Molecular consequences of cystic fibrosis transmembrane regulator (CFTR) gene mutations in the exocrine pancreas
Bibliographic record
Abstract
BACKGROUND AND AIMS: We tested the hypothesis that the actual or predicted consequences of mutations in the cystic fibrosis transmembrane regulator gene correlate with the pancreatic phenotype and with measures of quantitative exocrine pancreatic function. METHODS: We assessed 742 patients with cystic fibrosis for whom genotype and clinical data were available. At diagnosis, 610 were pancreatic insufficient, 110 were pancreatic sufficient, and 22 pancreatic sufficient patients progressed to pancreatic insufficiency after diagnosis. RESULTS: We identified mutations on both alleles in 633 patients (85.3%), on one allele in 95 (12.8%), and on neither allele in 14 (1.9%). Seventy six different mutations were identified. The most common mutation was DeltaF508 (71.3%) followed by G551D (2.9%), G542X (2.3%), 621+1G-->T (1.2%), and W1282X (1.2%). Patients were categorized into five classes according to the predicted functional consequences of each mutation. Over 95% of patients with severe class I, II, and III mutations were pancreatic insufficient or progressed to pancreatic insufficiency. In contrast, patients with mild class IV and V mutations were consistently pancreatic sufficient. In all but four cases each genotype correlated exclusively with the pancreatic phenotype. Quantitative data of acinar and ductular secretion were available in 93 patients. Patients with mutations belonging to classes I, II, and III had greatly reduced acinar and ductular function compared with those with class IV or V mutations. CONCLUSION: The predicted or known functional consequences of specific mutant alleles correlate with the severity of pancreatic disease in cystic fibrosis.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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".