Evidence map›Paper›PMID 38255822›Full record

ArticleInternational journal of molecular sciences2024

Immune-Related Molecules

Nanxi Li, Peng Ren, Jingya Wang, Xiaohui Zhu, Xuan Qiao, Zhirui Zeng, Tong Ye, Shanshan Wang, Zhiyun Meng, Hui Gan and 5 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 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
0.2field-weighted citation impact, top 48% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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

15 authors at 2 institutions in 1 country.

Nanxi LiDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Peng RenBeijing Institute of Basic Medical Sciences, Beijing 100850, China.
Jingya WangBeijing Institute of Basic Medical Sciences, Beijing 100850, China.
Xiaohui ZhuDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Xuan QiaoDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Zhirui ZengGuizhou Provincial Key Laboratory of Pathogenesis & Drug Research on Common Chronic Diseases, Department of Physiology, School of Basic Medical Sciences, Guizhou Medical University, Guiyang 550000, China.ORCID 0000-0001-9547-9074
Tong YeDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Shanshan WangDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Zhiyun MengDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Hui GanDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Shuchen LiuDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Yunbo SunDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Xiaoxia ZhuDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Guifang DouDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.ORCID 0000-0001-5004-2194
Ruolan GuDepartment of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, China.
Beijing Institute of Education · CNGuiyang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis ranks among the most common health problems worldwide, characterized by organ dysfunction resulting from infection. Excessive inflammatory responses, cytokine storms, and immune-induced microthrombosis are pivotal factors influencing the progression of sepsis. Our objective was to identify novel immune-related hub genes for sepsis through bioinformatic analysis, subsequently validating their specificity and potential as diagnostic and prognostic biomarkers in an animal experiment involving a sepsis mice model. Gene expression profiles of healthy controls and patients with sepsis were obtained from the Gene Expression Omnibus (GEO) and analysis of differentially expressed genes (DEGs) was conducted. Subsequently, weighted gene co-expression network analysis (WGCNA) was used to analyze genes within crucial modules. The functional annotated DEGs which related to the immune signal pathways were used for constructing protein-protein interaction (PPI) analysis. Following this, two hub genes,

Indexed as

Animal ExperimentationSepsisAnimalsBiomarkersCD3 ComplexCell AdhesionComputational BiologyDisease Models, AnimalHumansMembrane ProteinsMiceNeoplasm ProteinsBiomarkersCD3 antigen, gamma chainCD3 ComplexFERMT3 protein, humanFermt3 protein, mouseMembrane ProteinsNeoplasm ProteinsbiomarkersCD3GFERMT3hub genesepsisWGCNA

Identifiers

PMID38255822
PMCPMC10815248
OpenAlexW4390672276

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.