Na<sup>+</sup>‐Activated K<sup>+</sup> Channels in Rat Supraoptic Neurones
Bibliographic record
Abstract
The magnocellular neurosecretory cells (MNCs) of the hypothalamus secrete the neurohormones vasopressin and oxytocin. The systemic release of these hormones depends on the rate and pattern of MNC firing and it is therefore important to identify the ion channels that contribute to the electrical behaviour of MNCs. In the present study, we report evidence for the presence of Na(+) -activated K(+) (KN a ) channels in rat MNCs. KN a channels mediate outwardly rectifying K(+) currents activated by the increases in intracellular Na(+) that occur during electrical activity. Although the molecular identity of native KN a channels is unclear, their biophysical properties are consistent with those of expressed Slick (slo 2.1) and Slack (slo 2.2) proteins. Using immunocytochemistry and Western blot experiments, we found that both Slick and Slack proteins are expressed in rat MNCs. Using whole cell voltage clamp techniques on acutely isolated rat MNCs, we found that inhibiting Na(+) influx by the addition of the Na(+) channel blocker tetrodotoxin or the replacement of Na(+) in the external solution with Li(+) caused a significant decrease in sustained outward currents. Furthermore, the evoked outward current density was significantly higher in rat MNCs using patch pipettes containing 60 mm Na(+) than it was when patch pipettes containing 0 mm Na(+) were used. Our data show that functional KN a channels are expressed in rat MNCs. These channels could contribute to the activity-dependent afterhyperpolarisations that have been identified in the MNCs and thereby play a role in the regulation of their electrical behaviour.
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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) | 0.001 | 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".