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Record W2342277829 · doi:10.3390/molecules21040487

Comparison of Antioxidant Activities of Melanin Fractions from Chestnut Shell

2016· article· en· W2342277829 on OpenAlexfundno aff
Zeng-Yu Yao, Jianhua Qi

Bibliographic record

VenueMolecules · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaNational Natural Science Foundation of China
KeywordsChemistryAntioxidantFerrousDPPHChelationScavengingNuclear chemistrySuperoxideOrganic chemistryRadical

Abstract

fetched live from OpenAlex

Chestnut shell melanin can be used as a colorant and antioxidant, and fractionated into three fractions (Fr. 1, Fr. 2, and Fr. 3) with different physicochemical properties. Antioxidant activities of the fractions were comparatively evaluated for the first time. The fractions exhibited different antioxidative potential in different evaluation systems. Fr. 1, which is only soluble in alkaline water, had the strongest peroxidation inhibition and superoxide anion scavenging activity; Fr. 2, which is soluble in alkaline water and hydrophilic organic solvents but insoluble in neutral and acidic water, had the greatest power to chelate ferrous ions; and Fr. 3, which is soluble both in hydrophilic organic solvents and in water at any pH conditions, had the greatest hydroxyl (·OH) and 1,1-diphenyl-2-picryl-hydrazyl (DPPH·) radicals scavenging abilities, reducing power, and phenolic content. The pigment fractions were superior to butylated hydroxytolune (BHT) in ·OH and DPPH· scavenging and to ethylene diamine tetraacetic acid (EDTA) in the Fe(2+)-chelation. They were inferior to BHT in peroxidation inhibition and O₂·(-) scavenging and reducing power. However, BHT is a synthetic antioxidant and cannot play the colorant role. The melanin fractions might be used as effective biological antioxidant colorants.

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 score0.013
Threshold uncertainty score0.235

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 head0.018
GPT teacher head0.299
Teacher spread0.281 · 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

Citations47
Published2016
Admission routes1
Has abstractyes

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