Therapeutic effects of intranasal tocotrienol-rich fraction on rhinitis symptoms in platelet-activating factor induced allergic rhinitis
Bibliographic record
Abstract
BACKGROUND: Platelet-activating factor (PAF) has been suggested to be a potent inflammatory mediator in Allergic rhinitis (AR) pathogenesis. Vitamin E, an essential nutrient that comprises tocopherol and tocotrienol, is known as a potential therapeutic agent for airway allergic inflammation. This study aimed to investigate the beneficial effects of intranasal Tocotrienol-rich fraction (TRF) on PAF-induced AR in a rat model. METHODS: Sprague Dawley rats were randomly assigned into 3 groups: Control, PAF-induced AR and PAF-induced AR with TRF treatment. To induce AR, 50 μl of 16 μg/ml PAF was nasally instilled into each nostril. From day 1 to 7 after AR induction, 10 μl of 16 μg/μl TRF was delivered intranasally to the TRF treatment group. Complete upper skulls were collected for histopathological evaluation on day 8. RESULTS: The average severity scores of AR were significantly higher in the PAF-induced AR rats compared to both control and PAF-induced AR with TRF treatment. The histologic examination of the nasal structures showed moderate degree of inflammation and polymorphonuclear cells infiltration in the lamina propria, mucosa damage and vascular congestion in the PAF-induced AR rats. TRF was able to ameliorate the AR symptoms by restoring the nasal structures back to normal. H&E staining demonstrated a statistically significant benefit upon TRF treatment, where minimal degree of inflammation, and a reduction in the infiltration of polymorphonuclear cells, mucosa damage and vascular congestion were observed. CONCLUSION: TRF exhibited symptomatic relief action in AR potentially due to its antioxidant, anti-inflammatory and anti-allergic properties.
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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) | 0.001 | 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".