Engeletin protects against cerebral ischemia/reperfusion injury by modulating the VEGF/vasohibin and Ang-1/Tie-2 pathways
Bibliographic record
Abstract
Engeletin is a natural derivative of Smilax glabra rhizomilax that exhibits anti-inflammatory activity and suppresses lipid peroxidation. In the present study, we sought to elucidate the mechanistic basis for the neuroprotective and pro-angiogenic activity of engeltin in a human umbilical vein endothelial cells (HUVECs) oxygen-glucose deprivation and reoxygenation (OGD/R) model system and a middle cerebral artery occlusion (MCAO) rat model of cerebral ischemia and reperfusion injury. These analyses revealed that engeletin (10, 20, or 40 mg/kg) was able to reduce the infarct volume, increase cerebral blood flow, improve neurological function, and bolster the expression of vascular endothelial growth factor (VEGF), vasohibin-2 (Vash-2), angiopoietin-1 (Ang-1), phosphorylated human angiopoietin receptor tyrosine kinase 2 (p-Tie2), and platelet endothelial cell adhesion molecule-1 (PECAM-1/CD31) in MCAO rats. Similarly, engeletin (100, 200, or 400 nM) markedly enhanced the migration, tube formation, and VEGF expression of HUVECs in an OGD/R model system, while the VEGF receptor (R) inhibitor axitinib reversed the observed changes in HUVEC tube formation activity and Vash-2, VEGF, and CD31 expression. These data suggested that engeletin exhibited significant neuroprotective effects against cerebral ischemia and reperfusion injury in rats, and improved cerebrovascular angiogenesis by modulating the VEGF/vasohibin and Ang-1/Tie-2 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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.086 | 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".