BL: 9.95±2.18 vs. P2: 7.55±1.07) had not recovered by P2. Only upper body muscular endurance and strength (metronome push-up and pull-up, respectively) were similar to BL by P2. Percent body fat increased from 15.62±3.94 (BL) to 19.33±2.99 (P2) (p<0.001). There were no significant associations between changes in body composition and performance. A comprehensive characterization of physical performance and body composition revealed Rangers did not experience full recovery of fitness six weeks after training. Optimal recovery strategies are needed to return Soldiers to a state of readiness following arduous training.

AbstractObjectivesObesity is associated with chronic inflammation, which may impact recovery from mild traumatic brain injury (mTBI). The objective was to assess the role of obesity in recovery of symptoms, functional outcome and inflammatory blood biomarkers after mTBI.MethodsTRACK-TBI is a prospective study of patients with acute mTBI (Glasgow Coma Scale=13–15) who were enrolled ≤24 hours of injury at an emergency department of level 1 trauma centres and followed for 12 months. A total of 770 hospitalised patients who were either obese (body mass index (BMI) >30.0) or healthy mass (BMI=18.5–24.9) were enrolled. Blood concentrations of high-sensitivity C reactive protein (hsCRP), interleukin (IL) 6, IL-10, tumour necrosis factor alpha; Rivermead Post-Concussion Symptoms Questionnaire (RPQ), Quality of Life After Brain Injury and Glasgow Outcome Score-Extended reflecting injury-related functional limitations at 6 and 12 months were collected.ResultsAfter adjusting for age and gender, obese participants had higher concentrations of hsCRP 1 day after injury (mean difference (MD)=0.65; 95% CI: 0.44 to 0.87, p<0.001), at 2 weeks (MD=0.99; 95% CI: 0.74 to 1.25, p<0.001) and at 6 months (MD=1.08; 95% CI: 0.79 to 1.37, p<0.001) compared with healthy mass participants. Obese participants had higher concentrations of IL-6 at 2 weeks (MD=0.37; 95% CI: 0.11 to 0.64, p=0.006) and 6 months (MD=0.42; 95% CI: 0.12 to 0.72, p=0.006). Obese participants had higher RPQ total score at 6 months (MD=2.79; p=0.02) and 12 months (MD=2.37; p=0.049).ConclusionsObesity is associated with higher symptomatology at 6 and 12 months and higher concentrations of blood inflammatory markers throughout recovery following mTBI.

Aneuploidy and epigenetic alterations have long been associated with carcinogenesis, but it was unknown whether aneuploidy could disrupt the epigenetic states required for cellular differentiation. In this study, we found that ~3% of random aneuploid karyotypes in yeast disrupt the stable inheritance of silenced chromatin during cell proliferation. Karyotype analysis revealed that this phenotype was significantly correlated with gains of chromosomes III and X. Chromosome X disomy alone was sufficient to disrupt chromatin silencing and yeast mating-type identity as indicated by a lack of growth response to pheromone. The silencing defect was not limited to cryptic mating type loci and was associated with broad changes in histone modifications and chromatin localization of Sir2 histone deacetylase. The chromatin-silencing defect of disome X can be partially recapitulated by an extra copy of several genes on chromosome X. These results suggest that aneuploidy can directly cause epigenetic instability and disrupt cellular differentiation.