Subcellular Dynamics of Somatostatin Receptor Subtype 1 in the Rat Arcuate Nucleus: Receptor Localization and Synaptic Connectivity Vary in Parallel with the Ultradian Rhythm of Growth Hormone Secretion
Bibliographic record
Abstract
Growth hormone (GH) secretion in male rats exhibits a 3.3 h ultradian rhythm generated by the reciprocal interaction of GH-releasing hormone (GHRH) and somatostatin (SRIF). SRIF receptor subtypes sst(1) and sst(2) are highly expressed in GHRH neurons of the hypothalamic arcuate nucleus (ARC). We previously demonstrated an ultradian oscillation in binding of SRIF analogs to the ARC in relation to GH peaks and troughs. Here we tested the hypothesis that these ultradian changes in SRIF binding are due to differential plasma membrane targeting of sst(1) receptors in ARC neurons using immunocytochemistry and electron microscopy. We found that 87% of sst(1)-positive ARC neurons also synthesized GHRH. Subcellularly, 80% of sst(1) receptors were located intracellularly and 20% at the plasma membrane regardless of GH status. However, whereas 30% of the cell-surface sst(1) receptors were located perisynaptically or subsynaptically following exposure to high GH secretion, this fraction was increased to 42% following a GH trough period (p = 0.05). Furthermore, the relative abundance of symmetric and asymmetric synapses on sst(1)-positive dendrites also varied significantly, depending on the GH cycle, from approximately equal numbers following GH troughs to 70:30 in favor of symmetric, i.e., inhibitory, inputs after GH peaks (p < 0.02). These findings suggest that postsynaptic localization of sst(1) receptors and synaptic connectivity in the ARC undergo pronounced remodeling in parallel with the GH rhythm. Such synaptic plasticity may be an important mechanism by which sst(1) mediates SRIF's cyclical effects on ARC GHRH neurons to generate the ultradian rhythm of GH secretion.
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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".