Fragments of -thymosin from the sea urchin Paracentrotus lividus as potential antimicrobial peptides against staphylococcal biofilms

The immune mediators in echinoderms can be a potential source of novel antimicrobial peptides (AMPs) applied toward controlling pathogenic staphylococcal biofilms that are intrinsically resistant to conventional antibiotics. The peptide fraction <5 kDa from the cytosol of coelomocytes of the sea urchin Paracentrotus lividus (5-CC) was tested against a group of Gram-positive and Gram-negative pathogen reference strains. The 5-CC of P. lividus was active against all planktonic-tested strains but also showed antibiofilm properties against staphylococcal strains. Additionally,wedemonstrated the presenceof three smallpeptides in the5-CCbelonging tosegment 9-41of aP. lividus -thymosin. The smallest of these peptides in particular, showed the common chemical\u2013physical characteristics of AMPs. This novel AMP from -thymosin has high potential activity as an antibiofilm agent, acting on slow-growing bacterial cells that exhibit a reduced susceptibility to conventional antibiotics and represent a reservoir for recurrent biofilm-associated infections

Hydrogeochemistry of a wetland area of southwestern Sicily (Italy)

The “Preola” and “Gorghi tondi” lakes are the most noticeable wetlands in the Mazara del Vallo territory (south-west Sicily). There are four karst origin lakes located in a natural depression formed by gypsum dissolution and subsequent collapse of the “Calcarenite di Marsala”, a few meters above sea level. Erosion of the depression sides and human activity has caused visible colluvial deposits, which have contributed to a natural filling process of the lakes. A hydrogeological map of the area and the reconstruction of a water circulation model supplying the lakes have been drafted from geochemical and hydrogeological data. It is apparent from 18O values that the well waters are mainly fed by local meteoric water circulating within the calcarenitic aquifer. However, the lake waters chemical composition are very likely controlled by evaporation processes and a complex mixing between seawater and groundwater, depending on seasonal variation in the hydrodynamic equilibrium

Spatially Extended SHAR Epidemiological Framework of Infectious Disease Transmission

Mathematical models play an important role in epidemiology. The inclusion of a spatial component in epidemiological models is especially important to understand and address many relevant ecological and public health questions, e.g., when wanting to differentiate transmission patterns across geographical regions or when considering spatially heterogeneous intervention measures. However, the introduction of spatial effects can have significant consequences on the observed model dynamics and hence must be carefully analyzed and interpreted. Cellular automata epidemiological models typically rely on simplified computational grids but can provide valuable insight into the spatial dynamics of transmission within a population by suitably accounting for the connections between individuals in the considered community. In this paper, we describe a stochastic cellular automata disease model based on an extension of the traditional Susceptible-Infected-Recovered (SIR) compartmentalization of the population, namely, the Susceptible-Hospitalized-Asymptomatic-Recovered (SHAR) formulation, in which infected individuals either present a severe form of the disease, thus requiring hospitalization, or belong to the so-called mild/asymptomatic class. The critical transmission threshold is derived analytically in the nonspatial SHAR formulation, and this generalizes previously obtained theoretical results for the SIR model. We present simulation results discussing the effect of key model parameters and of spatial correlations on model outputs and propose an algorithm for tracking the evolution of infection clusters within the considered population. Focusing on the role of import and criticality on the overall dynamics, we conclude that the current spatial setting increases the critical transmission threshold in comparison to the nonspatial model

Palermo tra aspirazioni Euro-Mediterranee e processi innovativi

Lo scopo di questo lavoro \ue8 quello di fornire una panoramica dei cambiamenti culturali, sociali ed economici che si sono verificati a Palermo a partire dal 90 ', fornedo per quanto possibile un quadro di riferimento per il pensiero, il dibattito e l'azione politica nelle grandi aree metropolitane del Mezzogiorno mediterraneo che come Plaermo rappresenatano un punto di contatto culturale e un luogo per nuove opportunit\ue0, non solo commerciali, ma anche sociali e turistiche. Una reinterpretazione del sistema di innovazione in Sicilia che si configura come una rete di tipo policentrica, i cui nodi sono rappresentati dalla citt\ue0 di Palermo, Catania e Messina. In questo contesto, a Palermo, dove il settore dei servizi \ue8 ancora il pi\uf9 importante settore produttivo, si pu\uf2 notare un recente processo di "metamorfosi" che le recenti politiche di sviluppo regionale hanno tentato di favorire grazie ad ingenti investimenti in innovazione e ricerca

A Novel Mathematical Approach for Analysis of Integrated Cell–Patient Data Uncovers a 6-Gene Signature Linked to Endocrine Therapy Resistance

A significant number of breast cancers develop resistance to hormone therapy. This progression, while posing a major clinical challenge, is difficult to predict. Despite important contributions made by cell models and clinical studies to tackle this problem, both present limitations when taken individually. Experiments with cell models are highly reproducible but do not reflect the indubitable heterogeneous landscape of breast cancer. On the other hand, clinical studies account for this complexity but introduce uncontrolled noise due to external factors. Here, we propose a new approach for biomarker discovery that is based on a combined analysis of sequencing data from controlled MCF7 cell experiments and heterogeneous clinical samples that include clinical and sequencing information from The Cancer Genome Atlas. Using data from differential gene expression analysis and a Bayesian logistic regression model coupled with an original simulated annealing-type algorithm, we discovered a novel 6-gene signature for stratifying patient response to hormone therapy. The experimental observations and computational analysis built on independent cohorts indicated the superior predictive performance of this gene set over previously known signatures of similar scope. Together, these findings revealed a new gene signature to identify patients with breast cancer with an increased risk of developing resistance to endocrine therapy

