Dielectric barrier plasma discharge exsolution of nanoparticles at room temperature and atmospheric pressure Dataset

The dataset that corresponds to the results reported in the paper are included within this record as an Excel file and with tabs corresponding to each figure. Additional results and raw data underlying this work (full set of microscopy images and size analysis and statistics, high resolution deconvoluted x-ray photoelectron spectra and control magnetic measurements) are available in the Supporting Information (in PDF format) or on request following instructions provided here. This work has been supported by EPSRC through the UK Catalysis Hub (EP/R027129/1) and the Emergent Nanomaterials-Critical Mass Initiative (EP/R023638/1, EP/R023921/1, EP/R023522/1, EP/R008841/1) as well as the Royal Society (IES\R2\212049). F.F. gratefully acknowledges support from the National Research Council of Italy (2020 STM program). I.S.M. acknowledges funding from the Royal Academy of Engineering through a Chair in Emerging Technologies Award entitled “Engineering Chemical Reactor Technologies for a Low-Carbon Energy Future” (Grant CiET1819\2\57). KK acknowledges funding from the Henry Royce Institute (EP/X527257/1)

Use of biosensors for rapid and sensitive detection of pesticides in food samples for food safety chemical risk assessment

Abstract The utility of pesticides in the agricultural field is unquestionable, but at the same time pesticide use presents serious hazards to the environment and the human health. For that reason, detection of pesticides and their biotransformation products in food is of utmost importance. According to previous studies, esterase‐based biosensors have been proposed as a viable and efficient solution for the detection of organophosphate pesticides. In this project, a double mutant of the thermostable esterase‐2 (EST2) from Alicyclobacillus acidocaldarius was studied as a potential biosensor, for its ability to detect residual amounts of pesticides. Initial characterisation of the enzyme was performed, that included determination of optimal pH, thermophilicity, as well as kinetic analysis. Subsequently, the enzyme was studied by enzymatic activity assays with and without the presence of various organophosphate compounds. The effect of the organophosphates on the enzymatic activity was measured and complete inhibition of the enzyme was observed after incubation with paraoxon. These experiments were followed by an additional method involving labelling of the enzyme with a fluorescent probe. In this case, the effect of different pesticides on the EST2 enzyme was monitored by measuring the fluorescence quenching upon addition to the enzyme. Fourteen compounds were screened with this method and significant fluorescence quenching was observed in the presence of paraoxon and methyl‐paraoxon when used in equimolar amounts with the enzyme in the range of nanomolar. This biosensor has been also used to test the presence of pesticides in real food samples, like fruits and juices. This research represents a starting point to develop effective fluorescence‐based biosensors aiming at the screening of mutants with different pesticide selectivity profiles. The use of this enzyme‐based biosensor can have applications in the field of food traceability as well as environmental monitoring, to control the presence of toxic chemicals, in particular organophosphate pesticides

Supplementary Material for: Snoring Amplifies the Risk of Heart Failure and Mortality in Dialysis Patients

Background: Snoring, an indicator of sleep-disordered breathing (SDB), associates with all-cause and cardiovascular (CV) mortality in high-risk conditions such as chronic heart failure (HF). Because SDB and HF are exceedingly frequent in end-stage kidney disease (ESKD), we hypothesized that SDB as detected by snoring may impact upon the relationship between chronic HF and all-cause and CV mortality in these patients. Methods: We tested this hypothesis in a cohort of 827 ESKD patients, followed up for 2.3 years. Results: In this population, snoring was a strong modifier of the risk of chronic HF for all-cause and CV death. In fully adjusted Cox models, the hazard ratio (HR) associated to chronic HF for the study outcomes was highest in heavy snorers [all-cause death: HR 2.6 (95% CI 1.6-4.3, p < 0.001); CV death: HR 4.0 (95% CI 2.1-7.6, p < 0.001)], intermediate in moderate snorers [all-cause death: HR 1.6 (95% CI 1.1-2.2, p = 0.01); CV death: HR 1.8 (95% CI 1.2-2.8, p = 0.01)], and lowest and not significant in non-snorers [all-cause death: HR 0.9 (95% CI 0.6-1.6, p = NS); CV death: HR 0.8 (95% CI 0.4-1.6, p = NS)]. Conclusions: Snoring is a strong and independent effect modifier of the relationship between chronic HF and all-cause and CV mortality in ESKD. Since SDB and snoring are in part attributable to reversible pharyngeal oedema, intensified surveillance and treatment of chronic HF snorers on dialysis may translate into better clinical outcomes in this very high-risk population, an issue which remains to be tested in specifically designed clinical trials

