Angiogenesis effects of 4-methoxy benzyl alcohol on cerebral ischemia-reperfusion injury via regulation of VEGF-Ang/Tie2 balance
Bibliographic record
Abstract
Angiogenesis facilitates the formation of microvascular networks and promotes neurological deficit recovery after cerebral ischemia-reperfusion injury (CIRI). This study investigated the angiogenesis effects of 4-methoxy benzyl alcohol (4-MA) on CIRI. The angiogenesis effects of 4-MA and the potential underlying mechanisms were assessed based on a middle cerebral artery occlusion/reperfusion (MCAO/R) rat model and a hind limb ischemic (HLI) mouse model. Immunofluorescence was conducted to detect microvessel density, and Western blotting and polymerase chain reaction were performed to determine the expression of angiogenesis-promoting factors. In addition, we investigated whether the angiogenesis effects of 4-MA caused damage to the blood-brain barrier (BBB). After treatment with 4-MA (20 mg/kg) for 7 days, the neurological deficits recovered and microvessel density in the cerebral cortex increased in the MCAO/R rats. Additionally, 4-MA also regulated the expression of angiogenesis factors, with an increase in vascular endothelial growth factor (VEGF) and vascular endothelial growth factor receptor 2 (VEGFR-2) expression and a decrease in angiopoietin 1 (Ang-1), Ang-2, and Tie-2 expression in both MCAO/R rats and HLI mice. Moreover, 4-MA increased the expression of angiogenesis-promoting factors without exacerbating BBB cascade damage in MCAO/R rats. Our results indicated that 4-MA may contribute to the formation of microvascular networks, thus promoting neurological deficit recovery after CIRI.
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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) | 0.001 | 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".