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Record W1969678037 · doi:10.1017/s0007114512003406

Molecular mechanisms of the cardiovascular protective effects of polyphenols

2012· review· en· W1969678037 on OpenAlexafffund
Ramaroson Andriantsitohaina, Cyril Auger, Thierry Chataigneau, Nelly Étienne-Selloum, Huige Li, Maria Carmen Martínez, Valérie B. Schini‐Kerth, Ismail Laher

Bibliographic record

VenueBritish Journal Of Nutrition · 2012
Typereview
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsUniversity of British Columbia
FundersCentre National de la Recherche ScientifiqueUniversité de StrasbourgCanadian Society of Pharmacology and TherapeuticsInstitut National de la Santé et de la Recherche MédicaleUniversite AngersDeutsche Forschungsgemeinschaft
KeywordsPolyphenolOxidative stressAntioxidantReactive oxygen speciesBiochemistryEndothelial dysfunctionChemistryIntracellularPharmacologyBiologyEndocrinology

Abstract

fetched live from OpenAlex

Epidemiological studies have reported a greater reduction in cardiovascular risk and metabolic disorders associated with diets rich in polyphenols. The antioxidant effects of polyphenols are attributed to the regulation of redox enzymes by reducing reactive oxygen species production from mitochondria, NADPH oxidases and uncoupled endothelial NO synthase in addition to also up-regulating multiple antioxidant enzymes. Although data supporting the effects of polyphenols in reducing oxidative stress are promising, several studies have suggested additional mechanisms in the health benefits of polyphenols. Polyphenols from red wine increase endothelial NO production leading to endothelium-dependent relaxation in conditions such as hypertension, stroke or the metabolic syndrome. Numerous molecules contained in fruits and vegetables can activate sirtuins to increase lifespan and silence metabolic and physiological disturbances associated with endothelial NO dysfunction. Although intracellular pathways involved in the endothelial effects of polyphenols are partially described, the molecular targets of these polyphenols are not completely elucidated. We review the novel aspects of polyphenols on several targets that could trigger the health benefits of polyphenols in conditions such as metabolic and cardiovascular disturbances.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.837
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.257
Teacher spread0.240 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations209
Published2012
Admission routes2
Has abstractyes

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