Hormone and pharmaceutical regulation of ASP production in 3T3‐L1 adipocytes
Bibliographic record
Abstract
Several studies have demonstrated increases in acylation stimulating protein (ASP), and precursor protein C3 in obesity, diabetes and dyslipidemia, however the nature of the regulation is unknown. To evaluate chronic hormonal and pharmaceutical mediated changes in ASP and potential mechanisms, 3T3-L1 adipocytes were treated with physiological concentrations of relevant hormones and drugs currently used in treatment of metabolic diseases for 48 h. Medium ASP production and C3 secretion were evaluated in relation to changes in adipocyte lipid metabolism (cellular triglyceride (TG) mass, non-esterified fatty acid (NEFA) release and real-time FA uptake). Chylomicrons increased ASP production (up to 411 +/- 133% P < 0.05), while leptin, triiodothyronine, and beta-blockers atenolol and propranolol had no effect. Dexamethasone, lovastatin, rosiglitazone and rimonabant decreased ASP production (-53 to -85%, P < 0.05), associated with a decrease in the precursor protein C3 (-37% to -65%, P < 0.01). By contrast, epinephrine, progesterone, testosterone, angiotensin II and metformin also decreased ASP (-54% to -100%, P < 0.05), but without change in precursor protein C3, suggesting a direct effect on convertase activity, possibly mediated by interference (except metformin) due to marked increases in NEFA (5.6-31-fold, increased P < 0.05). Both lovastatin and metformin induced decreases in ASP were also associated with decreased TG mass (maximal -60%, P < 0.05) and real-time FA uptake (maximum -75%, P < 0.05), suggesting a change in adipocyte differentiation status. These in vitro results are consistent with in vivo ASP profiles in subjects, and suggest that ASP may be regulated through precursor C3 availability, convertase activity and differentiation status.
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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 | 0.001 |
| 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".