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Resveratrol as a Protective Molecule for Neuroinflammation: A Review of Mechanisms

2014· review· en· W1982678998 on OpenAlexaff
Justine Renaud, Maria‐Grazia Martinoli

Bibliographic record

VenueCurrent Pharmaceutical Biotechnology · 2014
Typereview
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsNeuroinflammationResveratrolChemistryPharmacologyMedicineNeuroscienceInflammationImmunologyBiology

Abstract

fetched live from OpenAlex

Under normal conditions, most of the central nervous system (CNS) is protected by the blood brain barrier (BBB) from systemic inflammation progression and from the infiltration of immune cells. As a consequence, the CNS developed an original way to provide surveillance, defense and repair, which relies on the complex process of neuroinflammation. Despite tight regulation, neuroinflammation is frequently the cause of irreversible nerve cell loss but it is also where the solution lies. Specific immune crosstalk taking place in the CNS needs to be decoded in order to identify the best therapeutic strategies aimed at helping the CNS restore homeostasis in difficult conditions such as in neurodegenerative disorders. This review deals with the double-edged sword nature of neuroinflammation and the use of resveratrol in various models as one of the most promising therapeutic molecules for preventing the consequences of nerve cell autodestruction.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.082
GPT teacher head0.459
Teacher spread0.377 · 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

Citations35
Published2014
Admission routes1
Has abstractyes

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