Clinical and Serologic Characterization of an Argentine Pediatric Myositis Cohort: Identification of a Novel Autoantibody (anti-MJ) to a 142-kDa Protein
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.
Bibliographic record
Abstract
OBJECTIVE: Autoantibodies are frequently found in adult patients with polymyositis (PM), dermato-myositis (DM), and overlap myositis disorders. They are less common in pediatric patients with myositis. We investigated the autoantibody pattern in a pediatric Argentine Caucasian cohort to characterize novel autoantibodies. METHODS: Sera from children that satisfied published criteria for idiopathic inflammatory myopathy were analyzed for autoantibodies by RNA and protein immunoprecipitation and immunoblotting techniques. Routine myositis-specific and myositis-associated autoantibodies as well as autoantibody specificities were determined. RESULTS: We tested sera from 64 consecutive pediatric myositis patients, including 40 with juvenile DM, 7 with juvenile PM, and 17 with overlap myositis syndromes. Sixteen (25%) patients were found to have anti-MJ autoantibody exclusively, which appears to identify a subset of pediatric myositis patients with severe disease characterized by muscle contractures and atrophy and significant compromise of functional status. Fourteen (22%) patients were found to have an antibody targeting 2 proteins of 155 and 140 kDa. Other myositis-specific autoantibodies were uncommon in this pediatric cohort. CONCLUSION: A newly recognized autoantibody, anti-MJ, was the most common antibody found in this Argentine pediatric cohort. The clinical features indicated that this antibody is distinct from other reported antibodies in pediatric patients with myositis.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it