Funnel plots and choropleth maps in cancer risk communication: a comparison of tools for disseminating population-based incidence data to stakeholders

Background: Population-based cancer registries provide epidemiological cancer information, but the indicators are often too complex to be interpreted by local authorities and communities, due to numeracy and literacy limitations. The aim of this paper is to compare the commonly used visual formats to funnel plots to enable local public health authorities and communities to access valid and understandable cancer incidence data obtained at the municipal level. Methods: A funnel plot representation of standardised incidence ratio (SIR) was generated for the 82 municipalities of the Palermo Province with the 2003 2011 data from the Palermo Province Cancer Registry (Sicily, Italy). The properties of the funnel plot and choropleth map methodologies were compared within the context of disseminating epidemiological data to stakeholders. Results: The SIRs of all the municipalities remained within the control limits, except for Palermo city area (SIR=1.12), which was sited outside the upper control limit line of 99.8%. The Palermo Province SIRs funnel plot representation was congruent with the choropleth map generated from the same data, but the former resulted more informative as shown by the comparisons of the weaknesses and strengths of the 2 visual formats. Conclusions: Funnel plot should be used as a complementary valuable tool to communicate epidemiological data of cancer registries to communities and local authorities, visually conveying an efficient and simple way to interpret cancer incidence data

Understanding COVID-19 Epidemics: A Multi-Scale Modeling Approach

COVID-19 was declared a pandemic by the World Health Organization in March 2020 and, since then, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading and control under different scenarios. In this chapter, two different approaches to model the spread of COVID-19 are presented. The model frameworks are described and results are presented in connection with the current epidemiological situation of vaccination roll-out. This chapter is structured as follows. Section 2 presents the stochastic SHARUCD modeling framework developed within a modeling task force created to support public health managers during the COVID-19 crisis. As an extension of the basic SHAR (Susceptible-Hospitalized-Asymptomatic-Recovered) model, the SHARUCD models were parameterized and validated with empirical data for the Basque Country, Spain, and have been used (up until now) to monitor COVID-19 spreading and control over the course of the pandemic. Section 3 introduces the kinetic theory of active particles (KTAP) model for the spread of a disease. With an exploratory analysis, we present a possible way to deal with heterogeneity and multiscale features. Section 4 concludes this work, with a discussion on both models and further research perspectives description

Origanum vulgare subsp. hirtum essential oil prevented biofilm formation and showed antibacterial activity against planktonic and sessile bacterial cells

Essential oils from six different populations of Origanum vulgare subsp. hirtum were compared for their antibiofilm properties. The six essential oils (A to F) were characterized by a combination of gas chromatography with flame ionization detector and gas chromatography with mass spectrometer detector analyses. All oils showed weak activity against the planktonic form of a group of Staphylococcus aureus strains and against a Pseudomonas aeruginosa ATCC 15442 reference strain. The ability to inhibit biofilm formation was investigated at sub-MIC levels of 200, 100, and 50 m g/ml by staining sessile cells with safranin. Sample E showed the highest average effectiveness against all tested strains at 50 m g/ml and had inhibition percentages ranging from 30 to 52%. In the screening that used preformed biofilm from the reference strain P. aeruginosa, essential oils A through E were inactive at 200 m g/ml; F was active with a percentage of inhibition equal to 53.2%. Oregano essential oil can inhibit the formation of biofilms of various food pathogens and food spoilage organisms.Essential oils from six different populations of Origanum vulgare subsp. hirtum were compared for their antibiofilm properties. The six essential oils (A to F) were characterized by a combination of gas chromatography with flame ionization detector and gas chromatography with mass spectrometer detector analyses. All oils showed weak activity against the planktonic form of a group of Staphylococcus aureus strains and against a Pseudomonas aeruginosa ATCC 15442 reference strain. The ability to inhibit biofilm formation was investigated at sub-MIC levels of 200, 100, and 50 m g/ml by staining sessile cells with safranin. Sample E showed the highest average effectiveness against all tested strains at 50 m g/ml and had inhibition percentages ranging from 30 to 52%. In the screening that used preformed biofilm from the reference strain P. aeruginosa, essential oils A through E were inactive at 200 m g/ml; F was active with a percentage of inhibition equal to 53.2%. Oregano essential oil can inhibit the formation of biofilms of various food pathogens and food spoilage organisms

The artificial retina for track reconstruction at the LHC crossing rate

We present the results of an R&D study for a specialized processor capable of precisely reconstructing events with hundreds of charged-particle tracks in pixel and silicon strip detectors at $40\,\rm MHz$, thus suitable for processing LHC events at the full crossing frequency. For this purpose we design and test a massively parallel pattern-recognition algorithm, inspired to the current understanding of the mechanisms adopted by the primary visual cortex of mammals in the early stages of visual-information processing. The detailed geometry and charged-particle's activity of a large tracking detector are simulated and used to assess the performance of the artificial retina algorithm. We find that high-quality tracking in large detectors is possible with sub-microsecond latencies when the algorithm is implemented in modern, high-speed, high-bandwidth FPGA devices.Comment: 3 pages, 3 figures, ICHEP14. arXiv admin note: text overlap with arXiv:1409.089