Dehydration increases L‐type Ca<sup>2+</sup> current in rat supraoptic neurons
Bibliographic record
Abstract
The magnocellular neurosecretory cells of the hypothalamus (MNCs) regulate water balance by releasing vasopressin (VP) and oxytocin (OT) as a function of plasma osmolality. Release is determined largely by the rate and pattern of MNC firing, but sustained increases in osmolality also produce structural adaptations, such as cellular hypertrophy, that may be necessary for maintaining high levels of neuropeptide release. Since increases in Ca(2+) current could enhance exocytotic secretion, influence MNC firing patterns, and activate gene transcription and translation, we tested whether Ca(2+) currents in MNCs acutely isolated from the supraoptic nucleus (SON) of the hypothalamus are altered by 16-24 h of water deprivation. A comparison of whole-cell patch-clamp recordings demonstrated that dehydration causes a significant increase in the amplitude of current sensitive to the L-type Ca(2+) channel blocker nifedipine (from -56 +/- 6 to -99 +/- 10 pA; P < 0.001) with no apparent change in other components of Ca(2+) current. Post-recording immunocytochemical identification showed that this increase in current occurred in both OT- and VP-releasing MNCs. Radioligand binding studies of tissue from the SON showed there is also an increase in the density of binding sites for an L-type Ca(2+) channel ligand (from 51.5 +/- 4.8 to 68.1 +/- 4.1 fmol (mg protein)(-1); P < 0.05), suggesting that there was an increase in the number of L-type channels on the plasma membrane of the MNCs or some other cell type in the SON. There were no changes in the measured number of binding sites for an N-type Ca(2+) channel ligand. Dehydration was not associated with changes in the levels of mRNA coding for Ca(2+) channel alpha(1) subunits. These data are consistent with the hypothesis that a selective increase of L-type Ca(2+) current may contribute to the adaptation that occurs in the MNCs during dehydration.
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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) | 0.002 | 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".