The identification of a novel Sulfolobus islandicus CAMP-like peptide points to archaeal microorganisms as cell factories for the production of antimicrobial molecules

Background: Pathogenic bacteria easily develop resistance to conventional antibiotics so that even relatively new molecules are quickly losing efficacy. This strongly encourages the quest of new antimicrobials especially for the treatment of chronic infections. Cationic antimicrobial peptides (CAMPs) are small positively charged peptides with an amphipathic structure, active against Gram-positive and Gram-negative bacteria, fungi, as well as protozoa.Results: A novel (CAMP)-like peptide (VLL-28) was identified in the primary structure of a transcription factor, Stf76, encoded by pSSVx, a hybrid plasmid-virus from the archaeon Sulfolobus islandicus. VLL-28 displays chemical, physical and functional properties typical of CAMPs. Indeed, it has a broad-spectrum antibacterial activity and acquires a defined structure in the presence of membrane mimetics. Furthermore, it exhibits selective leakage and fusogenic capability on vesicles with a lipid composition similar to that of bacterial membranes. VLL-28 localizes not only on the cell membrane but also in the cytoplasm of Escherichia coli and retains the ability to bind nucleic acids. These findings suggest that this CAMP-like peptide could exert its antimicrobial activity both on membrane and intra cellular targets.Conclusions: VLL-28 is the first CAMP-like peptide identified in the archaeal kingdom, thus pointing to archaeal microorganisms as cell factories to produce antimicrobial molecules of biotechnological interest. Furthermore, results from this work show that DNA/RNA-binding proteins could be used as sources of CAMPs

Using a Soft Growing Robot as a Sensor Delivery System in Remote Environments: A Practical Case Study

Soft continuum robots are a new class of robotic devices, which are very promising for enabling measurement applications especially in remote, difficult-to-reach environments. In this work, we propose the use of a particular soft robot, which is able to evert and steer from the tip, as a sensor delivery system. The measurement system consists of two major sections: i) the robotic platform for movement purposes; and ii) the sensing part (i.e., a sensor attached to its tip to enable the measurement). As a case study of the use of the soft-growing robot as a sensor-delivery system, the transportation of a wired thermocouple towards a remote hot source was considered. The preliminary results anticipate the suitability of soft continuum robotic platforms for remote applications in confined and constrained environments

The perception of healthcare quality of elderly in the city of Bari, South Italy

<p>Abstract</p> <p>Background</p> <p>In recent decades in Italy, as in all the industrialized nations, the proportion of elderly subjects in the total population is constantly on the increase. However the increased life expectancy is not always paralleled by a true improvement in the quality of life.</p> <p>In this context, it is essential to analyze elderly real health needs and the responses to these needs, especially in terms of healthcare, that the territorial services are perceived to offer.</p> <p>Methods</p> <p>In the period from June to September 2006 we selected randomly one General Practitioner (GP) for each district of the Bari Municipal Area and, form each GP, we randomly chose 25 patients over 65 years old (YO). We conducted phone interviews using a standard data collection questionnaire and, for each of the recruited subjects, the GP filled a data collection sheet.</p> <p>Results</p> <p>Although the mean age (73.6 years) of the population under study was quite high, the general state of health was judged good both by the G P- and by their elderly patients (>75%).</p> <p>Notably, the great majority of elderly patients considered the healthcare they receive to be satisfactory (>60%): in particular, the GP was the true point of reference for this slice of the population for strictly medical problems as well as for advice. On the contrary, the patients attributed little value to social services, which were poorly known and scarcely used (8.5%). Public hospital facilities played a central role in second level healthcare in more than 30% of cases; private facilities covered by public health insurance were also very important. As possible solutions to the problem of loneliness, 36.6% of the patients declared that they approved of nursing homes.</p> <p>Conclusion</p> <p>Decision makers need to create services supporting the key role played by General Practitioners, who are well aware that their assistance is not sufficient to satisfy the health needs of the elderly.</p

Trends in Net Survival from Vulvar Squamous Cell Carcinoma in Italy (1990–2015)

Objective: In many Western countries, survival from vulvar squamous cell carcinoma (VSCC) has been stagnating for decades or has increased insufficiently from a clinical perspective. In Italy, previous studies on cancer survival have not taken vulvar cancer into consideration or have pooled patients with vulvar and vaginal cancer. To bridge this knowledge gap, we report the trend in survival from vulvar cancer between 1990 and 2015. (2) Methods: Thirty-eight local cancer registries covering 49% of the national female population contributed the records of 6274 patients. Study endpoints included 1- and 2-year net survival (NS) calculated using the Pohar-Perme estimator and 5-year NS conditional on having survived two years (5|2-year CNS). The significance of survival trends was assessed with the Wald test on the coefficient of the period of diagnosis, entered as a continuous regressor in a Poisson regression model. (3) Results: The median patient age was stable at 76 years. One-year NS decreased from 83.9% in 1990–2001 to 81.9% in 2009–2015 and 2-year NS from 72.2% to 70.5%. Five|2-year CNS increased from 85.7% to 86.7%. These trends were not significant. In the age stratum 70–79 years, a weakly significant decrease in 2-year NS from 71.4% to 65.7% occurred. Multivariate analysis adjusting for age group at diagnosis and geographic area showed an excess risk of death at 5|2-years, of borderline significance, in 2003–2015 versus 1990–2002. (4) Conclusions: One- and 2-year NS and 5|2-year CNS showed no improvements. Current strategies for VSCC control need to be revised both in Italy and at the global level

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Distribution of diseases defined as limiting, by the patient and by the GP

<p><b>Copyright information:</b></p><p>Taken from "The perception of healthcare quality of elderly in the city of Bari, South Italy"</p><p>http://www.biomedcentral.com/1472-6963/7/174</p><p>BMC Health Services Research 2007;7():174-174.</p><p>Published online 24 Oct 2007</p><p>PMCID:PMC2194769.</p><p></p