Locus Coeruleus Neurons’ Firing Pattern Is Regulated by ERG Voltage-Gated K+ Channels
Bibliographic record
Abstract
Locus coeruleus (LC) neurons, with their extensive innervations throughout the brain, control a broad range of physiological processes. Several ion channels have been characterized in LC neurons that control intrinsic membrane properties and excitability. However, ERG (ether-à-go-go–related gene) K+ channels that are particularly important in setting neuronal firing rhythms and automaticity have not as yet been discovered in the LC. Moreover, the neurophysiological and pathophysiological roles of ERG channels in the brain remain unclear despite their expression in several structures. By performing immunohistochemical investigations, we found that ERG-1A, ERG-1B, ERG-2 and ERG-3 are highly expressed in the LC neurons of mice. To examine the functional role of ERG channels, current-clamp recordings were performed on mouse LC neurons in brain slices under visual control. ERG channel blockade by WAY-123,398, a class III anti-arrhythmic agent, increased the spontaneous firing activity and discharge irregularity of LC neurons. Here, we have shown the presence of distinct ERG channel subunits in the LC which play an imperative role in modulating neuronal discharge patterns. Thus, we propose that ERG channels are important players behind the changes in, and/or maintenance of, LC firing patterns that are implicated in the generation of different behaviors and in several disorders.
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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) | 0.000 | 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".