Black hair follicular dysplasia in Large Münsterländer dogs: clinical, histological and ultrastructural features
Bibliographic record
Abstract
Four Large Münsterländer cross-bred dogs affected with black hair follicular dysplasia (BHFD) and one unaffected control littermate were observed, and skin was sampled weekly over the first 19 weeks of life. Affected dogs were born with silvery grey hair, a consequence of melanin clumping in the hair shafts. Hair bulb melanocytes were densely pigmented, and contained abundant stage IV melanosomes but adjacent matrix keratinocytes lacked melanosomes. Melanin clumping was not prominent in epidermal melanocytes in the haired skin but occurred in the foot pads. Follicular changes progressed from bulbar clumping, clumping in the isthmus/infundibulum and finally to dysplastic hair shafts. Alopecia developed progressively in pigmented areas. Silver-grey hair, melanin clumping, accumulation of stage IV melanosomes within melanocytes and insufficient melanin transfer to adjacent keratinocytes are also classic features of human Griscelli syndrome. The underlying cause in Griscelli syndrome is a defect of melanocytic intracellular transport proteins leading to inadequate and disorganized melanosome transfer to keratinocytes with resultant melanin clumping. In view of the correlation in the phenotype, histology and ultrastructure between both disorders, a defect in intracellular melanosome transport is postulated as the pathogenic mechanism in BHFD.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".