A peptidoglycan hydrolase motif within the mycobacteriophage TM4 tape measure protein promotes efficient infection of stationary phase cells

The predominant morphotype of mycobacteriophage virions has a DNA-containing capsid attached to a long flexible non-contractile tail, features characteristic of the Siphoviridae. Within these phage genomes the tape measure protein (tmp) gene can be readily identified due to the well-established relationship between the length of the gene and the length of the phage tail - because these phages typically have long tails, the tmp gene is usually the largest gene in the genome. Many of these mycobacteriophage Tmp's contain small motifs with sequence similarity to host proteins. One of these motifs (motif 1) corresponds to the Rpf proteins that have lysozyme activity and function to stimulate growth of dormant bacteria, while the others (motifs 2 and 3) are related to proteins of unknown function, although some of the related proteins of the host are predicted to be involved in cell wall catabolism. We show here that motif 3-containing proteins have peptidoglycan-hydrolysing activity and that while this activity is not required for phage viability, it facilitates efficient infection and DNA injection into stationary phase cells. Tmp's of mycobacteriophages may thus have acquired these motifs in order to avoid a selective disadvantage that results from changes in peptidoglycan in non-growing cells. © 2006 The Authors

Complete Genome Sequences of Lactobacillus Phages J-1 and PL-1

Lactobacillus phages J-1 and PL-1 were isolated during the 1960s from abnormal fermentations of Yakult. The genomes are almost identical, but PL-1 has a deletion in the genetic switch region and also differs in a gene coding for a putative tail protein.Fil: Dieterle, María Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina. University of Pittsburgh; Estados UnidosFil: Jacobs Sera, Deborah. University of Pittsburgh; Estados UnidosFil: Russel, Daniel. University of Pittsburgh; Estados UnidosFil: Hatfull, Graham. University of Pittsburgh; Estados UnidosFil: Piuri, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentin

Analysis and application of digital spectral warping in analog and mixed-signal testing

Spectral warping is a digital signal processing transform which shifts the frequencies contained within a signal along the frequency axis. The Fourier transform coefficients of a warped signal correspond to frequency-domain 'samples' of the original signal which are unevenly spaced along the frequency axis. This property allows the technique to be efficiently used for DSP-based analog and mixed-signal testing. The analysis and application of spectral warping for test signal generation, response analysis, filter design, frequency response evaluation, etc. are discussed in this paper along with examples of the software and hardware implementation

A Web-Based Distributed Virtual Educational Laboratory

Evolution and cost of measurement equipment, continuous training, and distance learning make it difficult to provide a complete set of updated workbenches to every student. For a preliminary familiarization and experimentation with instrumentation and measurement procedures, the use of virtual equipment is often considered more than sufficient from the didactic point of view, while the hands-on approach with real instrumentation and measurement systems still remains necessary to complete and refine the student's practical expertise. Creation and distribution of workbenches in networked computer laboratories therefore becomes attractive and convenient. This paper describes specification and design of a geographically distributed system based on commercially standard components

Fluoromycobacteriophages for rapid, specific, and sensitive antibiotic susceptibility testing of Mycobacterium tuberculosis

Rapid antibiotic susceptibility testing of Mycobacterium tuberculosis is of paramount importance as multiple- and extensively- drug resistant strains of M. tuberculosis emerge and spread. We describe here a virus-based assay in which fluoromycobacteriophages are used to deliver a GFP or ZsYellow fluorescent marker gene to M. tuberculosis, which can then be monitored by fluorescent detection approaches including fluorescent microscopy and flow cytometry. Pre-clinical evaluations show that addition of either Rifampicin or Streptomycin at the time of phage addition obliterates fluorescence in susceptible cells but not in isogenic resistant bacteria enabling drug sensitivity determination in less than 24 hours. Detection requires no substrate addition, fewer than 100 cells can be identified, and resistant bacteria can be detected within mixed populations. Fluorescence withstands fixation by paraformaldehyde providing enhanced biosafety for testing MDR-TB and XDR-TB infections. © 2009 Piuri et al

Designing Information Technology Architectures: A Cost-Oriented Methodology

This paper proposes a design methodology of information technology architectures tying organizational requirements to technical choices and costs. The primary goal is to provide a structured support for the selection of the minimum-cost architecture satisfying given organizational requirements. Previous empirical studies have attempted absolute cost comparisons of different architectural solutions, primarily relying on the expertise of practitioners and a priori beliefs, but have rarely taken into account the impact of organizational requirements on costs. Requirements are modelled as information processes, composed of tasks exchanging information and characterized by varying levels of computational complexity. Different architectural distributions of presentation, computation and data management applications are compared. The cost implications of organizational requirements for processing intensity, communication intensity and networking are analysed. The results show a relationship between structural features of information processes and architectural costs and indicate how architectural design should be based on organizational as well as technology considerations

Anomaly-based intrusion detection system for DDoS attack with Deep Learning techniques

The increasing number of connected devices is fostering a rising frequency of cyber attacks, with Distributed Denial of Service (DDoS) attacks among the most common. To counteract DDoS, companies and large organizations are increasingly deploying anomaly-based Intrusion Detection Systems (IDS), which detect attack patterns by analyzing differences in malicious network traffic against a baseline of legitimate traffic. To differentiate malicious and normal traffic, methods based on artificial intelligence and, in particular, Deep Learning (DL) are being increasingly considered, due to their ability to automatically learn feature representations for the different traffic types, without need of explicit programming or handcrafted feature extraction. In this paper, we propose a novel methodology for simulating an anomaly-based IDS based on adaptive DL by designing multiple DL models working with both binary and multi-label classification on multiple datasets with different degrees of comp lexity. To make the DL models adaptable to different conditions, we consider adaptive architectures obtained by automatically tuning the number of neurons for each situation. Results on publicly-available datasets confirm the validity of our proposed methodology, with DL models adapting to the different conditions by increasing the number of neurons on more complex datasets and achieving the highest accuracy in the binary classification configuration

Tasks Scheduling with Load Balancing in Fog Computing: a Bi-level Multi-Objective Optimization Approach

Fog computing is characterized by its proximity to edge devices, allowing it to handle data near the source. This capability alleviates the computational burden on data centers and minimizes latency. Ensuring high throughput and reliability of services in Fog environments depends on the critical roles of load balancing of resources and task scheduling. A significant challenge in task scheduling is allocating tasks to optimal nodes. In this paper, we tackle the challenge posed by the dependency between optimally scheduled tasks and the optimal nodes for task scheduling and propose a novel bi-level multi-objective task scheduling approach. At the upper level, which pertains to task scheduling optimization, the objective functions include the minimization of makespan, cost, and energy. At the lower level, corresponding to load balancing optimization, the objective functions include the minimization of response time and maximization of resource utilization. Our approach is based on an Improved Multi-Objective Ant Colony algorithm (IMOACO). Simulation experiments using iFogSim confirm the performance of our approach and its advantage over existing algorithms, including heuristic and meta-heuristic approaches