Cold acclimation enhances UCP1 content, lipolysis, and triacylglycerol resynthesis, but not mitochondrial uncoupling and fat oxidation, in rat white adipocytes
Bibliographic record
Abstract
The objective of this study was to investigate whether cold-induced browning of the subcutaneous (Sc) inguinal (Ing) white adipose tissue (WAT) increases the capacity of this tissue to oxidize fatty acids through uncoupling protein 1 (UCP1)-mediated thermogenesis. To accomplish that, rats were acclimated to cold (4°C for 7 days). Subsequently, interscapular and aortic brown adipose tissues (iBAT and aBAT, respectively), epididymal (Epid), and Sc Ing WAT were used for adipocyte isolation. In BAT adipocytes, cold acclimation increased UCP1 content and palmitate oxidation either in the absence or presence of oligomycin, whereas in Sc Ing adipocytes glucose and palmitate oxidation were not affected, although multilocular adipocytes were formed and UCP1 content increased upon cold acclimation in the WAT. Furthermore, isoproterenol-stimulated cold Sc Ing adipocytes exhibited significantly lower rates of palmitate oxidation than control cells when exposed to oligomycin. These findings provide evidence that, despite increasing UCP1 levels, cold acclimation essentially reduced mitochondrial uncoupling-mediated fat oxidation in Sc Ing adipocytes. Conversely, glycerol kinase and phosphoenolpyruvate carboxykinase levels, isoproterenol-induced lipolysis, as well as glycerol and palmitate incorporation into lipids significantly increased in these cells. Therefore, instead of UCP1-mediated mitochondrial uncoupling, cold acclimation increased the capacity of Sc Ing adipocytes to export fatty acids and enhanced key components of the triacylglycerol resynthesis pathway in the Sc Ing WAT.
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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 | 0.000 |
| 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".