A novel O2-sensing mechanism in rat glossopharyngeal neurones mediated by a halothane-inhibitable background K+ conductance
Bibliographic record
Abstract
Modulation of K+ channels by hypoxia is a common O2-sensing mechanism in specialised cells. More recently, acid-sensitive TASK-like background K+ channels, which play a key role in setting the resting membrane potential, have been implicated in O2-sensing in certain cell types. Here, we report a novel O2 sensitivity mediated by a weakly pH-sensitive background K+ conductance in nitric oxide synthase (NOS)-positive neurones of the glossopharyngeal nerve (GPN). This conductance was insensitive to 30 mM TEA, 5 mM 4-aminopyridine (4-AP) and 200 microM Cd2+, but was reversibly inhibited by hypoxia (O2 tension (PO2) = 15 mmHg), 2-5 mM halothane, 10 mM barium and 1 mM quinidine. Notably, the presence of halothane occluded the inhibitory effect of hypoxia. Under current clamp, these agents depolarised GPN neurones. In contrast, arachidonic acid (5-10 microM) caused membrane hyperpolarisation and potentiation of the background K+ current. This pharmacological profile suggests the O2-sensitive conductance in GPN neurones is mediated by a class of background K+ channels different from the TASK family; it appears more closely related to the THIK (tandem pore domain halothane-inhibited K+) subfamily, or may represent a new member of the background K+ family. Since GPN neurones are thought to provide NO-mediated efferent inhibition of the carotid body (CB), these channels may contribute to the regulation of breathing during hypoxia via negative feedback control of CB function, as well as to the inhibitory effect of volatile anaesthetics (e.g. halothane) on respiration.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".