SPLUNC1 expression reduces surface levels of the epithelial sodium channel (ENaC) in<i>Xenopus laevis</i>oocytes
Bibliographic record
Abstract
Throughout the body, the epithelial Na(+) channel (ENaC) plays a critical role in salt and liquid homeostasis. In cystic fibrosis airways, for instance, improper regulation of ENaC results in hyperabsorption of sodium that causes dehydration of airway surface liquid. This dysregulation then contributes to mucus stasis and chronic lung infections. ENaC is known to undergo proteolytic cleavage, which is required for its ability to conduct Na(+) ions. We have previously shown that the short, palate lung and nasal epithelial clone (SPLUNC1) binds to and inhibits ENaC in both airway epithelia and in Xenopus laevis oocytes. In this study, we found that SPLUNC1 was more potent at inhibiting ENaC than either SPLUNC2 or long PLUNC1 (LPLUNC1), two other PLUNC family proteins that are also expressed in airway epithelia. Furthermore, we were able to shed light on the potential mechanism of SPLUNC1's inhibition of ENaC. While SPLUNC1 did not inhibit proteolytic activity of trypsin, it significantly reduced ENaC currents by reducing the number of ENaCs in the plasma membrane. A better understanding of ENaC's regulation by endogenous inhibitors may aid in the development of novel therapies designed to inhibit hyperactive ENaC in cystic fibrosis epithelia.
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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) | 0.002 | 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".