Npy transcription is regulated by noncanonical STAT3 signaling in hypothalamic neurons: Implication with lipotoxicity and obesity
Bibliographic record
Abstract
Neuropeptide Y (Npy) is an abundant neuropeptide expressed in the central and peripheral nervous systems. NPY-secreting neurons in the hypothalamic arcuate nucleus regulate energy homeostasis, and Npy mRNA expression is regulated by peripheral nutrient and hormonal signals like leptin, interleukin-6 (IL-6), and fatty acids. This study demonstrates that IL-6 that phosphorylates tyrosine 705 (Y705) of STAT3 decreased Npy mRNA in arcuate immortalized hypothalamic neurons. In parallel, inhibitors of STAT3-Y705 phosphorylation, stattic and cucurbitacin I, robustly upregulated Npy mRNA. Chromatin-immunoprecipitation showed high baseline total STAT3 binding to multiple regulatory regions of the Npy gene, which are decreased by IL-6 exposure. The STAT3-Npy interaction was further examined in obesity-related pathologies. Notably, in four different hypothalamic neuronal models where palmitate potently stimulated Npy mRNA, Socs3, a specific STAT3 activity marker, was downregulated and was negatively correlated with Npy mRNA levels (R2 = 0.40, p < 0.001), suggesting that disrupted STAT3 signaling is involved in lipotoxicity-mediated dysregulation of Npy. Finally, human NPY SNPs that map to human obesity or body mass index were investigated for potential STAT3 binding sites. Although none of the SNPs were linked to direct STAT3 binding, analysis show that rs17149106 (−602 G > T) is located on an upstream enhancer element of NPY, where the variant is predicted to disrupt validated binding of KLF4, a known inhibitory cofactor of STAT3 and downstream effector of leptin signaling. Collectively, this study demonstrates that canonical p-STAT3-Y705 signaling negatively regulates Npy transcription, and that disruption of this interaction may contribute to metabolic 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".