Evidence map›Paper›PMID 36685392›Full record

ArticleHeliyon2023

Dynamic transcriptome analyses reveal m

Ya Zhang, Jing Guo, Yueying Gao, Si Li, Tao Pan, Gang Xu, Xia Li, Yongsheng Li, Jun Yang

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 9 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

9 authors at 2 institutions in 1 country.

Ya ZhangKey Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China.
Jing GuoKey Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China.
Yueying GaoKey Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China.
Si LiKey Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China.
Tao PanKey Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China.
Gang XuKey Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China.
Xia LiKey Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China.
Yongsheng LiKey Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China.
Jun YangKey Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China.
Hainan Medical University · CNHarbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dengue infection is one of the most prevalent arthropod-borne viral diseases, which can result in severe complications. Identification of genes and long non-coding RNAs (lncRNAs) involved in dengue infection would help in deciphering potential mechanisms responsible for the disease progression. We comprehensively analyzed the dynamic transcriptome during dengue disease progression and identified critical genes and lncRNAs with expression perturbations. Our findings revealed that the expression of genes (i.e., CCR10 and GNG7) and lncRNAs (i.e., CTBP1-AS and MAFG-AS1) were potentially regulated by m6A RNA methylation. Interestingly, dengue viral proteins prevalently interact with genes or lncRNAs with expression perturbations, which are involved in cell cycle, inflammation signaling pathways and immune response. Dynamically expressed genes and lncRNAs were likely to locate in the central regions of human protein-protein network, which play crucial roles in mediating signaling spread and helping viral replication. Immune microenvironments analysis revealed that plasma cells levels were increased and T cells infiltrations were decreased during dengue disease progression. Dynamically expressed genes and lncRNAs were correlated with immune cell infiltrations. Moreover, network analysis reveals the associations between dengue viral infections and human complex diseases (i.e., digestive diseases and neoplasms). Our comprehensive transcriptome analysis of dengue disease progression identified potential gene and lncRNA biomarkers, providing novel insights for understanding the pathogenesis of and developing effective therapeutic strategies for dengue infection.

Indexed as

BiomarkersImmuneLong noncoding RNAsNetwork analysisTranscriptome

Identifiers

PMID36685392
PMCPMC9850062
OpenAlexW4313593968

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.