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Record W3205836138 · doi:10.1093/mr/roab057

Complexity of enthesitis and new bone formation in ankylosing spondylitis: current understanding of the immunopathology and therapeutic approaches

2021· article· en· W3205836138 on OpenAlexafffund
Masaki Kusuda, Nigil Haroon, Akihiro Nakamura

Bibliographic record

VenueModern Rheumatology · 2021
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsEnthesitisMedicineAnkylosing spondylitisImmunologyImmune systemTumor necrosis factor alphaRheumatoid arthritisHoming (biology)SpondyloarthropathyPsoriatic arthritisBiology

Abstract

fetched live from OpenAlex

Despite increasing availability of treatments for spondyloarthritis (SpA) including tumour necrosis factor (TNF) and interleukin-17 (IL-17) inhibitors, there is no established treatment that abates new bone formation (NBF) in ankylosing spondylitis (AS), a subset of SpA. Recent research on TNF has revealed the increased level of transmembrane TNF in the joint tissue of SpA patients compared to that of rheumatoid arthritis patients, which appears to facilitate TNF-driven osteo-proliferative changes in AS. In addition, there is considerable interest in the central role of IL-23/IL-17 axis in type 3 immunity and the therapeutic potential of blocking this axis to ameliorate enthesitis and NBF in AS. AS immunopathology involves a variety of immune cells, including both innate and adoptive immune cells, to orchestrate the immune response driving type 3 immunity. In response to external stimuli of inflammatory cytokines, local osteo-chondral progenitor cells activate intra-cellular anabolic molecules and signals involving hedgehog, bone morphogenetic proteins, receptor activator of nuclear factor kappa-B ligand, and Wnt pathways to promote NBF in AS. Here, we provide an overview of the current immunopathology and future directions for the treatment of enthesitis and NBF associated with AS.

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 score0.097
Threshold uncertainty score0.288

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 head0.155
GPT teacher head0.289
Teacher spread0.134 · 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

Citations23
Published2021
Admission routes2
Has abstractyes

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