Frontiers in Physiology最新文献

Purpose: This study aimed to determine the optimal recovery time for maximizing post-activation performance enhancement in resistance-trained males grouped by local muscle endurance, and evaluate its effects on anaerobic performance and neuromuscular activity.

Methods: Twenty-four healthy men were grouped by repetitions completed at 80% of 1 repetition maximum (1RM) back squat, serving as a functional proxy for muscle endurance characteristics: Low-Muscle-Endurance (LME, n = 8, 20.5 ± 1.2 years), Intermediate-Muscle-Endurance (IME, n = 8, 20.3 ± 1.3 years), and High-Muscle-Endurance (HME, n = 8, 20.1 ± 1.1 years). Participants completed a control session (CON) and three experimental trials involving a back squat conditioning protocol (3 × 3 repetitions at 80% 1RM), followed by a 30-s Wingate Anaerobic Test (WAnT) after 3 (T3), 8 (T8), or 12 (T12) minutes of recovery. Surface electromyography (EMG) signals were recorded from the right rectus femoris (RF), biceps femoris (BF), and gastrocnemius lateralis (GL) during WAnT and analyzed for integrated EMG (IEMG) and mean power frequency (MPF).

Results: A clear hierarchy in baseline peak power (PP) was observed across groups, with LME > IME > HME (all p < 0.05). The LME group also demonstrated a higher fatigue index (FI) than both HME and IME groups (all p < 0.05). Regarding the time course of PAPE, PP for the cohort was significantly higher at T12 than at CON (p = 0.021). RF IEMG at T12 was significantly elevated versus CON (p = 0.024), while BF IEMG increased at T8 (p = 0.011). BF MPF was also higher at T12 compared to CON (p = 0.039). No significant recovery effects were observed for mean power (MP).

Conclusion: Individuals stratified by local muscle endurance exhibited distinct baseline anaerobic capacities and fatigue profiles. The optimal PAPE window occurred 8-12 min post-activation, marked by initial biceps femoris neural drive enhancement, followed by peak power and improved neuromuscular efficiency at 12 min. These findings support this practical stratification method for personalizing recovery strategies, linking PAPE magnitude differences to physiological traits reflected in endurance-based grouping.

Chronic Exertional Compartment Syndrome (CECS) is an uncommon yet debilitating condition that causes activity-induced pain due to increased pressure within muscle compartments. While typically diagnosed through dynamic intercompartmental pressure testing, CECS presents significant diagnostic challenges due to overlapping symptoms with other musculoskeletal conditions. This first-person narrative describes a 23-month journey through inconclusive imaging, multiple rounds of physical therapy, and pressure testing that met, but was ultimately dismissed despite established CECS diagnostic criteria. The case underscores the mismatch that can occur between objective findings and clinical interpretation, particularly when symptoms affect atypical compartments. With surgery ruled out and conservative treatments offering minimal relief, the experience reveals critical gaps in diagnostic consistency, clinician-patient communication, and care pathways for individuals whose symptoms reside in a diagnostic gray zone. This narrative calls for more nuanced application of diagnostic tools, greater attention to patient-reported symptoms, and improved support systems for those navigating prolonged diagnostic uncertainty.

Background: Renal ischemia-reperfusion injury (RIRI) represents a leading cause of acute kidney injury (AKI). Mitochondria, serving as the central organelles for cellular energy metabolism and signal transduction, play a pivotal role in the pathogenesis of RIRI.

Methods: Utilizing the three major academic databases-Web of Science Core Collection (WoSCC), PubMed, and Scopus, this study conducted a comprehensive bibliometric analysis and visualization to explore research trends and key thematic areas related to mitochondrial involvement in renal ischemia-reperfusion injury from 2005 to 2024.

Results: Bibliometric analysis reveals a sustained increase in research output concerning mitochondrial roles in RIRI over the past two decades. China and the United States have emerged as the most active contributors in this field. The U.S. Department of Veterans Affairs leads in terms of total publications, while Dong Zheng from the Second Xiangya Hospital of Central South University has contributed the highest number of publications by an individual author. Kidney International and the Journal of the American Society of Nephrology are the most frequently cited journals. This study systematically identified key research themes, including the mechanisms of mitochondrial dysfunction in RIRI, mitochondrial quality control mechanisms, and potential therapeutic strategies targeting mitochondria.

Conclusion: Through bibliometric analysis, this study elucidates the knowledge structure and developmental trends in mitochondrial research related to RIRI. Over the past 20 years, mitochondrial dysfunction, mitochondrial quality control, and mitochondria-targeted therapeutic approaches have consistently constituted major research hotspots in this domain.

Objective: Osteoporosis poses a major global public health challenge. The limitations of current diagnostic methods, primarily diagnostic delays in bone density testing, are compounded by the insufficient exploration of inflammatory factors in predictive models for the disease's pathogenesis. This study aims to leverage multi-source data and machine learning to explore the value of inflammatory markers for osteoporosis prediction, establishing a high-precision model for early screening and precise prevention.

Methods: A multi-center, multi-level research design was employed, integrating four independent datasets: the National Health and Nutrition Examination Survey (NHANES) database (12,988 adult women), a Chinese postmenopausal women specialized cohort (CPW-BMI) (312 participants), the Osteoporosis Phenotype Validation Cohort (OP-VC) (60 participants), and animal experimental data (40 C57BL/6J mice). A predictive indicator system comprising 22 clinical features and inflammatory markers was constructed. Various machine learning algorithms (including RUSBoosted Trees, Bagged Trees, Support Vector Machines, Gaussian Process Regression, etc.) were used to establish classification and regression prediction models, and model performance was evaluated through rigorous five-fold cross-validation and external validation.

