HNF4α is a novel regulator of intestinal glucose-dependent insulinotropic polypeptide
Bibliographic record
Abstract
Abstract Mutations in the HNF4A gene cause MODY1 and are associated with an increased risk of Type 2 diabetes mellitus. On the other hand, incretins are hormones that potentiate reductions in blood glucose levels. Given the established role of incretin-based therapy to treat diabetes and metabolic disorders, we investigated a possible regulatory link between intestinal epithelial HNF4α and glucose-dependent insulinotropic polypeptide (GIP), an incretin that is specifically produced by gut enteroendocrine cells. Conditional deletion of HNF4α in the whole intestinal epithelium was achieved by crossing Villin-Cre and Hnf4αloxP/loxP C57BL/6 mouse models. GIP expression was measured by qPCR, immunofluorescence and ELISA. Gene transcription was assessed by luciferase and electrophoretic mobility shift assays. Metabolic parameters were analyzed by indirect calorimetry and dual-energy X-ray absorptiometry. HNF4α specific deletion in the intestine led to a reduction in GIP. HNF4α was able to positively control Gip transcriptional activity in collaboration with GATA-4 transcription factor. Glucose homeostasis and glucose-stimulated insulin secretion remained unchanged in HNF4α deficient mice. Changes in GIP production in these mice did not impact nutrition or energy metabolism under normal physiology but led to a reduction of bone area and mineral content, a well described physiological consequence of GIP deficiency. Our findings point to a novel regulatory role between intestinal HNF4α and GIP with possible functional impact on bone density.
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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".