Is resveratrol therapeutic when used to treat allergic rhinitis in rats?
Bibliographic record
Abstract
PURPOSE: Resveratrol has anti-infective, anti-inflammatory and antioxidant activities. The purpose of this study was to determine the effect of resveratrol in a rat experimental model of allergic rhinitis (AR). METHODS: Wistar albino rats were divided into three groups: control (n=7), AR with no treatment (AR+NoTr, n=7) and AR with resveratrol treatment (AR+Res, n=7). For AR+Res, AR was induced and resveratrol given on days 21-28. On day 28, the total blood IgE levels were measured. Allergic symptoms (sneezing, nose-rubbing, eye lacrimation and nasal congestion) were scored on a 0-3 point scale, and histopathological changes in the nasal mucosa were evaluated. RESULTS: Allergic symptom score of AR+NoTr was higher than the other two groups and the score of AR+Res was higher than the control group. Histopathologically, neither ciliary loss nor chondrocyte hypertrophy differed among the three groups; however, vascular congestion, inflammatory and plasma cell numbers, eosinophil and mast cell infiltration and goblet cell numbers were higher and mast cell infiltration was more prominent in AR+NoTr than in AR+Res and control. AR+Res and control did not differ significantly in any histological parameter. In AR+NoTr, nasal mucosa exhibited ciliary loss, squamous epithelial metaplasia, inflammatory cell infiltration, vascular congestion of the lamina propria and goblet cell epithelial metaplasia. In AR+Res, goblet cell metaplasia was focal or absent and infiltration of the lamina propria by inflammatory cells, eosinophils, and plasma cells was reduced relative to AR+NoTr. CONCLUSION: Allergic symptoms and tissue reactions were reduced by resveratrol treatment in rats with experimentally-induced AR.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".