Evidence map›Paper›PMID 32915913›Full record

ArticlePloS one2020

Novel genes associated with folic acid-mediated metabolism in mouse: A bioinformatics study.

Jianwen Zhao, Wen Zou, Tingxi Hu

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 32% of its field
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

4 citing papers in PubMed, 7 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Jianwen ZhaoShenyang Medical College, Shenyang, Liaoning, China.
Wen ZouLiaoning Vocational College of Ecological Engineering, Shenyang, Liaoning, China.
Tingxi HuShenyang Medical College, Shenyang, Liaoning, China.ORCID 0000-0001-7316-686X
Shenyang Medical College · CNHeilongjiang Vocational Institute of Ecological Engineering · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Folic acid plays an essential role in the central nervous system and cancer. This study aimed to screen genes related to folic acid metabolism. Datasets (GSE80587, GSE65267 and GSE116299) correlated to folic acid were screened in the Gene Expression Omnibus. Weighed gene co-expression network analysis was performed to identify modules associated with sample traits of folic acid and organs (brain, prostate and kidney). Functional enrichment analysis was performed for the eigengenes in modules that were significantly correlated with sample traits. Accordingly, the hub genes and key nodes in the modules were identified using the protein interaction network. A total of 17,252 genes in three datasets were identified. One module, which included 97 genes that were highly correlated with sample traits (including folic acid treatment [cor = -0.57, P = 3e-04] and kidney [cor = -0.68, p = 4e-06]), was screened out. Hub genes, including tetratricopeptide repeat protein 38 (Ttc38) and miR-185, as well as those (including Sema3A, Insl3, Dll1, Msh4 and Snai1) associated with "neuropilin binding", "regulation of reproductive process" and "vitamin D metabolic process", were identified. Genes, including Ttc38, Sema3A, Insl3, Dll1, Msh4 and Snai1, were the novel factors that may be associated with the development of the kidneys and related to folic acid treatment.

Indexed as

Gene Regulatory NetworksAnimalsComputational BiologyDatabases, GeneticFemaleFolic AcidGene Expression ProfilingHomocysteineKidneyMaleMiceMicroRNAsProtein Interaction MapsTetratricopeptide RepeatFolic AcidHomocysteineMicroRNAsMirn185 microRNA, mouse

Identifiers

PMID32915913
PMCPMC7485790
OpenAlexW3084994537

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.