Histologic morphology and involucrin, filaggrin, and keratin expression in normal canine skin from dogs of different breeds and coat types
Bibliographic record
Abstract
The purpose of this study was to measure the thickness of canine epidermis at various anatomical sites according to localization of cornified envelopes (involucrin and filaggrin), keratins (keratin 10, 5), and their mRNA expression. This was done in the skin of five breeds of dogs including seven poodles, six golden retrievers, six Shih Tzus, four pugs, and four Labrador retrievers. Epidermal thickness of the stratum corneum and nucleated epidermal layer was significantly different. The greatest thickness was observed in the digital web area and the thinnest epidermis was in the axilla. Epidermal thickness was also significantly different between the breeds (p < 0.05). Immunohistochemical staining scores revealed significant decreases of involucrin, filaggrin, and keratin 10 in the ventral and weight-bearing sites, and a relative increase of keratin 5 (p < 0.05). q-PCR analysis showed that their the levels of mRNA were positively correlated with expression of the corresponding proteins in skin samples (p < 0.05). The present study is the first to report the relationship between epidermal gene expression and histologic morphology of the skin in normal dogs. Further studies will be essential to fully understand the pathogenesis of skin barrier dysfunctions in canines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".