Effects of the adiponectin mimetic compound ALY688 on glucose and fat metabolism in visceral and subcutaneous rat adipocytes
Bibliographic record
Abstract
Adiponectin regulates white adipose tissue (WAT) metabolism and promotes insulin-sensitizing and anti-atherosclerotic effects in vivo. In this context, small molecule adiponectin receptor agonists have become of great therapeutic value for the treatment of metabolic diseases. Here, we investigated the effects of the adiponectin mimetic compound ALY688 on WAT metabolism. To accomplish this, rat epididymal (Epid) and subcutaneous inguinal (Sc Ing) adipocytes were isolated and incubated with ALY688. Subsequently, several parameters of glucose and fat metabolism were assessed. ALY688 promoted AMP-activated protein kinase (AMPK) and acetyl-CoA carboxylase (ACC) phosphorylation, enhanced glucose oxidation, and suppressed fat oxidation in adipocytes from both fat depots. ALY688 did not affect basal and insulin-stimulated rates of glucose uptake, glucose incorporation into lipids, and AKTSer473 and p38 mitogen-activated protein kinase (MAPK) phosphorylations in either Epid or Sc Ing adipocytes. ALY688 did not alter basal lipolysis in Epid and Sc Ing adipocytes, but it enhanced isoproterenol-induced lipolysis in Epid adipocytes. Adiponectin receptor 2 (AdipoR2) mRNA was the prevalent isoform expressed in all adipocytes, and Epid adipocytes displayed significantly higher AdipoR2 mRNA expression than Sc Ing adipocytes. In conclusion, ALY688 can regulate adiposity and affect glycaemic control by altering substrate portioning in the WAT in a fat depot-specific manner.
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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) | 0.002 | 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".