Do Genetic Mutations and Genotypes Contribute to Onychomycosis?
Bibliographic record
Abstract
BACKGROUND: The variability in susceptibility to onychomycosis for individuals exposed to the same environmental risk factors raises the possibility that there may be individuals with a genetic predisposition to dermatophyte infection. OBJECTIVE: To determine whether there are genetic mutations or genotypes which contribute to onychomycosis. METHODS: The PubMed database was searched for examples of immune deficiencies resulting in dermatophyte infections. RESULTS: There are mutations in the innate immune receptors Dectin-1 and its adaptor protein CARD9 which result in familial mucocutaneous infections. There are also specific human leukocyte antigen genotypes that are more common in individuals and families with a high prevalence of onychomycosis. In addition, some patients have been reported with insufficient levels of CD4+CD25+ regulatory T cells. These deficits impair a full innate and adaptive immune response and may result in chronic or recurrent infections. CONCLUSIONS: There are documented mutations and genotypes that contribute to familial and individual susceptibility to onychomycosis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 0.001 |
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".