Attenuation of food allergy symptoms following treatment with human milk oligosaccharides in a mouse model
Bibliographic record
Abstract
BACKGROUND: The prebiotic nature of human milk oligosaccharides (HMOs) and increasing evidence of direct immunomodulatory effects of these sugars suggest that they may have some therapeutic potential in allergy. Here, we assess the effect of two HMOs, 2'-fucosyllactose and 6'-sialyllactose, on symptomatology and immune responses in an ovalbumin-sensitized mouse model of food allergy. METHODS: The effects of oral treatment with 2'-fucosyllactose and 6'-sialyllactose on anaphylactic symptoms induced by oral ovalbumin (OVA) challenge in sensitized mice were investigated. Mast cell functions in response to oral HMO treatment were also measured in the passive cutaneous anaphylaxis model, and direct effects on IgE-mediated degranulation of mast cells were assessed. RESULTS: Daily oral treatment with 2'-fucosyllactose or 6'-sialyllactose attenuated food allergy symptoms including diarrhea and hypothermia. Treatment with HMOs also suppressed antigen-induced increases in mouse mast cell protease-1 in serum and mast cell numbers in the intestine. These effects were associated with increases in the CD4(+) CD25(+) IL-10(+) cell populations in the Peyer's patches and mesenteric lymph nodes, while 6'-sialyllactose also induced increased IL-10 and decreased TNF production in antigen-stimulated splenocytes. Both 2'-fucosyllactose and 6'-sialyllactose reduced the passive cutaneous anaphylaxis response, but only 6'-sialyllactose directly inhibited mast cell degranulation in vitro, at high concentrations. CONCLUSIONS: Our results suggest that 2'-fucosyllactose and 6'-sialyllactose reduce the symptoms of food allergy through induction of IL-10(+) T regulatory cells and indirect stabilization of mast cells. Thus, human milk oligosaccharides may have therapeutic potential in allergic disease.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".