Endothelial Activation Markers as Disease Activity and Damage Measures in Juvenile Dermatomyositis
Bibliographic record
Abstract
Objective. Circulating endothelial cells (CEC), von Willebrand factor (vWF) antigen, P-selectin, and thrombomodulin are released from damaged endothelium, while decreases in circulating endothelial progenitor cells (CEPC) have been associated with poor vascular outcomes. We examined these markers in the peripheral blood of patients with juvenile dermatomyositis (JDM) and their correlations with disease assessments. Methods. Peripheral blood endothelial cells and biomarkers were assessed in 20 patients with JDM and matched healthy controls. CEC and CEPC were measured by flow cytometry, while vWF antigen and activity, factor VIII, P-selectin, and thrombomodulin were measured in plate-based assays. Disease activity and damage, nailfold capillary density, and brachial artery flow dilation were assessed. Serum cytokines/chemokines were measured by Luminex. Results. CEC, vWF antigen, factor VIII, and thrombomodulin, but not vWF activity, CEPC, or P-selectin, were elevated in the peripheral blood of patients with JDM. CEC correlated with pulmonary activity (r s = 0.56). The vWF antigen correlated with Patient’s/Parent’s Global, cutaneous, and extramuscular activity (r s = 0.47–0.54). CEPC negatively correlated with muscle activity and physical function (r s = −0.52 to −0.53). CEPC correlated inversely with endocrine damage. The vWF antigen and activity correlated with interleukin 10 and interferon-gamma inducible protein-10 (r s = 0.64–0.82). Conclusion. Markers of endothelial injury are increased in patients with JDM and correlate with extramuscular activity. CEPC correlate inversely with muscle activity, suggesting a functional disturbance in repair mechanisms.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".