Pulmonary neuroendocrine H146 cells as hypercapnic sensors
Bibliographic record
Abstract
Singular pulmonary neuroendocrine cells (pNEC) or clusters called pulmonary neuroepithelial bodies (NEBs) are widely distributed within the airway mucosa of human and mammalian lungs. NEB cells produce amines (e.g. 5‐HT), and are thought to modulate the control of breathing in response to low O 2 conditions (hypoxia). The mechanism by which these cells detect hypoxia is thought to occur via activity of NADPH oxidase in conjunction with K + channels. Exposure of NEBs to hypoxia causes K + channel closure, membrane depolarization and 5‐HT release. In other chemosensory organs (e.g. the well studied carotid body) the sensory cells are often polymodal, capable of responding to high CO 2 levels (hypercapnia) and/or hypoxia (usually via different mechanisms). However it is currently unknown whether NEBs can sense hypercapnia in addition to hypoxia. Using molecular biology, immunocytochemistry, and electrophysiology we explore whether H146 cells (a model cell line of pNEC/NEB) are capable of responding hypercapnia. In other hypercapnic sensing organs (e.g. adrenal chromaffin cells), carbonic anhydrase 2 (CA II) is thought to play a role in mediating the hypercapnic response. Although native NEB do express this isoform (among several others), CA II is not expressed in H146 cells. Nevertheless they do respond to hypercapnia via membrane depolarization and 5‐HT release, as determined using electrophysiology. This finding suggests that another isoform of CA or alternate mechanism may be involved in mediating hypercapnic sensitivity in H146 cells. Funded by: NSERC Discovery Grant
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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 | 0.000 |
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".