Hypothalamic GABAergic Neurons Expressing Cellular Retinoic Acid Binding Protein 1 (CRABP1) Are Sensitive to Metabolic Status and Liraglutide in Male Mice
Bibliographic record
Abstract
INTRODUCTION: Owing to their privileged anatomical location, neurons of the arcuate nucleus of the hypothalamus (ARC) play critical roles in sensing and responding to metabolic signals such as leptin and glucagon-like peptide 1 (GLP-1). In addition to the well-known proopiomelanocortin (POMC)- and agouti-related peptide (AgRP)-expressing neurons, subpopulations of GABAergic neurons are emerging as key regulators of energy balance. However, the precise identity of these metabolic neurons is still elusive. Here, we identified and characterized the molecular signature of a novel population of GABAergic neurons of the ARC expressing Cellular retinoic acid binding protein 1 (Crabp1). METHODS: Using a combination of immunohistochemistry and in situ hybridization techniques, we investigated the expression of Crabp1 across the mouse brain and characterized the molecular identity of Crabp1ARC neurons. We also determined whether Crabp1ARC neurons are sensitive to fasting, leptin, and GLP1R agonism by assessing cFOS immunoreactivity as a marker of neuronal activity. RESULTS: Crabp1ARC neurons represent a novel GABAergic neuronal population robustly enriched in the ARC and are distinct from the prototypical melanocortin neurons. Crabp1ARC neurons overlap with three subpopulations of yet uncharacterized ARC neurons expressing Htr3b, Tbx19, and Tmem215. Notably, Crabp1ARC neurons express receptors for metabolic hormones and their activity is modulated by the nutritional state and GLP1R agonism. CONCLUSION: Crabp1ARC neurons represent a novel heterogeneous population of GABAergic neurons sensitive to metabolic status.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".