Anti Diabetic effect of CL 316,243 (A β3-Adrenergic Agonist) by Down Regulation of Tumour Necrosis Factor (TNF-α) Expression
Bibliographic record
Abstract
OBJECTIVE: Obesity is a risk factor for the development of insulin resistance and is one of the most important contributors to the pathogenesis of type 2 diabetes, which acts mainly through the secretion of adipokines such as TNF-α that may influence insulin sensitivity. TNF-α affects many aspects of adipocyte function, such as adipocyte development and lipid metabolism. MATERIAL AND METHODS: We demonstrated that there is a correlation between the expressions of TNF-α in retroperitoneal WAT and insulin-resistance in 8 genetically obese fa/fa rats. Treatment of animals with CL 316,243, a β3-adrenergic agonist, showed an improvement of insulin-resistance that was linked with the suppression of TNF-α mRNA expression in WAT. RESULTS: These results confirm the association between TNF-α expression and the insulin-resistant condition in rats. Our finding indicates that the hyperglycaemia and hyperinsulinemia induced by insulin-resistance correlated positively with the expression of TNF-α mRNA in an abdominal WAT depot. CONCLUSION: We conclude that CL 316,243 possesses both anti-diabetic effects and anti-obesity effects in rodents.
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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".