Downregulation of acylglycerol kinase suppresses high-glucose-induced endothelial-mesenchymal transition in human retinal microvascular endothelial cells through regulating the LPAR1/TGF-β/Notch signaling pathway
Bibliographic record
Abstract
The endothelial-mesenchymal transition (EndMT) participates in the progression of diabetic retinopathy (DR), but cell-intrinsic factors modulating this process remain elusive. In this study, we explored the role of lysophosphatidic acid (LPA) - producing enzyme, acylglycerol kinase (AGK), in the EndMT of human retinal microvascular endothelial cells (HRECs) under high-glucose (HG) conditions. We found that AGK was significantly elevated in HG-treated cells. In addition, AGK knockdown reversed the HG-induced EndMT in HRECs, which was evidenced by the increased endothelial markers (CD31 and VE-cadherin) and decreased mesenchymal markers (FSP1 and α-SMA). Furthermore, downregulation of AGK inhibited the HG-induced activation of transforming growth factor β (TGF-β)/Notch pathways, whereas exogenous TGF-β1 (10 ng/mL) impeded the inhibitory effects of AGK knockdown on HG-induced EndMT in HRECs. Additionally, the silencing of AGK abolished the HG-induced upregulation of LPA and its receptor, LPA receptor 1 (LPAR1), and overexpression of LPAR1 further rescued the AGK knockdown-mediated inhibition of the EndMT process. In conclusion, we demonstrate that downregulation of AGK suppresses HG-induced EndMT in HRECs through regulating the LPAR1/TGF-β/Notch signaling pathway, indicating that AGK might be a potential therapeutic target for the treatment of DR.
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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 | 0.001 |
| 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".