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Record W2167724775 · doi:10.1139/cjpp-2015-0088

Grape seed and skin extract protects against arsenic trioxide induced oxidative stress in rat heart

2015· article· en· W2167724775 on OpenAlexvenueno aff
Ichraf Sfaxi, Kamel Charradi, Férid Limam, Michèle Véronique El May, Ezzedine Aouani

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsnot available
Fundersnot available
KeywordsArsenic trioxideOxidative stressChemistrySuperoxide dismutaseAntioxidantCatalaseGlutathione peroxidasePharmacologyArsenicProtein CarbonylationBiochemistryCardiotoxicityLipid peroxidationBiologyApoptosisToxicity

Abstract

fetched live from OpenAlex

Arsenic is a metalloid found in water, soil, and air from natural and anthropogenic sources, and is commonly found in inorganic as well as organic forms. The clinical use of arsenic trioxide (As 2 O 3 ) in the treatment of acute promyelocytic leukemia (APL) is limited by its cardiotoxic side effects. Grape seed and skin extract (GSSE) is a polyphenolic mixture with antioxidant properties. This study aimed to evaluate the protective effect of GSSE on arsenic-induced cardiac oxidative stress and injury. Animals exposed to 2.5 mg/kg As 2 O 3 for 21 days exhibited a relevant increase in heart lipoperoxidation, protein carbonylation, and inflammation, as well as a drop in the activity of antioxidant enzymes such as catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GPx). In addition, As 2 O 3 disturbed heart lipidemia and lipase activity, transition metals distribution and the associated enzymes, intracellular mediators such as calcium and the associated calpain activity, as well as myocardial architecture. Treatment with 4 g/kg GSSE protected against most of the deleterious effects provoked by As 2 O 3 . Our data suggest that GSSE has the potential to protect against As 2 O 3 -induced cardiotoxicity.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.268
Teacher spread0.252 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations30
Published2015
Admission routes1
Has abstractyes

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