<i>n</i>-3 Fatty acids inhibit transcription of human IL-13: implications for development of T helper type 2 immune responses
Bibliographic record
Abstract
Fish oil supplementation during pregnancy has been associated with lower levels of cord blood IL-13, suggesting that the administration of n-3 fatty acids may attenuate the development of allergic disease. The present study aimed to investigate the mechanism by which n-3 fatty acid administration influences the production of IL-13. Pregnant BALB/c mice were fed nutritionally complete high-fat diets (15 %, w/w) with an n-3 fatty acid-enriched (DHA 1 %, w/w) or control diet (0 % DHA) immediately following delivery. Pups were exposed during suckling and weaned to the maternal diet for the remainder of the study. The production of IL-13, IL-4, IL-10 and interferon-γ from the splenocytes of ovalbumin (ova)-sensitised animals was assessed following in vitro ova stimulation or unstimulated conditions. Human T helper type 2 (Th2) cells were mitogen-stimulated in the presence or absence of DHA (10 μM) and assessed for IL-13 and IL-4 expression using intracellular flow cytometry. The influence on transcriptional activation was studied using a human IL-13 promoter reporter construct and electromobility shift assay. Ova-activated splenocytes from DHA-fed mice produced less IL-13 (57.2 (se 21.7) pg/ml) and IL-4 (7.33 (SE 3.4) pg/ml) compared with cells from the animals fed the control diet (161.5 (SE 45.0), P< 0.05; 33.2 (SE 11.8), P< 0.05). In vitro, DHA inhibited the expression of IL-13 protein from human Th2 cells as well as transcriptional activation and binding of the transcription factors cyclic AMP response element binding and activating transcription factor 2 to the human IL-13 promoter. These data indicate the potential of n-3 fatty acids to attenuate IL-13 expression, and suggest that they may subsequently reduce allergic sensitisation and the development of 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) | 0.000 | 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) | 0.002 | 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".