Metabolic remodeling of visceral and subcutaneous white adipose tissue during reacclimation of rats after cold
Bibliographic record
Abstract
Deciphering lipid metabolism in white adipose tissue (WAT) depots during weight gain is important to understand the heterogeneity of WAT and its roles in obesity. Here, we examined the expression of key enzymes of lipid metabolism and changes in the morphology of representative visceral (epididymal) and subcutaneous (inguinal) WAT (eWAT and iWAT, respectively)-in adult male rats acclimated to cold (4 ± 1 °C) for 45 days and reacclimated to room temperature (RT, 22 ± 1 °C) for 1, 3, 7, 12, 21, or 45 days. The relative mass of both depots decreased to a similar extent after cold acclimation. However, fatty acid synthase (FAS), glucose-6-phosphate dehydrogenase (G6PDH), and medium-chain acyl-CoA dehydrogenase (ACADM) protein level increased only in eWAT, whereas adipose triglyceride lipase (ATGL) expression increased only in iWAT. During reacclimation, the relative mass of eWAT reached control values on day 12 and that of iWAT on day 45 of reacclimation. The faster recovery of eWAT mass is associated with higher expression of FAS, acetyl-CoA carboxylase (ACC), G6PDH, and ACADM during reacclimation and a delayed increase in ATGL. The absence of an increase in proliferating cell nuclear antigen suggests that the observed depot-specific mass increase is predominantly due to metabolic adjustments. In summary, this study shows a differential rate of visceral and subcutaneous adipose tissue weight regain during post-cold reacclimation of rats at RT. Faster recovery of the visceral WAT as compared to subcutaneous WAT during reacclimation at RT could be attributed to observed differences in the expression patterns of lipid metabolic enzymes.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".