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Record W2158357844 · doi:10.1155/2011/913802

Platelet-Activating Factor Induces Th17 Cell Differentiation

2011· article· en· W2158357844 on OpenAlexafffund
Anne-Marie Drolet, Maryse Thivierge, Sylvie Turcotte, Dominique Hanna, Bruno Maynard, Jana Staňková, Marek Rola‐Pleszczynski

Bibliographic record

VenueMediators of Inflammation · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsPlatelet-activating factorRAR-related orphan receptor gammaMediatorCell biologyInterleukin 17ImmunologyInflammationBiologyMonocyteChemistryImmune system

Abstract

fetched live from OpenAlex

Th17 cells have been implicated in a number of inflammatory and autoimmune diseases. The phospholipid mediator platelet-activating factor (PAF) is found in increased concentrations in inflammatory lesions and has been shown to induce IL-6 production. We investigated whether PAF could affect the development of Th17 cells. Picomolar concentrations of PAF induced IL-23, IL-6, and IL-1β expression in monocyte-derived Langerhans cells (LCs) and in keratinocytes. Moreover, when LC were pretreated with PAF and then cocultured with anti-CD3- and anti-CD28-activated T cells, the latter developed a Th17 phenotype, with a significant increase in the expression of the transcriptional regulator RORγt and enhanced expression of IL-17, IL-21, and IL-22. PAF-induced Th17 development was prevented by the PAF receptor antagonist WEB2086 and by neutralizing antibodies to IL-23 and IL-6R. This may constitute a previously unknown stimulus for the development and persistence of inflammatory processes that could be amenable to pharmacologic intervention.

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 score0.002
Threshold uncertainty score0.008

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.212
Teacher spread0.190 · 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

Citations26
Published2011
Admission routes2
Has abstractyes

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