Microvascular pathology of Friedreich cardiomyopathy
Bibliographic record
Abstract
Nikolaus Friedreich (1877) was aware of heart disease in his patients but thought it was unrelated to the neurological disorder. In 1946, Dorothy Russell considered cardiomyopathy an integral part of Friedreich ataxia (FA). In addition to sparse inflammatory infiltration, sections show fibrosis and capillary hyperplasia. We examined the left ventricular walls of 41 homozygous FA patients aged 10–87 and 21 controls aged 2–69. An antibody to CD34 enabled quantitative capillary profile counts for a comparison with cardiomyocyte counts in the same field. Mean capillary counts in normals were 1926±341/mm2, and the median ratio of capillaries to cardiomyocytes was 1.0 (interquartile range [IQR]: 0.9-1.2). In FA, however, the number of cardiomyocytes/mm2 was less, and the median ratio of capillaries to heart fibers was 2.0 (IQR 1.4-2.4). There was a significant correlation of the higher guanine-adenine-adenine trinucleotide length (shorter allele, GAA1) with the younger age of onset, shorter disease duration, and lower cardiomyocyte counts. The ratio of capillaries to heart fibers was higher in patients with long GAA1 repeat expansions (e.g., 3.31 in GAA1 of 1200). Double-label immunofluorescence for CD34 and S100A4 revealed co-expression in endothelial cells, supporting endothelial-to-mesenchymal transition in the pathogenesis of cardiac fibrosis (supported by Friedreich’s Ataxia Research Alliance). LEARNING OBJECTIVES The presentation will enable the learner to: 1. Describe endothelial-to-mesenchymal transition in the pathogenesis of cardiac fibrosis in Friedreich cardiomyopathy
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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 | 0.000 | 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".