IGF1 Signaling Regulates Neuropeptide Expression in Hypothalamic Neurons Under Physiological and Pathological Conditions
Bibliographic record
Abstract
Insulin-like growth factor 1 (IGF1) plays a critical role in metabolism and aging, but its role in the brain remains unclear. This study examined whether hypothalamic neurons respond to IGF1 and how its actions are modulated. RT-qPCR and single-cell RNA sequencing indicated that Igf1r mRNA is expressed in neuropeptide Y/Agouti-related peptide (NPY/AgRP) neurons but has higher expression in pro-opiomelanocortin (POMC) neurons. IGF1 binding proteins Igfbp3 and Igfbp5 were significantly expressed, whereby Igfbp5 levels were modulated by fasting, nutrient availability, and circadian rhythms, implying that IGF1 signaling can be controlled by multiple mechanisms. In mouse and human models, IGF1 regulated Agrp, Npy, Pomc, Cartpt, Spx, Gal, and Fam237b expression, producing an overall anorexigenic profile. Hyperinsulinemia induced IGF1 resistance, accompanied by reduced IGF1R protein, as well as Igf1r and Irs2 mRNA expression via over-activation of phosphoinositide 3-kinase/forkhead box O1 (PI3K-FOXO1) signaling. Thus, hypothalamic neurons respond to IGF1 under physiological conditions, and hyperinsulinemia is a novel mechanism that drives cellular IGF1 resistance.
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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".