Capillary pathology with prominent basement membrane reduplication is the hallmark histopathological feature of scleromyositis
Bibliographic record
Abstract
AIMS: We aim to perform ultrastructural and histopathological analysis of muscle biopsies from a large group of systemic sclerosis (SSc) patients, including some with early/mild SSc features, and examine whether capillary pathology differentiates 'scleromyositis' (SM) from other auto-immune myositis (AIM) subsets. METHODS: Muscle biopsies from a total of 60 SM patients and 43 AIM controls from two independent cohorts were examined by electron microscopy, collagen-4 immunofluorescence (Col4IF) and routine light microscopy. RESULTS: Ultrastructural examination revealed prominent capillary basement membrane (BM) reduplication (4+ layers in >50% of capillaries) in 65% of SM vs 0% of AIM controls (p < 0.001). In SM cases without prominent BM reduplication, capillary dilation was the most distinctive feature, present in 8% of capillaries in SM vs 2% in controls (p = 0.001). Accumulation of ensheathed pericyte processes was another characteristic feature of SM and closely correlated with the degree of BM reduplication (r = 0.833, p < 0.001). On light microscopy, BM marker Col4IF revealed more frequent capillary enlargement in SM than in controls (84% vs 21%, p < 0.001). SM cases were classified as non-inflammatory myopathy (36%), non-specific myositis (33%) or immune-mediated necrotizing myopathy (31%), but despite this histopathological heterogeneity, prominent BM reduplication remained a constant finding. In the 16 SM patients with early/mild SSc features, 63% showed prominent BM reduplication. CONCLUSIONS: These results show that capillary pathology, and in particular prominent capillary BM reduplication, is the hallmark histopathological feature of SM even in patients with early/mild SSc and support the concept of SM as an organ manifestation of SSc and a distinct subset of AIM.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".