MicroRNA-29 Fine-tunes the Expression of Key FOXA2-Activated Lipid Metabolism Genes and Is Dysregulated in Animal Models of Insulin Resistance and Diabetes
Bibliographic record
Abstract
MicroRNAs (miRNAs) have emerged as biomarkers of metabolic status, etiological factors in complex disease, and promising drug targets. Recent reports suggest that miRNAs are critical regulators of pathways underlying the pathophysiology of type 2 diabetes. In this study, we demonstrate by deep sequencing and real-time quantitative PCR that hepatic levels of Foxa2 mRNA and miR-29 are elevated in a mouse model of diet-induced insulin resistance. We also show that Foxa2 and miR-29 are significantly upregulated in the livers of Zucker diabetic fatty (fa/fa) rats and that the levels of both returned to normal upon treatment with the insulin-sensitizing agent pioglitazone. We present evidence that miR-29 expression in human hepatoma cells is controlled in part by FOXA2, which is known to play a critical role in hepatic energy homeostasis. Moreover, we demonstrate that miR-29 fine-tunes FOXA2-mediated activation of key lipid metabolism genes, including PPARGC1A, HMGCS2, and ABHD5. These results suggest that miR-29 is an important regulatory factor in normal metabolism and may represent a novel therapeutic target in type 2 diabetes and related metabolic syndromes.
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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".