Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1038/s41540-017-0005-4 http://scihub22266oqcxt.onion/10.1038/s41540-017-0005-4 C5445610!5445610!28649431     free     free     free Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       NPJ+Syst+Biol+Appl 2017 ; 3 (ä): ä Nephropedia Template TP {{tp|p=28649431|t=2017. Meta-analysis of host response networks identifies a common core in tuberculosis |pdf=|usr=}}{{28649431}} gab.com Text Meta-analysis of host response networks identifies a common core in tuberculosis JO: NPJ Syst Biol Appl http://www.kidney.de/pget.php?&tw=1&pmid=28649431 #FOAvip Tuberculosis remains a major global health challenge worldwide, causing more than a million deaths annually. To determine newer methods for detecting and combating the disease, it is necessary to characterise global host responses to infection. Several high throughput omics studies have provided a rich resource including a list of several genes differentially regulated in tuberculosis. An integrated analysis of these studies is necessary to identify a unified response to the infection. Such data integration is met with several challenges owing to platform dependency, patient heterogeneity, and variability in the extent of infection, resulting in little overlap among different datasets. Network-based approaches offer newer alternatives to integrate and compare diverse data. In this study, we describe a meta-analysis of host?s whole blood transcriptomic profiles that were integrated into a genome-scale protein?protein interaction network to generate response networks in active tuberculosis, and monitor their behaviour over treatment. We report the emergence of a highly active common core in disease, showing partial reversals upon treatment. The core comprises 380 genes in which STAT1, phospholipid scramblase 1 (PLSCR1), C1QB, OAS1, GBP2 and PSMB9 are prominent hubs. This network captures the interplay between several biological processes including pro-inflammatory responses, apoptosis, complement signalling, cytoskeletal rearrangement, and enhanced cytokine and chemokine signalling. The common core is specific to tuberculosis, and was validated on an independent dataset from an Indian cohort. A network-based approach thus enables the identification of common regulators that characterise the molecular response to infection, providing a platform-independent foundation to leverage maximum insights from available clinical data. Twit Text FOAVip Meta-analysis of host response networks identifies a common core in tuberculosis ????NPJ Syst Biol Appl http://www.kidney.de/pget.php?&tw=1&pmid=28649431 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28649431 #FOAvip English Wikipedia <ref>{{Cite pmid|28649431}}</ref> Meta-analysis of host response networks identifies a common core in tuberculosis #MMPMID28649431 Sambarey A; Devaprasad A; Baloni P; Mishra M; Mohan A; Tyagi P; Singh A; Akshata J; Sultana R; Buggi S; Chandra N NPJ Syst Biol Appl 2017[]; 3 (ä): ä PMID28649431show ga Tuberculosis remains a major global health challenge worldwide, causing more than a million deaths annually. To determine newer methods for detecting and combating the disease, it is necessary to characterise global host responses to infection. Several high throughput omics studies have provided a rich resource including a list of several genes differentially regulated in tuberculosis. An integrated analysis of these studies is necessary to identify a unified response to the infection. Such data integration is met with several challenges owing to platform dependency, patient heterogeneity, and variability in the extent of infection, resulting in little overlap among different datasets. Network-based approaches offer newer alternatives to integrate and compare diverse data. In this study, we describe a meta-analysis of host?s whole blood transcriptomic profiles that were integrated into a genome-scale protein?protein interaction network to generate response networks in active tuberculosis, and monitor their behaviour over treatment. We report the emergence of a highly active common core in disease, showing partial reversals upon treatment. The core comprises 380 genes in which STAT1, phospholipid scramblase 1 (PLSCR1), C1QB, OAS1, GBP2 and PSMB9 are prominent hubs. This network captures the interplay between several biological processes including pro-inflammatory responses, apoptosis, complement signalling, cytoskeletal rearrangement, and enhanced cytokine and chemokine signalling. The common core is specific to tuberculosis, and was validated on an independent dataset from an Indian cohort. A network-based approach thus enables the identification of common regulators that characterise the molecular response to infection, providing a platform-independent foundation to leverage maximum insights from available clinical data. äMeta-analysis of host response networks identifies a common core in tu(epmc).pdf DeepDyve Pubget Overpricing