Reprint of: miRNA-1 regulates endothelin-1 in diabetes
Bibliographic record
Abstract
AIMS: MicroRNAs (miRNAs) play important roles in several biological processes. In this study, we investigated the role of miR-1, an endothelin-1 (ET-1) targeting miRNA, in endothelial cells (ECs) and tissues of diabetic animals. ET-1 is known to be of pathogenetic significance in several chronic diabetic complications. MAIN METHODS: PCR array was used to identify alterations of miRNA expression in ECs exposed to glucose. miR-1 expression was validated by TaqMan real-time PCR assay. Human retinal ECs (HRECs) and human umbilical vein ECs (HUVECs) exposed to various glucose levels with or without miR-1 mimic transfection, and tissues from streptozotocin-induced diabetic animals after two months of follow-up, were examined for miR-1 expression, as well as ET-1 and fibronectin (FN) mRNA and protein levels. KEY FINDINGS: Array analyses showed glucose-induced alterations of 125 miRNAs (out of 381) in ECs exposed to 25 mM glucose compared to 5 mM glucose. Fifty-one miRNAs were upregulated and 74 were downregulated. 25 mM glucose decreased miR-1 expression and increased ET-1 mRNA and protein levels. miR-1 mimic transfection prevented HG-induced ET-1 upregulation. Furthermore, glucose induced upregulation of FN, which is mediated partly by ET-1, was also prevented by such transfection. Diabetic animals showed decreased miR-1 expression in the retina, heart and kidneys. In parallel, ET-1 mRNA expressions were increased in these tissues of diabetic animals, in association with upregulation of FN. SIGNIFICANCE: These results indicate a novel glucose-induced mechanism of tissue damage, in which miR-1 regulates ET-1 expressions in diabetes. Identifying such mechanisms may lead to RNA based treatment for diabetic complications.
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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".