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Parkinson's disease (PD) is the second most prevalent neurodegenerative disease throughout the globe whose specific pathophysiology is unknown. Researchers believe that inflammation and oxidative stress contribute to PD development. Also, alterations in cytokines production appear to have a key role in the pathogenesis of PD. The aim of the current study was to evaluate gene expression levels of nine cytokines in the peripheral blood of PD patients compared to a healthy control group.Real-time PCR was used to analyze cytokines gene expression followed by advanced statistical analysis performed using Bayesian regression model in R (version 4.1.0) statistical software.TNF-α, IL-1β, IL-2, IL-4, IFN-γ, IL-17 and IL-6 transcript levels were upregulated in patients compared to healthy controls. However, CXCL8 expression was downregulated in patients compared to controls and IFN-β expression was not statistically different between the two groups. While we found no significant difference between the groups based on gender and age regarding TNF-α, IL-1β, CXCL8, IL-2, IL-4, IFN-γ and IFN-β gene expression, IL-6 and IL-17 transcript levels showed significant upregulations in older subjects and in females, respectively. In addition, we found that the interaction effects between gender and group on gene expression levels were not significant. In this way, the subgroup analysis within gender revealed that in each gender, expression levels of TNF-α, IL-2, IL-4, IL-6, IFN-γ and IL-17 were significantly higher in patients than controls. However, IFN-β expression level did not show any significant difference between groups and subgroups.The present study provides evidence on significant alterations in cytokine expression with different patterns and points to immune system dysregulation in PD.

Background. Parkinson’s disease (PD) is a neurological disorder that is marked by the deficit of neurons in the midbrain that changes motor and cognitive function. In the substantia nigra, the selective demise of dopamine-producing neurons was the main cause of this disease. The purpose of this research was to discover genes involved in PD development. Methods. In this study, the microarray dataset (GSE22491) provided by GEO was used for further analysis. The Limma package under R software was used to examine and assess gene expression and identify DEGs. The DAVID online tool was used to accomplish GO enrichment analysis and KEGG pathway for DEGs. Furthermore, the PPI network of these DEGs was depicted using the STRING database and analyzed through the Cytoscape to identify hub genes. Support vector machine (SVM) classifier was subsequently employed to predict the accuracy of genes. Result. PPI network consisted of 264 nodes as well as 502 edges was generated using the DEGs recognized from the Limma package under the R software. Moreover, three genes were identified as hubs: GNB5, GNG11, and ELANE. By using 3-gene combination, SVM found that prediction accuracy of 88% can be achieved. Conclusion. According to the findings of the study, the 3 hub genes GNB5, GNG11, and ELANE may be used as PD detection biomarkers. Moreover, the results obtained from SVM with high accuracy can be considered as PD biomarkers in further investigations.

Matrix metalloproteinase-9 (MMP-9) is a zinc and calcium-dependent proteolytic enzyme involved in extracellular matrix degradation. Overexpression of MMP-9 has been confirmed in several disorders, including cancers, Alzheimer′s disease, autoimmune diseases, cardiovascular diseases, and dental caries. Therefore, MMP-9 inhibition is recommended as a therapeutic strategy for combating various diseases. Cinnamic acid derivatives have shown therapeutic effects in different cancers, Alzheimer′s disease, cardiovascular diseases, and dental caries. A computational drug discovery approach was performed to evaluate the binding affinity of selected cinnamic acid derivatives to the MMP-9 active site. The stability of docked poses for top-ranked compounds was also examined. Twelve herbal cinnamic acid derivatives were tested for possible MMP-9 inhibition using the AutoDock 4.0 tool. The stability of the docked poses for the most potent MMP-9 inhibitors was assessed by molecular dynamics (MD) in 10 nanosecond simulations. Interactions between the best MMP-9 inhibitors in this study and residues incorporated in the MMP-9 active site were studied before and after MD simulations. Cynarin, chlorogenic acid, and rosmarinic acid revealed a considerable binding affinity to the MMP-9 catalytic domain (ΔGbinding < -10 kcal/mol). The inhibition constant value for cynarin and chlorogenic acid were calculated at the picomolar scale and assigned as the most potent MMP-9 inhibitor from the cinnamic acid derivatives. The root-mean-square deviations for cynarin and chlorogenic acid were below 2 Å in the 10 ns simulation. Cynarin, chlorogenic acid, and rosmarinic acid might be considered drug candidates for MMP-9 inhibition.

This paper presents a deep convolutional neural network (CNN) based method that automatically segments arc- like structures of coronal loops from the intensity images of Sun’s corona. The method explores multiple U-Net architecture variants which enable segmentation of coronal loop structures of active regions from NASA’s Solar Dynamic Observatory (SDO) imagery. The effectiveness of the method is evaluated through experiments on both synthetic and real images, and the results show that the method segments the coronal loop structures accurately.

The genus Hypericum consists of the most important medicinally active plants with a wide distribution throughout the world. In the present study, 18 populations belong to three Hypericum species (H. asperulum Jaub. & Spach (HA), H. scabrum (HS) and H. vermiculare Boiss. & Hausskn. (HV)) were collected at flowering stage from different habitats. The essential oils of aerial part of plants were extracted by water distillation method and analyzed using GC-FID and GC-MS. The essential oil content of populations varied from 0.02% (in HV3) to 0.43% (in HS4). The highest essential oil content among populations of H. asperulum, H. scabrum and H. vermiculare were belonged to the HA3 (0.4%), HS4 (0.43%) and HV5 (0.38%) populations, respectively. The number, type and percentage of essential oil constituents varied among different populations. Generally, α-pinene, caryophyllene oxide, E-caryophyllene and spathulenol were the dominant components in H. asperulum and H. vermiculare populations; however α-pinene, β-pinene, limonene and E-caryophyllene were identified as the major constituents of H. scabrum populations. The major components of the essential oil (except spathulenol) were not significantly affected by habitat conditions. Cluster analysis based on the essential oil content and essential oil components divided the populations into three distinct groups. Overall, based on the essential oil content, HA3, HS4 and HV5 were identified as the superior populations. Chemical diversity in the essential oil of studied Hypericum populations provides possibility of selection of specific population for different industries.