Anion secretion by a model epithelium: more lessons from Calu‐3
Bibliographic record
Abstract
Anion transport drives fluid into the airways and is essential for humidifying inspired air and supplying surface liquid for mucociliary transport. Despite the importance of airway secretion in diseases such as cystic fibrosis, the cellular mechanisms remain poorly understood, in part due to the small size and complicated structure of the submucosal glands that produce most of the fluid. The Calu-3 human lung adenocarcinoma cell line has become a popular model for studying airway secretion because it can be cultured as a flat sheet, expresses the cystic fibrosis transmembrane conductance regulator and several acinar cell markers, forms polarized monolayers with tight junctions, has robust cAMP-stimulated anion transport, and responds to secretagogues that regulate the glands in vivo. However, some properties of Calu-3 cells are less consistent with those of native tissue. In particular, Calu-3 monolayers do not secrete chloride when stimulated by forskolin under short-circuit conditions. Bicarbonate ions are thought to carry the short-circuit current (I(sc)) and the drive secretion of alkaline fluid, in contrast to the neutral pH secretions that are produced by submucosal glands. Calu-3 cells also have abnormal chromosomes and characteristics of both serous and mucus cells. In this article, we discuss Calu-3 as a model in light of our ongoing studies, which suggest that Calu-3 monolayers resemble submucosal glands more closely than was previously thought. For example, we find that net HCO(3)(-) flux fully accounts for I(sc) as previously suggested but Cl(-) is the main anion transported under physiological conditions. A novel, HCO(3)(-) -dependent mechanism of Cl(-) transport is emerging which may explain secretion by Calu-3 and perhaps other epithelial cells.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 teacher head, 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".