Expression of functional nicotinic acetylcholine receptors in neuroepithelial bodies of neonatal hamster lung
Bibliographic record
Abstract
Pulmonary neuroepithelial bodies (NEB) are presumed airway chemoreceptors involved in respiratory control, especially in the neonate. Nicotine is known to affect both lung development and control of breathing. We report expression of functional nicotinic acetylcholine receptors (nAChR) in NEB cells of neonatal hamster lung using a combination of morphological and electrophysiological techniques. Nonisotopic in situ hybridization method was used to localize mRNA for the beta 2-subunit of nAChR in NEB cells. Double-label immunofluorescence confirmed expression of alpha 4-, alpha 7-, and beta 2-subunits of nAChR in NEB cells. The electrophysiological characteristics of nAChR in NEB cells were studied using the whole cell patch-clamp technique on fresh lung slices. Application of nicotine ( approximately 0.1-100 microM) evoked inward currents that were concentration dependent (EC50 = 3.8 microM; Hill coefficient = 1.1). ACh (100 microM) and nicotine (50 microM) produced two types of currents. In most NEB cells, nicotine-induced currents had a single desensitizing component that was blocked by mecamylamine (50 microM) and dihydro-beta-erythroidine (50 microM). In some NEB cells, nicotine-induced current had two components, with fast- and slow-desensitizing kinetics. The fast component was selectively blocked by methyllcaconitine (MLA, 10 nM), whereas both components were inhibited by mecamylamine. Choline (0.5 mM) also induced an inward current that was abolished by 10 nM MLA. These studies suggest that NEB cells in neonatal hamster lung express functional heteromeric alpha 3 beta 2, alpha 4 beta 2, and alpha 7 nAChR and that cholinergic mechanisms could modulate NEB chemoreceptor function under normal and pathological 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 | 0.000 | 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".