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      Cycloastragenol Inhibits Experimental Abdominal Aortic Aneurysm Progression

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          Abstract

          The pathogenesis of abdominal aortic aneurysm involves vascular inflammation and elastin degradation. Astragalusradix contains cycloastragenol, which is known to be anti-inflammatory and to protect against elastin degradation. We hypothesized that cycloastragenol supplementation inhibits abdominal aortic aneurysm progression. Abdominal aortic aneurysm was induced in male rats by intraluminal elastase infusion in the infrarenal aorta and treated daily with cycloastragenol (125 mg/kg/day). Aortic expansion was followed weekly by ultrasound for 28 days. Changes in aneurysmal wall composition were analyzed by mRNA levels, histology, zymography and explorative proteomic analyses. At day 28, mean aneurysm diameter was 37% lower in the cycloastragenol group (p < 0.0001). In aneurysm cross sections, elastin content was insignificantly higher in the cycloastragenol group (10.5% ± 5.9% vs. 19.9% ± 16.8%, p = 0.20), with more preserved elastin lamellae structures (p = 0.0003) and without microcalcifications. Aneurysmal matrix metalloprotease-2 activity was reduced by the treatment (p = 0.022). Messenger RNA levels of inflammatory- and anti-oxidative markers did not differ between groups. Explorative proteomic analysis showed no difference in protein levels when adjusting for multiple testing. Among proteins displaying nominal regulation were fibulin-5 (p = 0.02), aquaporin-1 (p = 0.02) and prostacyclin synthase (p = 0.007). Cycloastragenol inhibits experimental abdominal aortic aneurysm progression. The suggested underlying mechanisms involve decreased matrix metalloprotease-2 activity and preservation of elastin and reduced calcification, thus, cycloastragenol could be considered for trial in abdominal aortic aneurysm patients.

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          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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            The PRIDE database and related tools and resources in 2019: improving support for quantification data

            Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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              Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

              Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.
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                Journal
                BIOMID
                Biomedicines
                Biomedicines
                MDPI AG
                2227-9059
                February 2022
                February 02 2022
                : 10
                : 2
                : 359
                Article
                10.3390/biomedicines10020359
                35203568
                be91fd5a-f439-4534-84f5-cf33eca5dddc
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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