Roles of miR-640 and Zinc Finger Protein 91 (ZFP91) in Angiopoietin-1-Induced In Vitro Angiogenesis
Bibliographic record
Abstract
Angiopoietin-1 (Ang-1) is a ligand of Tie-2 receptors that promotes angiogenesis. It has been established that regulatory loops exist between angiogenic growth factors and distinct pro or anti-angiogenic miRNAs, but the nature and the roles of Ang-1-regulated miRNAs remain unclear. In this study, we assessed the role of miR-640 in Ang-1-induced angiogenesis in human umbilical vein endothelial cells (HUVECs). Exposure to Ang-1 (300 ng/mL) from 6 to 72 h significantly decreased expression of mature miR-640, a response that was mediated by Tie-2 receptors and was also observed in response to Ang-2, the vascular endothelial growth factor, and transforming growth factor β. Increasing miR-640 levels using a mimic inhibited Ang-1-induced cell migration and capillary-like tube formation whereas inhibition of miR-640 enhanced these responses. Pull down assays of biotinylated miR-640 revealed that miR-640 directly targets Zinc Finger Protein 91 (ZFP91), an atypical E3-ubiquitin ligase. Ang-1 exposure induced ZFP91 expression through down-regulation of miR-640. Silencing of ZFP91 significantly inhibited Ang-1-induced cell migration and tube formation. We conclude that Ang-1 upregulates ZFP91 expression through transcriptional down-regulation of miR-640 and that ZFP91 plays important roles in the promotion of Ang-1-induced endothelial cell migration and differentiation.
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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) | 0.000 | 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 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".