Chronic glucocorticoid exposure causes brown adipose tissue whitening, alters whole‐body glucose metabolism and increases tissue uncoupling protein‐1
Bibliographic record
Abstract
Adipose tissue (AT) has been found to exist in two predominant forms, white and brown. White adipose tissue (WAT) is the body's conventional storage organ, and brown adipose tissue (BAT) is responsible for non-shivering thermogenesis which allows mammals to produce heat and regulate body temperature. Studies examining BAT and its role in whole-body metabolism have found that active BAT utilizes glucose and circulating fatty acids and is associated with improved metabolic outcomes. While the beiging of WAT is a growing area of interest, the possibility of the BAT depot to "whiten" and store more triglycerides also has metabolic and health implications. Currently, there are limited studies that examine the effects of chronic stress and its ability to induce a white-like phenotype in the BAT depot. This research examined how chronic exposure to the murine stress hormone, corticosterone, for 4 weeks can affect the whitening process of BAT in C57BL/6 male mice. Separate treatments with mirabegron, a known β3-adrenergic receptor agonist, were used to directly compare the effects of corticosterone with a beiging phenotype. Corticosterone-treated mice had significantly higher body weight (p ≤ 0.05) and BAT mass (p ≤ 0.05), increased adipocyte area (p ≤ 0.05), were insulin resistant (p ≤ 0.05), and significantly elevated expressions of uncoupling protein 1 (UCP-1) in BAT (p ≤ 0.05) while mitochondrial content remained unchanged. This whitened phenotype has not been previously associated with increased uncoupling proteins under chronic stress and may represent a compensatory mechanism being initiated under these conditions. These findings have implications for the study of BAT in response to chronic glucocorticoid exposure potentially leading to BAT dysfunction and negative impacts on whole-body glucose metabolism.
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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 | 0.000 | 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".