Markers for identifying or assisting in identifying vascular cells and/or vascular cell aging degrees and applications of markers
A vascular cell and auxiliary identification technology, applied in the field of biomedicine, can solve problems such as unoptimistic treatment of cardiovascular diseases and side effects
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Embodiment 1
[0089] Example 1. Acquisition of cynomolgus monkey vascular single-cell sequencing library
[0090] According to the average life span of cynomolgus monkeys and its corresponding relationship with human age, select 4 female cynomolgus monkeys aged 4-5 and 4 male cynomolgus monkeys aged 4-5 to form a young group, and 4 monkeys are 18-20 years old The female cynomolgus monkeys and 4 male cynomolgus monkeys aged 18-20 formed the old group. All cynomolgus monkeys undergo a physical examination, including the measurement of basic parameters (such as Body Mass Index (BMI)), the detection of biochemical indicators (such as blood routine, urine routine), brain MRI and ultrasound of important internal organs such as the heart Tested to confirm that all cynomolgus monkeys in the young group and the old group were free from major diseases.
[0091] Schematic diagram of the construction and analysis of cynomolgus monkey single-cell sequencing library, see figure 1 , the specific steps a...
Embodiment 2
[0111] Example 2. Acquisition and detection of vascular cell molecular markers
[0112] 1. Bioinformatics analysis to obtain vascular cell molecular markers
[0113] Taking the cynomolgus monkey genome Macaca_fascicularis_5.0 (Ensemble) as a reference, count the unique alignment read length and split it into different cell data, such as figure 2 Cells shown are aortic endothelial cells, coronary endothelial cells, aortic smooth muscle cells, coronary smooth muscle cells, adventitial fibroblasts, immune cells, and epicardial cells. A single molecule is marked with a unique molecular number, the amplification bias is corrected, and the single-cell expression map of cynomolgus monkey blood vessels is obtained. Search for highly variable genes through the Seurat software package, perform nonlinear dimensionality reduction (t-SNE) on these genes in the measured cells based on the gene group, perform clustering through the Find Clusters function of the Seurat software package and ...
Embodiment 3
[0125] Example 3, Acquisition and Detection of Molecular Markers of Senescent Vascular Cells
[0126] 1. Bioinformatics analysis to obtain molecular markers of aging vascular cells
[0127] Based on the cynomolgus monkey vascular cell sequencing library of the young group and the old group in Example 1, the aging vascular cell molecular markers (|log 2 (fold change)|≥0.5, P<0.05, FDR<0.05).
[0128] The expression of FOXO3 in different types of vascular cells in the young group and the old group was as follows: Figure 5 Shown: the expression levels of FOXO3 in the aortic endothelial cells of the young group and the old group were 2.02±1.74 and 1.21±1.44 (mean±standard deviation); The expression levels were 2.09±1.77 and 1.23±1.64 (mean±standard deviation); the expression levels of coronary artery endothelial cells 2 in the young group and the old group were 1.97±1.71 and 1.25±1.53 (mean±standard deviation ); the expression levels of aortic smooth muscle cells in the young ...
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