Evidence map›Paper›PMID 36771125›Full record

ArticleMolecules (Basel, Switzerland)2023

Feature Selection for the Interpretation of Antioxidant Mechanisms in Plant Phenolics.

Taiki Fujimoto, Hiroaki Gotoh

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

2 authors.

Taiki FujimotoDepartment 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

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antioxidants, represented by plant phenolics, protect living tissues by scavenging reactive oxygen species through diverse reaction mechanisms. Research on antioxidants is often individualized, for example, focusing on the evaluation of their activity against a single reactive oxygen species or examining the antioxidant properties of compounds with similar structures. In this study, multivariate analysis was used to comprehensively examine antioxidant properties. Eighteen features were selected to explain the results of the antioxidant capacity tests. These selected features were then evaluated by supervised learning, using the results of the antioxidant capacity assays. Dimension-reduction techniques were also used to represent the compound space with antioxidants as a two-dimensional distribution. A small amount of data obtained from several assays provided us with comprehensive information on the relationships between the structures and activities of antioxidants.

Indexed as

AntioxidantsPhenolsPlant ExtractsPlantsReactive Oxygen SpeciesAntioxidantsPhenolsPlant ExtractsReactive Oxygen Speciesantioxidantschemical spacefeature selectioninterpretationmachine learningstructure–activity relationship

Identifiers

PMID36771125
PMCPMC9921549

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.