Sex differences in the relationships between body composition, fat distribution, and mitochondrial energy metabolism: a pilot study
Bibliographic record
Abstract
Abstract Background Adiposity and mitochondrial dysfunction are related factors contributing to metabolic disease development. This pilot study examined whether in vivo and ex vivo indices of mitochondrial metabolism were differentially associated with body composition in males and females. Methods Thirty-four participants including 19 females (mean 27 yr) and 15 males (mean 29 yr) had body composition assessed by dual energy x-ray absorptiometry and magnetic resonance (MR) imaging. Monocyte reserve capacity and maximal oxygen consumption rate (OCR) were determined ex vivo using extracellular flux analysis. In vivo quadriceps mitochondrial function was measured using 31P-MR spectroscopy based on post-exercise recovery kinetics (τPCr). The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated from fasting glucose and insulin levels. Variables were log-transformed, and Pearson correlations and partial correlations were used for analyses. Results Mitochondrial metabolism was similar between sexes (p > 0.05). In males only, higher fat mass percent (FM%) was correlated with lower reserve capacity (r = − 0.73; p = 0.002) and reduced muscle mitochondrial function (r = 0.58, p = 0.02). Thigh subcutaneous adipose tissue was inversely related to reserve capacity in males (r = − 0.75, p = 0.001), but in females was correlated to higher maximal OCR (r = 0.48, p = 0.046), independent of FM. In females, lean mass was related to greater reserve capacity (r = 0.47, p = 0.04). In all participants, insulin (r = 0.35; p = 0.04) and HOMA-IR (r = 0.34; p = 0.05) were associated with a higher τPCr. Conclusions These novel findings demonstrate distinct sex-dependent associations between monocyte and skeletal muscle mitochondrial metabolism with body composition. With further study, increased understanding of these relationships may inform sex-specific interventions to improve mitochondrial function and metabolic health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".