Journal of applied physiology最新文献

The aim of this study was to investigate whether baseline values and acute and chronic changes in androgen receptors (AR) markers, including total AR, cytoplasmic (cAR), and nuclear (nAR) fractions, as well as DNA-binding activity (AR-DNA), are involved in muscle hypertrophy responsiveness by comparing young nonresponder and responder individuals. After 10 wk of resistance training (RT), participants were identified as nonresponders using two typical errors (TE) obtained through two muscle cross-sectional area (mCSA) ultrasound measurements (2 × TE; 4.94%), and the highest responders within our sample were numerically matched. Muscle biopsies were performed at baseline, 24 h after the first RT session (acute responses), and 96 h after the last session (chronic responses). AR, cAR, and nAR were analyzed using Western blotting, and AR-DNA was analyzed using an ELISA-oligonucleotide assay. Twelve participants were identified as nonresponders (ΔmCSA: -1.32%) and 12 as responders (ΔmCSA: 21.35%). There were no baseline differences between groups in mCSA, AR, cAR, nAR, or AR-DNA (P > 0.05). For acute responses, there was a significant difference between nonresponders (+19.5%) and responders (-14.4%) in AR-DNA [effect size (ES) = -1.39; 95% confidence interval (CI): -2.53 to -0.16; P = 0.015]. There were no acute between-group differences in any other AR markers (P > 0.05). No significant differences between groups were observed in chronic responses across any AR markers (P > 0.05). Nonresponders and responders presented similar baseline, acute, and chronic results for the majority of the AR markers. Thus, our findings do not support the influence of AR markers on muscle hypertrophy responsiveness to RT in untrained individuals.NEW & NOTEWORTHY We explored, for the first time, the influence of androgen receptor (AR) through the separation of cytoplasmic and nuclear cell fractions [i.e., cytoplasmic androgen receptor (cAR), nuclear androgen receptor (nAR), and androgen receptor DNA-binding activity (AR-DNA)] on muscle hypertrophy responsiveness to resistance training. The absence of muscle hypertrophy in naïve individuals does not seem to be explained by baseline values, and acute or chronic changes in AR markers.

Sickle cell disease (SCD) is characterized by central (cardiac) and peripheral vascular dysfunctions, significantly diminishing exercise capacity and quality of life. Although central cardiopulmonary abnormalities in SCD are known to reduce exercise capacity and quality of life; the impact of hemolysis and subsequent cell-free hemoglobin (Hb)-mediated peripheral vascular abnormalities on those outcomes are not fully understood. Despite the recognized benefits of exercise training for cardiovascular health and clinical management in chronic diseases like heart failure, there remains substantial debate on the advisability of regular physical activity for patients with SCD. This is primarily due to concerns that prolonged and/or high-intensity exercise might trigger metabolic shifts leading to vaso-occlusive crises. As a result, exercise recommendations for patients with SCD are often vague or nonexistent, reflecting a gap in knowledge about the mechanisms of exercise intolerance and the impact of exercise training on SCD-related health issues. This mini-review sheds light on recent developments in understanding how SCD affects exercise tolerance, with a special focus on the roles of hemolysis and the release of cell-free hemoglobin in altering cardiovascular and skeletal muscle function. Also highlighted here is the emerging research on the therapeutic effects and safety of exercise training in patients with SCD. In addition, the review identifies future research opportunities to fill existing gaps in our understanding of exercise (in)tolerance in SCD.

Effective execution of military missions in cold environments requires highly trained, well-equipped, and operationally ready service members. Understanding the metabolic energetic demands of performing physical work in extreme cold conditions is critical for individual medical readiness of service members. In this narrative review, we describe 1) the extreme energy costs of performing militarily relevant physical work in cold environments, 2) key factors specific to cold environments that explain these additional energy costs, 3) additional environmental factors that modulate the metabolic burden, 4) medical readiness consequences associated with these circumstances, and 5) potential countermeasures to be developed to aid future military personnel. Key characteristics of the cold operational environment that cause excessive energy expenditure in military personnel include thermoregulatory mechanisms, winter apparel, inspiration of cold air, inclement weather, and activities specific to cold weather. The combination of cold temperatures with other environmental stressors, including altitude, wind, and wet environments, exacerbates the overall metabolic strain on military service members. The high energy cost of working in these environments increases the risk of undesirable consequences, including negative energy balance, dehydration, and subsequent decrements in physical and cognitive performance. Such consequences may be mitigated by the application of enhanced clothing and equipment design, wearable technologies for biomechanical assistance and localized heating, thermogenic pharmaceuticals, and cold habituation and training guidance. Altogether, the reduction in energy expenditure of modern military personnel during physical work in cold environments would promote desirable operational outcomes and optimize the health and performance of service members.

