Pendrin Mediates Bicarbonate Secretion and Enhances Cystic Fibrosis Transmembrane Conductance Regulator Function in Airway Surface Epithelia
Bibliographic record
Abstract
Abstract Bicarbonate facilitates mucin unpacking and bacterial killing; however, its transport mechanisms in the airways are not well understood. cAMP stimulates anion efflux through the cystic fibrosis (CF) transmembrane conductance regulator (CFTR; ABCC7) anion channel, and this is defective in CF. The anion exchanger pendrin (SLC26A4) also mediates HCO3 − efflux and is upregulated by proinflammatory cytokines. Here, we examined pendrin and CFTR expression and their contributions to HCO3 − secretion by human nasal and bronchial epithelia. In native tissue, both proteins were most abundant at the apical pole of ciliated surface cells with little expression in submucosal glands. In well-differentiated primary nasal and bronchial cell cultures, IL-4 dramatically increased pendrin mRNA levels and apical immunostaining. Exposure to low-Cl− apical solution caused intracellular alkalinization (ΔpHi) that was enhanced fourfold by IL-4 pretreatment. ΔpHi was unaffected by 4,4′-diisothiocyano-2,2′-stilbenedisulfonic acid (DIDS) or CFTR inhibitor CFTRinh-172, but was reduced by adenoviral shRNA targeting pendrin. Forskolin increased ΔpHi, and this stimulation was prevented by CFTRinh-172, implicating CFTR, yet forskolin only increased ΔpHi after pendrin expression had been induced by IL-4. The dependence of ΔpHi on pendrin suggests there is minimal electrical coupling between Cl− and HCO3 − fluxes and that CFTR activation increases anion exchange–mediated HCO3 − influx. Conversely, inducing pendrin expression increased forskolin-stimulated, CFTRinh-172–sensitive current by approximately twofold in epithelial and nonepithelial cells. We conclude that pendrin mediates most HCO3 − secretion across airway surface epithelium during inflammation and enhances electrogenic Cl− secretion via CFTR, as described for other SLC26A transporters.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".