Expression of CFTR and Cl<sup>−</sup>conductances in cells of pulmonary neuroepithelial bodies
Bibliographic record
Abstract
The pulmonary neuroendocrine cell system comprises solitary neuroendocrine cells and clusters of innervated cells or neuroepithelial bodies (NEBs). NEBs figure prominently during the perinatal period when they are postulated to be involved in physiological adaptation to air breathing. Previous studies have documented hyperplasia of NEBs in cystic fibrosis (CF) lungs and increased neuropeptide (bombesin) content produced by these cells, possibly secondary to chronic hypoxia related to CF lung disease. However, little is known about the role of NEBs in the pathogenesis of CF lung disease. In the present study, using a panel of cystic fibrosis transmembrane conductance regulator (CFTR)-specific antibodies and confocal microscopy in combination with RT-PCR, we demonstrate expression of CFTR message and protein in NEB cells of rabbit neonatal lungs. NEB cells expressed CFTR along with neuroendocrine markers. Confocal microscopy established apical membrane localization of the CFTR protein in NEB cells. Cl(-) conductances corresponding to functional CFTR were demonstrated in NEB cells in a fresh lung slice preparation. Our findings suggest that NEBs, and related neuroendocrine mechanisms, likely play a role in the pathogenesis of CF lung disease, including the early stages before establishment of chronic infection and chronic lung disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".