Petroleum ether extract of Njavara rice (<i>Oryza sativa</i>) bran upregulates the JAK2–STAT3-mediated anti-inflammatory profile in macrophages and aortic endothelial cells promoting regression of atherosclerosis
Bibliographic record
Abstract
"Njavara" (Oryza sativa L.) is a unique rice variety grown in Kerala that is reported to have significantly higher antioxidant, anti-inflammatory, chemical indices, and bioactive components compared with staple rice varieties. However, the role of NBE in reversing the atherosclerosis development remains unclear. The present study aimed to elucidate the role of NBE in promoting atherosclerotic regression. Male New Zealand white breed rabbits were divided into three groups. Group I was the control, group II was the regression control, and group III was NBE treated (100 mg/kg body mass). Serum and tissue lipids, CRP, antioxidant enzyme activities, mRNA, and protein expression of genes of RTC and mRNA expression of cytokines were studied. The current study showed that hypercholesterolemic rabbits treated with NBE decreased the serum and tissue lipids concentrations, ApoB expression, and CRP levels and enhanced the activities of antioxidant enzymes and PON1expression, JAK2, STAT3, ABCA1, and ApoA. Our results indicate that NBE attenuates proinflammatory cytokine production (IL-1β), enhanced expression and interactions of ABCA1/ApoA1 leading to JAK2/STAT3 activation in macrophages switching to an anti-inflammatory milieu in the system, and enhanced expression of IL-10 and decreased expression of ApoB, indicating that treatment with NBE facilitates plaque regression.
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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 | 0.000 |
| 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".