5th Global Conference on Myositis (GCOM)
Bibliographic record
Abstract
Background. Anti-synthetase syndrome (ASyS) is an autoimmune condition, characterized by the presence of autoantibodies directed against an aminoacyl-tRNA synthetase (anti-ARS). Patients present clinical symptoms such as myositis, interstitial lung disease, Raynaud's phenomenon, and arthritis. Anti-Jo-1, anti-PL-7 and anti-PL-12 are the most frequent anti-ARS. However, their role in ASyS pathogenesis remains incompletely understood. Therefore, robust animal models are essential to gain a detailed insight into the underlying pathophysiology. Aiming to characterize these pathophysiological features, we established and studied a mouse model for Jo-1, PL-7 and PL-12 associated ASyS. Methods. ASyS was induced in NOD.Idd3/5 mice by injection of 200 g Jo-1, PL-7 or PL-12 recombinant protein emulsified in Complete Freund's Adjuvant (CFA) in combination with OX86. Controls received CFA and Phosphate Buffered Saline only. Muscle strength was assessed by rotarod tests and the effects on the peripheral immune system were investigated by flow cytometry in spleen and lymph nodes. Morphological characteristics of skeletal muscle and lung tissue of immunized mice and the tissue infiltrating immune cells were validated using histology and immunohistochemistry. Results. Immunization of mice led to clinical symptoms including muscle weakness and demonstrated variations in the immune cell response between the ARS subtypes. Histological analysis of skeletal muscle tissues showed infiltration by immune cells in the epimysium, spreading into the adjacent perifascicular area with progressing disease. Analysis of lung specimens by immunohistological staining demonstrated peribronchial accentuated accumulation of lymphocyte aggregates.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.112 | 0.063 |
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".