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Record W4414081731 · doi:10.1002/art.43376

Cytokine Pathways Driving Diverse Tissue Pathologies in Rheumatoid Arthritis

2025· review· en· W4414081731 on OpenAlexaff
Aurélie Najm, Lyn D Ferguson

Bibliographic record

VenueArthritis & Rheumatology · 2025
Typereview
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsInstitute of Infection and Immunity
FundersFoundation for Research in Rheumatology
KeywordsRheumatoid arthritisCytokinePathogenesisInflammationDiseaseArthritisClinical trial

Abstract

fetched live from OpenAlex

Rheumatoid arthritis (RA) is a complex systemic disorder characterized primarily by articular inflammation and destruction with associated functional loss and reduced quality of life. RA is also associated with extra-articular disease, such as that of the lung, with potentially devastating clinical consequences. The critical importance of comorbidities, and consequent multimorbidity, in determining outcomes in RA has now been recognized, not least as novel therapeutics have emerged with attendant increased life expectancy. The primary role of cytokine networks in mediating RA pathogenesis was established in extensive preclinical and clinical trials and in the adoption of cytokine-targeted therapeutics in clinical care over three decades. Herein, we briefly review those pivotal cytokine pathways that are associated with RA articular disease and extend these insights to include extra-articular RA and its common comorbidities.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.027
GPT teacher head0.314
Teacher spread0.287 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2025
Admission routes1
Has abstractyes

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