Human cystic fibrosis airway epithelia have reduced Cl <sup>−</sup> conductance but not increased Na <sup>+</sup> conductance
Bibliographic record
Abstract
Loss of cystic fibrosis transmembrane conductance regulator (CFTR) anion channel function causes cystic fibrosis (CF) lung disease. CFTR is expressed in airway epithelia, but how CF alters electrolyte transport across airway epithelia has remained uncertain. Recent studies of a porcine model showed that in vivo, excised, and cultured CFTR(-/-) and CFTR(ΔF508/ΔF508) airway epithelia lacked anion conductance, and they did not hyperabsorb Na(+). Therefore, we asked whether Cl(-) and Na(+) conductances were altered in human CF airway epithelia. We studied differentiated primary cultures of tracheal/bronchial epithelia and found that transepithelial conductance (Gt) under basal conditions and the cAMP-stimulated increase in Gt were markedly attenuated in CF epithelia compared with non-CF epithelia. These data reflect loss of the CFTR anion conductance. In CF and non-CF epithelia, the Na(+) channel inhibitor amiloride produced similar reductions in Gt and Na(+) absorption, indicating that Na(+) conductance in CF epithelia did not exceed that in non-CF epithelia. Consistent with previous reports, adding amiloride caused greater reductions in transepithelial voltage and short-circuit current in CF epithelia than in non-CF epithelia; these changes are attributed to loss of a Cl(-) conductance. These results indicate that Na(+) conductance was not increased in these cultured CF tracheal/bronchial epithelia and point to loss of anion transport as key to airway epithelial dysfunction in CF.
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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 | 0.000 |
| 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) | 0.003 | 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 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".