Investigation of anti-asthmatic potential of dried fruits of Vitis vinifera L. in animal model of bronchial asthma
Bibliographic record
Abstract
BACKGROUND: Fruits of Vitis vinifera L., commonly known as grapes, are largely consumed worldwide because of their high nutritional and medicinal benefits. CONTEXT AND PURPOSE: The present study investigated effects of V. vinifera fruits in ovalbumin-induced animal model of bronchial asthma. METHODS: Male wistar rats (except group 1) were sensitized with allergen (ovalbumin, 40 mg/rat + aluminum hydroxide, 2 mg/rat). Groups of sensitized animals were treated orally with either vehicle (0.4 mL/kg), standard dexamethasone (2.5 mg/kg) or alcoholic extract of V. vinifera dried fruits (31 and 42.5 mg/kg) from day 1 to 28 (n = 6 for all groups). Inflammatory markers including cell counts, cytokines such as interleukin (IL)-4, IL-5, IL-1β, tumor necrosis factor, immunoglobulin E (IgE), leukotrienes and nitrite levels in both blood/serum and bronchoalveolar fluid were analysed. Breathing rate and tidal volume as lung function parameters were examined by spirometer. Lung tissues were studied for histamine content and histopathology. RESULTS: Treatment of sensitized animals with dexamethasone or two doses of V. vinifera fruits extract inhibited recruitment of inflammatory cytokines, IgE, nitrites and circulating cells particularly eosinophils in blood/serum and bronchoalveolar fluid (p < 0.001, p < 0.01 and p < 0.05). Dexamethasone and V. vinifera fruits extract treatment also normalized lung functions and histamine levels compared to ovalbumin-sensitized controls (p < 0.05 and p < 0.01). Moreover, both drugs exhibited protection against airway inflammation in lung histology. CONCLUSION: Results of study demonstrate the effectiveness of V. vinifera fruits in allergic asthma possibly related to its ability to inhibit cellular response and subsequent production of inflammatory cytokines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".