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Human T cell subset commitment determined by the intrinsic property of antigen: the proteolytic activity of the major mite allergen Der p 1 conditions T cells to produce more IL-4 and less IFN-γ

2001· article· en· W2084054430 on OpenAlexaff
Amir M. Ghaemmaghami, Adrian Robins, Lucy Gough, Herb F. Sewell, Farouk Shakib

Bibliographic record

VenueEuropean Journal of Immunology · 2001
Typearticle
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsQueen's University
Fundersnot available
KeywordsBiologyImmunoglobulin EIL-2 receptorSecretionImmunologyT cellCD8CytokineAllergenAntigenAntigen-presenting cellCell biologyAntibodyImmune systemAllergyBiochemistry

Abstract

fetched live from OpenAlex

The house dust mite Dermatophagoides pteronyssinus allergen Der p 1 elicits IgE antibody responses in a significant proportion of patients suffering from dust mite allergy. We have recently shown that Der p 1 proteolytically cleaves a cell surface molecule involved in the homeostatic control of human IgE synthesis, namely the IL-2 receptor (CD25) on T cells. As a result, these T cells show markedly diminished proliferation and IFN-gamma secretion in response to stimulation by anti-CD3 antibody. However, these observations still leave open the important issue of whether CD25 cleavage, and the consequent suppression of IFN-gamma secretion, leads to enhanced IL-4 secretion, and whether such cytokine changes would be exhibited by both CD4 and CD8 T cells. Here we demonstrate for the first time that the proteolytic activity of Der p 1 biases human CD4 and CD8 T cells towards a type 2 cytokine profile. Our data provide compelling evidence for the role of the proteolytic activity of Der p 1 in creating a microenvironment conducive for IgE synthesis.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.001

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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations84
Published2001
Admission routes1
Has abstractyes

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