Regulation of Vascular Endothelial Growth Factor Expression by Extra Domain B Segment of Fibronectin in Endothelial Cells
Bibliographic record
Abstract
PURPOSE: Diabetic retinopathy entails proliferation of vascular endothelial cells (ECs) and unregulated angiogenesis. We have previously shown that ECs increase the expression of an embryonic variant of fibronectin (FN), called extra domain-B FN (ED-B FN) in response to high glucose. We also showed that ED-B FN regulates EC tube morphogenesis, possibly through vascular endothelial growth factor (VEGF). In the present study, we have attempted to decipher the mechanisms by which ED-B FN may modulate EC phenotype. METHODS: We hypothesized that ED-B FN regulates VEGF expression in ECs through interaction with selected integrin receptors. To test this hypothesis, we first cultured ECs in high levels of glucose to investigate for any alteration. We then used integrin-specific matrix mimetic peptides, neutralizing antibodies, and RNAi to identify the integrin(s) involved in VEGF expression. Finally, we used an animal model of diabetes to study whether these in vitro mechanisms also take place in the retina. RESULTS: Our results show that exposure of ECs to high levels of glucose increased VEGF expression. ED-B FN mediated this increase since knockdown of ED-B FN completely prevented glucose-induced VEGF expression. We then identified β1 integrin as the essential receptor involved in high glucose-induced VEGF expression. We also showed that diabetes increased β1 integrin and VEGF expression in the retina, which normalized upon ED-B knockdown. CONCLUSIONS: These findings showed that high levels of glucose in diabetes increased VEGF expression in ECs through ED-B FN and β1 integrin interaction. These results provide novel mechanistic basis of increased VEGF expression in diabetes.
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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".