Effects of acetylcholine and cholinergic antagonists on the activity of nucleus of the solitary tract (NTS) neurons
Bibliographic record
Abstract
It has been shown that acetylcholine (ACh) can depolarize neurons in the NTS (Shihara et al ., 1999). Thus, in the present study, we tested the electrophysiological effects of ACh, alone or combined with cholinergic antagonists, on the commissural NTS (cNTS) or intermediate NTS (iNTS). Coronal slices of the brainstem containing either cNTS or iNTS subnuclei, 600 μm apart, were obtained from male Sprague‐Dawley rats (p21–28 days) and used in whole cell patch clamp – current clamp recordings. ACh (10 mM, 1 min) was applied to slices 10 min before and 5 min after application of atropine (ATR, non‐selective muscarinic antagonist, 10 μM, 5 min) or mecamylamine (MEC, non‐selective nicotinic antagonists, 10 μM, 5 min). In cNTS, 7/12 neurons (58%) were depolarized by ACh (6.9 ± 1.5 mV), effects which were maintained in the presence of ATR (Control 5.1 ± 1.4, ATR 4.8 ± 0.7 mV, p>;0.05, n=6). However, MEC inhibited the ACh actions on cNTS (Control 10.4 ± 2.7, MEC 1.3 ± 0.9 mV, p<0.05, n=5). ACh also depolarized (9.8 ± 2.4 mV) 13/17 neurons (76%) of the iNTS. ATR reduced the depolarization induced by ACh (Control 12.5 ± 2.8, ATR 7.8 ± 2.4 mV, p<0.05, n=8), as well as MEC (Control 9.5 ± 2.0, MEC 2.9 ± 1.0 mV, p<0.05, n=8). These data demonstrate that ACh depolarizes cNTS neurons through actions on nicotinic receptors, while depolarizing effects in iNTS are apparently mediated by both receptors. Supported by: FAPESP, Canadian Inst. for Health Research
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".