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

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

A novel antimicrobial activity of a Paenibacillus polymyxa strain isolated from regional fermented sausages

A strain isolated from Argentinean regional fermented sausages was found to produce and secrete a compound that inhibited growth of Lactobacillus strains used as indicators. It was characterized as Paenibacillus polymyxa (P13). The antimicrobial activity, named polyxin, was obtained from culture supernatant fluid of late stationary phase and was inhibitory to actively growing cells. It was effective against a wide range of Gram-positive and Gram-negative bacterial species tested including food-borne pathogens. Bacteriocin-like properties such as proteinaceous nature (sensitive to proteases), insensitivity to organic solvents and chelators, stability to heat (up to 10 min at 90°C), and acidic pH but instability in alkaline conditions, were determined. A molecular mass of 10 kDa was estimated by molecular gel filtration.Fil:Piuri, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Ruzal, S.M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

The future of Cybersecurity in Italy: Strategic focus area

This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management

Towards explainable semantic segmentation for autonomous driving systems by multi-scale variational attention

Explainable autonomous driving systems (EADS) are emerging recently as a combinatory field of explainable artificial intelligence (XAI) and vehicular automation (VA). EADS explains events, ambient environments, and engine operations of an autonomous driving vehicular, and it also delivers explainable results in an orderly manner. Explainable semantic segmentation (ESS) plays an essential role in building EADS, where it offers visual attention that helps the drivers to be aware of the ambient objects irrespective if they are roads, pedestrians, animals, or other objects. In this paper, we propose the first ESS model for EADS based on the variation autoencoder (VAE), and it uses the multiscale first-order derivatives between the latent space and the encoder layers to capture the curvatures of the neurons’ responses. Our model is termed as Mgrad2VAE and is bench-marked on the SYNTHIA dataset, where it outperforms the recent deep models in terms of image segmentation metrics

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

Model-Agnostic Utility-Preserving Biometric Information Anonymization

The recent rapid advancements in both sensing and machine learning technologies have given rise to the universal collection and utilization of people’s biometrics, such as fingerprints, voices, retina/facial scans, or gait/motion/gestures data, enabling a wide range of applications including authentication, health monitoring, or much more sophisticated analytics. While providing better user experiences and deeper business insights, the use of biometrics has raised serious privacy concerns due to their intrinsic sensitive nature and the accompanying high risk of leaking sensitive information such as identity or medical conditions. In this paper, we propose a novel modality-agnostic data transformation framework that is capable of anonymizing biometric data by suppressing its sensitive attributes while retaining features relevant to downstream machine learning-based analyses that are of research and business values. We carried out a thorough experimental evaluation using publicly available facial, voice, motion, and EEG datasets. Results show that our proposed framework can achieve a high suppression level for sensitive information, while at the same time retain underlying data utility such that subsequent analyses on the anonymized biometric data could still be carried out to yield satisfactory accuracy

Gestational diabetes severity stratification during pregnancy: role of plasma oleic acid as a possible early marker

Normal pregnancy is characterized by changes in lipid metabolism with significant implications for the health of both mother and offspring. When these changes develop into maternal dyslipidemia, a significant association with adverse pregnancy outcomes has been observed, including the development of gestational diabetes (GD), modulation of the inflammatory response, and excessive fetal growth. In the present study, we performed a lipidomic assessment of patients at GD diagnosis (24–28 weeks of gestation) and 12 weeks after diagnosis. We found higher levels of esterified oleic acid in plasma at the time of GD diagnosis in women who subsequently required pharmacological therapy to control blood glucose levels compared to those who did not require additional treatment, suggesting that the measurement of plasma oleic acid might be an additional tool for the early identification of patients with a more severe form of gestational diabetes. Moreover, plasma oleic acid levels showed a positive correlation with fetal growth in the context of adequate glycemic control, supporting a metabolic dysregulation of other pathways whose identification could help clinicians to discriminate different cases within the spectrum of severity of the disease. Finally, the correlation between plasma oleic acid and circulating BAFF levels at the time of diagnosis and 12 weeks later adds a possible mechanism to support the pro-inflammatory and pro-diabetic state in the metabolic set of GD. Overall, these findings strongly support the role of plasma oleic acid as a possible early marker for GD severity stratification during pregnancy