Evidence map›Paper›PMID 37626824›Full record

ArticleBiomedicines2023

Single-Cell RNA Sequencing and Microarray Analysis Reveal the Role of Lipid-Metabolism-Related Genes and Cellular Immune Infiltration in Pre-Eclampsia and Identify Novel Biomarkers for Pre-Eclampsia.

Yujie Liu, Borui Xu, Cuifang Fan

Open access · goldAbstract read
In one paragraph

Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Yujie LiuDepartment of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan 430060, China.ORCID 0009-0006-7432-5045
Borui XuDepartment of Pancreato-Biliary Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China.
Cuifang FanDepartment of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan 430060, China.
Wuhan University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pre-eclampsia (PE) is a gestational hypertensive disorder that is characterized by hypertension and proteinuria, typically occurring after 20 weeks of gestation. Despite its global impact on pregnant women, the precise pathogenic mechanisms of PE remain unclear. Dysregulated lipid metabolism and immune cell infiltration contribute to PE development. Our study aimed to identify lipid-metabolism-related genes (LMRG-PEs) and investigate their association with immune infiltration. We utilized the "Seurat" R package for data quality control, cell clustering, and marker gene identification. The "SingleR" package enabled the matching of marker genes to specific cell types. Pseudotemporal ordering analysis was conducted using the "Monocle" package. Weighted correlation network analysis (WGCNA), gene set variation analysis (GSVA), and gene set enrichment analysis (GSEA) approaches were employed to explore lipid-metabolism-related genes, while potential targeted drugs were predicted using the drug-gene interaction database (DGIdb). Hub gene expression was validated through RT-qPCR. By analyzing single-cell RNA sequencing data, we identified and classified 20 cell clusters into 5 distinct types. Differential gene expression analysis revealed 186 DEGs. WGCNA identified 9 critical modules and 265 genes significantly associated with PE diagnosis, emphasizing the importance of the core genes

Indexed as

immune infiltrationlipid metabolismnovel biomarkerspre-eclampsiasingle-cell analysis

Identifiers

PMID37626824
PMCPMC10452287
OpenAlexW4386052039

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.