Evidence map›Paper›PMID 35514751›Full record

ArticleFrontiers in medicine2022

Wen Wang, Xiaojing Liu, Peiyao Wei, Feng Ye, Yunru Chen, Lei Shi, Xi Zhang, Jianzhou Li, Shumei Lin, Xueliang Yang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

15 citing papers in PubMed, 21 citations in OpenAlex.

  1. [SingleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
    Article
  2. Article
  3. Article
  4. Identifying the Crucial Biomarker of MASH-Related HCC.Combinatorial chemistry & high throughput screening · 2025
    Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
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

10 authors at 1 institution in 1 country.

Wen WangDepartment of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Xiaojing LiuDepartment of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Peiyao WeiDepartment of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Feng YeDepartment of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yunru ChenDepartment of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Lei ShiDepartment of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Xi ZhangDepartment of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Jianzhou LiDepartment of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Shumei LinDepartment of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Xueliang YangDepartment of Nutrition, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
First Affiliated Hospital of Xi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Non-alcoholic fatty liver disease (NAFLD) is a major chronic liver disease worldwide, and non-alcoholic steatohepatitis (NASH) is one of its pathological subtypes. The pathogenesis of NASH has not yet been fully elucidated. The purpose of this study was to identify the hub genes and pathways involved in NASH using bioinformatics methods. The hub genes were confirmed in human and animal models. Materials and Methods: Three Gene Expression Omnibus (GEO) datasets (GSE48452, GSE58979, and GSE151158) of NASH patients and healthy controls were included in the study. We used GEO2R to identify differentially expressed genes (DEGs) between NASH patients and healthy controls. Functional enrichment analyses were then performed to explore the potential functions and pathways of the DEGs. In all DEGs, only two genes were highly expressed in NASH patients throughout the three datasets; these two genes, Results: Conclusion:

Indexed as

bioinformatics analysisCXCL9MCD dietNASHSPP1

Identifiers

PMID35514751
PMCPMC9063562
OpenAlexW4224252063

What OpenQuestion holds

Textmetadata
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.