Requirement for the intestinal epithelial insulin‐like growth factor‐1 receptor in the intestinal responses to glucagon‐like peptide‐2 and dietary fat
Bibliographic record
Abstract
Abstract The intestinal hormone, glucagon‐like peptide‐2 (GLP‐2), enhances the enterocyte chylomicron production. However, GLP‐2 is known to require the intestinal‐epithelial insulin‐like growth factor‐1 receptor (IE‐IGF‐1R) for its other actions to increase intestinal growth and barrier function. The role of the IE‐IGF‐1R in enterocyte lipid handling was thus tested in the GLP‐2 signaling pathway, as well as in response to a Western diet (WD). IE‐IGF‐1R knockout (KO) and control mice were treated for 11 days with h(GLY 2 )GLP‐2 or fed a WD for 18 weeks followed by a duodenal fat tolerance test with C 14 ‐labeled triolein. Human Caco‐2BBE cells were treated with an IGF‐1R antagonist or signaling inhibitors to determine triglyceride‐associated protein expression. The IE‐IGF‐1R was required for GLP‐2‐induced increases in CD36 and FATP‐4 in chow‐fed mice, and for expression in vitro; FATP‐4 also required PI3K/Akt. Although WD‐fed IE‐IGF‐1R KO mice demonstrated normal CD36 expression, the protein was incorrectly localized 2h post‐duodenal fat administration. IE‐IGF‐1R KO also prevented the WD‐induced increase in MTP and decrease in APOC3, increased jejunal mucosal C 14 ‐fat accumulation, and elevated plasma triglyceride and C 14 ‐fat levels. Collectively, these studies elucidate new roles for the IE‐IGF‐1R in enterocyte lipid handling, under basal conditions and in response to GLP‐2 and WD‐feeding.
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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 | 0.001 |
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".