Evidence map›Paper›PMID 41614844›Full record

ArticleCurrent issues in molecular biology2025

DPPH Measurement for Phenols and Prediction of Antioxidant Activity of Phenolic Compounds in Food.

Riku Kato, Chihiro Tada, Moeka Yamauchi, Yuto Matsumoto, Hiroaki Gotoh

Abstract read
In one paragraph

Article in Current issues in molecular biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Riku KatoDepartment of Chemistry and Life Science, Yokohama National University, Hodogaya-ku, Yokohama 240-8501, Japan.
Chihiro TadaDepartment of Chemistry and Life Science, Yokohama National University, Hodogaya-ku, Yokohama 240-8501, Japan.
Moeka YamauchiDepartment of Chemistry and Life Science, Yokohama National University, Hodogaya-ku, Yokohama 240-8501, Japan.
Yuto MatsumotoDepartment of Chemistry and Life Science, Yokohama National University, Hodogaya-ku, Yokohama 240-8501, Japan.
Hiroaki GotohDepartment of Chemistry and Life Science, Yokohama National University, Hodogaya-ku, Yokohama 240-8501, Japan.ORCID 0000-0002-1920-6020

Funding

Japan Society for the Promotion of Science JP24K08785
6 · The paper itself

Abstract

Consuming foods with high antioxidant capacity is considered beneficial to health, and predicting the antioxidant capacity of food components is important. In the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, multiple reactions occur simultaneously, and because the experimental conditions are not standardized across studies, quantitative prediction of DPPH activity is difficult. In this study, we qualitatively and quantitatively predicted the DPPH activity of phenols in food using data obtained under unified experimental conditions and machine learning. We measured DPPH activity of 96 compounds to create a dataset comprising measurements of 274 compounds, including values previously reported by our laboratory. The classification model implemented using LightGBM showed high performance, achieving an accuracy of 0.88 and an F1 score of 0.86. The support vector regression model satisfied the Golbraikh-Tropsha criteria, with an R

Indexed as

antioxidant capacityDPPHfood informaticsmachine learningphenolQSAR

Identifiers

PMID41614844
PMCPMC12840554

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.