Mori Fructus polysaccharides (MFP) are macromolecules extracted from Mori Fructus (MF), which has the biological activity of anti-liver damage. Our group found that MFP maybe down regulate the serum triglyceride level in mice with alcohol-induced liver damage, suggesting that MFP can regulate lipid metabolism, but its specific mechanism is still not clear. Fifty SPF-ICR male mice weighing 18–22 g were randomly divided into five groups, blank group, model group, bifendate group, MFPA1 group and MFPB1 group. The blood and liver tissues were taken from mice for nontargeted lipidomic analysis and histopathological examination after 7 day’s treatment. The histopathological changes indicated that the normal liver cells were intact and regular, with orderly arrangement and distinct cell boundaries; the liver of model mice showed inflammatory infiltration, ballooning degeneration in the cells and small lipid drops; the liver of mice in the bifendate, MFPA1 and MFPB1 groups showed similar symptoms to those of model mice, but the lesions were less severe and the ballooning degeneration were reduced. Multivariate analysis of all lipids in the serum of five groups of mice showed there were obvious differences in lipid metabolism between the model group and the blank group. At the same time, seven kinds of differential lipids were precisely identified after screening, including prostaglandins, long-chain fatty acids, glycerophospholipids, acyl carnitines. In summary, alcohol intake and MFP intervention have significant effects on fatty acid synthesis, degradation and glycerophospholipid metabolism.

Parkinson’s disease (PD) is one of the common neurodegenerative diseases of the elderly. However, modern healthcare lacks the apparatus to detect the early signs of the disease, with only selected experts being able to spot the onset. Therefore, the early detection of PD is particularly important. Convolutional neural networks, a deep learning technique that can automatically extract image features, have been widely used in the diagnosis of medical images. Due to the complexity of the organization in the brain, we proposed a multiscale hybrid attention network (MSHANet) for the automatic detection of healthy and PD patients. MSHANet consisted of designed multiscale convolutional blocks and introduced hybrid attention blocks, so it can capture complex features in brain images. Two datasets were created using the images in the publicly available Parkinson’s progression markers initiative (PPMI) dataset, where the SV_3Dataset consisted of axial slices located in the substantia nigra region, and the MV_3Dataset adds mid-sagittal slices and striatal slices based on SV_3Dataset. For these two datasets, we proposed two different classification strategies, namely, parallel network classification (PNC) and multislice fusion classification (MSFC), to improve the classification performance of PD. After cross-validation experiments, the best results for the model using the PNC strategy achieved are 90.59% of accuracy, 90.59% of precision, 90.61% of recall, 90.6% of F1 score, and 0.956 of area under the curve (AUC). By analyzing the above results, the striatal slice in MV_3Dataset provides higher accuracy than the other two slices. Both PNC and MSFC improved the classification effect of MSHANet on PD and healthy control (HC), and the effect of PNC was better. The PNC strategy is used to test the performance of MSHANet on the test set. The best result is that the accuracy rate is 94.11%, the accuracy rate is 94.18%, the recall rate is 94.16, the F1 value is 94.17%, and the AUC is 0.9585. Our proposed method can help clinicians in accurately diagnosing the PD.

To better understand the molecular mechanisms of intracranial aneurysm (IA) pathogenesis, we used gene coexpression networks to identify hub genes and functional pathways associated with IA onset. Two Gene Expression Omnibus (GEO) datasets encompassing intracranial aneurysm tissue samples and cerebral artery control samples were included. To discover functional pathways and potential biomarkers, weighted gene coexpression network analysis was employed. Next, single-gene gene set enrichment analysis was employed to investigate the putative biological roles of the chosen genes. We also used receiver operating characteristic analysis to confirm the diagnostic results. Finally, we used a rat model to confirm the hub genes in the module of interest. The module of interest, which was designated the green module and included 115 hub genes, was the key module that was most strongly and negatively associated with IA formation. According to gene set variation analysis results, 15 immune-related pathways were significantly activated in the IA group, whereas 7 metabolic pathways were suppressed. In two GEO datasets, SLC2A12 could distinguish IAs from control samples. Twenty-nine hub genes in the green module might be biomarkers for the occurrence of cerebral aneurysms. SLC2A12 expression was significantly downregulated in both human and rat IA tissue. In the present study, we identified 115 hub genes related to the pathogenesis of IA onset and deduced their potential roles in various molecular pathways; this new information may contribute to the diagnosis and treatment of IAs. By external validation, the SLC2A12 gene may play an important role. The molecular function of SLC2A12 in the process of IA occurrence can be further studied in a rat model.

