High Glucose Treatment Limits Drosha Protein Expression and Alters AngiomiR Maturation in Microvascular Primary Endothelial Cells via an Mdm2-dependent Mechanism
Bibliographic record
Abstract
Diabetes promotes an angiostatic phenotype in the microvascular endothelium of skeletal muscle and skin. Angiogenesis-related microRNAs (angiomiRs) regulate angiogenesis through the translational repression of pro- and anti-angiogenic genes. The maturation of micro-RNA (miRs), including angiomiRs, requires the action of DROSHA and DICER proteins. While hyperglycemia modifies the expression of angiomiRs, it is unknown whether high glucose conditions alter the maturation process of angiomiRs in dermal and skeletal muscle microvascular endothelial cells (MECs). Compared to 5 mM of glucose, high glucose condition (30 mM, 6–24 h) decreased DROSHA protein expression, without changing DROSHA mRNA, DICER mRNA, or DICER protein in primary dermal MECs. Despite DROSHA decreasing, high glucose enhanced the maturation and expression of one angiomiR, miR-15a, and downregulated an miR-15a target: Vascular Endothelial Growth Factor-A (VEGF-A). The high glucose condition increased Murine Double Minute-2 (MDM2) expression and MDM2-binding to DROSHA. Inhibition of MDM2 prevented the effects evoked by high glucose on DROSHA protein and miR-15a maturation in dermal MECs. In db/db mice, blood glucose was negatively correlated with the expression of skeletal muscle DROSHA protein, and high glucose decreased DROSHA protein in skeletal muscle MECs. Altogether, our results suggest that high glucose reduces DROSHA protein and enhances the maturation of the angiostatic miR-15a through a mechanism that requires MDM2 activity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".