Nitric Oxide Exerts Basal and Insulin-Dependent Anorexigenic Actions in POMC Hypothalamic Neurons
Bibliographic record
Abstract
The arcuate nucleus of the hypothalamus represents a key center for the control of appetite and feeding through the regulation of 2 key neuronal populations, notably agouti-related peptide/neuropeptide Y and proopimelanocortin (POMC)/cocaine- and amphetamine-regulated transcript neurons. Altered regulation of these neuronal networks, in particular the dysfunction of POMC neurons upon high-fat consumption, is a major pathogenic mechanism involved in the development of obesity and type 2 diabetes mellitus. Efforts are underway to preserve the integrity or enhance the functionality of POMC neurons in order to prevent or treat these metabolic diseases. Here, we report for the first time that the nitric oxide (NO(-)) donor, sodium nitroprusside (SNP) mediates anorexigenic actions in both hypothalamic tissue and hypothalamic-derived cell models by mediating the up-regulation of POMC levels. SNP increased POMC mRNA in a dose-dependent manner and enhanced α-melanocortin-secreting hormone production and secretion in mHypoA-POMC/GFP-2 cells. SNP also enhanced insulin-driven POMC expression likely by inhibiting the deacetylase activity of sirtuin 1. Furthermore, SNP enhanced insulin-dependent POMC expression, likely by reducing the transcriptional repression of Foxo1 on the POMC gene. Prolonged SNP exposure prevented the development of insulin resistance. Taken together, the NO(-) donor SNP enhances the anorexigenic potential of POMC neurons by promoting its transcriptional expression independent and in cooperation with insulin. Thus, increasing cellular NO(-) levels represents a hormone-independent method of promoting anorexigenic output from the existing POMC neuronal populations and may be advantageous in the fight against these prevalent disorders.
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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) | 0.000 | 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".