Ginkgo biloba extract EGb 761 alleviates hepatic fibrosis and sinusoidal microcirculation disturbance in patients with chronic hepatitis B
Bibliographic record
Abstract
BACKGROUND: Few clinical data are available regarding the effect of Ginkgo biloba extract (EGb 761) on liver microcirculation and fibrosis. This randomized, controlled trial is to investigate the effect of Ginko biloba extract EGb 761 on liver fibrosis and hepatic microcirculation in patients with chronic hepatitis B. METHODS: Sixty-four patients with chronic hepatitis B were randomized for intention-to-treat. Thirty-two patients were assigned to treated group receiving EGb 761 plus polyunsaturated phosphatidylcholine (Essentiale), 32 patients received Essentiale as controls. Blood samples were taken for measurement of transforming growth factor beta-1 (TGF-β1), platelet activate factor (PAF), endothelin 1 (ET-1). Twenty-six patients in treated group and 21 patients in control group underwent liver biopsies for histology before and after treatment. Ultrastructural study for sinusoidal microcirculation before and after treatment was carried out on 10 randomly selected patients in each group. RESULTS: In the treated group, after EGb 761 treatment, there was a significant reduction of blood TGF- β1, PAF and ET-1 (p<0.05), whereas this was not observed in the controls. After treatment in both groups, there were significant decrease of ALT, TBil and PT (p<0.05), and significant increase of ALB (p<0.05). Hepatic inflammation and fibrosis significantly alleviated in the treated group, but not in the controls. After EGb 761 treatment, electron microscopy showed red blood cell aggregates and microthrombosis disappeared or decreased in sinusoids; collagen deposits in sinusoidal lumen and Disse space reduced; sinusoidal capillarization alleviated. CONCLUSIONS: EGb 761 can improve sinusoidal microcirculation, alleviate inflammation and inhibit fibrosis through multiple mechanisms, it is effective in the treatment of chronic liver diseases.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".