Effects of Ginkgo Biloba Extract on A53T α-Synuclein Transgenic Mouse Models of Parkinson’s Disease
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) is a degenerative disorder of the central nervous system mainly affecting the motor system. Presently, there is no effective and safe drug to treat patients with PD. Ginkgo biloba extract (GBE), obtained from leaves of the Ginkgo biloba tree, is a complex mixture of ingredients primarily containing two active components: flavonoids and terpenoids. In this study, we investigated the effects of GBE on A53T α-synuclein transgenic mice, a PD model that has better simulated the progression of PD patients than other models such as the 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine-induced PD model. METHODS: Fifty α-synuclein A53T transgenic mice were fed and treated with GBE, and locomotor activity was detected by pole test, forced swim test, and wire-hang test. The expression of tyrosine hydroxylase and dopamine transporters was detected using immunohistochemistry. Superoxide dismutase activity, glutathione peroxidase activity, and malondialdehyde expression were detected using an assay kit. RESULTS: Our results show that GBE treatment improved locomotor activity and that superoxide dismutase and glutathione peroxidase inhibited the expression of methane dicarboxylic aldehyde and recovered the expression of tyrosine hydroxylase and dopamine transporters. CONCLUSIONS: The GBE treatment improved locomotor activity and inhibited the development of PD in the A53T α-synuclein transgenic mice, which may be partly responsible for decreased oxidative damage and maintain the normal dopamine homeostasis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it