Pathophysiology of De Novo Food Allergies After Solid Organ Transplant in Pediatric Patients
Bibliographic record
Abstract
De novo food allergy is a common phenomenon among pediatric solid organ recipients (8.5%-57%) when compared with the general population (0.45%-10%). Other associated disorders include non-IgE-mediated immune reactions and clinical predisposition to asthma and alterations in the oral mucosa. Originally, passive mechanisms (passive transfer of IgE and immune cells) were thought to be responsible for acute, transient cases of food allergies with a previous history of sensitization for a specific allergen in the donor. Recently proposed pathophysiological mechanisms to explain de novo allergies include TH2/B-cell imbalance, regulatory T-cell (Treg) disruption, gastrointestinal immaturity, and altered gastrointestinal permeability. Recent studies also suggest that immunosuppressive drugs, especially tacrolimus, promote naïve T-cell differentiation into TH2 cells, IgE-promoting cytokine production, decreased IL-5 and IL-10 levels, increased IgA levels, and Treg disruption. Such immunological interactions, in conjunction with altered intestinal permeability, intestinal immaturity in children, history of viral infection, and a personal history of allergies or eczema, are thought to explain most clinical cases of pediatric de novo food allergy after solid organ transplantation reported in the literature. A better understanding of the immunological mechanisms underpinning organ donors and recipients may unveil some of the caveats concerning therapeutic management and improve the quality of life of affected individuals.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".