Results: Machine learning models based on inflammatory markers exhibited excellent predictive performance across different bone sites. At the femoral neck, the RUSBoosted Trees model achieved an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.9643 and an accuracy of 90.55%; at the lumbar spine, the Efficient Logistic Regression model achieved an AUC of 0.9685 and an accuracy of 91.79%. External validation demonstrated good generalization ability: in the Chinese population cohort, the Fine Gaussian Support Vector Machine model had a prediction error (Root Mean Square Error, RMSE) of 0.681; in the clinical cohort, serum levels of Interleukin-6 (IL-6), Tumor Necrosis Factor-alpha (TNF-α), and Interleukin-1 beta (IL-1β) were significantly elevated in the osteoporosis group; in animal experiments, a Linear Discriminant Analysis model based on three core inflammatory factors achieved 97.5% accuracy (AUC = 0.9574). These results confirm the value of inflammatory markers in osteoporosis risk assessment.

Conclusion: Using inflammation markers and machine learning, we created accurate models to predict osteoporosis. This work confirms inflammation's key role in the disease, providing new insights for early detection and targeted intervention.

This study aimed to produce predictive equations to determine the optimal paddle size for young Iberian kayakers competing in three categories: U14, U16, and U18. Data were collected in Portugal and Spain between 2005 and 2018, with a sample that includes 149 kayakers aged 14.42 ± 1.20 years. The kayakers were assessed for somatic maturation using the maturity offset and the percentage of the predicted adult height (%PAH). For anthropometry, assessing body mass (kg), stretch stature (cm), sitting height (cm), arm span (cm), arm length (cm), forearm length (cm), biacromial diameter (cm) and chest girth (cm), and for equipment setup, measuring paddle and blade length, blade maximum width, handgrip distance. A stepwise multiple linear regression analysis was performed to determine which anthropometric and maturity attributes could predict the paddle configuration for the total sample and each category analysed. Significant differences were found between the three categories for anthropometry, paddle setup, and maturity, except for PAH. Significant differences between U16 and U18 were only found in CA, maturity offset, %PAH, and paddle length. The predictive equation for the total sample explains the variance in paddle length by 75% and may be used as a more objective guide for paddle scaling.

Introduction: Intensive aquaculture frequently utilizes high-fat diets (HF) as a cost-effective strategy, yet this practice often induces hepatic steatosis, oxidative stress, and chronic inflammation in carnivorous fish. Betaine, a natural methyl donor, has shown potential as a functional feed additive, but its comprehensive protective mechanisms under HF stress remain to be fully elucidated.

Methods: Juvenile largemouth bass (Micropterus salmoides) were fed one of four isonitrogenous diets for 8 weeks: a normal-fat control (Control), a high-fat diet (HF), and two high-fat diets supplemented with 0.5% (HFB0.5) or 1.0% (HFB1) betaine. Growth performance, digestive enzyme activities, serum biochemical parameters, hepatic antioxidant capacity, and the expression of genes related to antioxidant defense, lipid metabolism, and inflammation were analyzed.

Results: The HF group exhibited significantly impaired growth, digestive function, and antioxidant capacity, along with elevated lipid peroxidation, dyslipidemia, and pro-inflammatory cytokine expression. Betaine supplementation restored growth performance and feed efficiency to control levels, ameliorated digestive enzyme activities (particularly enhancing lipase), and activated the hepatic Nrf2-Keap1 pathway, upregulating antioxidant genes (nrf2, sod1, cat, gpx, ho-1, gr) and enhancing enzyme activities. Betaine also improved serum lipid profiles, upregulated genes related to fatty acid oxidation (pparα, cpt-1) and lipolysis (lpl, hsl), suppressed lipogenic genes (srebp-1, fas), and rebalanced inflammatory cytokines by reducing tnf-α and il-1β while increasing tgf-β1 and il-10.

Discussion: Dietary betaine effectively counteracts HF-induced metabolic stress in M. salmoides through coordinated multi-pathway regulation. It enhances antioxidant defense, reprograms hepatic lipid metabolism toward catabolism, and restores inflammatory homeostasis. These findings underscore betaine's role as a multi-functional feed additive capable of mitigating HF-related metabolic disorders and promoting overall health in carnivorous fish aquaculture.

Simulated microgravity profoundly alters endothelial function, particularly cell migration. However, the mechanosensitive molecular pathways involved remain incompletely understood. In this study, we performed integrated transcriptomic and proteomic analyses of human umbilical vein endothelial cells exposed to simulated microgravity to identify key regulators of endothelial migration. RNA-seq and proteomic profiling identified 964 differentially expressed genes and 183 differentially expressed proteins, primarily enriched in stress response, signal transduction, and angiogenesis pathways. Combined analysis of both datasets revealed four key genes-TLR2, HSPB1, RBM3, and HSPA1B-with more than a twofold change. Protein-protein interaction analysis incorporating 48 endothelial migration-related genes further highlighted TLR2 as a central hub with strong interaction with CXCR4. Functional experiments demonstrated that simulated microgravity significantly enhanced endothelial migration through TLR2 upregulation, while TLR2 activation further promoted this response by increasing CXCR4 expression. These findings identify the TLR2-CXCR4 axis as a previously unrecognized mechanosensitive signaling pathway driving endothelial adaptation to simulated microgravity, offering potential molecular targets for therapeutic intervention against microgravity-induced vascular remodeling.