Acute Antilipolytic Effects of Elevated Levels of Corticosterone in Differentiated Murine White Adipocytes
Bibliographic record
Abstract
Glucocorticoids (GC) are a group of steroid hormones that affects white adipose tissue (WAT) lipogenesis (biosynthesis of triglycerides) and lipolysis (hydrolysis of triglycerides). At the cellular level, prolonged GC exposure promotes increases in WAT lipolysis through glucocorticoid receptor (GR) mediated mechanisms; however, elevated GC levels can decrease WAT lipolysis through unknown mechanisms that remain unclear. Evidence suggests that GCs may also have actions independent of GR binding, though how these GR-independent effects impact WAT lipolysis also remains unknown. Therefore, the objective of this study was to assess how elevated GCs impact WAT lipolysis through non-GR mediated mechanisms. Mature white adipocytes (3T3-L1 cells) were acutely exposed to various GC concentrations (10-200 μM) and lipolytic rates were quantified in the presence or absence of lipolytic pathway inhibitors or siRNA GR. Contradictory to chronic in vitro and in vivo studies, acute (1-4 hrs), high GC levels (50-200 μM) significantly decreased basal lipolysis. These inhibitory effects persisted when the GR or gene transcription was blocked after 1 hr, suggesting GCs inhibition of lipolysis occurred independent of GR-mediated pathways. Interestingly, 1 hr of elevated GC exposure decreased hormone sensitive lipase (HSL) activity through a reduction of ser563 phosphorylation. However, this decrease in HSL activity was independent of cAMP signalling, as elevated GCs had no effect on cAMP or PKA activity relative to controls. Ex vivo adipose explant studies also revealed depot-specific suppression of lipolysis by CORT. Therefore, elevated GC levels can acutely decrease lipolysis in WAT independent of GR-mediated mechanisms, suggesting an alternative pathway in which GCs act to regulate lipolysis.
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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) | 0.000 | 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".