Evidence map›Paper›PMID 33024988›Full record

ArticleBriefings in bioinformatics2021

Network-based identification genetic effect of SARS-CoV-2 infections to Idiopathic pulmonary fibrosis (IPF) patients.

Tasnimul Alam Taz, Kawsar Ahmed, Bikash Kumar Paul, Md Kawsar, Nargis Aktar, S M Hasan Mahmud, Mohammad Ali Moni

Open access · bronzeAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 2 pooled it
9.1field-weighted citation impact, top 2% 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

59 citing papers in PubMed, 2 syntheses or guidelines pooled it, 82 citations in OpenAlex.

  1. Pooled it
  2. The role of microRNAs in modulating SARS-CoV-2 infection in human cells: a systematic review.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2021
    Pooled it
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  18. Systems biology andHeliyon · 2022
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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

7 authors at 4 institutions in 3 countries.

Tasnimul Alam TazDepartment of Software Engineering, Daffodil International University.
Kawsar AhmedInformation and Communication Technology (ICT) at Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
Bikash Kumar PaulDepartment of Information and Communication Technology (ICT) at Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
Md KawsarDepartment of Software Engineering, Daffodil International University.
Nargis AktarDepartment of Information and Communication Technology, Mawlana Bhashani Science and Technology University, Santosh, Tangail-1902, Bangladesh.
S M Hasan MahmudShenyang University of Chemical Technology, China.
Mohammad Ali MoniUniversity of New South Wales, Australia.
Mawlana Bhashani Science and Technology University · BDDaffodil International University · BDShenyang University of Chemical Technology · CNUNSW Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the cause of coronavirus disease (COVID-19) that causes a major threat to humanity. As the spread of the virus is probably getting out of control on every day, the epidemic is now crossing the most dreadful phase. Idiopathic pulmonary fibrosis (IPF) is a risk factor for COVID-19 as patients with long-term lung injuries are more likely to suffer in the severity of the infection. Transcriptomic analyses of SARS-CoV-2 infection and IPF patients in lung epithelium cell datasets were selected to identify the synergistic effect of SARS-CoV-2 to IPF patients. Common genes were identified to find shared pathways and drug targets for IPF patients with COVID-19 infections. Using several enterprising Bioinformatics tools, protein-protein interactions (PPIs) network was designed. Hub genes and essential modules were detected based on the PPIs network. TF-genes and miRNA interaction with common differentially expressed genes and the activity of TFs are also identified. Functional analysis was performed using gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathway and found some shared associations that may cause the increased mortality of IPF patients for the SARS-CoV-2 infections. Drug molecules for the IPF were also suggested for the SARS-CoV-2 infections.

Indexed as

COVID-19Datasets as TopicEpithelial CellsGene OntologyGenes, ViralHumansIdiopathic Pulmonary FibrosisLungSARS-CoV-2Transcriptomedifferentially expressed genesdrug moleculegene ontologyhub geneidiopathic pulmonary fibrosisprotein–protein interactionsSARS-CoV-2

Identifiers

PMID33024988
PMCPMC7665362
OpenAlexW3092577522

What OpenQuestion holds

Textmetadata
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.