Serotonin (5-HT) Activation of Immortalized Hypothalamic Neuronal Cells Through the 5-HT1B Serotonin Receptor
Bibliographic record
Abstract
Serotonin [or 5-hydroxytryptamine or (5-HT)] has been implicated as a key modulator in energy homeostasis and a primary focus in the treatment of obesity. There is growing evidence that 5-HT, acting through the 5-HT 1B receptor (5-HT(1B)R) in the paraventricular nucleus of the hypothalamus (PVN), is important to this regulation. However, there is some contention as to whether 5-HT(1B)R action occurs directly on PVN neurons or indirectly via inhibitory inputs into the PVN. To address these questions, we used a novel clonal, hypothalamic neuronal cell model, adult mouse hypothalamic-2/30 (mHypoA-2/30), expressing a PVN-specific marker, single-minded homolog 1, as well as a complement of PVN neuropeptides, including TRH, vasopressin, ghrelin, nucleobindin-2, and galanin. Adult mouse hypothalamic-2/30 neurons were also found to express the 5-HT(1B)R and 5-HT 6 receptor, but not 2C, all previously linked to feeding regulation. Direct serotonergic stimulation (100 nm to 10 μm) of these neurons resulted in dose-dependent cFos activation. 5-HT (10 μm) suppressed forskolin-induced cAMP levels and induced a rise in intracellular Ca(2+) through ER Ca(2+) release, effects that were mimicked by the 5-HT(1B)R agonists, CGS12066B and CP93129, and that were attenuated in the presence of the 5-HT(1B)R-specific inhibitors, GR55562 and isamoltane hemifumarate. Modest transcriptional changes in ghrelin and nucleobindin-2 were also observed in response to 100 nm and 10 μm 5-HT, respectively. These findings support the model wherein 5-HT action through the 1B receptor subtype occurs directly on PVN neurons, leading to potential modification of neuronal transcriptional and secretory machinery.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".