Effects of Ginkgo biloba Extract (EGb 761) on Arteriolar Spasm in a Rat Cremaster Muscle Preparation
Bibliographic record
Abstract
The effects of an extract of Ginkgo biloba (EGb 761) on arteriolar spasm were confirmed using a preparation of rat cremaster muscle. When vasospasm was induced by rat serum, arteriolar constriction reached 25-30% of the initial diameter after 10 min. Intravenous injection of EGb 761 (30 mg/kg) 5 min after inducing spasm inhibited about 80% of this serum-induced vasoconstriction. As previous studies have shown that EGb 761 has an antiaggregatory effect on platelets, thrombin, serotonin (platelet-derived compounds that are present in the serum) and a thromboxane analogue (U46619) were also used to induce vasospasm. Administration of EGb 761 (30 mg/kg) 5 min after exposure of the preparation to serotonin (10(-3) M) or 10 min after exposure to thrombin (20 units) did not affect vasospasm induced by these agents. In contrast, treatment with this same dose of EGb 761 5 min after exposure of the preparation to U46619 (10(-4) M) abolished the arteriolar constriction induced by this agent in 15 min. The thromboxane/prostaglandin H2 receptor antagonist SQ29548 antagonized serum-induced vasospasm, indicating an involvement of thromboxane. Other experiments indicated that the effects of EGb 761 of counteracting vasospasm may be mediated in part by ginkgolide B, a triterpene constituent of the extract that is an antagonist of platelet-activating factor and in part by an 'NO-like' action of its proanthocyanidin constituents. Taken together, these results have revealed that EGb 761 treatment can antagonize the vasoconstrictor effect of thromboxane on arterioles. As thromboxane is implicated in many cardiovascular disorders, this property of EGb 761 may explain some of its beneficial clinical effects in such pathologies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".