Evidence map›Paper›PMID 37955337›Full record

ArticlePhysiological genomics2024

Exploring myometrial microenvironment changes at the single-cell level from nonpregnant to term pregnant states.

Kaiyuan Ji, Junmin Zhong, Long Cui, Xiaodi Wang, Li-Na Chen, Bolun Wen, Fan Yang, Wenfeng Deng, Xiuyu Pan, Lele Wang and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Physiological genomics, 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
3.5field-weighted citation impact, top 7% 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

2 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 1 institution in 1 country.

Kaiyuan JiGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Junmin ZhongGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Long CuiGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Xiaodi WangGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Li-Na ChenGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Bolun WenGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Fan YangGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Wenfeng DengGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Xiuyu PanGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Lele WangGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Junjie BaoGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.ORCID 0000-0003-3391-8478
YunShan ChenGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.
Huishu LiuGuangzhou Key Laboratory of Maternal-Fetal Medicine, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, People's Republic of China.ORCID 0000-0002-1197-5343
Guangzhou Medical University · CN

Funding

Foundation of guangzhou municipal science and technology bureau 202102010016high-tech major feauured technology program of guangzhou municipal health commission 2019GX07MOST | National Natural Science Foundation of China (NSFC) 81871181
6 · The paper itself

Abstract

The microenvironment and cell populations within the myometrium play crucial roles in maintaining uterine structural integrity and protecting the fetus during pregnancy. However, the specific changes occurring at the single-cell level in the human myometrium between nonpregnant (NP) and term pregnant (TP) states remain unexplored. In this study, we used single-cell RNA sequencing (scRNA-Seq) and spatial transcriptomics (ST) to construct a transcriptomic atlas of individual cells in the myometrium of NP and TP women. Integrated analysis of scRNA-Seq and ST data revealed spatially distinct transcriptional characteristics and examined cell-to-cell communication patterns based on ligand-receptor interactions. We identified and categorized 87,845 high-quality individual cells into 12 populations from scRNA-Seq data of 12 human myometrium tissues. Our findings demonstrated alterations in the proportions of five subpopulations of smooth muscle cells in TP. Moreover, an increase in monocytic cells, particularly M2 macrophages, was observed in TP myometrium samples, suggesting their involvement in the anti-inflammatory response. This study provides unprecedented single-cell resolution of the NP and TP myometrium, offering new insights into myometrial remodeling during pregnancy.

Indexed as

MyometriumUterusAnti-Inflammatory AgentsFemaleHumansMyocytes, Smooth MusclePregnancyAnti-Inflammatory Agentsmyometriumpregnancysingle-cell RNA sequencingspatial transcriptomics

Identifiers

PMID37955337
PMCPMC11281821
OpenAlexW4388631127

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LicenceCC BY
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Registered trials

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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.