Characterization of basolateral K<sup>+</sup> channels underlying anion secretion in the human airway cell line Calu‐3
Bibliographic record
Abstract
Transepithelial anion secretion in many tissues depends upon the activity of basolateral channels. Using monolayers of the Calu-3 cell line, a human submucosal serous cell model mounted in an Ussing chamber apparatus, we investigated the nature of the K+ channels involved in basal, cAMP- and Ca2+-stimulated anion secretion, as reflected by the transepithelial short circuit current (I(sc)). The non-specific K+ channel inhibitor Ba2+ inhibited the basal I(sc) by either 77 or 16 % when applied directly to the basolateral or apical membranes, respectively, indicating that a basolateral K+ conductance is required for maintenance of basal anion secretion. Using the K+ channel blockers clofilium and clotrimazole, we found basal I(sc) to be sensitive to clofilium, with a small clotrimazole-sensitive component. By stimulating the cAMP and Ca2+ pathways, we determined that cAMP-stimulated anion secretion was almost entirely abolished by clofilium, but insensitive to clotrimazole. In contrast, the Ca2+-stimulated response was sensitive to both clofilium and clotrimazole. Thus, pharmacologically distinct basolateral K+ channels are differentially involved in the control of anion secretion under different conditions. Isolation of the basolateral K+ conductance in permeabilized monolayers revealed a small basal and forskolin-stimulated I(sc). Finally, using the reverse transcriptase-polymerase chain reaction, we found that Calu-3 cells express the K+ channel genes KCNN4 and KCNQ1 and the subunits KCNE2 and KCNE3. We conclude that while KCNN4 contributes to Ca2+-activated anion secretion by Calu-3 cells, basal and cAMP-activated secretion are more critically dependent on other K+ channel types, possibly involving one or more class of KCNQ1-containing channel complexes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".