PurposeThe purpose of this study was to examine the mediating role of community health services and the moderating role of formal social support in the relationship between migration trajectory and individuals' quality of life (QoL).Design/methodology/approachUsing data from 16,604 adults aged 45 and above in the nationally representative 2014 China Health and Retirement Longitudinal Study, this study used sequence analysis to identify typical migration trajectory patterns and conditional process analysis to examine their impact mechanisms on QoL.FindingsThis study found that the migration trajectories of Chinese adults can be divided into six clusters: "non-migrants," "infrequent migrants," "young adult migrants," "late adult migrants," "late life migrants," and "frequent migrants." The clusters of late-adult migrants and late life migrants had a significant direct effect on health-related QoL. Community health services played a mediating role in the relationship between late adult and late life migration trajectory types and health-related quality of life (HRQoL). Formal social support moderated the direct effect of young adult, late adult and late life migration trajectories and HRQoL.Practical implicationsPolicy should differentiate between migrant types, offering targeted health services for early migrants and human capital training for all to maintain labor market competitiveness. Formal social support should prioritize disadvantaged migration trajectory groups to enhance their social welfare.Originality/valueThese findings advanced their understanding of how migration trajectory affected QoL by moving beyond single events to demonstrate the value of examining migration histories for their longitudinal health impacts.
The rapid expansion of China's sports sector, particularly in action sports such as surfing, has created new labor opportunities for informal migrant workers. However, their professional integration remains constrained by institutional barriers and market precarity. Focusing on surfing coaches in Wanning-dubbed "China's Surfing Capital"-this study investigates how informal sports laborers navigate industry gray zones by converting embodied cultural capital (e.g., surfing skills) into institutionalized capital (e.g., certifications). Drawing on semistructured interviews and Bourdieu's field-capital theory (n = 20), the findings reveal a stratified formalization process: while surfing proficiency enables market entry, certification remains elusive due to skill-based disparities-low-skilled workers struggle with practical assessments, while high-skilled ones face theoretical exam barriers. Additionally, economic constraints (high certification costs) and social-structural obstacles (regulatory ambiguities, weak occupational networks) further entrench informality. Over time, coaches who successfully cultivate social capital transition into formal roles, whereas others exit due to unsustainable conditions. By exposing the uneven conversion of cultural capital into professional legitimacy, this study contributes to sports sociology by elucidating how informal sports labor navigates the interplay between institutional barriers and market opportunities, and demonstrates how credentialization processes reproduce stratification within emerging athletic professions.
Aerobic exercise improves systemic insulin sensitivity by modulating muscle glucose metabolism. The CHRONO/BMAL1 pathway constitutes a core component of the endogenous molecular clock and participates in glucose metabolic regulation; however, whether it mediates exercise-induced metabolic benefits under high-fat diet (HFD) conditions remains unclear. We therefore investigated the role of this pathway in conferring protective effects of aerobic exercise against HFD-induced glucose metabolic dysfunction in skeletal muscle, by subjecting wild-type (WT) and inducible muscle-specific Chrono overexpression (Chrono IMOE) mice to an HFD with or without 12-week exercise. Unlike in WT mice, exercise failed to ameliorate adipose mass, dyslipidemia, and insulin resistance in HFD-fed Chrono IMOE mice. Mechanistically, in skeletal muscle of Chrono IMOE mice, Chrono overexpression suppressed exercise-induced reductions in CHRONO expression and CHRONO-BMAL1 binding, as well as the increase in BMAL1 levels. Consequently, despite elevated p-TBC1D1Ser237 and GLUT4 expression, exercise failed to promote GLUT4 sarcolemmal colocalization or upregulate gene expression of key enzymes for glycolysis and glycogen metabolism in skeletal muscle of Chrono IMOE mice. These findings demonstrate that preventing CHRONO‑BMAL1 dissociation via muscle-specific Chrono overexpression abrogates exercise-induced GLUT4 membrane trafficking, transcriptional activation of glycolytic/glycogen metabolic genes, and systemic insulin sensitivity improvements in HFD-fed mice, establishing CHRONO‑BMAL1 dissociation as a required step for these exercise adaptations. Chrono overexpression aggravates HFD-induced insulin resistance. Chrono overexpression blunts exercise-induced improvement in muscle glucose metabolism under HFD.
This study addresses persistent challenges in youth soccer training, including limited personalization, delayed scientific feedback, and the lack of injury risk early warnings. To fill gaps in applicability, functional completeness, and technological integration, an innovative training optimization framework based on an artificial intelligence (AI) digital twins network was developed. The framework integrates publicly available large-scale match and training datasets, Wyscout and StatsBomb, to create virtual twins. These twins map athletes' multidimensional states - including position, actions, and physiological signals - in real time. Deep learning was applied for high-precision feature extraction and movement trajectory tracking. Reinforcement learning mechanisms enabled the system to adaptively optimize training strategies and load based on real-time feedback. Experimental results demonstrate that the model significantly outperforms traditional methods. Real-time player position tracking reached 95% accuracy. Motion pattern analysis and classification efficiency improved by 20%. The system also identifies potential high-risk movement patterns, providing early warnings to prevent injuries. In summary, the framework achieves a closed loop from data perception to intelligent decision-making and provides coaches with an actionable, personalized, and evidence-based tool for scientific training. This approach has important theoretical and practical implications for improving the quality, safety, and long-term development of youth soccer training.
While heart rate variability (HRV) offers a non-invasive alternative for ventilatory thresholds (VTs) estimation, its conventional linear parameters (e.g., RMSSD) exhibit a “floor effect” limiting utility. DFAα1 is a promising non-linear HRV parameter, reflecting the complex pattern of autonomic regulation. This study evaluated DFAα1 for threshold estimation, intensity monitoring, and recovery assessment. 27 healthy adults underwent an incremental cycle ergometer test. VTs were determined via standard criteria, while HRV thresholds (HRVTs) were determined using multiple parameters. A subset (n = 19) then performed low to severe intensity exercise tests (E1-E4) to validate HRV sensitivity and dynamic responses. For HRVT1 vs. VT1: DFAα1-derived HRVT1 exhibited the highest ICC (> 0.60) among all parameters but with a systematic bias; for HRVT2 vs. VT2: DFAα1-derived HRVT2 exhibited moderate-to-high ICC (> 0.60) and RMSSD-derived achieved the highest ICC (0.88–0.95). During E1-E4, DFAα1 and the natural log of RMSSD (LnRMSSD) both decreased during exercise and increased during recovery. During exercise, DFAα1 in E1 and E2 exceeded in E3 and E4, while LnRMSSD was higher in E1 than in E2-E4 (all P < 0.05). During recovery in E2-E4, DFAα1 exceeded baseline, and this rebound was delayed with intensity, while LnRMSSD was lower than baseline with a downward trend. DFAα1 showed potential for estimating both VTs, retained sensitivity across intensity domains, and showed recovery dynamics proportional to prior intensity. Despite individual variability suggesting use for broad zoning rather than precise estimation, DFAα1 serves as an intensity-sensitive biomarker for individualized exercise prescription.
