NOX2 (gp91<sup>phox</sup>) is a predominant O<sub>2</sub> sensor in a human airway chemoreceptor cell line: biochemical, molecular, and electrophysiological evidence
Bibliographic record
Abstract
Pulmonary neuroepithelial bodies (NEBs), composed of clusters of amine [serotonin (5-HT)] and peptide-producing cells, are widely distributed within the airway mucosa of human and animal lungs. NEBs are thought to function as airway O(2)-sensors, since they are extensively innervated and release 5-HT upon hypoxia exposure. The small cell lung carcinoma cell line (H146) provides a useful model for native NEBs, since they contain (and secrete) 5-HT and share the expression of a membrane-delimited O(2) sensor [classical NADPH oxidase (NOX2) coupled to an O(2)-sensitive K(+) channel]. In addition, both native NEBs and H146 cells express different NADPH oxidase homologs (NOX1, NOX4) and its subunits together with a variety of O(2)-sensitive voltage-dependent K(+) channel proteins (K(v)) and tandem pore acid-sensing K(+) channels (TASK). Here we used H146 cells to investigate the role and interactions of various NADPH oxidase components in O(2)-sensing using a combination of coimmunoprecipitation, Western blot analysis (quantum dot labeling), and electrophysiology (patchclamp, amperometry) methods. Coimmunoprecipitation studies demonstrated formation of molecular complexes between NOX2 and K(v)3.3 and K(v)4.3 ion channels but not with TASK1 ion channels, while NOX4 associated with TASK1 but not with K(v) channel proteins. Downregulation of mRNA for NOX2, but not for NOX4, suppressed hypoxia-sensitive outward current and significantly reduced hypoxia -induced 5-HT release. Collectively, our studies suggest that NOX2/K(v) complexes are the predominant O(2) sensor in H146 cells and, by inference, in native NEBs. Present findings favor a NEB cell-specific plasma membrane model of O(2)-sensing and suggest that unique NOX/K(+) channel combinations may serve diverse physiological functions.
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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) | 0.001 | 0.001 |
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".