Pulmonary neuroepithelial bodies are polymodal airway sensors: Evidence for CO<sub>2</sub>/H<sup>+</sup>sensing
Bibliographic record
Abstract
Pulmonary neuroepithelial bodies (NEB) in mammalian lungs are thought to function as airway O2 sensors that release serotonin (5-HT) in response to hypoxia. Direct evidence that NEB cells also respond to airway hypercapnia/acidosis (CO2/H(+)) is presently lacking. We tested the effects of CO2/H(+) alone or in combination with hypoxia on 5-HT release from intact NEB cells in a neonatal hamster lung slice model. For the detection of 5-HT release we used carbon fiber amperometry. Fluorescence Ca(2+) imaging method was used to assess CO2/H(+)-evoked changes in intracellular Ca(2+). Exposure to 10 and 20% CO2 or pH 6.8-7.2 evoked significant release of 5-HT with a distinct rise in intracellular Ca(2+) in hamster NEBs. This secretory response was dependent on the voltage-gated entry of extracellular Ca(2+). Moreover, the combined effects of hypercapnia and hypoxia were additive. Critically, an inhibitor of carbonic anhydrase (CA), acetazolamide, suppressed CO2/H(+)-mediated 5-HT release. The expression of mRNAs for various CA isotypes, including CAII, was identified in NEB cells from human lung, and protein expression was confirmed by immunohistochemistry using a specific anti-CAII antibody on sections of human and hamster lung. Taken together our findings provide strong evidence for CO2/H(+) sensing by NEB cells and support their role as polymodal airway sensors with as yet to be defined functions under normal and disease conditions.
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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 | 0.001 | 0.000 |
| 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".