Effect of Ginseng Saponins on β-Amyloid-Suppressed Acetylcholine Release from Rat Hippocampal Slices
Bibliographic record
Abstract
In view of the facts that ginseng has been shown to improve age-related memory deficits and beta-amyloid-related peptides have been suggested to play a significant role in memory degeneration in the elderly, the present study was carried out to examine the effect of various ginsenosides on beta-amyloid peptides-modulated acetylcholine (ACh) release, a key neurotransmitter in memory processing, from the hippocampal slices. Addition of beta-amyloid fragment(25 - 35) (0.01 - 1 microM) in the superfusion medium suppressed the K(+)-evoked [(3)H]-ACh release from the rat hippocampal slices in a concentration-related manner and about 40 % reduction in ACh outflow was observed when incubating with the highest concentration of an amyloid fragment (1 microM). Inclusion of the ginsenoside components Rb(1) (0.1 microM), but not Rg(1), caused a rightward shift of the concentration-response curve of beta-amyloid. The reversal of the beta-amyloid-inhibited ACh release by Rb(1) was not blocked by tetrodotoxin (1 microM) indicating that an interaction occurs at the cholinergic synapse. These results suggest that Rb(1) may elicit its anti-amnesic effect by minimizing the inhibitory effect of beta-amyloid peptides.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".