Potential Key Genes Associated with Stroke types and its subtypes: A Computational Approach

To investigate prospective key genes and pathways associated with the pathogenesis and prognosis of stroke types along with subtypes. Human genes using genome assembly build 38 patch release 13 with known gene symbols through NCBI gene database (https://www.ncbi.nlm.nih.gov/gene) were fetched. PubMed advanced queries were constructed using stroke-related keywords and associations were calculated using Normalized pointwise mutual information (nPMI) between each gene symbol and queries. Genes related with stroke risk within their types and subtypes were investigated in order to discover genetic markers to predict individuals who are at the risk of developing stroke with their subtypes. A total of 2,785 (9.4%) genes were found to be linked to the risk of stroke. Based on stroke types, 1,287 (46.2%) and 376 (13.5%) genes were found to be related with IS and HS respectively. Further stratification of IS based on TOAST classification, 86 (6.6%) genes were confined to Large artery atherosclerosis; 131 (10.1%) and 130 (10%) genes were related with the risk of small vessel disease and Cardioembolism subtypes of IS. Besides, a prognostic panel of 9 genes signature consisting of CYP4A11, ALOX5P, NOTCH, NINJ2, FGB, MTHFR, PDE4D, HDAC9, and ZHFX3 can be treated as a diagnostic marker to predict individuals who are at the risk of developing stroke with their subtypes.

Anti-inflammatory Mechanism of Rhein in Treating Asthma Based on Network Pharmacology

BackgroundNetwork pharmacology was used to study Rhein -target-pathway and to clarify its anti-inflammatory mechanism in the treatment of asthma.and provide a new idea for the treatment of asthmaMethodsThis method, which allows using network pharmacology to figure out the operational mechanism of Rhein-Target-Pathway, defines the effect of anti-inflammatory in treating asthma. The platform of Traditional Chinese Medicine Molecular Mechanism Bioinformatics, a web server for network, is used to get the corresponding target of Rhein and permit molecular docking. Cytoscape3.7.1, a kind of network software, is used to construct Rhein-predicted target network and analyse network topology. Search anti-inflammatory targets in the database of TTD and then construct the PPI network as well as create protein interaction networks that are combined with the Rhein-predicted target network. The anti-inflammatory targets of Rhein should be presented. The asthma genes of human being can be attained from the database of NCBI Gene Database and construct correspondence vivo response network model. Find Anti-inflammatory targets of Rhein against asthma, screen anti-inflammatory targets of Rhein related with Pathogenesis of asthma. Enrichr database is used to analyse signal pathway from anti-inflammatory targets of Rhein KEGG.ResultsAccording to the study, Rhein corresponds to 17 target proteins, four anti-inflammatory targets of Rhein related to asthma(MAPK14, EGFR, ERBB2, TNFRSF1A) are probably the most important targets where asthma is treated by Rhein.ConclusionsThese four anti-inflammatory targets of Rhein related to asthma are probably the key targets in the treatment of asthma by using Rhein. For the purpose of preventing the occurrence as well as development of asthma and delaying the progress of the disease, one or some of the four anti-inflammatory targets of Rhein related to asthma can be controlled.

Genotyping of the EIF1AY Gene in Iranian Patients with Non-Obstructive Azoospermia

Background: EIF1AY is one of the genes essential for normal spermatogenesis and is located in azoospermic factors region. Objective: The present study was designed to investigate the EIF1AY gene nucleotide variations, and correlate it with spermatogenic maturation arrest and azoospermia in Iranian population. Methods: A total number of 30 Iranian idiopathic non-obstructive azoospermic patients were selected as case group and 30 fertile men served as a control group who had at least 1 child. Nucleotide variation was analyzed in exon 3 and exon 5 in EIF1AY gene of both groups. DNA extraction from peripheral blood samples of selected individuals was done followed by amplification by PCR and sequencing with Sangar method. Results: Totally 3 single nucleotide variations were identified: one in the intronic region of exon 3, next one in non-coding transcript exon variant (rs13447352) and the third one in the exonic region of exon 5, all were registered in NCBI-Gene database. Conclusion: There was no statistically significant difference in the incidence of nucleotide variation between 2 study populations (p > 0.05). Further studies are required to specify the effects of Y: T20588295G variation on modification of protein structure, as well as the expression pattern of the gene and its association with azoospermia.