Ginkgo biloba extract EGb 761 has anti-inflammatory properties and ameliorates colitis in mice by driving effector T cell apoptosis
Bibliographic record
Abstract
Ulcerative colitis is a dynamic, chronic inflammatory condition of the colon associated with an increased colon cancer risk. Ginkgo biloba is a putative antioxidant and has been used for thousands of years to treat a variety of ailments. The aim of this study was to test whether the standardized G.biloba extract, EGb 761, is an antioxidant that can be used to prevent and treat colitis in mice. Here, we show that EGb 761 suppresses the activation of macrophages and can be used to both prevent and treat mouse colitis. Markers of inflammation (iNOS, Cox-2 and tumor necrosis factor-alpha) and inflammatory stress (p53 and p53-phospho-serine 15) are also downregulated by EGb 761. Furthermore, we show that EGb 761 reduces the numbers of CD4+/CD25-/Foxp3- effector T cells in the colon. Interestingly, EGb 761 drives CD4+ effector T cell apoptosis in vitro and in vivo, providing a mechanistic explanation to the reduction in numbers of this cell type in the colon. This current study is in agreement with previous studies supporting a use of EGb 761 as a complementary and alternative strategy to abate colitis and associated colon cancer.
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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) | 0.000 | 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 | 0.001 |
| 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".