The ASP receptor C5L2 is regulated by metabolic hormones associated with insulin resistance
Bibliographic record
Abstract
Acylation-stimulating protein (ASP) and interaction with its receptor C5L2 influences adipocyte metabolism. We examined insulin resistance and differentiation-mediated regulation of C5L2 and the mechanistic impact on both C5L2 cell-surface protein and ligand binding to the receptor. C5L2 mRNA increased 8.7-fold with differentiation in 3T3-L1 cells (p < 0.0001) by day 9. In preadipocytes, insulin and dexamethasone increased C5L2 mRNA (1 micromol/L insulin resulted in a 2.6-fold increase, p < 0.01; 10 nmol/L dexamethasone resulted in a 17.9-fold increase, p < 0.01) and C5L2 cell-surface protein (100 nmol insulin resulted in a 2.7-fold increase, p < 0.001; 10 nmol/L dexamethasone resulted in a 2.8-fold increase, p < 0.001). In adipocytes, 100 nmol/L insulin increased C5L2 mRNA and ASP binding (respectively, 1.3-fold, p < 0.01; and 2.4-fold, p < 0.05). Dexamethasone decreased ligand binding (-60%, p < 0.02) without changing mRNA. Tumor necrosis factor alpha decreased C5L2 mRNA (-88% in preadipocytes and -38% in adipocytes, p < 0.001), C5L2 cell-surface protein (-53% in preadipocytes, p < 0.0001), and ASP binding (-60% and -49% in, respectively, preadipocytes and adipocytes, p < 0.05). Conversely, 1 micromol/L and 10 nmol/L rosiglitazone increased, respectively, C5L2 mRNA (9.3-fold, p < 0.0001) and ASP binding (2.4-fold, p < 0.05). Thus, C5L2 mRNA increases with differentiation, insulin, and thiazolidinedione treatment, and decreases with tumor necrosis factor alpha, all of which results in functional changes in ASP-C5L2 response and may have implications for human metabolism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".