Adipogenic and lipolytic effects of chronic glucocorticoid exposure
Bibliographic record
Abstract
Glucocorticoids have been proposed to be both adipogenic and lipolytic in action within adipose tissue, although it is unknown whether these actions can occur simultaneously. Here we investigate both the in vitro and in vivo effects of corticosterone (Cort) on adipose tissue metabolism. Cort increased 3T3-L1 preadipocyte differentiation in a concentration-dependent manner, but did not increase lipogenesis in adipocytes. Cort increased lipolysis within adipocytes in a concentration-dependent manner (maximum effect at 1–10 μM). Surprisingly, removal of Cort further increased lipolytic rates (∼320% above control, P < 0.05), indicating a residual effect on basal lipolysis. mRNA and protein expression of adipose triglyceride lipase and phosphorylated status of hormone sensitive lipase (Ser563/Ser660) were increased with 48 h of Cort treatment. To test these responses in vivo, Sprague-Dawley rats were subcutaneously implanted with wax pellets with/without Cort (300 mg). After 10 days, adipose depots were removed and cultured ex vivo. Both free fatty acids and glycerol concentrations were elevated in fed and fasting conditions in Cort-treated rats. Despite increased lipolysis, Cort rats had more visceral adiposity than sham rats (10.2 vs. 6.9 g/kg body wt, P < 0.05). Visceral adipocytes from Cort rats were smaller and more numerous than those in sham rats, suggesting that adipogenesis occurred through preadipocyte differentiation rather than adipocyte hypertrophy. Visceral, but not subcutaneous, adipocyte cultures from Cort-treated rats displayed a 1.5-fold increase in basal lipolytic rates compared with sham rats ( P < 0.05). Taken together, our findings demonstrate that chronic glucocorticoid exposure stimulates both lipolysis and adipogenesis in visceral adipose tissue but favors adipogenesis primarily through preadipocyte differentiation.
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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".