Interstitial lung disease in an adult patient with dermatomyositis and anti-NXP2 autoantibody
Bibliographic record
Abstract
Idiopathic inflammatory myopathies (IIMs) are characterised by inflammatory involvement of skeletal muscles causing weakness and pain, with possible associated systemic manifestations including frequent interstitial lung disease (ILD), and significant morbidity and mortality. Accumulating evidence suggests an important contribution of autoimmune responses to the pathogenesis of these diseases. Autoantibodies are present in at least half of patients with IIMs [1]. Some of these autoantibodies are frequently detected in patients with other connective diseases associated with myositis (especially systematic sclerosis) and are referred to as myositis-associated autoantibodies, whereas others are considered specific to IIMs and are referred to as myositis-specific antibodies (MSAs), including antibodies against aminoacyl transfer RNA (tRNA) synthetases, Mi-2 (a nuclear helicase) and the signal recognition particle [1, 2]. MSAs, when present, contribute to the diagnosis of IIM, especially in patients with mild muscle involvement or with ILD pre-existing to the myositis, although other, nonspecific antibodies are associated with various frequencies of manifestations and distinct clinical phenotypes within the spectrum of IIM [1, 2]. Novel targets of autoantibodies have recently been described in IIM patients without “classical” MSAs, including p155/140 (transcriptional intermediary factor (TIF)-1-γ), CADM-140 (melanoma differentiation-associated gene 5), small ubiquitin-like modifier activating enzyme (SAE)1 and SAE2, and nuclear matrix protein 2/MJ (NXP2) [3]. Anti-NXP2 antibodies should be tested in patients with dermatomyositis, ILD and idiopathic inflammatory myopathies
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".