Effects of supplementing different ratios of omega-3 and omega-6 fatty acids in western-style diets on cow's milk protein allergy in a mouse model
Bibliographic record
Abstract
SCOPE: This study investigated the effects of supplementing different ratios of omega-6 and omega-3 fatty acids (O6H = 10:1, O3O6 = 4:1, and O3H = 1:4) to western-style diets on cow β-lactoglobulin (BLG) induced allergic reactions in Balb/c mice. METHODS AND RESULTS: Three-week-old mice were randomly assigned to three diet groups (n = 20/group). At 9 wk of age, half of the mice from each dietary treatment (n = 10) were intraperitoneally (i.p.) sensitized with three weekly doses of BLG and alum while the remaining half from each group was sham sensitized (controls). One week after the final sensitization, all mice were orally challenged with BLG. Elevated BLG-specific serum Igs were observed in all sensitized and challenged mice. IFN-γ, MCP-1, and IL-12p40 concentrations from lymphocytes of mesenteric lymph nodes were highest in O3H mice, compared to O3O6 and O6H mice. O6H mice had the highest IL-4 concentrations from splenic lymphocytes and a significantly lower rectal temperature after the challenge in comparison to O3O6 and O3H mice. CONCLUSIONS: Our results suggest that the ω-3 PUFA rich diets alleviated the severity of allergic reactions, and may modulate immune response toward T helper cell (Th)1-favoured immune response while the ω-6 PUFA rich diet exhibited no allergy alleviation with a stronger Th2 polarized immune response.
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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 | 0.001 | 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".