Cigarette smoke and calcium conspire to impair CFTR function in airway epithelia
Bibliographic record
Abstract
To maintain health and function in response to inhaled environmental irritants and toxins, the lungs and airways depend upon an innate defense system that involves the secretion of mucus (i.e., mucin, salts, and water) by airway epithelium onto the apical surface to trap foreign particles. Airway mucus is then transported in an oral direction via ciliary beating and coughing, which helps to keep the airways clear. CFTR (cystic fibrosis transmembrane conductance regulator) is a cAMP-regulated Cl(-) channel in the apical membrane of epithelium that contributes to salt and water secretion onto the luminal surface of airways, thereby ensuring that secreted mucus is sufficiently hydrated for movement along the epithelial surface. Dehydration of airway mucus, as occurs in cystic fibrosis, results in a more viscous, less mobile secretion that compromises the lung’s innate defense system by facilitating a build-up of foreign particles and bacterial growth. Related to this situation is chronic obstructive pulmonary disease (COPD), which is a leading cause of death globally. A major cause of COPD is cigarette smoking, which has been reported to decrease the cellular levels of CFTR in airway epithelia. In their recent article, Rasmussen and coworkers now report that exposure to cigarette smoke elevates cytosolic free Ca(2+) in airway epithelium, leading to decreased surface localization and cellular expression of CFTR and reduced levels of secreted airway surface liquid. Blocking this increase in cytosolic Ca(2+) largely prevented CFTR loss in airway epithelium and surprisingly, cellular lysosomes appear to be a major source for smoke-induced Ca(2+) elevation.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".