The Loss of ARNT/HIF1β in Male Pancreatic β-Cells Is Protective Against High-Fat Diet–Induced Diabetes
Bibliographic record
Abstract
The transcription factor aryl hydrocarbon receptor nuclear translocator (ARNT)/hypoxia-inducible factor (HIF)-1β (ARNT/HIF1β) plays a key role in maintaining β-cell function and has been shown to be one of the most downregulated transcription factors in islets from patients with type 2 diabetes. We have shown a role for ARNT/HIF1β in glucose sensing and insulin secretion in vitro and no defects in in vivo glucose homeostasis. To gain a better understanding of the role of ARNT/HIF1β in the development of diabetes, we placed control (+/+/Cre) and β-cell-specific ARNT/HIF1β knockout (fl/fl/Cre) mice on a high-fat diet (HFD). Unlike the control (+/+/Cre) mice, HFD-fed fl/fl/Cre mice had no impairment in in vivo glucose tolerance. The lack of impairment in HFD-fed fl/fl/Cre mice was partly due to an improved islet glucose-stimulated NADPH/NADP+ ratio and glucose-stimulated insulin secretion. The effects of the HFD-rescued insulin secretion in fl/fl/Cre islets could be reproduced by treating low-fat diet (LFD)-fed fl/fl/Cre islets with the lipid signaling molecule 1-monoacylglcyerol. This suggests that the defects seen in LFD-fed fl/fl/Cre islet insulin secretion involve lipid signaling molecules. Overall, mice lacking ARNT/HIF1β in β-cells have altered lipid signaling in vivo and are resistant to an HFD's ability to induce diabetes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".