Effect of a prebiotic‐enriched phytocompound in improving ovalbumin allergenicity
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to test a prebiotic-phytotherapic compound in an experimental model of oral allergenicity. METHODS: Antigen-specific immunoglobulin E (IgE) elevated mice were prepared by injecting them intraperitoneally with 10 microg of ovalbumin. Subsequently, the mice were exposed to ovalbumin solution intranasally and blood samples were obtained on weekly intervals for 4 weeks to measure serum-ovalbumin-specific IgE and total immunoglobulin G. Mice with high titers of ovalbumin-IgE were intragastrically administered with 0.3 mL of phosphate buffered solution containing either 20 mg of ovalbumin, the same solution with 5 mL of milk, or 20 mg milk added to prebiotic-phytocompound. RESULTS: Ovalbumin administration caused a significant increase of plasma ovalbumin concentration in sensitized mice while prebiotic-phytocompound-supplemented mice showed a significantly reduced peak value (P < 0.05). Prebiotic-phytocompound added to milk exerted a significant effect in lowering the ovalbumin-IgE level and the total immunoglobulin G level as compared to control plain milk (P < 0.01). CONCLUSION: This study provides a rationale basis for a feasible non-pharmacological therapeutic strategy in food allergen hypersensitivity syndromes.
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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".