Evidence map›Paper›PMID 41073490›Full record

ArticleScientific reports2025

Identification and validation of cell senescence genes in recurrent spontaneous abortion via multiple bioinformatics algorithms.

Yiyun Wei, Zhuolin Zhou, Changqiang Wei, Jinlian Cheng, Shanshan Lin, Zhiwei Zhu, Lihong Pang

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
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0citing papers in PubMed
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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

0 citing papers in PubMed.

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

7 authors.

Yiyun Wei *Department of Prenatal Diagnosis and Genetic Diseases Diagnosis, The First Affliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Zhuolin Zhou *Department of Obstetrics and Gynecology, The First Affliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Changqiang Wei *Department of Prenatal Diagnosis and Genetic Diseases Diagnosis, The First Affliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Jinlian ChengDepartment of Prenatal Diagnosis and Genetic Diseases Diagnosis, The First Affliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Shanshan LinDepartment of Obstetrics and Gynecology, The First Affliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Zhiwei ZhuUCL Cancer Institute, London, UK. 1653091728@qq.com.
Lihong PangDepartment of Prenatal Diagnosis and Genetic Diseases Diagnosis, The First Affliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. panglihong@stu.gxmu.edu.cn.

Funding

National Natural Science Foundation of China Nos. 81960464the construction of clinical intervention protocols Guangxi Key R & D program Guike AB22080045
6 · The paper itself

Abstract

Recurrent spontaneous abortion (RSA) represents a significant challenge in reproductive obstetrics, affecting approximately 5% of couples globally. Despite various treatments, the effectiveness of these interventions remains highly contentious. Emerging evidence suggests that cellular senescence plays a critical role in the pathogenesis of multiple diseases, potentially implicating its involvement in RSA as well. This study integrated two RNA sequencing datasets and employed Weighted Gene Co-Expression Network Analysis (WGCNA) alongside five machine learning algorithms (XGBoost, Boruta, LASSO, SVM-RFE, and Random Forest) to identify cellular senescence genes linked to RSA. Gene expression was validated at both the transcriptome and protein levels using qPCR, Western blot, and immunofluorescence techniques. An Artificial Neural Network (ANN) model was implemented to evaluate their diagnostic value. Additionally, functional enrichment and single-cell RNA sequencing analyses were conducted to investigate the biological functions of these genes. Three cellular senescence genes-TBX2, SRSF3, and TNRC6B-were identified and found to be upregulated in RSA patients. Functional enrichment analysis revealed these genes' involvement in the MAPK signaling pathway, ECM-receptor interaction, and cell-cell communication. Single-cell RNA sequencing demonstrated the distribution of these genes across various cell types, underscoring their significance in RSA. Furthermore, drug sensitivity analysis identified potential small molecule therapeutics for RSA. Cellular senescence may play a central role in the pathology of RSA, with TBX2, SRSF3, and TNRC6B emerging as potential diagnostic biomarkers. This research enhances our understanding of the molecular mechanisms underlying RSA and lays the groundwork for new diagnostic and therapeutic strategies. Nonetheless, further experimental studies are required to elucidate the specific roles and mechanisms of these genes in RSA, with the ultimate goal of achieving precise prevention and personalized treatment.

Indexed as

Abortion, HabitualAlgorithmsCellular SenescenceComputational BiologyFemaleGene Expression ProfilingGene Regulatory NetworksHumansMachine LearningNeural Networks, ComputerPregnancyTranscriptomeCell senescenceMachine learningRSASRSF3TBX2TNRC6B

Identifiers

PMID41073490
PMCPMC12514248

What Socratic holds

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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 Socratic graph.