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Record W3194078993 · doi:10.3390/molecules26164865

A Concise Review of Current In Vitro Chemical and Cell-Based Antioxidant Assay Methods

2021· review· en· W3194078993 on OpenAlexafffund
Ifeanyi D. Nwachukwu, Roghayeh Amini Sarteshnizi, Chibuike C. Udenigwe, Rotimi E. Aluko

Bibliographic record

VenueMolecules · 2021
Typereview
Languageen
FieldChemistry
TopicFree Radicals and Antioxidants
Canadian institutionsUniversity of ManitobaUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAntioxidantRadicalChemistryHydrogen peroxideDPPHBiochemistrySuperoxideFerricReactive oxygen speciesCombinatorial chemistryOrganic chemistryEnzyme

Abstract

fetched live from OpenAlex

Antioxidants remain interesting molecules of choice for suppression of the toxic effects of free radicals in foods and human systems. The current practice involves the use of mainly synthetic molecules as potent antioxidant agents. However, due to the potential negative impact on human health, there is an intensive effort within the research community to develop natural alternatives with similar antioxidant efficacy but without the negative side effects of synthetic molecules. Still, the successful development of new molecules depends on the use of reliable chemical or cell culture assays to screen antioxidant properties. Chemical antioxidant assays include the determination of scavenging ability against free radicals such as DPPH, superoxide anion radicals, hydroxyl radicals, hydrogen peroxide, and nitric oxide. Other antioxidant tests include the ability of compounds to bind and sequester prooxidant metal cations, reduce ferric iron, and attenuate the rate of lipid oxidation. Ex vivo tests utilize cell cultures to confirm entry of the molecules into cells and the ability to quench synthetic intracellular free radicals or to stimulate the increased biosynthesis of endogenous antioxidants. In order to assist researchers in their choice of antioxidant evaluation methods, this review presents background scientific information on some of the most commonly used antioxidant assays with a comparative discussion of the relevance of published literature data to food science and human nutrition applications.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.004

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 head0.043
GPT teacher head0.379
Teacher spread0.336 · 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

Citations109
Published2021
Admission routes2
Has abstractyes

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