Dihydromyricetin protects against high glucose-induced endothelial dysfunction: Role of HIF-1α/ROR2/NF-κB
Bibliographic record
Abstract
OBJECTIVES: Dihydromyricetin (DHM), a natural flavonoid isolated from vine tea with anti-inflammatory activity was evaluated for its ability to prevent vascular endothelial dysfunction caused by hyperglycaemia. METHODS: Vasoconstrictor (phenylephrine-PE) and vasodilator (acetylcholine-ACh) responses were monitored for female rat aorta rings maintained in a bioassay organ bath for 3 h at 37 °C in either low (LG: 10 mM) or high (HG: 40 mM, to mimic hyperglycaemia) glucose-Krebs buffer in the absence or presence of 50 µM DHM. Tissues recovered from the organ bath at 3 h were fixed and analyzed for morphological changes and their expression of eNOS, iNOS, HIF-1α, GLUT1, ROR2 tyrosine kinase, NF-κB, TNF-α, Bax, Bcl2, caspase-3, and forindices of increased oxidative stress. KEY FINDINGS: HG-incubated tissues showed increased PE-stimulated contractile response and decreased ACh-mediated endothelial vasodilation. DHM prevented both of these changes. Besides, HG incubation increased the immunoreactivity to iNOS, HIF-1α, GLUT1, ROR2, NF-κB, TNF-α, Bax, and active caspase-3, and decreased the expression of eNOS and Bcl2. Hyperglycaemia-like conditions also increased the indices of oxidative/nitrosative stress. These HG-induced changes, which were accompanied by an increase in tissue adventitial thickness and inflammatory cell infiltration, were all prevented by DHM. CONCLUSION: Our data demonstrate an anti-inflammatory protective action of DHM to preserve vascular function in the setting of hyperglycaemia.
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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".