Signalling pathways involved in retinal endothelial cell proliferation induced by advanced glycation end products: inhibitory effect of gliclazide
Bibliographic record
Abstract
AIM: We have previously demonstrated that advanced glycation end products (AGEs) stimulate bovine retinal endothelial cell (BREC) proliferation through induction of vascular endothelial growth factor (VEGF) production by these cells. We have also shown that gliclazide, a sulfonylurea which decreases oxidative stress, inhibits this effect. The aim of the present study was to characterize the signalling pathways involved in AGE-induced BREC proliferation and VEGF production and mediating the inhibitory effect of gliclazide on these biological events. METHODS: BRECs were treated or not treated with AGEs in the presence or absence of gliclazide, antioxidants, protein kinase C (PKC), mitogen-activated protein kinase (MAPK) or nuclear factor-kappaB (NF-kappaB) inhibitors. BREC proliferation was assessed by measuring [3H]-thymidine incorporation into DNA. Activation of PKC, MAPK and NF-kappaB signal transduction pathways and determination of VEGF expression were assessed by Western blot analysis using specific antibodies. MAPK activity was also determined by an in vitro kinase assay. RESULTS: Treatment of BRECs with AGEs significantly increased cell proliferation and VEGF expression. AGEs induced PKC-beta translocation, extracellular signal-regulated protein kinase 1/2 and NF-kappaB activation in these cells. Pharmacological inhibition of these signalling pathways abolished AGE effects on cell proliferation and VEGF expression. Exposure of BRECs to gliclazide or antioxidants such as vitamin E or N-acetyl-l-cysteine resulted in a significant decrease in AGE-induced activation of PKC-, MAPK- and NF-kappaB-signalling pathways. CONCLUSIONS: Our results demonstrate the involvement of PKC, MAPK and NF-kappaB in AGE-induced BREC proliferation and VEGF expression. Gliclazide inhibits BREC proliferation by interfering with these intracellular signal transduction pathways.
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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 | 0.001 | 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".