Pediatric cholesteatoma and variants in the gene encoding connexin 26
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Connexin 26 is a gap junction protein encoded by the GJB2 gene. It is expressed in cholesteatoma, and mutations cause proliferative skin disorders and sensorineural hearing loss (SNHL). Deletions of GJB6, which encodes connexin 30, cause SNHL in a digenic manner with a heterozygous GJB2 mutation. We hypothesize that GJB2 and GJB6 mutations might influence the development of cholesteatoma. STUDY DESIGN: Prospective observational study to identify GJB mutations in pediatric cholesteatoma. METHODS: Peripheral blood samples from 98 children with cholesteatoma were screened for mutations in the GJB2 gene by direct sequencing of the coding region (exon 2 and the intron/exon boundary). Deletions of the GJB6 gene were tested using multiple ligation probe amplification methods. GJB status was compared with other populations and patient age and extent of cholesteatoma at presentation. RESULTS: Fourteen children had at least one GJB2 variant (14%). Of these, three had two variants. Two of the variants were neutral polymorphisms. One child with the GJB2 genotype 35delG/35delG also had SNHL. No correlation was found between GJB2 status and patient age or cholesteatoma severity at presentation. No GJB6 deletions were found. CONCLUSIONS: GJB2 gene variants are present in a minority of children with cholesteatoma, but may be more common than in normal populations. It is conceivable that alterations of connexin 26 expression could contribute to the multifactorial disease process in cholesteatoma by modifying the cell-to-cell communication that is important in proliferation and migration of keratinocytes.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".