A novel regulatory network of linc00174/miR-150-5p/VEGFA modulates pathological angiogenesis in diabetic retinopathy
Bibliographic record
Abstract
Diabetic retinopathy (DR) has been regarded as a sight-threatening vascular complication of diabetes mellitus. Accumulating evidence has identified the involvement of long non-coding RNAs (lncRNAs) in DR pathogenesis. We aim to investigate the role and underlying mechanism of linc00174 in the DR process. Samples of human vitreous humour from proliferative DR and non-diabetic individuals were collected to examine the levels of linc00174. Human retinal microvascular endothelial cells (HRMECs) exposed with high glucose (HG) were employed to simulate the pathological statues of DR. Short hairpin RNA specifically targeting linc00174 was applied. CCK-8, transwell, and matrigel tube formation were performed to evaluate cell proliferation, migration, and angiogenesis. Bioinformatics analysis and luciferase reporter assay were conducted to verify the linc00174/miR-150-5p/vascular endothelial growth factor A (VEGFA) regulatory network. Western blotting was employed to determine the expression of VEGFA. Linc00174 was significantly elevated in patients with DR, as well as HG-stimulated HRMECs, of which knockdown repressed HG-induced proliferation, migration, and angiogenesis. miR-150-5p was identified as a downstream effector to be involved in linc00174-mediated protective effects. miR-150-5p directly bound to the 3' untranslated region of VEGFA. The linc00174/miR-150-5p/VEGFA axis was confirmed in retinal vascular dysfunction. The linc00174 deteriorates diabetic retinal microangiopathy via regulating miR-150-5p/VEGFA pathway, indicating a novel therapeutic target for DR treatment.
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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".