Transforming Growth Factor-β1 Decreases Expression of the Epithelial Sodium Channel αENaC and Alveolar Epithelial Vectorial Sodium and Fluid Transport via an ERK1/2-dependent Mechanism
Bibliographic record
Abstract
Acute lung injury (ALI) is characterized by the flooding of the alveolar airspaces with protein-rich edema fluid and diffuse alveolar damage. We have previously reported that transforming growth factor-beta1 (TGF-beta1) is a critical mediator of ALI after intratracheal administration of bleomycin or Escherichia coli endotoxin, at least in part due to effects on lung endothelial and alveolar epithelial permeability. In the present study, we hypothesized that TGF-beta1 would also decrease vectorial ion and water transport across the distal lung epithelium. Therefore, we studied the effect of active TGF-beta1 on 22Na+ uptake across monolayers of primary rat and human alveolar type II (ATII) cells. TGF-beta1 significantly reduced the amiloride-sensitive fraction of 22Na+ uptake and fluid transport across monolayers of both rat and human ATII cells. TGF-beta1 also significantly decreased alphaENaC mRNA and protein expression and inhibited expression of a luciferase reporter downstream of the alphaENaC promoter in lung epithelial cells. The inhibitory effect of TGF-beta1 on sodium uptake and alphaENaC expression in ATII cells was mediated by activation of the MAPK, ERK1/2. Consistent with the in vitro results, TGF-beta1 inhibited the amiloride-sensitive fraction of the distal airway epithelial fluid transport in an in vivo rat model at a dose that was not associated with any change in epithelial protein permeability. These data indicate that increased TGF-beta1 activity in the distal airspaces during ALI promotes alveolar edema by reducing distal airway epithelial sodium and fluid clearance. This reduction in sodium and fluid transport is attributable in large part to a reduction in apical membrane alphaENaC expression mediated through an ERK1/2-dependent inhibition of the alphaENaC promoter activity.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".