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Record W2295836868 · doi:10.1155/2011/768750

Development of Transient Peanut Allergy Following Lung Transplantation: A Case Report

2011· article· en· W2295836868 on OpenAlexaff
Sacha Bhinder, Matthew J. Heffer, Jason K. Lee, Cecilia Chaparro, Susan M. Tarlo

Bibliographic record

VenueCanadian Respiratory Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineLung transplantationPeanut allergyAllergyTransplantationDermatologyIntensive care medicineSurgeryFood allergyImmunology

Abstract

fetched live from OpenAlex

A 47-year-old woman underwent bilateral lung transplantation for nonspecific interstitial pneumonitis and received donor lungs from a 12-year-old patient with a known peanut allergy. Post-transplant, the patient experienced four anaphylaxis-like reactions. A skin prick test to peanut was initially positive; however, it steadily declined over serial assessments and reverted to negative one year post-transplant. The patient subsequently had a negative oral peanut challenge. Transfer of food allergy post-transplantation is theorized to occur via transfer of donor B lymphocytes producing peanut-specific immunoglobulin E into the circulation of the recipient. An alternate mechanism proposes passive transfer of immunoglobulin E-sensitized mast cells and⁄or basophils within the transplanted tissue that subsequently migrate into recipient tissues. The gradual decline in the magnitude of the peanut skin prick test and its return to negative over the course of one year supports the gradual depletion of sensitized cells in the recipient (B lymphocytes and, possibly, mast cells), and supports the initial passive transfer of sensitized cells from donor tissue during transplantation. This should be considered when donor organs are obtained from allergic individuals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.058
GPT teacher head0.296
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2011
Admission routes1
Has abstractyes

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