Allergen degradation of bee pollen by lactic acid bacteria fermentation and its alleviatory effects on allergic reactions in BALB/c mice
Bibliographic record
Abstract
Food allergy as a global health problem threatens food industry. Bee pollen (BP) is a typical food with allergenic potentials, although it performs various nutritional/pharmacological functions to humans. In this study, lactic acid bacteria (LAB) were used to ferment Brassica napus BP for alleviating its allergenicity. Four novel allergens (glutaredoxin, oleosin-B2, catalase and lipase) were identified with significant decreases in LAB-fermented BP (FBP) than natural BP by proteomics. Meanwhile, metabolomics analysis showed significant increases of twenty-eight characteristic oligopeptides and amino acids in FBP versus BP, indicating the degradation of LAB on allergens. Moreover, FBP showed alleviatory effects in BALB/c mice, which relieved pathological symptoms and lowered production of allergic mediators. Microbial high-throughput sequencing analysis showed that FBP could regulate gut microbiota and metabolism to strengthen immunity, which were closely correlated with the alleviation of allergic reactivity. These findings could contribute to the development and utilization of hypoallergenic BP products.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".