Cutaneous collagenous vasculopathy with generalized telangiectasia: an immunohistochemical and ultrastructural study
Bibliographic record
Abstract
We report a 54-year-old male, with a 5-year history of spreading asymptomatic generalized cutaneous telangiectases. The patient had no mucosal or nail involvement, no positive family history and no clinical evidence of systemic disease or bleeding diathesis. Histologically, the superficial small dermal blood vessels were dilated and showed thickened walls with hyaline perivascular material, staining as collagen. The vessel walls were PAS and colloidal iron stain positive, and immuno-histochemically lacked actin staining. Collagen IV, fibronectin and laminin antibodies showed the material deposited around the basement membrane zone. Ultrastructurally, the vessels were post-capillary venules (PCV) and showed marked collagen deposition around the basal lamina. There were many abnormally banded widely spaced fibres with 100-150 nm periodicity (Luse bodies), in addition to regular banded collagen. Pericytes were sparse and lacked intracytoplasmic filaments, and few veil or fibroblastic cells were seen embedded within the collagen. We believe this is a form of cutaneous microangiopathy not previously described, with distinct morphology and unique ultrastructural features. It may be due to a genetic defect with erroneous production of disorganized collagen in the cutaneous microvasculature. Dermatologists and Dermatopathologists should be aware of this unusual cutaneous vasculopathy.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".