Tannin extracted from Sumac inhibits vascular smooth muscle cell migration
Bibliographic record
Abstract
BACKGROUND: Vascular smooth muscle cell (VSMC) migration is integral in the pathogenesis of atherosclerosis. Sumac (Rhus coriaria) berries are believed to have atheroprotective effects. Therefore, Sumac, which is a rich source of tannin antioxidants, was tested for its capacity to inhibit VSMC migratory activity. MATERIALS & METHODS: Tannin was extracted and purified from ground Sumac. Cultured rat carotid VSMCs were treated with different concentrations of tannin. After 10 days of tannin treatment, VSMC migratory activity in response to platelet-derived growth factor-BB was measured by transmembrane migration assay. An equal number of VSMCs was loaded on top of the inserts and at the bottom of the wells. After fixation and staining, cells migrating through the inserts and cells seeded at the bottom of the wells were counted. RESULTS: A significant reduction (62%) of VSMC migration was evident in tannin-treated cells. To rule out any possible toxicity and cell death, cells at the bottom of the wells were also counted. No difference between the tannin-treated group and the controls was observed in the number of cells seeded at the bottom of the wells. CONCLUSION: Our data suggest that tannin extracted from Sumac possesses potent antimigratory activity. Sumac may have potential for the prevention or treatment of atherosclerosis and its clinical manifestations. Further experiments, especially in vivo, are required to examine the atheroprotective effect of Sumac.
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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".