Identification of Kaempferol as a Monoamine Oxidase Inhibitor and Potential Neuroprotectant in Extracts of <i>Ginkgo Biloba</i> Leaves
Bibliographic record
Abstract
The effects of Ginkgo biloba leaf extract on rat brain or livermonoamine oxidase (MAO)-A and -B activity, biogenic amine concentration in nervous tissue, N-methyl-D-aspartate (NMDA)- and N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine (DSP-4)-induced neurotoxicity and antioxidant activity was investigated to determine the effects of the extract on monoamine catabolism and neuroprotection. Ginkgo biloba leaf extract was shown to produce in-vitro inhibition of rat brain MAO-A and -B. The Ginkgo biloba extract was chromatographed on a reverse-phase HPLC system and two of the components isolated were shown to be MAO inhibitors (MAOIs). These MAOIs were identified by high-resolution mass spectrometry as kaempferol and isorhamnetin. Pure kaempferol and a number of related flavonoids were examined as MAOIs in-vitro. Kaempferol, apigenin and chrysin proved to be potent MAOIs, but produced more pronounced inhibition of MAO-A than MAO-B. IC50 (50% inhibition concentration) values for the ability of these three flavones to inhibit MAO-A were 7 x 10(-7), 1 x 10(-6) and 2 x 10(-6) M, respectively. Ginkgo biloba leaf extract and kaempferol were found to have no effect ex-vivo on rat or mouse brain MAO or on concentrations of dopamine, noradrenaline, 5-hydroxytryptamine and 5-hydroxyindoleacetic acid. Kaempferol was shown to protect against NMDA-induced neuronal toxicity in-vitro in rat cortical cultures, but did not prevent DSP-4-induced noradrenergic neurotoxicity in an in-vivo model. Both Ginkgo biloba extract and kaempferol were demonstrated to be antioxidants in a lipid-peroxidation assay. This data indicates that the MAO-inhibiting activity of Ginkgo biloba extract is primarily due to the presence of kaempferol. Ginkgo biloba extract has properties indicative of potential neuroprotective ability.
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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) | 0.000 | 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 | 0.000 |
| 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".