Angiotensin Receptor Autoantibodies in Dupuytren Disease: A Biomarker Study
Bibliographic record
Abstract
Background: Dupuytren disease (DD) is a fibroproliferative disorder characterized by excess collagen deposition in the digitopalmar fascia resulting in disabling flexion contractures. The angiotensin II type 1 receptor (AT1R) pathway has previously been shown to be upregulated in a variety of other fibrotic disorders. We explored the potential association between DD and activating autoantibodies (AAb) against the profibrotic AT1R or counterregulatory antifibrotic angiotensin II type 2 receptor (AT2R). Methods: Patients with DD and controls were recruited from a single hand clinic. Demographic and clinical data and total flexion deformity angle of each digit were recorded. Serum levels of AT1R-AAb and AT2R-AAb were measured by enzyme-linked immunosorbent assay. Results: No differences were noted in serum AT1R-AAb levels between control and DD patients. In women with DD, circulating AT2R-AAb were significantly lower than in control women (7.61 ± 3.0 U/mL vs 13.5 ± 3.1 U/mL, respectively). AT2R-AAb observed values tended to be lower in women with higher Tubiana severity scores. In contrast, AT2R-AAb levels were not different between control or DD male subjects. Conclusions: These early findings suggest angiotensin II signaling differences may contribute to sex differences in DD and that an AT2R agonist may be particularly beneficial in treating women with DD. Level of Evidence: Diagnostic, Level II.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".