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81.
    

Objective

The purpose of this study is to provide a further theoretical basis for the role of Suberoyllanilide hyroxamic acid (SAHA) affect on Dendritic cells (DCs).

Methods

We first downloaded the GSE74306 microarray data, which was about the effect of SAHA act on DCs, from the Gene Expression Omnibus database. Then we analyzed the differential expression genes (DEGs) between SAHA-treated DCs and SAHA-untreated DCs by limma package of R software; The Database for Annotation, Visualization and Integrated Discovery was used to analyze the Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for these DEGs. The protein protein interaction (PPI) network was constructed by using STRING database, Cytoscape 3.6.1 software was used to dispose the PPI network for visualization. Finally, we determine the Hub genes in the PPI network according by the degree centrality and betweenness centrality, which were calculated by the CentScaPe 2.2 plug-in of Cytoscape 3.6.1 software.

Result

There were 551 DEGs between SAHA-treated DC cells and SAHA-untreated DC cells, including 357 upregulated genes and 194 downregulated genes. These DEGs genes were enriched in 115 Go terms (Biological Process, 51; Cellular Component, 35 and Molecular Function, 29) and a total of 16 pathways. Glutathione metabolic process, Glutathione metabolism pathway, Rheumatoid arthritis pathway and Systemic lupus erythematosus pathway were most significant function clusters. In the PPI network, Rad51, Src, and Eno2 were Hub genes.

Conclusion

The biological function and KEGG pathway enriched by DEGs may reveal the molecular mechanism of SAHA acting on DC cells. Its Hub genes, Src, Rad51 and Eno2, were expected to be new targets for SAHA therapeutic effects. However, it still need to be confirmed by the next more rigorous molecular biological experiments research.  相似文献   
82.
    
The development of next generation sequencing techniques has facilitated the detection of mutations at an unprecedented rate. These efficient tools have been particularly beneficial for extremely heterogeneous disorders such as autosomal recessive non-syndromic hearing loss, the most common form of genetic deafness. GJB2 mutations are the most common cause of hereditary hearing loss. Amongst them the NM_004004.5: c.506G > A (p.Cys169Tyr) mutation has been associated with varying severity of hearing loss with unclear segregation patterns. In this study, we report a large consanguineous Emirati family with severe to profound hearing loss fully segregating the GJB2 missense mutation p.Cys169Tyr. Whole exome sequencing (WES), in silico, splicing and expression analyses ruled out the implication of any other variants and confirmed the implication of the p.Cys169Tyr mutation in this deafness family. We also show preliminary murine expression analysis that suggests a link between the TMEM59 gene and the hearing process. The present study improves our understanding of the molecular pathogenesis of hearing loss. It also emphasizes the significance of combining next generation sequencing approaches and segregation analyses especially in the diagnosis of disorders characterized by complex genetic heterogeneity.  相似文献   
83.
    
Staphylococcal protein A (SpA) domain B (the basis of affibody) has been widely used in affinity chromatography and found therapeutic applications against inflammatory diseases through targeting the Fc part of immunoglobulin G (IgG). We have performed extensive molecular dynamics simulation of 41 SpA mutants and compared their dynamics and conformations to wild type. The simulations revealed the molecular details of structural and dynamics changes that occurred due to introducing point mutations and helped to explain the SPR results. It was observed in some variants a point mutation caused extensive structural changes far from the mutation site, while an effect of some other mutations was limited to the site of the mutated residue. Also, the pattern of hydrogen bond networks and hydrophobic core arrangements were investigated. We figured out mutations that occurred at positions 128, 136, 150 and 153, affected two hydrophobic cores at the interface as well as mutations introduced at positions 129 and 154 interrupted two hydrogen bond networks of the interface, SPR data showed all of these mutations reduced binding affinity significantly. Overall, by scanning the SpA-Fc interface through the large numbers of introduced mutations, the new insights have been gained which would help to design high- affinity ligands of IgG.  相似文献   
84.
    