Objective: We intended to identify the potential key biomarker and pathways that correlated with infiltrating immune cells during the pathogenesis of intracranial aneurysms (IA), to develop a diagnostic model, and to predict therapeutic drugs.Methods: Three datasets containing intracranial aneurysm tissue samples and normal artery control samples from Gene Expression Omnibus (GEO) were included. Gene-set variation analysis(GSVA) and gene set enrichment analysis (GSEA) were conducted to find the significant differentially expressed pathways in IA formation. The least absolute shrinkage and selection operator (LASSO) regression and the multivariate logistic regression analysis were performed to identify the characteristic genes in the IL6/JAK/STAT signaling pathway (ISP) and the estrogen response pathway (ERP). A diagnostic model was constructed. xCell was used to identify immune cell types in IA pathogenesis. We used the weighted gene co-expression network analysis (WGCNA) algorithm to explore the correlations between the key modules and the four traits. Potential therapeutic drugs were investigated in Enrichr and Drugbank database.Results: The ISP is significant positively correlated with IA onset. The biological function of the ISP is positively correlated with that of the ERP, and is significantly associated with immune cells activities. CSF2RB, FAS, IL6, PTPN1, STAT2, TGFB1 of the ISP gene set and ALDH3A2, COX6C, IGSF1, KRT18, MICB, NPY1R of the ERP gene set were proved to be the characteristic genes. The STAT2 gene can be the potential biomarker of IA onset. The immune score of IA samples was significantly higher than the controls. The STAT2 gene expression is associated with infiltration of immune cells. The WGCNA results were consistent with our finds. Acetaminophen can be a potential therapeutic drug for IA targeting STAT2.Conclusions: We identified that the ISP was one of the most significant positively correlated pathways in IA onset, and it was activated in this process concordant with the ERP and immune responses. Except for beneficial effects, complex and multiple roles of estrogen may be involved in IA formation. STAT2 could be a potential biomarker and a promising therapeutic target of IA pathogenesis.

The hedgehog signaling pathway plays a vital role in human and animal patterning and cell proliferation during the developmental process. The hedgehog gene family of vertebrate species includes three genes,Shh,Dhh, andIhh, which possess different functions and expression patterns. Despite the importance of hedgehog genes, genomic evidence of this gene family in reptiles is lacking. In this study, the available genomes of a number of representative reptile species were explored by utilizing adaptive evolutionary analysis methods to characterize the evolutionary patterns of the hedgehog gene family. Altogether, 33 sonic hedgehog (Shh), 25 desert hedgehog (Dhh), and 20 Indian hedgehog (Ihh) genes were obtained from reptiles, and six avian and five mammalian sequences were added to the analysis. The phylogenetic maximum likelihood (ML) tree of theShh,Dhh, andIhhgenes revealed a similar topology, which is approximately consistent with the traditional taxonomic group. No shared positive selection site was identified by the PAML site model or the three methods in the Data Monkey Server. Branch model and Clade model C analyses revealed that theDhhandIhhgenes experienced different evolutionary forces in reptiles and other vertebrates, while theShhgene was not significantly different in terms of selection pressure. The different evolutionary rates of theDhhandIhhgenes suggest that these genes may be potential contributors to the discrepant sperm and body development of different clades. The different adaptive evolutionary history of theShh,Dhh, andIhhgenes among reptiles may be due to their different functions in regulating cellular events of development from the embryonic stages to adulthood. Overall, this study has provided meaningful information regarding the evolution of the hedgehog gene family in reptiles and a theoretical foundation for further analyses on the functional and molecular mechanisms that have shaped the reptilian hedgehog genes.

This study is intended to find possible pathogenesis-related genetic overlap and common molecular mechanisms of intracranial aneurysm, abdominal aortic aneurysm and aortic dissection. Three mRNA microarray datasets,GSE75436 of intracranial aneurysms, GSE7084 of abdominal aortic aneurysm and GSE52093 of aortic dissection were downloaded from Gene Expression Omnibus and detected in silico . DEGs of these three datasets screened through GEO2R, respectively . The overlapping genes were found by Venny mapping. Subsequently, Gene Ontology, Kyoto Encyclopedia of Genes and Genomespathway enrichment analysiswere performed using the DAVID database and protein-protein interaction network analyses were conducted by STRING and Cytoscape webpage tool to illustrate the molecular mechanisms in their pathogenesis and progression.This study identified 178 DEGs, including SMTN, MYH11, TAGLN, ACTG2, CNN1, MYLK, LMOD1, MYL9,VCL and ACTC1 in the the most significant module. Except for those confirmed biological processes, mesenchyme migration and platelet aggregation are common biological processes shared by genes in the most significant module and the hub genes. Focal adhesionssignaling pathway is highlighted in this analysis. The present study identified possible pathogenesis-related genetic overlap and common molecular mechanisms of intracranial aneurysm, abdominal aortic aneurysm and aortic dissection, which may contribute to their diagnosis, treatment and prognostic prediction with a systematic view.