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Record W2149605891 · doi:10.3899/jrheum.130677

Expression of B Cell Activating Factor (BAFF) and BAFF-binding Receptors in Rheumatoid Arthritis

2013· letter· en· W2149605891 on OpenAlexvenueno aff
Maria Leandro, Geraldine Cambridge

Bibliographic record

VenueThe Journal of Rheumatology · 2013
Typeletter
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsB-cell activating factorMedicineImmunologyB cellRituximabCytokineRheumatoid arthritisAutoantibodyRheumatoid factorReceptorCD19Peripheral blood mononuclear cellPathogenesisCD20AntibodyInternal medicineBiology

Abstract

fetched live from OpenAlex

It is widely accepted that B cells play an essential role in the pathogenesis of rheumatoid arthritis (RA). B cell involvement is well documented in the presence of detectable autoantibodies in the majority of patients, in particular, rheumatoid factor (RF) and antibodies against citrullinated proteins (ACPA), which can be detected many years before development of clinical disease, indicating that autoreactive B cell clones are involved in disease induction1. B cell depletion therapy with rituximab (anti-CD20) is effective in treating RA, proving an essential role for B cells in disease persistence2. Although B cell depletion therapy can induce longterm responses in a small number of patients, almost all patients eventually relapse. There is therefore much interest in finding out whether analysis of B cell-related factors can guide the development of treatment strategies and/or prediction of disease flare. The cytokine B cell activating factor (BAFF; also known as BLyS) plays an essential role in B cell survival and homeostasis. BAFF binds to 3 different receptors: BAFF-R, TACI, and BCMA. Expression of the different BAFF-binding receptors varies in distinct subsets of B cells, and their expression is coordinated and intimately related to maturation and activation status3. In the study by Moura, et al in this issue of The Journal 4, gene expression of molecules related to B cell survival and differentiation were studied in peripheral blood mononuclear cells (PBMC) in a small group of patients with very early RA (VERA; i.e., < 6 weeks of symptoms) and compared with other patients with RA at different stages [early RA (ERA) > 6 weeks and < 1 year duration; and established RA > 1 year duration], with patients with other forms of early arthritis (EA), and with healthy controls (HC). Patients with established RA were all taking methotrexate, … Address correspondence to Dr. M.J. Leandro, Centre for Rheumatology Research, Division of Medicine, University College London, Rayne Building, 5 University Street, London WC1E 6JF, UK; E-mail: maria.leandro{at}ucl.ac.uk

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.255
Teacher spread0.239 · 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 designObservational
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

Citations10
Published2013
Admission routes1
Has abstractyes

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