ENaC‐mediated effects assessed by MRI in a rat model of hypertonic saline‐induced lung hydration
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The epithelial sodium channel (ENaC) regulates airway mucosal hydration and mucus clearance. The lack of such regulation in cystic fibrosis patients leads to desiccation of the airway lumen, resulting in mucostasis that establishes the environment for infections. Osmotic agents and negative ENaC regulators can be used to restore mucosal hydration. We aimed to assess whether: (i) osmotically driven fluid flux into the rat lung could be quantified in vivo by magnetic resonance imaging (MRI); and (ii) the MRI signals could be modulated through the regulation of ENaC function. EXPERIMENTAL APPROACH: Lung images from spontaneously breathing rats were acquired following intra-tracheal (i.t.) administration of physiological or hypertonic saline (HS). Compounds known to modulate the ENaC function were given i.t. prior to saline. Volumes of fluid signals were quantified on the images. KEY RESULTS: A tonicity-dependent increase in lung fluid was demonstrated following HS administration. Pretreatment with the ENaC blockers, amiloride or 552-02, resulted in an enhancement of HS-induced lung fluid signals, which were detectable for up to 4 h, consistent with a role for ENaC in fluid clearance. Aprotinin, a serine protease inhibitor that attenuates ENaC function, likewise enhanced the HS-induced increase in lung fluid signal, while alpha(1)-anti-trypsin was without significant effect. CONCLUSIONS AND IMPLICATIONS: Proton MRI provides a non-invasive technique for studying modulators of lung fluid hydration in rat lung in vivo. The pharmacological sensitivity of MRI-detected fluid signals is consistent with ENaC-mediated fluid reabsorption after HS. This target-related readout may be used to characterize new ENaC modulators.
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) | 0.000 | 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".