Role of Central Nervous System Glucagon-Like Peptide-1 Receptors in Enteric Glucose Sensing
Bibliographic record
Abstract
OBJECTIVE: Ingested glucose is detected by specialized sensors in the enteric/hepatoportal vein, which send neural signals to the brain, which in turn regulates key peripheral tissues. Hence, impairment in the control of enteric-neural glucose sensing could contribute to disordered glucose homeostasis. The aim of this study was to determine the cells in the brain targeted by the activation of the enteric glucose-sensing system. RESEARCH DESIGN AND METHODS: We selectively activated the axis in mice using a low-rate intragastric glucose infusion in wild-type and glucagon-like peptide-1 (GLP-1) receptor knockout mice, neuropeptide Y-and proopiomelanocortin-green fluorescent protein-expressing mice, and high-fat diet diabetic mice. We quantified the whole-body glucose utilization rate and the pattern of c-Fos positive in the brain. RESULTS: Enteric glucose increased muscle glycogen synthesis by 30% and regulates c-Fos expression in the brainstem and the hypothalamus. Moreover, the synthesis of muscle glycogen was diminished after central infusion of the GLP-1 receptor (GLP-1Rc) antagonist Exendin 9-39 and abolished in GLP-1Rc knockout mice. Gut-glucose-sensitive c-Fos-positive cells of the arcuate nucleus colocalized with neuropeptide Y-positive neurons but not with proopiomelanocortin-positive neurons. Furthermore, high-fat feeding prevented the enteric activation of c-Fos expression. CONCLUSIONS: We conclude that the gut-glucose sensor modulates peripheral glucose metabolism through a nutrient-sensitive mechanism, which requires brain GLP-1Rc signaling and is impaired during diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".