<p class="jove_content">This study used integrated transcriptomic analysis, machine learning (LASSO, SVM-RFE, and XGBoost), immune infiltration analysis, molecular docking, and RT-qPCR validation to identify glycosylation-related genes associated with idiopathic pulmonary fibrosis. Ten candidate diagnostic genes were identified, and a diagnostic model with strong performance in lung tissue datasets was developed and validated.</p>

integrated-machine-learning-approaches-to-explore-role-glycosylation

Integrated Machine Learning Approaches to Explore the Role of Glycosylation-Related Genes in Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive chronic lung disease with an unclear etiology, and the contribution of glycosylation-related genes ...

<p class="jove_content">Identifying microglia (MG) and peripheral infiltrating macrophages (M&#248;) in injured spinal cords is difficult. In this protocol, flow cytometry (FCM) was used to identify M1-like MG, M2-like MG, M1-like M&#248;, and M2-like M&#248;, respectively. This technology can also be applied to other central nervous system diseases to understand the role of MG and M&#248;.</p>

identifying-microglia-peripheral-infiltrating-macrophages-injured

Identifying Microglia and Peripheral Infiltrating Macrophages in the Injured Spinal Cords Using Flow Cytometry

In a healthy spinal cord, peripheral infiltrating macrophages are almost undetectable, and microglia (MG) participate in maintaining the stability of the ...

Institution - the First Affiliated Hospital of Bengbu Medical University

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