Prior Exercise Training Alters the Response of White and Brown Adipose Tissue to Cold Stress
Bibliographic record
Abstract
Brown adipose tissue is a thermogenic tissue bed that produces heat in conditions of cold environmental temperatures. While possessing much lower oxidative capacity than brown adipose tissue, recent findings have suggested that exercise training can increase the thermogenic capacity of white adipose tissue. What is not known is if exercise training can alter the response of an animal to cold stress. To address this question, male C57BL/6 mice were subject to either exercise training by voluntary wheel running (EX) or a sedentary (SED) intervention for 12 days. EX mice ran approximately 6km/day, which led to decreased body weight and increased glucose tolerance, while maintaining a similar pattern of food intake to SED. Mice were then further divided into groups that would be kept at room temperature (22°C) or a cold challenge of 4°C for 48‐hrs, thus we examined four groups in this study; (i) SED kept at room temperature (SRT), (ii) exercise trained kept at room temperature (EXRT), (iii) SED kept at 4°C (SC), and (iv) EX kept at 4°C (EXC). Rectal temperatures (T b ) of SC and EXC were lower than that of SRT and EXRT, and the initial drop in T b of EXC was less than that observed in the SC 2‐hours following the start of the cold, however this difference was not maintained throughout the rest of the cold exposure. 48‐hrs of cold exposure led to reductions in body weight and epididymal and subcutaneous adipose tissue mass in the SED but not EX mice. Conversely, interscapular brown adipose tissue mass was increased following cold exposure in previously EX but not SED animals Taken together, our data demonstrates a unique effect of prior exercise on altering the response of adipose tissue to cold stress. Support or Funding Information D.C.W. is a Tier II Canada Research Chair. This work was funded by an NSERC Discovery Grant to D.C.W.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".