Peripheral and central regulation of insulin by the intestine and microbiome
Bibliographic record
Abstract
Blood glucose and insulin homeostasis is disrupted during the progression of type 2 diabetes. Insulin levels and action are regulated by both peripheral and central responses that involve the intestine and microbiome. The intestine and its microbiota process nutrients and generate molecules that influence blood glucose and insulin. Peripheral insulin regulation is regulated by gut-segment-dependent nutrient sensing and microbial factors such as short-chain fatty acids and bile acids that engage G-protein-coupled receptors. Innate immune sensing of gut-derived bacterial cell wall components and lipopolysaccharides also alter insulin homeostasis. These bacterial metabolites and postbiotics influence insulin secretion and insulin clearance in part by altering endocrine responses such as glucagon-like peptide-1. Gut-derived bacterial factors can promote inflammation and insulin resistance, but other postbiotics can be insulin sensitizers. In parallel, activation of small intestinal sirtuin 1 increases insulin sensitivity by reversing high fat-induced hypothalamic insulin resistance through a gut-brain neuronal axis, whereas high fat-feeding alters small intestinal microbiome and increases taurochenodeoxycholic acid in the plasma and the dorsal vagal complex to induce insulin resistance. In summary, emerging evidence indicates that intestinal molecular signaling involving nutrient sensing and the host-microbe symbiosis alters insulin homeostasis and action. Gut-derived host endocrine and paracrine factors as well as microbial metabolites act on the liver, pancreas, and the brain, and in parallel on the gut-brain neuronal axis. Understanding common nodes of peripheral and central insulin homeostasis and action may reveal new ways to target the intestinal host-microbe relationship in obesity, metabolic disease, and type 2 diabetes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".