GLP-1R Agonists Modulate Enteric Immune Responses Through the Intestinal Intraepithelial Lymphocyte GLP-1R
Bibliographic record
Abstract
Obesity and diabetes are characterized by increased inflammation reflecting disordered control of innate immunity. We reveal a local intestinal intraepithelial lymphocyte (IEL)-GLP-1 receptor (GLP-1R) signaling network that controls mucosal immune responses. Glp1r expression was enriched in intestinal IEL preparations and copurified with markers of Tαβ and Tγδ IELs, the two main subsets of intestinal IELs. Exendin-4 increased cAMP accumulation in purified IELs and reduced the production of cytokines from activated IELs but not from splenocytes ex vivo. These actions were mimicked by forskolin, absent in IELs from Glp1r(-/-) mice, and attenuated by the GLP-1R agonist exendin (9-39) consistent with a GLP-1R-dependent mechanism of action. Furthermore, Glp1r(-/-) mice exhibited dysregulated intestinal gene expression, an abnormal representation of microbial species in feces, and enhanced sensitivity to intestinal injury following administration of dextran sodium sulfate. Bone marrow transplantation using wild-type C57BL/6 donors normalized expression of multiple genes regulating immune function and epithelial integrity in Glp1r(-/-) recipient mice, whereas acute exendin-4 administration robustly induced the expression of genes encoding cytokines and chemokines in normal and injured intestine. Taken together, these findings define a local enteroendocrine-IEL axis linking energy availability, host microbial responses, and mucosal integrity to the control of innate immunity.
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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 | 0.001 |
| 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".