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Record W3045629449

Avidity maturation of ACPA in rheumatoid arthritis.

2011· article· en· W3045629449 on OpenAlexaboutno aff
Parawee Suwannalai, Lotte A van de Stadt, Helga Radner, G Steiner, Hani El‐Gabalawy, Cornelia M. Jol‐van der Zijde, Maarten J. van Tol, Dirkjan van Schaardenburg, T. Huizinga, René E. M. Toes, Leendert A. Trouw

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2011
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsnot available
Fundersnot available
KeywordsAvidityRheumatoid arthritisImmunologyMedicineAntibodyArthritisDiseasePopulationCohortInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: Anti-citrullinated protein antibodies (ACPA) are highly specific for rheumatoid arthritis (RA) and are present years before onset of symptoms. Avidity of (auto) antibodies can have a strong impact on their effector potency. Here, we analyzed the avidity of ACPA in pre-disease, early-disease and established RA samples as well as avidity maturation in time in samples of healthy subjects that later developed RA. METHODS: We measured ACPA avidity in samples from ACPA-positive healthy individuals, symptomatic individuals and patients with established RA derived from five collections from The Netherlands, Canada and Austria. Furthermore, we determined the dynamics of avidity maturation of ACPA from the stage of pre-disease to established disease in one case from the native North American population and 10 cases from a Dutch blood donor cohort. RESULTS: The overall ACPA response was characterized by low avidity antibodies. Individuals with higher avidity ACPA were confined to symptomatic patients, while low avidity ACPA were observed in both healthy subjects and patients. In longitudinal samples obtained from subjects prior to disease onset, the ACPA avidity increased over time until disease onset. Following onset of disease no further avidity maturation was observed. CONCLUSIONS: Avidity maturation of the ACPA response takes place prior to disease onset.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.051
GPT teacher head0.287
Teacher spread0.236 · 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 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

Citations1
Published2011
Admission routes1
Has abstractyes

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