EGb 761 is a neuroprotective agent against beta-amyloid toxicity.
Bibliographic record
Abstract
Beta-amyloid (Abeta) deposition likely plays a causal role in the lesions that occur in Alzheimer's disease (AD). The Ginkgo biloba extract EGb 761 is widely prescribed in the treatment of cognitive deficits that are associated with normal and pathological brain aging such as AD. We have investigated here the potential effectiveness of EGb 761 against cell death produced by Abeta fragments on primary cultures of hippocampal cells, these cells being severely damaged in AD. A co-treatment with EGb 761 protected cells against toxicity induced by Abeta fragments in a concentration dependent manner. The effect of EGb 761 was even significant if added up to 8 hr to cells and was shared by its flavonoid fraction CP 205, whereas the terpenes bilobalide and ginkgolide B were ineffective. EGb 761 also displayed protective effects against toxicity produced by either H2O2 or nitric oxide, two neurotoxic agents that possibly mediate Abeta toxicity. Moreover, EGb 761, and to a lesser extent CP 205, completely blocked Abeta-induced events, such as reactive oxygen species accumulation and apoptosis. Taken together, these results and those obtained by other groups highlight the neuroprotective abilities of EGb 761 against dysfunction and death of neurons caused by Abeta deposits.
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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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".