Protective effects of polyphenol-rich extracts against neurotoxicity elicited by paraquat or rotenone in cellular models of Parkinson’s disease
Bibliographic record
Abstract
Abstract Parkinson’s disease (PD) is a neurodegenerative disorder involving motor symptoms caused by a loss of dopaminergic neurons in the substantia nigra region of the brain. Epidemiological evidence suggests that anthocyanin (ANC) intake is associated with a low risk of PD. Previously, we reported that extracts enriched with ANC and proanthocyanidins (PAC) suppressed dopaminergic neuron death elicited by the PD-related toxin rotenone in a primary midbrain culture model. Here, we characterized botanical extracts enriched with a mixed profile of polyphenols, as well as a set of purified polyphenolic standards, in terms of their ability to mitigate dopaminergic cell death in midbrain cultures exposed to another PD-related toxicant, paraquat (PQ), and we examined underlying neuroprotective mechanisms. Extracts prepared from blueberries, black currants, grape seeds, grape skin, mulberries, and plums, as well as several ANC, were found to rescue dopaminergic neuron loss in PQ-treated cultures. Comparison of a subset of ANC-rich extracts for the ability to mitigate neurotoxicity elicited by PQ versus rotenone revealed that a hibiscus or plum extract was only neuroprotective in cultures exposed to rotenone or PQ, respectively. Several extracts or compounds with the ability to protect against PQ neurotoxicity increased the activity of the antioxidant transcription factor Nrf2 in cultured astrocytes, and PQ-induced dopaminergic cell death was attenuated in Nrf2-expressing midbrain cultures. In other studies, we found that extracts prepared from hibiscus, grape skin, or purple basil (but not plums) rescued defects in O 2 consumption in neuronal cells treated with rotenone. Collectively, these findings suggest that extracts enriched with certain combinations of ANC, PAC, stilbenes, and other polyphenols could potentially slow neurodegeneration in the brains of individuals exposed to PQ or rotenone by activating cellular antioxidant mechanisms and/or alleviating mitochondrial dysfunction.
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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 | 0.000 |
| 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".