Proteomics boosts translational and clinical microbiology

The application of proteomics to translational and clinical microbiology is one of the most advanced frontiers in the management and control of infectious diseases and in the understanding of complex microbial systems within human fluids and districts. This new approach aims at providing, by dedicated bioinformatic pipelines, a thorough description of pathogen proteomes and their interactions within the context of human host ecosystems, revolutionizing the vision of infectious diseases in biomedicine and approaching new viewpoints in both diagnostic and clinical management of the patient.Indeed, in the last few years, many laboratories have matured a series of advanced proteomic applications, aiming at providing individual proteome charts of pathogens, with respect to their morph and/or cell life stages, antimicrobial or antimycotic resistance profiling, epidemiological dispersion. Herein, we aim at reviewing the current state-of-the-art on proteomic protocols designed and set-up for translational and diagnostic microbiological purposes, from axenic pathogens' characterization to microbiota ecosystems' full description. The final goal is to describe applications of the most common MALDI-TOF MS platforms to advanced diagnostic issues related to emerging infections, increasing of fastidious bacteria, and generation of patient-tailored phylotypes. This article is part of a Special Issue entitled: Trends in Microbial Proteomics. © 2013 The Authors

Network analysis of gut microbiome and metabolome to discover microbiota-linked biomarkers in patients affected by non-small cell lung cancer

Several studies in recent times have linked gut microbiome (GM) diversity to the pathogenesis of cancer and its role in disease progression through immune response, inflammation and metabolism modulation. This study focused on the use of network analysis and weighted gene co-expression network analysis (WGCNA) to identify the biological interaction between the gut ecosystem and its metabolites that could impact the immunotherapy response in non-small cell lung cancer (NSCLC) patients undergoing second-line treatment with anti-PD1. Metabolomic data were merged with operational taxonomic units (OTUs) from 16S RNA-targeted metagenomics and classified by chemometric models. The traits considered for the analyses were: (i) condition: disease or control (CTRLs), and (ii) treatment: responder (R) or non-responder (NR). Network analysis indicated that indole and its derivatives, aldehydes and alcohols could play a signaling role in GM functionality. WGCNA generated, instead, strong correlations between short-chain fatty acids (SCFAs) and a healthy GM. Furthermore, commensal bacteria such as Akkermansia muciniphila, Rikenellaceae, Bacteroides, Peptostreptococcaceae, Mogibacteriaceae and Clostridiaceae were found to be more abundant in CTRLs than in NSCLC patients. Our preliminary study demonstrates that the discovery of microbiota-linked biomarkers could provide an indication on the road towards personalized management of NSCLC patients

Network analysis of gut microbiome and metabolome to discover microbiota-linked biomarkers in patients affected by non-small cell lung cancer

Several studies in recent times have linked gut microbiome (GM) diversity to the pathogenesis of cancer and its role in disease progression through immune response, inflammation and metabolism modulation. This study focused on the use of network analysis and weighted gene co-expression network analysis (WGCNA) to identify the biological interaction between the gut ecosystem and its metabolites that could impact the immunotherapy response in non-small cell lung cancer (NSCLC) patients undergoing second-line treatment with anti-PD1. Metabolomic data were merged with operational taxonomic units (OTUs) from 16S RNA-targeted metagenomics and classified by chemometric models. The traits considered for the analyses were: (i) condition: disease or control (CTRLs), and (ii) treatment: responder (R) or non-responder (NR). Network analysis indicated that indole and its derivatives, aldehydes and alcohols could play a signaling role in GM functionality. WGCNA generated, instead, strong correlations between short-chain fatty acids (SCFAs) and a healthy GM. Furthermore, commensal bacteria such as Akkermansia muciniphila, Rikenellaceae, Bacteroides, Peptostreptococcaceae, Mogibacteriaceae and Clostridiaceae were found to be more abundant in CTRLs than in NSCLC patients. Our preliminary study demonstrates that the discovery of microbiota-linked biomarkers could provide an indication on the road towards personalized management of NSCLC patients

WA92: a fixed target experiment to trigger on and identify beauty particle decays

We describe the detectors and trigger system used in the CERN WA92 experiment. The experiment was designed to study the production and decay of beauty particles from 350 GeV/$c\,$ $\,\pi^-$ interactions in copper and tungsten targets. Charged particle tracking is performed using the Omega spectrometer. Silicon microstrip detectors are used to provide precise tracking information in the region of the production and the decay of heavy-flavoured particles and to trigger on the resulting high impact parameter tracks. The precision of vertex reconstruction corresponds to $\pm 3.7\%$ of the mean B-decay proper lifetime. Lepton and high transverse momentum hadron signals are also used in the trigger, which accepts 29\% of B-decays and rejects 98\% of non-beauty interactions

Alignment of the Pixel and SCT Modules for the 2004 ATLAS Combined Test Beam

A small set of final prototypes of the ATLAS Inner Detector silicon tracker (Pixel and SCT) were used to take data during the 2004 Combined Test Beam. Data were collected from runs with beams of different flavour (electrons, pions, muons and photons) with a momentum range of 2 to 180 GeV/c. Four independent methods were used to align the silicon modules. The corrections obtained were validated using the known momenta of the beam particles and were shown to yield consistent results among the different alignment approaches. From the residual distributions, it is concluded that the precision attained in the alignment of the silicon modules is of the order of 5 micrometers in their most precise coordinate.Comment: 22 pages, submitted to JINST, 129 author

ATLAS pixel detector electronics and sensors

The silicon pixel tracking system for the ATLAS experiment at the Large Hadron Collider is described and the performance requirements are summarized. Detailed descriptions of the pixel detector electronics and the silicon sensors are given. The design, fabrication, assembly and performance of the pixel detector modules are presented. Data obtained from test beams as well as studies using cosmic rays are also discussed

Continuous network models of gene expression in knock-out experiments: a preliminary study

analysis of avalanche distribution in the Glass continuous model of genetic network