Cyclical and Alternating Infusions of Glucose and Intralipid in Rats Inhibit Insulin Gene Expression and Pdx-1 Binding in Islets
Bibliographic record
Abstract
OBJECTIVE: Prolonged exposure of isolated islets of Langerhans to elevated levels of fatty acids, in the presence of high glucose, impairs insulin gene expression via a transcriptional mechanism involving nuclear exclusion of pancreas-duodenum homeobox-1 (Pdx-1) and loss of MafA expression. Whether such a phenomenon also occurs in vivo is unknown. Our objective was therefore to ascertain whether chronic nutrient oversupply inhibits insulin gene expression in vivo. RESEARCH DESIGN AND METHODS: Wistar rats received alternating 4-h infusions of glucose and Intralipid for a total of 72 h. Control groups received alternating infusions of glucose and saline, saline and Intralipid, or saline only. Insulin and C-peptide secretion were measured under hyperglycemic clamps. Insulin secretion and gene expression were assessed in isolated islets, and beta-cell mass was quantified by morphometric analysis. RESULTS: Neither C-peptide secretion nor insulin sensitivity was different among infusion regimens. Insulin content and insulin mRNA levels were lower in islets isolated from rats infused with glucose plus Intralipid. This was associated with reduced Pdx-1 binding to the endogenous insulin promoter, and an increased proportion of Pdx-1 localized in the cytoplasm versus the nucleus. In contrast, MafA mRNA and protein levels and beta-cell mass and proliferation were unchanged. CONCLUSIONS: Cyclical and alternating infusions of glucose and Intralipid in normal rats inhibit insulin gene expression without affecting insulin secretion or beta-cell mass. We conclude that fatty acid inhibition of insulin gene expression, in the presence of high glucose, is an early functional defect that may contribute to beta-cell failure in type 2 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 | 0.001 |
| 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".