Oxidative stress increases chloride transport in human CF nasal epithelial cell
Bibliographic record
Abstract
Cystic fibrosis is a genetic disease characterized by a defective CFTR protein, it is associated with an oxidative stress response leading to structural damage. The aim of the study was to determine the impact of oxidative stress on Cl − transport in human non‐CF and CF nasal epithelial cells. Cells were grown on a Costar filter at air/liquid interface and were treated with DMNQ 15μM for 24 hours. Cl − transport was monitored in Ussing chamber by measuring short‐circuit current (I sc ) following an amphotericin B permeabilization of the basolateral membrane in presence of a Cl − gradient. Treatment with DMNQ lead to an increase of 5.6 μA/cm 2 in total I sc in CF cells but no change were observed in non‐CF cells. Forskolin and genistein stimulation induced ΔI sc of 22.4 μA/cm 2 inhibited by the specific CFTR inhibitor (CFTRinh 172), in both control and DMNQ treated non‐CF cells. In CF cells, these activators induced a ΔI sc of 1.19 μA/cm 2 in control cells compared to 5.43 μA/cm 2 in DMNQ treated cells. This increase was inhibited by NPPB, a broad range Cl − inhibitor. These result suggest that the DMNQ induced probably a non‐CFTR dependent Cl − current in CF cells. Further studies are needed to characterise the chloride channels involved in this response. Supported by the CCFF and CIHR.
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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 | 0.000 |
| 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".