Comparative Neuroprotective Properties of Stilbene and Catechin Analogs: Action Via a Plasma Membrane Receptor Site?
Bibliographic record
Abstract
Various studies have reported on the neuroprotective effects of polyphenols, widely present in food, beverages, and natural products. For example, we have shown that resveratrol, a polyphenol enriched in red wine and other foods such as peanuts, protects hippocampal cells against beta-amyloid (Abeta)-induced toxicity, a key protein involved in the neuropathology of Alzheimer disease. This effect involves, at least in part, the capacity of resveratrol to activate the phosphorylation of delta isoform of protein kinase C (PKC-delta). The neuroprotective action of resveratrol is shared by piceatannol, a stilbene derivative, as well as by tea-derived catechin gallate esters. The thioflavin T assay indicated that all these polyphenols inhibited the formation of Abeta fibrils, suggesting that this action likely also contributes to their neuroprotective effects. Binding and autoradiographic studies revealed that the effects of polyphenols might involve specific binding sites that are particularly enriched in the choroid plexus in the rat brain. Interestingly, the choroid plexus secretes transthyretin, a protein that has been shown to modulate Abeta aggregation and that may be critical to the maintenance of normal learning capacities in aging. Taken together, these data suggest that polyphenols target multiple enzymes/proteins, leading to their neuroprotective actions, possibly through action via specific plasma membrane binding sites.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".