SynthesisFrontiers in immunology2026
Modality-specific effects of structured exercise on immunometabolic biomarkers in postmenopausal obesity: a Bayesian network meta-analysis.
Synthesis in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Objective: The present Bayesian network meta-analysis (NMA) aims to evaluate and compare the efficacy of aerobic training (AT), resistance training (RT), high-intensity interval training (HIIT), and combined training (CT) on biomarkers of chronic low-grade systemic inflammation (CLGSI) in postmenopausal women with overweight or obesity. Methods: Five databases were systematically searched from inception to November 2025 (PROSPERO: CRD420251237915) for randomized controlled trials (RCTs). Inclusion required strict clinical verification of postmenopausal status and adiposity. Standardized mean differences (SMDs) with 95% credible intervals (CrIs) quantified comparative efficacy. Surface Under the Cumulative Ranking curve (SUCRA) established probabilistic hierarchical rankings, and the GRADE framework evaluated the certainty of evidence. Results: Synthesis of 39 RCTs ( Conclusion: Distinct exercise modalities elicit biomarker-specific anti-inflammatory responses in postmenopausal women with overweight or obesity. Based on probabilistic rankings, RT demonstrates the highest potential for mitigating systemic CRP, whereas CT appears most effective in attenuating IL-6 and TNF-α. The stability of systemic leptin levels indicates that physical activity alone may be insufficient to reverse hyperleptinemia. Given the low to very low certainty of evidence, these modality-specific efficacies should be interpreted cautiously as probabilistic targets to inform biomarker-guided exercise prescriptions. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD420251237915.
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