Glucose-induced endothelin-1 expression is regulated by ERK5 in the endothelial cells and retina of diabetic ratsThis article is one of a selection of papers published in the two-part special issue entitled 20 Years of Endothelin Research.
Bibliographic record
Abstract
Upregulation of endothelin 1 (ET-1) causing blood flow alteration and increased extracellular matrix production are characteristic features of diabetic angiopathy. Several glucose-induced signaling mechanisms cause ET-1 upregulation in diabetic angiopathy. Extracellular signal-regulated kinase 5 (ERK5) is a member of the MAPK family, which plays a key role in cardiovascular development. ERK kinase (MEK) 5 is the specific MEK for ERK5 activation. In this study we examined the role of glucose-induced ERK5 signaling in mediating ET-1 expression in diabetic angiopathy. We investigated retinas from 1-month STZ-induced diabetic rats and human macro- and microvascular endothelial cells to study ERK5-dependent ET-1 alterations. Glucose (25 mmol/L) caused significant upregulation of ET-1 mRNA and downregulation of ERK5 and Kruppel-like factor 2 (KLF2) after 24 h treatment in the endothelial cells. Simultaneously, phospho-ERK5 proteins were reduced. Activation of ERK5 by constitutively active MEK5 (caMEK5) upregulated KLF2 and suppressed ET-1 expression in both cell lines, whereas ERK5 siRNA transfection resulted in decreased ERK5 and KLF2 and increased ET-1 mRNA expression. In addition, caMEK5 prevented glucose-induced upregulation of ET-1. Furthermore, 1 month of diabetes caused a significant increase in retinal ET-1 mRNA and decrease in ERK5 mRNA expression. These data indicate that ERK5 signaling regulates glucose-induced ET-1 expression in diabetes. The ERK5/ET-1 pathway may provide a potential novel target for the treatment of diabetic angiopathy.
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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".