Mutations in the Cystic Fibrosis Transmembrane Regulator Gene and <b> <i>In Vivo</i> </b> Transepithelial Potentials
Bibliographic record
Abstract
AIM: To examine the relationship between cystic fibrosis transmembrane regulator gene mutations (CFTR) and in vivo transepithelial potentials. METHODS: We prospectively evaluated 162 men including 31 healthy subjects, 21 obligate heterozygotes, 60 with congenital bilateral absence of the vas deferens (CBAVD) and 50 with CF by extensive CFTR genotyping, sweat chloride and nasal potential difference testing. RESULTS: Six (10%) men with CBAVD carried no CFTR mutations, 18 (30%) carried one mutation, including the 5T variant, and 36 (60%) carried mutations on both alleles, for a significantly higher rate carrying one or more mutations than healthy controls (90% versus 19%, p < 0.001). There was an overlapping spectrum of ion channel measurements among the men with CBAVD, ranging from values in the control and obligate heterozygote range at one extreme, to values in the CF range at the other. All pancreatic-sufficient patients with CF and 34 of 36 patients with CBAVD with mutations on both alleles carried at least one mild mutation. However, the distribution of mild mutations in the two groups differed greatly. Genotyping, sweat chloride and nasal potential difference (alone or in combination) excluded CF in all CBAVD men with no mutations. CF was confirmed in 56% and 67% of CBAVD men carrying 1 and 2 CFTR mutations, respectively. CONCLUSION: Abnormalities of CFTR transepithelial function correlate with the number and severity of CFTR gene mutations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".