GLP-1R signaling modulates colonic energy metabolism, goblet cell number and survival in the absence of gut microbiota
Bibliographic record
Abstract
OBJECTIVES: Gut microbiota increases energy availability through fermentation of dietary fibers to short-chain fatty acids in conventionally raised mice. Energy deficiency in germ-free (GF) mice increases glucagon-like peptide-1 (GLP-1) levels, which slows intestinal transit. To further analyze the role of GLP-1-mediated signaling in this model of energy deficiency, we re-derived mice lacking GLP-1 receptor (GLP-1R KO) as GF. METHODS: GLP-1R KO mice were rederived as GF through hysterectomy and monitored for 30 weeks. Mice were subjected to rescue experiments either through feeding an energy-rich diet or colonization with a normal cecal microbiota. Histology and intestinal function were assessed at different ages. Intestinal organoids were assessed to investigate stemness. RESULTS: Unexpectedly, 25% of GF GLP-1R KO mice died before 20 weeks of age, associated with enlarged ceca, increased cecal water content, increased colonic expression of apical ion transporters, reduced number of goblet cells and loss of colonic epithelial integrity. Colonocytes from GLP-1R KO mice were energy-deprived and exhibited increased ER-stress; mitochondrial fragmentation, increased oxygen levels and loss of stemness. Restoring colonic energy levels either by feeding a Western-style diet or colonization with a normal gut microbiota normalized gut phenotypes and prevented lethality. CONCLUSIONS: Our findings reveal a heretofore unrecognized role for GLP-1R signaling in the maintenance of colonic physiology and survival during energy deprivation.
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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".