Evidence map›Paper›PMID 39630316›Full record

ArticleCellular and molecular neurobiology2024

Identification of miRNA-TF Regulatory Pathways Related to Diseases from a Neuroendocrine-Immune Perspective.

Chengyi Wang, Meitao Wu, Ziyang Wang, Xiaoliang Wu, Hao Yuan, Shuo Jiang, Gen Li, Rifang Lan, Qiuping Wang, Guangde Zhang and 2 more

Abstract read
In one paragraph

Article in Cellular and molecular neurobiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Chengyi Wang *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Meitao Wu *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Ziyang Wang *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Xiaoliang WuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Hao YuanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Shuo JiangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Gen LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Rifang LanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Qiuping WangDepartment of Cardiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Guangde ZhangDepartment of Cardiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China. zhangguangde@ems.hrbmu.edu.cn.
Yingli LvCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. lyu.hrb.bio@hotmail.com.
Hongbo ShiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. shihongbo@ems.hrbmu.edu.cn.

Funding

Natural Science Foundation of Heilongjiang Province LH2021F042Postdoctoral Foundation of Heilongjiang Province LBH-Q17133,LBH-Q21152
6 · The paper itself

Abstract

The neuroendocrine-immune (NEI) network is fundamental for maintaining body's homeostasis and health. While the roles of microRNAs (miRNAs) and transcription factors (TFs) in disease processes are well-established, their synergistic regulation within the NEI network has yet to be elucidated. In this study, we constructed a background NEI-related miRNA-TF regulatory network (NEI-miRTF-N) by integrating NEI signaling molecules (including miRNAs, genes, and TFs) and identifying miRNA-TF feed-forward loops. Our analysis reveals that the number of immune signaling molecules is the highest and suggests potential directions for signal transduction, primarily from the nervous system to both the endocrine and immune systems, as well as from the endocrine system to the immune system. Furthermore, disease-specific NEI-miRTF-Ns for depression, Alzheimer's disease (AD) and dilated cardiomyopathy (DCM) were constructed based on the known disease molecules and significantly differentially expressed (SDE) molecules. Additionally, we proposed a novel method using depth-first-search algorithm for identifying significantly dysregulated NEI-related miRNA-TF regulatory pathways (NEI-miRTF-Ps) and verified their reliability from multiple perspectives. Our study provides an effective approach for identifying disease-specific NEI-miRTF-Ps and offers new insights into the synergistic regulation of miRNAs and TFs within the NEI network. Our findings provide information for new therapeutic strategies targeting these regulatory pathways.

Indexed as

Gene Regulatory NetworksMicroRNAsNeurosecretory SystemsTranscription FactorsAlzheimer DiseaseHumansSignal TransductionMicroRNAsTranscription FactorsEndocrineImmunemiRNA-TF feed-forward loopsNervousNeuroendocrine-immune networkRegulatory pathway

Identifiers

PMID39630316
PMCPMC11618161

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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.