Marine amoebae with cytoplasmic and perinuclear symbionts deeply branching in the Gammaproteobacteria

Amoebae play an important ecological role as predators in microbial communities. They also serve as niche for bacterial replication, harbor endosymbiotic bacteria and have contributed to the evolution of major human pathogens. Despite their high diversity, marine amoebae and their association with bacteria are poorly understood. Here we describe the isolation and characterization of two novel marine amoebae together with their bacterial endosymbionts, tentatively named ‘Candidatus Occultobacter vannellae’ and ‘Candidatus Nucleophilum amoebae’. While one amoeba strain is related to Vannella, a genus common in marine habitats, the other represents a novel lineage in the Amoebozoa. The endosymbionts showed only low similarity to known bacteria (85–88% 16S rRNA sequence similarity) but together with other uncultured marine bacteria form a sister clade to the Coxiellaceae. Using fluorescence in situ hybridization and transmission electron microscopy, identity and intracellular location of both symbionts were confirmed; one was replicating in host-derived vacuoles, whereas the other was located in the perinuclear space of its amoeba host. This study sheds for the first time light on a so far neglected group of protists and their bacterial symbionts. The newly isolated strains represent easily maintainable model systems and pave the way for further studies on marine associations between amoebae and bacterial symbionts

NIST certified secure key generation via deep learning of physical unclonable functions in silica aerogels (dataset)

Physical unclonable functions (PUFs) are complex physical objects that aim at overcoming the vulnerabilities of traditional cryptographic keys, promising a robust class of security primitives for different applications. Optical PUFs present advantages over traditional electronic realizations, namely a stronger unclonability, but suffer from problems of reliability and weak unpredictability of the key. We here develop a two-step PUF generation strategy based on deep-learning, which associates reliable keys verified against the NIST certification standards of true random generators for cryptography. The idea explored in this work is to decouple the design of the PUFs from the key generation and train a neural architecture to learn the mapping algorithm between the key and the PUF. We report experimental results with all-optical PUFs realized in silica aerogels and analyzed a population of 100 generated keys, each of 10000 bit length. The key generated passed all tests required by the NIST standard, with proportion outcomes well beyond NIST’s recommended threshold. The two-step key generation strategy studied in this work can be generalized to any PUF based on either optical or electronic implementations. It can help the design of robust PUFs for both secure authentications and encrypted communications

An interactive web-GIS tool for risk analysis: a case study in the Fella River basin, Italy

This paper presents a prototype of an interactive web-GIS tool for risk analysis of natural hazards, in particular for floods and landslides, based on open-source geospatial software and technologies. The aim of the presented tool is to assist the experts (risk managers) in analysing the impacts and consequences of a certain hazard event in a considered region, providing an essential input to the decision-making process in the selection of risk management strategies by responsible authorities and decision makers. This tool is based on the Boundless (OpenGeo Suite) framework and its client-side environment for prototype development, and it is one of the main modules of a web-based collaborative decision support platform in risk management. Within this platform, the users can import necessary maps and information to analyse areas at risk. Based on provided information and parameters, loss scenarios (amount of damages and number of fatalities) of a hazard event are generated on the fly and visualized interactively within the web-GIS interface of the platform. The annualized risk is calculated based on the combination of resultant loss scenarios with different return periods of the hazard event. The application of this developed prototype is demonstrated using a regional data set from one of the case study sites, Fella River of northeastern Italy, of the Marie Curie ITN CHANGES project