Evidence map›Paper›PMID 35208208›Full record

ArticleMetabolites2022

Automated Recommendation of Research Keywords from PubMed That Suggest the Molecular Mechanism Associated with Biomarker Metabolites.

Shinji Kanazawa, Satoshi Shimizu, Shigeki Kajihara, Norio Mukai, Junko Iida, Fumio Matsuda

Abstract read
In one paragraph

Article in Metabolites, 2022. 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

6 authors.

Shinji KanazawaShimadzu Corporation, Kyoto 604-8511, Japan.ORCID 0000-0003-1244-9924
Satoshi ShimizuShimadzu Corporation, Kyoto 604-8511, Japan.
Shigeki KajiharaShimadzu Corporation, Kyoto 604-8511, Japan.
Norio MukaiShimadzu Corporation, Kyoto 604-8511, Japan.
Junko IidaShimadzu Corporation, Kyoto 604-8511, Japan.
Fumio MatsudaGraduate School of Information Science and Technology, Osaka University, Osaka 565-0871, Japan.ORCID 0000-0003-1091-778X

Funding

Japan Science and Technology Agency JPMJCR21N2
6 · The paper itself

Abstract

Metabolomics can help identify candidate biomarker metabolites whose levels are altered in response to disease development or drug administration. However, assessment of the underlying molecular mechanism is challenging considering it depends on the researcher's knowledge. This study reports a novel method for the automated recommendation of keywords known in the literature that may be overlooked by researchers. The proposed method aided in the identification of Medical Subject Headings (MeSH) terms in PubMed using MeSH co-occurrence data. The intended users are biocurators who have identified specific biomarker metabolites from a metabolomics study and would like to identify literature-reported molecular mechanisms that are associated with both the metabolite and their research area of interest. The proposed method finds MeSH terms that co-occur with a MeSH term of the candidate biomarker metabolite as well as a MeSH term of a researcher's known keyword, such as the name of a disease. The connectivity score

Indexed as

association analysisbiomarker discoverykeyword recommendationMedical Subject Headings termsMeSH co-occurrence

Identifiers

PMID35208208
PMCPMC8875447

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.