This article describes the development and validation of accurate whole body sweat rate prediction equations for individuals performing indoor cycle ergometer and treadmill exercise, where power output can be measured or derived from simple inputs. For cycle ergometry, 112 trials (67 participants) were used for model development and another 56 trials (42 participants) for model validation. For treadmill exercise, 171 trials (67 participants) were used for model development and another 95 trials (63 participants) for model validation. Trials were conducted over a range of dry-bulb temperature (20°C to 40°C), relative humidity (14% to 60%), and exercise intensity (∼40% to 85% of peak aerobic power) conditions, which were matched between model development and model validation. Whole body sweat rates were measured, and proprietary prediction models were developed (accounting for all relevant biophysical factors) and then validated. For model validation, mean absolute error for predicted sweating rate was 0.01 and 0.02 L·h^-1 for cycle and treadmill trials, respectively. The 95% confidence intervals were modest for cycle ergometer (+0.25 and -0.22 L·h^-1) and treadmill exercise (+0.33 and -0.29 L·h^-1). The accounted for variance between predicted and measured values was 92% and 78% for cycle and treadmill exercise, respectively. Bland-Altman analysis indicated that zero and one predicted value exceeded the a priori acceptable level of agreement (equivalent to ±2% of total body mass in 3 h) for cycle and treadmill exercise, respectively. There were fewer trials with female subjects, but their values did not differ from those expected for males. This is the foremost study to develop and validate whole body sweat rate prediction equations for indoor treadmill and cycle ergometer exercise of moderate to high intensity. These prediction equations are publicly available for use (https://sweatratecalculator.com).NEW & NOTEWORTHY This study presents the development of new proprietary whole body sweat rate prediction models for people exercising indoors on a cycle ergometer or treadmill using simple input parameters and delivered through a publicly available online calculator: https://sweatratecalculator.com. In an independent validation group, the predictive models for both indoor cycling and treadmill exercise were accurate across moderate to high exercise intensities in temperate to hot conditions. These equations will enable individualized hydration management during physical training and exercise physiology experiments.

Arterial carbon dioxide ([Formula: see text]) and posture influence the middle (MCAv) and posterior (PCAv) cerebral artery blood velocities, but there is paucity of data about their interaction and need for an integrated model of their effects, including dynamic cerebral autoregulation (dCA). In 22 participants (11 males, age 30.2 ± 14.3 yr), blood pressure (BP, Finometer), dominant MCAv and nondominant PCAv (transcranial Doppler ultrasound), end-tidal CO₂ (EtCO₂, capnography), and heart rate (HR, ECG) were recorded continuously. Two recordings (R) were taken when the participant was supine (R1, R2), two taken when the participant was sitting (R3, R4), and two taken when the participant was standing (R5, R6). R1, R3, and R5 consisted of 3 min of 5% CO₂ through a mask and R2, R4, and R6 consisted of 3 min of paced hyperventilation. The effects of [Formula: see text] were expressed with a logistic curve model (LCM) for each parameter. dCA was expressed by the autoregulation index (ARI), derived by transfer function analysis. Standing shifted LCM to the left for MCAv (P < 0.001), PCAv (P < 0.001), BP (P = 0.03), and ARI (P = 0.001); downward for MCAv and PCAv (both P < 0.001), and upward for HR (P < 0.001). For BP, LCM was shifted downward by sitting and standing (P = 0.024). For ARI, the hypercapnic range of LCM was shifted upward during standing (P < 0.001). A more complete mapping of the combined effects of posture and arterial CO₂ on the cerebral circulation and peripheral variables can be obtained with the LCM over a broad physiological range of EtCO₂ values.NEW & NOTEWORTHY Data from supine, sitting, and standing postures were measured. Modeling the data with logistic curves to express the effects of CO₂ reactivity on middle cerebral artery blood velocity (MCAv), posterior cerebral artery blood velocity (PCAv), heart rate, blood pressure (BP), and the autoregulation index (ARI), provided a more comprehensive approach to study the interaction of arterial CO₂ with posture than in previous studies. Above all, shifts of the logistic curve model with changes in posture have shown interactions with [Formula: see text] that have not been previously demonstrated.