Glucosensing in parvocellular neurons of the rat hypothalamic paraventricular nucleus
Bibliographic record
Abstract
Specialized hypothalamic neurons responding to rising extracellular glucose via increases or decreases in their electrical activity [glucose-excited (GE) and glucose-inhibited (GI) cells, respectively] have been reported in the hypothalamic arcuate, ventromedial and lateral nuclei. The hypothalamic paraventricular nucleus (PVN) is an important neurosecretory and preautonomic output nucleus. We tested whether parvocellular PVN neurons also possess glucosensing properties, using patch-clamp recording and immunocytochemistry. Putative neurosecretory (p-NS) and preautonomic (p-PA) cells were identified electrophysiologically. Although parvocellular neurons were insensitive to transitions from 10 to 2.5 mm glucose, approximately 68% of p-PA cells responded directly to glucopenia (mimicked by a step to 0.2 mm glucose) with an increased membrane conductance. Of these, approximately 24% hyperpolarized (accompanied by an outward current) and thus were GE, approximately 26% depolarized (with an inward current, thus GI) and approximately 18% did not change membrane potential. The concentration dependence of the glucose response was similar for both GE and GI cells (EC(50) of 0.67-0.7 mm), but was steep, with Hill slopes of 3-4. The K(ATP) channel blockers glibenclamide and tolbutamide did not prevent, while the K(ATP) channel opener diazoxide did not mimic, the effects of low glucose on GE neurons. Moreover, the K(ATP) sulfonylurea receptor SUR1 was not detected in glucosensitive neurons. We conclude that the PVN contains previously unknown GE and GI cells that could participate in regulation of autonomic functions. GE neurons in the PVN sense ambient glucose via a unique mechanism, probably independent of K(ATP) channels, in contrast to neurons in other hypothalamic nuclei.
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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) | 0.001 | 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".