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Record W2936608510 · doi:10.1136/lupus-2019-lsm.8

8 Anti-NT5c1A autoantibodies in systemic lupus erythematosus

2019· article· en· W2936608510 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAbstracts · 2019
Typearticle
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsMcGill UniversityUniversity of Calgary
Fundersnot available
KeywordsMedicineAutoantibodyInternal medicineSerologyCohortAntibodyMyositisSystemic lupus erythematosusBiomarkerClinical significanceImmunologyGastroenterologyDisease

Abstract

fetched live from OpenAlex

<h3>Background</h3> Autoantibodies to the 44 kDa cytosolic 5-nucleotidase 1A (NT5c1A/Mup44) are a biomarker for differentiating sporadic inclusion body myositis (sIBM) from other autoimmune myopathies. These antibodies have also been detected in 10%–20% of SLE patients but the clinical significance has not been reported. This study determined the frequency of anti-NT5c1A autoantibodies in a SLE cohort and then identify demographic, clinical, and serologic correlations. <h3>Methods</h3> Patients fulfilling the ACR or SLICC Classification Criteria for SLE were enrolled in a local cohort. Demographic, clinical information (disease activity SLEDAI-2K; damage SLICC/ACR Damage Index (SDI)), and sera were collected at time of enrollment. Antibodies to anti-NT5c1A were determined by an addressable laser bead immunoassay using a full-length human recombinant protein (Origene, Rockville, MD: Cat. #TP324617). The cutoff, established at 400 median fluorescence units (MFU), was two standard deviations above the mean of apparently healthy control sera. Univariable and multivariable analysis were performed to determine associations between the prevalence of high positive anti-NT5c1A and demographic (age, sex, race/ethnicity), clinical features (SLICC/ACR classification criteria, SLEDAI-2K and SDI total scores and subscales including myositis from SLEDAI-2K), medications, and other autoantibodies (anti-dsDNA, extractable nuclear antigens, and anti-phospholipid antibodies). <h3>Results</h3> 138 SLE patients were included; 89.1% were female with a mean age of 46.1 years (SD 18.1) and disease duration of 13.7 years (SD 11.6). The prevalence of positive anti-NT5c1A was 15.2% (21/138). Univariable analysis demonstrated that patients who had a positive anti-dsDNA (Odds Ratio (OR) 6.59 [95%CI: 2.21, 19.65]) or anti-nucleosome (OR 8.96 [95%CI: 2.43, 32.99]) were more likely to be positive for anti-NT5c1A. Patients with longer disease duration (OR 0.93 [95%:CI 0.88, 0.98]), proteinuria (24 hour urine protein greater than 500 mg on the SLICC criteria) (OR 0.20 [95%CI: 0.04, 0.88]), acute cutaneous SLE (OR 0.38 [95%CI: 0.15, 0.97] on the SLICC criteria), in particular malar rash (OR 0.25 [95%CI: 0.07, 0.89]) or photosensitivity (OR 0.27 [95%CI: 0.08, 0.84]) were less likely to be anti-NT5c1A positive. Multivariable analysis demonstrated that patients with proteinuria (OR 0.16 [95%CI: 0.03, 0.87]) were less likely to be anti-NT5c1A positive. <h3>Conclusions</h3> Anti-NT5c1A antibodies, a novel biomarker for sIBM, were found in 15.2% of SLE patients in keeping with previous reports. The patients were less likely to have a history of proteinuria and there was no association with myositis (on SLEDAI-2K). Further studies are needed to confirm these findings in larger SLE cohorts. <h3>Funding Source(s):</h3> The Arthritis Society Chair in Rheumatic Diseases at the Cumming School of Medicine, Calgary

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.999

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)0.0000.002

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 head0.008
GPT teacher head0.236
Teacher spread0.229 · 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