Effect of parthenolide, an NLRP3 inflammasome inhibitor, on insulin resistance in high-fat diet-obese mice
Bibliographic record
Abstract
The activation of Nod-like receptor proteins (NLRP3) containing the pyrin domain inflammasome is a hallmark of the pathogenesis of metabolic disorders. Inhibition of the NLRP3 inflammasome by phytoconstituents has been attempted as a strategy to mitigate these disorders. Therefore, the present study aimed to evaluate the efficacy of an NLRP3 inflammasome inhibitor, parthenolide (PN; 5 mg/kg i.p.) against inflammation and insulin resistance in high-fat diet (HFD) - obese mice. Treatment with PN and pioglitazone (PIO; 30 mg/kg p.o.) attenuated lipopolysaccharide (LPS; 1 ng/ml) - induced elevation of tumor necrosis factor-α and interleukin-1β in mouse peritoneal macrophages in a dose-dependent manner. Sixty days of PN and PIO treatment marginally reduced obesity-induced insulin resistance in HFD-obese mice. PN treatment also decreased blood glucose from 14th to 60th day, supporting the hypothesis of simultaneous attenuation of inflammation and insulin resistance in obese mice. Thus, PN treatment was also evident with significant improvement in glucose tolerance and peripheral insulin resistance validated through the respective tolerance tests. Therefore, the present study suggests that PN, an NLRP3 inflammasome inhibitor, could be a possible therapeutic agent for attenuating obesity-induced insulin resistance.
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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) | 0.001 | 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".