Evidence map›Paper›PMID 39606164›Full record

ArticleWorld journal of hepatology2024

Development and validation of biomarkers related to anoikis in liver cirrhosis based on bioinformatics analysis.

Jiang-Yan Luo, Sheng Zheng, Juan Yang, Chi Ma, Xiao-Ying Ma, Xing-Xing Wang, Xin-Nian Fu, Xiao-Zhou Mao

Abstract read
In one paragraph

Article in World journal of hepatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

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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

8 authors.

Jiang-Yan LuoDepartment of Gastroenterology, The Second Affiliated Hospital of Dali University, Kunming 650011, Yunnan Province, China.
Sheng ZhengDepartment of Gastroenterology, The Third People's Hospital of Yunnan Province, Kunming 650011, Yunnan Province, China. zheng_sheng523@163.com.
Juan YangDepartment of Gastroenterology, The Third People's Hospital of Yunnan Province, Kunming 650011, Yunnan Province, China.
Chi MaDepartment of Gastroenterology, The Second Affiliated Hospital of Dali University, Kunming 650011, Yunnan Province, China.
Xiao-Ying MaDepartment of Gastroenterology, The Second Affiliated Hospital of Dali University, Kunming 650011, Yunnan Province, China.
Xing-Xing WangDepartment of Gastroenterology, The Second Affiliated Hospital of Dali University, Kunming 650011, Yunnan Province, China.
Xin-Nian FuDepartment of Gastroenterology, The Second Affiliated Hospital of Dali University, Kunming 650011, Yunnan Province, China.
Xiao-Zhou MaoDepartment of Gastroenterology, The Second Affiliated Hospital of Dali University, Kunming 650011, Yunnan Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccording to study, anoikis-related genes (ARGs) have been demonstrated to play a significant impact in cirrhosis, a major disease threatening human health worldwide.

aimTo investigate the relationship between ARGs and cirrhosis development to provide insights into the clinical treatment of cirrhosis.

methodsRNA-sequencing data related to cirrhosis were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between cirrhotic and normal tissues were intersected with ARGs to derive differentially expressed ARGs (DEARGs). The DEARGs were filtered using the least absolute shrinkage and selection operator, support vector machine recursive feature elimination, and random forest algorithms to identify biomarkers for cirrhosis. These biomarkers were used to create a nomogram for predicting the prognosis of cirrhosis. The proportions of diverse immune cell subsets in cirrhotic

resultsThe comparison of cirrhotic and normal tissue samples led to the identification of 635 DEGs. Subsequent intersection of the DEGs with ARGs produced a set of 26 DEARGs. Subsequently, three DEARGs, namely,

conclusionThis study revealed

Indexed as

Anoikis-related genesBioinformaticsBiomarkerCirrhosisImmune infiltrationMachine learningTherapeutic drugs

Identifiers

PMID39606164
PMCPMC11586749

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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.