Damage-associated molecular patterns (DAMPs) are molecules that can be actively or passively released by injured tissues and that activate the immune system. Here we show that nicotinate phosphoribosyltransferase (NAPRT), detected by antibody-mediated assays and mass spectrometry, is an extracellular ligand for Toll-like receptor 4 (TLR4) and a critical mediator of inflammation, acting as a DAMP. Exposure of human and mouse macrophages to NAPRT activates the inflammasome and NF-κB for secretion of inflammatory cytokines. Furthermore, NAPRT enhances monocyte differentiation into macrophages by inducing macrophage colony-stimulating factor. These NAPRT-induced effects are independent of NAD-biosynthetic activity, but rely on NAPRT binding to TLR4. In line with our finding that NAPRT mediates endotoxin tolerance in vitro and in vivo, sera from patients with sepsis contain the highest levels of NAPRT, compared to patients with other chronic inflammatory conditions. Together, these data identify NAPRT as a endogenous ligand for TLR4 and a mediator of inflammation.

This study aims to estimate the economic costs of sickness absenteeism of health care workers in a large Italian teaching hospital during the seasonal flu periods. A retrospective observational study was performed. The excess data of hospital’s sickness absenteeism during three seasonal influenza periods (2010/2011; 2011/2012; 2012/2013) came from a previous study. The cost of sickness absenteeism was calculated for six job categories: medical doctor, technical executive (i.e., pharmacists); nurses and allied health professionals (i.e., radiographer), other executives (i.e., engineer), non-medical support staff, and administrative staff, and for four age ranges: 59 years. An average of 5401 employees working each year were under study. There were over 11,100 working days/year lost associated with an influenza period in Italy, the costs associated were approximately 1.7 million euros, and the average work loss was valued at € 327/person. The major shares of cost appeared related to nurses and allied health professionals (45% of total costs). The highest costs for working days lost were reported in the 40–49 age range, accounting for 37% of total costs. Due to the substantial economic burden of sickness absenteeism, there are clear benefits to be gained from the effective prevention of the influenza.

Today large scale genome sequencing technologies are uncovering an increasing amount of new genes and proteins, which remain uncharacterized. Experimental procedures for protein function prediction are low throughput by nature and thus can't be used to keep up with the rate at which new proteins are discovered. On the other hand, proteins are the prominent stakeholders in almost all biological processes, and therefore the need to precisely know their functions for a better understanding of the underlying biological mechanism is inevitable. The challenge of annotating uncharacterized proteins in functional genomics and biology in general motivates the use of computational techniques well orchestrated to accurately predict their functions.

What is the probability that the execution state of a given microprocessor running a given application is correct, in a certain working environment with a given soft-error rate? Trying to answer this question using fault injection can be very expensive and time consuming. This paper proposes the baseline for a new methodology, based on microprocessor error probability profiling, that aims at estimating fault injection results without the need of a typical fault injection setup. The proposed methodology is based on two main ideas: a one-time fault-injection analysis of the microprocessor architecture to characterize the probability of successful execution of each of its instructions in presence of a soft-error, and a static and very fast analysis of the control and data flow of the target software application to compute its probability of success. The presented work goes beyond the dependability evaluation problem; it also has the potential to become the backbone for new tools able to help engineers to choose the best hardware and software architecture to structurally maximize the probability of a correct execution of the target software.

Background: Biological research increasingly relies on network models to study complex phenomena. Signal Transduction Pathways are molecular circuits that model how cells receive, process, and respond to information from the environment providing snapshots of the overall cell dynamics. Most of the attempts to reconstruct signal transduction pathways are limited to single regulator networks including only genes/proteins. However, networks involving a single type of regulator and neglecting transcriptional and post-transcriptional regulations mediated by transcription factors and microRNAs, respectively, may not fully reveal the complex regulatory mechanisms of a cell. We observed a lack of computational instruments supporting explorative analysis on this type of three-component signal transduction pathways. Results: We have developed CyTRANSFINDER, a new Cytoscape plugin able to infer three-component signal transduction pathways based on user defined regulatory patterns and including miRNAs, TFs and genes. Since CyTRANSFINDER has been designed to support exploratory analysis, it does not rely on expression data. To show the potential of the plugin we have applied it in a study of two miRNAs that are particularly relevant in human melanoma progression, miR-146a and miR-214. Conclusions: CyTRANSFINDER supports the reconstruction of small signal transduction pathways among groups of genes. Results obtained from its use in a real case study have been analyzed and validated through both literature data and preliminary wet-lab experiments, showing the potential of this tool when performing exploratory analysis.