The glucose lowering effects of CL 316,243 dissipate with repeated use and are rescued by cilostamide
Bibliographic record
Abstract
Abstract Repeated activation of the beta 3 adrenergic receptor (β3AR) with the agonist CL 316,243 (CL) results in remodeling of white adipose tissue (WAT) characterized by increased mitochondrial enzymes and expression of uncoupling protein 1 (UCP1). β3AR activation also has profound acute metabolic effects including rapidly decreasing blood glucose, secondary to fatty acid‐induced increases in insulin, and increasing energy expenditure. The acute (single dose) effects of β3AR activation have largely been examined in treatment naive animals and under room temperature housing conditions. The current study examined if repeated CL treatment would lead to an attenuation of acute metabolic effects of CL treatment under thermoneutral housing conditions and if this could be rescued with cilostamide, a phosphodiesterase inhibitor. We provide evidence demonstrating that the acute effects of CL to increase serum fatty acids and insulin and reduce blood glucose, but not increases in energy expenditure, are attenuated in mice following repeated treatment with CL. This occurs in parallel with reductions in indices of protein kinase A signaling in WAT including the phosphorylation of hormone sensitive lipase. The findings of attenuated serum fatty acid, insulin, and blood glucose responses were confirmed in both high‐fat fed and UCP1 −/− mice repeatedly treated with CL. Desensitization to CL in mice was rescued by cilostamide. Herein, we provide evidence that the glucose lowering, but not thermogenesis inducing, effects of CL are attenuated with repeated treatment and can be rescued by cilostamide. The findings of this study point toward novel adjunct treatment approaches that could be used to maximize therapeutic, glucose lowering effects of β3AR agonists.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".