Isolation of Neuroprotective Anthocyanins from Black Chokeberry (Aronia melanocarpa) against Amyloid-β-Induced Cognitive Impairment
Bibliographic record
Abstract
Black chokeberry (Aronia melanocarpa) fruits are rich in anthocyanins, which are vital secondary metabolites that possess antioxidative properties. The aim of this study was to isolate and purify the anthocyanins from black chokeberry by simulated moving bed (SMB) chromatography, and to investigate the neuroprotective effect of SMB purified anthocyanin against Aβ-induced memory damage in rats. The parameters of the SMB process were studied and optimized. Anthocyanin extracts were identified by HPLC and UPLC-QTOF-MS, and antioxidant abilities were evaluated. The Aβ-induced animal model was established by intracerebral ventricle injection in rat brain. Through the SMB purification, anthocyanins were purified to 85%; cyanidin 3-O-galactoside and cyanidin 3-O-arabinoside were identified as the main anthocyanins by UPLC-QTOF-MS. The SMB purified anthocyanins exhibited higher DPPH and ABTS free radical scavenging abilities than the crude anthocyanins extract. Furthermore, rats receiving SMB purified anthocyanins treatment (50 mg/kg) showed improved spatial memory in a Morris water maze test, as well as protection of the cells in the hippocampus against Aβ toxicity. These results demonstrate that anthocyanins could serve as antioxidant and neuroprotective agents, with potential in the treatment of Alzheimer’s disease.
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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) | 0.001 | 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".