Evidence map›Paper›PMID 35174175›Full record

ReviewFrontiers in cell and developmental biology2021

Revealing Cavin-2 Gene Function in Lung Based on Multi-Omics Data Analysis Method.

Changsheng Li, Jingyu Huang, Hexiao Tang, Bing Liu, Xuefeng Zhou

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2021. 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
0.2field-weighted citation impact, top 54% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
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

5 authors at 2 institutions in 1 country.

Changsheng LiDepartment of Thoracic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.
Jingyu HuangDepartment of Thoracic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.
Hexiao TangDepartment of Thoracic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.
Bing LiuDepartment of Pulmonary and Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.
Xuefeng ZhouDepartment of Thoracic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.
Wuhan University · CNZhongnan Hospital of Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Research points out that it is particularly important to comprehensively evaluate immune microenvironmental indicators and gene mutation characteristics to select the best treatment plan. Therefore, exploring the relevant genes of pulmonary injury is an important basis for the improvement of survival. In recent years, with the massive production of omics data, a large number of computational methods have been applied in the field of biomedicine. Most of these computational methods are devel-oped for a certain type of diseases or whole diseases. Algorithms that specifically identify genes associated with pulmonary injury have not yet been developed. To fill this gap, we developed a novel method, named AdaRVM, to identify pulmonary injury-related genes in large scale. AdaRVM is the fusion of Adaboost and Relevance Vector Machine (RVM) to achieve fast and high-precision pattern recognition of pulmonary injury genetic mechanism. AdaRVM found that Cavin-2 gene has strong potential to be related to pulmonary injury. As we known, the formation and function of Caveolae are mediated by two family proteins: Caveolin and Cavin. Many studies have explored the role of Caveolin proteins, but people still knew little about Cavin family members. To verify our method and reveal the functions of cavin-2, we integrated six genome-wide association studies (GWAS) data related to lung function traits, four expression Quantitative Trait Loci (eQTL) data, and one methylation Quantitative Trait Loci (mQTL) data by Summary data level Mendelian Randomization (SMR). We found strong relationship between cavin-2 and canonical signaling pathways ERK1/2, AKT, and STAT3 which are all known to be related to lung injury.

Indexed as

adaboostcavin-2lung cancerpulmonary injuryrelevance vector machine

Identifiers

PMID35174175
PMCPMC8841408
OpenAlexW4210502419

What OpenQuestion holds

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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.