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Record W4407565752 · doi:10.1016/j.jaut.2025.103379

Treg fitness signatures as a biomarker for disease activity in Juvenile Idiopathic Arthritis

2025· article· en· W4407565752 on OpenAlex
Meryl H. Attrill, Diana Shinko, Telma Martins Viveiros, Martina Milighetti, Nina M. de Gruijter, Bethany R. Jebson, Melissa Kartawinata, Elizabeth C. Rosser, Lucy R. Wedderburn, Anne M. Pesenacker

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Autoimmunity · 2025
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsInstitute of Infection and Immunity
FundersVersus ArthritisBiotechnology and Biological Sciences Research CouncilKennedy Trust for Rheumatology ResearchGreat Ormond Street Hospital CharityMedical Research FoundationUCLH Biomedical Research CentreMedical Research CouncilShionogiFoundation for Research in RheumatologyCancer Research UK
KeywordsJuvenileBiomarkerArthritisDiseaseMedicineImmunologyBiologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Treg cluster predominated in inactive JIA PB (AJC = 0). The ratio of these Treg clusters correlated to cJADAS, and higher ratios could potentially predict inactive individuals that flared by 9-month follow-up. Thus, we demonstrate altered Treg signatures and subsets as an important factor, and useful biomarker, for disease progression versus remission in JIA, revealing genes and proteins contributing to Treg fitness. Ultimately, PB Treg fitness measures could serve as routine biomarkers to guide disease and treatment management to sustain remission in JIA.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.911
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.330
Teacher spread0.308 · 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