Exploration of the active components and pharmacological mechanism of Compound Longmaining for the treatment of myocardial infarction.

Background: Myocardial Infarction (MI) is a cardiovascular disease with a high morbidity and mortality rate. While MI is currently treated with pharmaceuticals, there is a need for new treatment options: compound Chinese medicines may have unique advantages for the treatment of MI. Methods: A combination of network pharmacology and experimental verification is used to identify the ingredients and mechanism of Compound Longmaining (CLMN) for treating MI. Network pharmacology combined with the gene expression omnibus (GEO) chip method is used to analyze the primary pathway of CLMN for treating MI, and then molecular docking is used to verify the affinity of key target proteins in the primary pathway that bind to active molecules. The major active compounds of CLMN are screened using the docking score results. The CIBERSORT algorithm is used to evaluate immune cell infiltration in MI, and high performance liquid chromatography (HPLC) is used to control the quality of the components. Finally, a mouse model is established to verify the molecular mechanism of CLMN for treating MI using hematoxlyn eosin (HE) staining and immunohistochemistry. Results: By utilizing network pharmacology combined with molecular docking, the mechanism of action of CLMN for the treatment of MI was found to possibly be related to the ingredients of puerarin, daidzein, ferulic acid, chrysin, and galangin. These molecules regulate the NF-Kappa B signaling pathway and the expression of RELA, IKBKB, NKBIA, and other targets. The CIBERSORT algorithm and ggplot2 package analysis were used to distinguish the immune cells, such as neutrophils, macrophages, and T cells, that play a key role in the development of MI. HPLC controlled the quality of the screened medicinal ingredients. An immunohistochemical analysis showed that the TNF-α and TRAF-2 expression levels in MI of the CLMN-treated mice were decreased, while IkBα was increased. HE staining showed CLMN reduced inflammation in mouse cardiomyocytes and decreased fibrosis. Conclusions: This study showed that CLMN treatment of MI is a process that involves multi-components, multi-targets and multi-pathways, and the established multi-index component content measurement of the CLMN decoction can be used for quality control of CLMN.

MiR-34a-5p and miR-452-5p: The Novel Regulators of Pancreatic Endocrine Dysfunction in Diabetic Zucker Rats?

Objective: The pancreatic endocrinal system dominates the regulation of blood glucose levels in vivo, and the dysfunction of pancreatic endocrine ß-cells is a major cause of the occurrence and development of Type 2 diabetes (T2D). Although microRNA (miRNA) have been found to be key regulators of pancreatic ß-cells proliferation, differentiation and apoptosis, the underlying mechanism remains enigmatic. The aim of this study was to identify several novel miRNAs which might be involved in the etiopathogenesis of diabetic ß-cells dysfunction. Methods: The miRNA expression profiles in the pancreas of high-fat diet (HFD) fed Zucker diabetic fatty (ZDF) rats and Zucker lean (ZL) rats feed with normal-fat diet (NFD) were detected by using miRNA microarray chip, and individually verified the most significant factors by quantitative real-time polymerase chain reaction (qRT-PCR) assay. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to predict the target genes related to each of the identified miRNAs and the functions of these target genes in different metabolic signaling pathways. Results: Compared with the ZL rats, a total of 24 differentially expressed miRNAs were detected in ZDF rats. Among which miR-34a-5p and miR-452-5p were the most significantly up-regulated and down-regulated respectively. These miRNAs have not been reported in rats' pancreas before. By GO and KEGG enrichment analyses, we found that miR-34a-5p could negatively regulate pancreatic ß-cell proliferation through the involvement of Wnt signaling pathway. In addition, it was also found to regulate insulin secretion through the insulin signaling pathway to modulate blood glucose levels. At the same time, miR-452-5p was found to positively regulate the activity of the key rate-limiting enzyme branched-chain α-keto acid dehydrogenase-ß (BCKDHB) in the catabolism of branched chain amino acids (BCAA), leading to mitochondrial dysfunction in pancreatic ß-cells. Conclusions: miR-34a-5p and miR-452-5p were identified as the novel regulators of pancreatic endocrine dysfunction. These miRNAs might have the potential to be utilized as the new predictive biomarkers for the diagnosis of the occurrence and development of T2D, as well as the therapeutic targets for T2D treatment.

VR/AR Technology in Human Anatomy Teaching and Operation Training.

AR/VR technology can fuse the clinical imaging data and information to build an anatomical environment combining virtual and real, which is helpful to improve the interest of teaching and the learning initiative of medical students, and then improve the effect of clinical teaching. This paper studies the application and learning effect of the VR/AR system in human anatomy surgery teaching. This paper first shows the learning environment and platform of the VR/AR system, then explains the interface and operation of the system, and evaluates the teaching situation. This paper takes the VR/AR operation simulation system of an Irish company as an example and evaluates the learning effect of 41 students in our hospital. Research shows that the introduction of the feature reweighting module in the VR/AR surgery simulation system improves the accuracy of bone structure segmentation (IOU value increases from 79.62% to 83.56%). For real human ultrasound image data, the IOU value increases from 80.21% to 82.23% after the feature reweighting module is introduced. Therefore, the dense convolution module and feature reweighting module improve the learning ability of the network for bone structure features in ultrasound images from two aspects of feature connection and importance understanding and effectively improve the performance of bone structure segmentation.