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Record W2083762249 · doi:10.1155/2015/384780

Enhanced Cysteinyl-Leukotriene Type 1 Receptor Expression in T Cells from House Dust Mite-Allergic Individuals following Stimulation with Der p

2015· article· en· W2083762249 on OpenAlexafffund
Maryse Thivierge, Sylvie Turcotte, Marek Rola‐Pleszczynski, Jana Staňková

Bibliographic record

VenueJournal of Immunology Research · 2015
Typearticle
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsUniversité de Sherbrooke
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsHouse dust miteImmunologyPeripheral blood mononuclear cellReceptorAllergenCD8T cellStimulationChemistryBiologyImmune systemAllergyMedicineEndocrinologyIn vitroInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

In order to determine the potential for allergen to modulate T cell expression of the CysLT1 receptor and responsiveness to leukotrienes, peripheral blood mononuclear cells from house dust mite-allergic or nonallergic individuals were incubated with D. pteronyssinus allergen (Der p). Baseline CysLT1 expression was similar in both groups of donors, but Der p significantly enhanced CysLT1 expression in CD4(+) and CD8(+) T cells of only allergic individuals and induced enhanced responsiveness of CD4(+) T cells to LTD4 in terms of calcium mobilisation. This effect was prevented by the CysLT1 antagonist MK571. Der p also induced IL-4 and IL-10 production, and neutralizing antibody to IL-4 prevented both the enhanced CysLT1 expression and the enhanced responsiveness of T cells to LTD4 induced by Der p. In allergic individuals, Der p also induced T cell proliferation and a Th2-biased phenotype. Our data suggest that, in allergen-sensitized individuals, exposure to allergen can enhance T cell expression of CysLT1 receptors through a mechanism involving IL-4 production. This, in turn, would induce CD4(+) T cell responsiveness to cysteinyl-leukotrienes and Th2 cell activation.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.261
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.344
Teacher spread0.278 · 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 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

Citations7
Published2015
Admission routes2
Has abstractyes

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