《IRBM》2020,41(3):161-171
BackgroundThe voice is a prominent tool allowing people to communicate and to change information in their daily activities. However, any slight alteration in the voice production system may affect the voice quality. Over the last years, researchers in biomedical engineering field worked to develop a robust automatic system that may help clinicians to perform a preventive diagnosis in order to detect the voice pathologies in an early stage.MethodIn this context, pathological voice detection and classification method based on EMD-DWT analysis and Higher Order Statistics (HOS) features, is proposed. Also DWT coefficients features are extracted and tested. To carry out our experiments a wide subset of voice signal from normal subjects and subjects which suffer from the five most frequent pathologies in the Saarbrücken Voice Database (SVD), is selected. In The first step, we applied the Empirical Mode Decomposition (EMD) to the voice signal. Afterwards, among the obtained candidates of Intrinsic Mode Functions (IMFs), we choose the robust one based on temporal energy criterion. In the second step, the selected IMF was decomposed via the Discrete Wavelet Transform (DWT). As a result, two features vector includes six HOSs parameters, and a features vector includes six DWT features were formed from both approximation and detail coefficients. In order to classify the obtained data a support vector machine (SVM) is employed. After having trained the proposed system using the SVD database, the system was evaluated using voice signals of volunteer's subjects from the Neurological department of RABTA Hospital of Tunis.ResultsThe proposed method gives promising results in pathological voices detection. The accuracies reached 99.26% using HOS features and 93.1% using DWT features for SVD database. In the classification, an accuracy of 100% was reached for “Funktionelle Dysphonia vs. Rekrrensparese” based on HOS features. Nevertheless, using DWT features the accuracy achieved was 90.32% for “Hyperfunktionelle Dysphonia vs. Rekurrensparse”. Furthermore, in the validation the accuracies reached were 94.82%, 91.37% for HOS and DWT features, respectively. In the classification the highest accuracies reached were for classifying “Parkinson versus Paralysis” 94.44% and 88.87% based on HOS and DWT features, respectively.ConclusionHOS features show promising results in the automatic voice pathology detection and classification compared to DWT features. Thus, it can reliably be used as noninvasive tool to assist clinical evaluation for pathological voices identification.  相似文献   
85.
    
In recent years proteomics became increasingly important to functional genomics. Although a large amount of data is generated by high throughput large‐scale techniques, a connection of these mostly heterogeneous data from different analytical platforms and of different experiments is limited. Data mining procedures and algorithms are often insufficient to extract meaningful results from large datasets and therefore limit the exploitation of the generated biological information. In our proteomic core facility, which almost exclusively focuses on 2‐DE/MS‐based proteomics, we developed a proteomic database custom tailored to our needs aiming at connecting MS protein identification information to 2‐DE derived protein expression profiles. The tools developed should not only enable an automatic evaluation of single experiments, but also link multiple 2‐DE experiments with MS‐data on different levels and thereby helping to create a comprehensive network of our proteomics data. Therefore the key feature of our “PROTEOMER” database is its high cross‐referencing capacity, enabling integration of a wide range of experimental data. To illustrate the workflow and utility of the system, two practical examples are provided to demonstrate that proper data cross‐referencing can transform information into biological knowledge.  相似文献   
86.
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88.
Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.  相似文献   
89.
Summary We report a collection of 53 prototypic sequences representing known families of repetitive elements from the human genome. The prototypic sequences are either consensus sequences or selected examples of repetitive sequences. The collection includes: prototypes for high and medium reiteration frequency interspersed repeats, long terminal repeats of endogenous retroviruses, alphoid repeats, telomere-associated repeats, and some miscellaneous repeats. The collection is annotated and available electronically.[/ap ]Offprint requests to: J. Jurka  相似文献   
90.
We compared the exon/intron organization of vertebrate genes belonging to different isochore classes, as predicted by their GC content at third codon position. Two main features have emerged from the analysis of sequences published in GenBank: (1) genes coding for long proteins (i.e., 500 aa) are almost two times more frequent in GC-poor than in GC-rich isochores; (2) intervening sequences (=sum of introns) are on average three times longer in GC-poor than in GC-rich isochores. These patterns are observed among human, mouse, rat, cow, and even chicken genes and are therefore likely to be common to all warm-blooded vertebrates. Analysis of Xenopus sequences suggests that the same patterns exist in cold-blooded vertebrates. It could be argued that such results do not reflect the reality because sequence databases are not representative of entire genomes. However, analysis of biases in GenBank revealed that the observed discrepancies between GC-rich and GC-poor isochores are not artifactual, and are probably largely underestimated. We investigated the distribution of microsatellites and interspersed repeats in introns of human and mouse genes from different isochores. This analysis confirmed previous studies showing that Ll repeats are almost absent from GC-rich isochores. Microsatellites and SINES (Alu, B1, B2) are found at roughly equal frequencies in introns from all isochore classes. Globally, the presence of repeated sequences does not account for the increased intron length in GC-poor isochores. The relationships between gene structure and global genome organization and evolution are discussed.  相似文献   
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