Subcutaneous inguinal white adipose tissue is responsive to, but dispensable for, the metabolic health benefits of exercise
Bibliographic record
Abstract
Exercise training has robust effects on subcutaneous inguinal white adipose tissue (iWAT), characterized by a shift to a brown adipose tissue (BAT)-like phenotype. Consistent with this, transplantation of exercise-trained iWAT into sedentary rodents activates thermogenesis and improves glucose homeostasis, suggesting that iWAT metabolism may contribute to the beneficial effects of exercise. However, it is yet to be determined if adaptations in iWAT are necessary for the beneficial systemic effects of exercise. To test this, male C57BL/6 mice were provided access to voluntary wheel running (VWR) or remained as a cage control (SED) for 11 nights after iWAT removal via lipectomy (LIPX) or SHAM surgery. We found that SHAM and LIPX mice with access to VWR ran similar distances and had comparable reductions in body mass, increased food intake, and increased respiratory exchange ratio (RER). Further, VWR improved indexes of glucose homeostasis and insulin tolerance in both SHAM and LIPX mice. The lack of effect of LIPX in the response to VWR was not explained by compensatory increases in markers of mitochondrial biogenesis and thermogenesis in skeletal muscle, epididymal white adipose tissue, or interscapular brown adipose tissue. Together, these data demonstrate that mice with and without iWAT have comparable adaptations to VWR, suggesting that iWAT may be dispensable for the metabolic health benefits of exercise.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".