From bite to brain: Neuro‐immune interactions in food allergy
Bibliographic record
Abstract
Immunoglobulin E (IgE)-mediated food allergies are reported to affect around 3.5% of children and 2.4% of adults, with symptoms varying in range and severity. While being the gold standard for diagnosis, oral food challenges are burdensome, and diagnostic tools based on specific IgE can be flawed. Furthering our understanding of the mechanisms behind food allergy onset, severity and persistence could help reveal immune profiles associated with the disease, to ultimately aid in diagnosis. Alterations to cytokine levels and immune cell ratios have been identified, though further research is needed to fully capture the heterogenous nature of food allergy. Moreover, the existence of such immune alterations also raises the question of potential wider systemic effects. For example, recent research has emphasised the existence and impact of neuro-immune interactions and implicated behavioural and neurological changes associated with food allergy. This review will provide an overview of such food allergy-driven neuro-immune interactions, with the aim of emphasising the importance of furthering our understanding of the immune mechanisms underlying IgE-mediated food allergy.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".