Genomic analysis of gum disease and hypertrichosis in foxes
Bibliographic record
Abstract
Since the 1940s, a proliferative gingival disease called hereditary hyperplastic gingivitis (HHG) has been described in the farmed silver fox, Vulpes vulpes (Dyrendahl and Henricson 1960). HHG displays an autosomal recessive transmission and has a pleiotropic relationship with superior fur quality in terms of length and thickness of guard hairs. An analogous human disease, hereditary gingival fibromatosis (HGF), is characterized by a predominantly autosomal dominant transmission and a complex etiology, occurring either as an isolated condition or as a part of a syndrome. Similar to HHG, the symptom most commonly associated with syndromic HGF is hypertrichosis. Here we explore potential mechanisms involved in HHG by comparison to known genetic information about hypertrichosis co-occurring with HGF, using an Affymetrix canine genome microarray platform, quantitative PCR, and candidate gene sequencing. We conclude that the mitogen-activated protein kinase pathway is involved in HHG, however despite involvement of the mitogen-activated protein kinase kinase 6 gene in congenital hypertrichosis with gingival fibromatosis in humans, this gene did not contain any fixed mutations in exons or exon-intron boundaries in HHG-affected foxes, suggesting that it is not causative of HHG in the farmed silver fox population. Differential up-regulation of MAP2K6 gene in HHG-affected foxes does implicate this gene in the HHG phenotype.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".