Tetrahydroxystilbene glucoside improves the learning and memory of amyloid-β<sub>1–42</sub>-injected rats and may be connected to synaptic changes in the hippocampus
Bibliographic record
Abstract
The aim of this study was to evaluate the protective effects of 2,3,5,4'-tetrahydroxystilbene-2-O-β-D-glucoside (TSG), an active component extracted from Polygonum multiflorum, on learning/memory deficits in Alzheimer's disease (AD). We randomly divided 24 male Sprague-Dawley rats among 4 groups: (i) the sham-operated group (control); (ii) sham-operated group also treated with TSG (sham+TSG); (iii) beta amyloid treated group (Aβ); and (iv) Aβ treatment group also treated with TSG (Aβ+TSG). Rats in the Aβ and Aβ+TSG groups were treated with Aβ₁₋₄₂ intracerebroventricularly, whereas the control and sham+TSG groups were given phosphate-buffered saline. Rats in the sham+TSG and Aβ+TSG groups were then treated intragastrically with TSG (50 mg·(kg body mass)⁻¹·day⁻¹) for 4 weeks, and rats in the Aβ and control groups were treated with saline. The results from Morris water maze tests, electron microscopy, real-time polymerase chain reaction, and Western blotting demonstrated that Aβ₁₋₄₂ induced impairment in learning and memory, degeneration in synaptic structures, and downregulation of Src and NR2B at the gene and protein level, respectively. These alterations were reversed by the administration of TSG, suggesting that TSG exerts anti-AD properties by protecting synaptic structure and function. TSG-induced upregulation of Src and NR2B may be responsible for this process.
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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".