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Related Experiment Video

Updated: Jun 16, 2026

Isolation and Flow Cytometric Assessment of Neuroimmune Interactions in a Mini-Stroke Murine Model
08:22

Isolation and Flow Cytometric Assessment of Neuroimmune Interactions in a Mini-Stroke Murine Model

Published on: June 20, 2025

Combining Machine Learning, Single-Cell Sequencing Data, and Mendelian Randomization Studies to Explore the

Si Wang1, Yan Xu1, Meilei Wang2

  • 1Department of Cardiology, Xishan People's Hospital of Wuxi City, Wuxi, Jiangsu, China.

International Journal of Genomics
|June 15, 2026
PubMed
Summary

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This study identifies key inflammatory genes linked to ischemic stroke (IS) progression. Findings highlight inflammation

Area of Science:

  • Neuroscience
  • Immunology
  • Genetics

Background:

  • Ischemic stroke (IS) is a severe neurological disorder where inflammation plays a critical role.
  • Understanding the genetic basis of inflammation in IS is crucial for disease management.

Purpose of the Study:

  • To investigate gene expression profiles related to inflammation in IS patients.
  • To identify key inflammatory pathway-related genes (IPRGs) associated with IS.
  • To explore the association between these genes and IS progression.

Main Methods:

  • Analysis of public gene expression datasets comparing IS patients and healthy controls.
  • Differential expression analysis and machine learning to identify IPRGs.
  • Consensus clustering, single-cell sequencing, and Mendelian randomization studies (including tumor necrosis factor - TNF).
Keywords:
Mendelian randomization studycytokineinflammatory pathwaymachine learningscRNA-seqtumor necrosis factor

Related Experiment Videos

Last Updated: Jun 16, 2026

Isolation and Flow Cytometric Assessment of Neuroimmune Interactions in a Mini-Stroke Murine Model
08:22

Isolation and Flow Cytometric Assessment of Neuroimmune Interactions in a Mini-Stroke Murine Model

Published on: June 20, 2025

Main Results:

  • Four genes (HLA-DRA, IL1A, IL15, TNF) were upregulated in IS patients and correlated with inflammation.
  • A diagnostic nomogram model was developed and validated.
  • Single-cell sequencing revealed distinct inflammatory roles for macrophages and monocytes; TNF may negatively regulate IS risk.

Conclusions:

  • Identified key IPRGs and gene expression profiles in IS patients.
  • Provided insights into IS pathogenesis and the role of inflammation.
  • Highlighted potential therapeutic targets and predictive tools for IS.