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Record W2073304331 · doi:10.3390/molecules15031196

trans-Resveratrol as A Neuroprotectant

2010· review· en· W2073304331 on OpenAlexaff
Ellen L. Robb, Jeffrey A. Stuart

Bibliographic record

VenueMolecules · 2010
Typereview
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsBrock University
Fundersnot available
KeywordsNeuroprotectionResveratrolOxidative stressProgrammed cell deathCell damageEstrogen receptorAntioxidantBiologyPharmacologyNeuroscienceEstrogenCell biologyChemistryApoptosisBiochemistryCancerEndocrinologyGenetics

Abstract

fetched live from OpenAlex

Epidemiological evidence indicates that nutritionally-derived polyphenols such as resveratrol (RES) have neuroprotective properties. Administration of RES to culture media protects a wide variety of neuronal cell types from stress-induced death. Dietary supplementation of RES can ameliorate neuronal damage and death resulting from both acute and chronic stresses in rodents. The specific molecular mechanisms by which RES acts at the cellular level remain incompletely understood. However, many experimental data indicate that RES reduces or prevents the occurrence of oxidative damage. Here we discuss possible mechanisms by which RES might exert protection against oxidative damage and cell death. Evidence suggesting that RES's chemical antioxidant potential is not sufficient explanation for its effects is discussed. Putative biological activities, including interactions with estrogen receptors and sirtuins are critically discussed. We provide a synthesis of how RES's phytoestrogenic properties might mediate the neuronal stress resistance underlying its observed neuroprotective properties.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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.

Opus teacher head0.026
GPT teacher head0.334
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations50
Published2010
Admission routes1
Has abstractyes

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