Intracorneal vacuoles in skin diseases with parakeratotic hyperkeratosis in the dog: a retrospective light‐microscopy study of 111 cases (1973–2000)
Bibliographic record
Abstract
Two recent case reports described a congenital keratinization defect (congenital follicular parakeratosis; CFP) in Rottweiler and Siberian Husky dogs. Skin biopsy specimens revealed marked parakeratosis targeting the hair follicle and numerous intracorneal vacuoles. A retrospective histopathological study was conducted on skin biopsy specimens from 111 dogs with diseases associated with parakeratotic hyperkeratosis to determine whether intracorneal vacuoles were present. Additional criteria evaluated were the size and location of the vacuoles and the degree of parakeratosis. Cases examined included dogs with primary idiopathic seborrhoea, necrolytic migratory erythema (NME), Malassezia dermatitis, zinc-responsive dermatosis, hereditary nasal hyperkeratosis of Labrador Retriever dogs, thallotoxicosis and CFP. Thirty-seven cases (37/111, 33%) had intracorneal vacuoles, including nine cases of primary idiopathic seborrhoea (9/29, 31%), 10 cases of NME (10/18, 56%), five cases of Malassezia dermatitis (5/19, 26%), five cases of zinc-responsive dermatosis (5/36, 14%), five cases of hereditary nasal hyperkeratosis (5/5, 100%) and three cases of CFP (3/3, 100%). If present, intracorneal vacuoles were found throughout all layers of the parakeratin. The sizes of intracorneal vacuoles varied among diseases, but large (> 5 microm) vacuoles only were present in CFP. Biopsies with a larger degree of parakeratosis were significantly more likely to have intracorneal vacuoles (P = < 0.001). Based on this study, intracorneal vacuoles are a common finding in many parakeratotic skin diseases of the dog, but large (> 5 microm) vacuoles are found only in CFP.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".