L-Cell Differentiation Is Induced by Bile Acids Through GPBAR1 and Paracrine GLP-1 and Serotonin Signaling
Bibliographic record
Abstract
Glucagon-like peptide 1 (GLP-1) mimetics are effective drugs for treatment of type 2 diabetes, and there is consequently extensive interest in increasing endogenous GLP-1 secretion and L-cell abundance. Here we identify G-protein–coupled bile acid receptor 1 (GPBAR1) as a selective regulator of intestinal L-cell differentiation. Lithocholic acid and the synthetic GPBAR1 agonist, L3740, selectively increased L-cell density in mouse and human intestinal organoids and elevated GLP-1 secretory capacity. L3740 induced expression of Gcg and transcription factors Ngn3 and NeuroD1. L3740 also increased the L-cell number and GLP-1 levels and improved glucose tolerance in vivo. Further mechanistic examination revealed that the effect of L3740 on L cells required intact GLP-1 receptor and serotonin 5-hydroxytryptamine receptor 4 (5-HT4) signaling. Importantly, serotonin signaling through 5-HT4 mimicked the effects of L3740, acting downstream of GLP-1. Thus, GPBAR1 agonists and other powerful GLP-1 secretagogues facilitate L-cell differentiation through a paracrine GLP-1–dependent and serotonin-mediated mechanism.
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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".