zhao, y. | bioRxiv Science

bioRxiv2019

Changes in the expression of interleukin-10 in myocardial infarction and its relationship with macrophage activation and cell apoptosis

Currently, the role of IL-10 as an anti-inflammatory factor in the occurrence and development of heart disease is still unclear. This study aimed to observe the dynamic changes in the expression of IL-10 in serum and myocardial tissues, as well as to investigate the relationship of IL-10 expression with macrophage activation and cardiomyocyte apoptosis during the occurrence of myocardial infarction. Mice models with myocardial infarction were prepared by ligating anterior descending branch of the coronary artery. The animals were classified into sham operation group (the control group), as well as groups of myocardial infarction based on days 1, 7, 14 and 28. On days 7 and 14, the cells with positive IL-10 expression were largely distributed in the infarct areas, while cells with positive IL-10 expression were decreased on day 28. Serum IL-10 was significantly positively correlated with IL-10 protein expression in myocardial tissues. Moreover, Bcl-2 and Bax protein expression in myocardial tissues, as well as the ratio of Bcl-2/Bax proteins were gradually elevated with prolonged time of infarction. There were positive correlations between IL-10 and Arginase expressions, and between the expressions of Bcl-2 and Bax proteins. After the occurrence of myocardial infarction, the expression of IL-10 was firstly increased and then decreased in serum and myocardial tissues, and this might affect macrophage activation, phenotypic transformation and the occurrence of cardiomyocyte apoptosis.

cell biology↗

bioRxiv2019

INeo-Epp: T-cell HLA class I immunogenic or neoantigenic epitope prediction via random forest algorithm based on sequence related amino acid features

In silico T-cell epitope prediction plays an important role in immunization experimental design and vaccine preparation. Currently, most epitope prediction research focuses on peptide processing and presentation, e.g. proteasomal cleavage, transporter associated with antigen processing (TAP) and major histocompatibility complex (MHC) combination. To date, however, the mechanism for immunogenicity of epitopes remains unclear. It is generally agreed upon that T-cell immunogenicity may be influenced by the foreignness, accessibility, molecular weight, molecular structure, molecular conformation, chemical properties and physical properties of target peptides to different degrees. In this work, we tried to combine these factors. Firstly, we collected significant experimental HLA-I T-cell immunogenic peptide data, as well as the potential immunogenic amino acid properties. Several characteristics were extracted, including amino acid physicochemical property of epitope sequence, peptide entropy, eluted ligand likelihood percentile rank (EL rank(%)) score and frequency score for immunogenic peptide. Subsequently, a random forest classifier for T cell immunogenic HLA-I presenting antigen epitopes and neoantigens was constructed. The classification results for the antigen epitopes outperformed the previous research (the optimal AUC=0.81, external validation data set AUC=0.77). As mutational epitopes generated by the coding region contain only the alterations of one or two amino acids, we assume that these characteristics might also be applied to the classification of the endogenic mutational neoepitopes also called neoantigens. Based on mutation information and sequence related amino acid characteristics, a prediction model of neoantigen was established as well (the optimal AUC=0.78). Further, an easy-to-use web-based tool INeo-Epp was developed (available at http://www.biostatistics.online/INeo-Epp/neoantigen.php)for the prediction of human immunogenic antigen epitopes and neoantigen epitopes.

immunology↗