Cholesterol effect on the specific capacitance of submicrometric DOPC bilayer patches measured by in-liquid scanning dielectric microscopy

The specific capacitance of biological membranes is a key physical parameter in bioelectricity that also provides valuable physicochemical information on composition, phase, or hydration properties. Cholesterol is known to modulate the physicochemical properties of biomembranes, but its effect on the specific capacitance has not been fully established yet. Here we use the high spatial resolution capabilities of in-liquid scanning dielectric microscopy in force detection mode to directly demonstrate that DOPC bilayer patches at 50% cholesterol concentration show a strong reduction of their specific capacitance with respect to pure DOPC bilayer patches. The reduction observed (around 35%) cannot be explained by the small increase in bilayer thickness (around 16%). We suggest that the reduction of the specific capacitance might be due to the dehydration of the polar head groups caused by the insertion of cholesterol molecules in the bilayer. The results reported confirm the potential of in-liquid SDM to study the electrical and physicochemical properties of lipid bilayers at very small scales (down to around 200 nm here), with implications in fields such as biophysics, bioelectricity, biochemistry, and biosensing

Dielectric properties and lamellarity of single liposomes measured by in-liquid scanning dielectric microscopy

Liposomes are widely used as drug delivery carriers and as cell model systems. Here, we measure the dielectric properties of individual liposomes adsorbed on a metal electrode by in-liquid scanning dielectric microscopy in force detection mode. From the measurements the lamellarity of the liposomes, the separation between the lamellae and the specifc capacitance of the lipid bilayer can be obtained. As application we considered the case of non-extruded DOPC liposomes with radii in the range ~100-800 nm. Uni-, bi- and tri-lamellar liposomes have been identifed, with the largest population corresponding to bi-lamellar liposomes. The interlamellar separation in the bi-lamellar liposomes is found to be below ~10 nm in most instances. The specifc capacitance of the DOPC lipid bilayer is found to be ~0.75 µF/cm2 in excellent agreement with the value determined on solid supported planar lipid bilayers. The lamellarity of the DOPC liposomes shows the usual correlation with the liposome's size. No correlation is found, instead, with the shape of the adsorbed liposomes. The proposed approach ofers a powerful label-free and non invasive method to determine the lamellarity and dielectric properties of single liposom

Nanoscale mapping of the conductivity and interfacial capacitance of an electrolyte-gated organic field-effect transistor under operation

Versió postprint del document publicat a: https://doi.org/10.1002/adfm.202008032Probing nanoscale electrical properties of organic semiconducting materials at the interface with an electrolyte solution under externally applied voltages is key in the field of organic bioelectronics. It is demonstrated that the conductivity and interfacial capacitance of the active channel of an electrolyte-gated organic field‐effect transistor (EGOFET) under operation can be probed at the nanoscale using scanning dielectric microscopy in force detection mode in liquid environment. Local electrostatic force versus gate voltage transfer characteristics are obtained on the device and correlated with the global current–voltage transfer characteristics of the EGOFET. Nanoscale maps of the conductivity of the semiconducting channel show the dependence of the channel conductivity on the gate voltage and its variation along the channel due to the space charge limited conduction. The maps reveal very small electrical heterogeneities, which correspond to local interfacial capacitance variations due to an ultrathin non-uniform insulating layer resulting from a phase separation in the organic semiconducting blend. Present results offer insights into the transduction mechanism at the organic semiconductor/electrolyte interfaces at scales down to ≈100 nm, which can bring substantial optimization of organic electronic devices for bioelectronic applications such as electrical recording on excitable cells or label-free biosensing

Prevalence and predictor factors of respiratory impairment in a large cohort of patients with Myotonic Dystrophy type 1 (DM1): A retrospective, cross sectional study

Introduction: Respiratory complications are relevant in DM1, leading to a significantly increased morbidity and mortality risk in these patients; however, so far only few studies concerning respiratory function have been conducted in DM1 patients. We report a retrospective, multicenter, cross sectional study on a large cohort of DM1 patients widely characterized in the phenotype, to assess prevalence and identify predictors of restrictive respiratory syndrome. Methods: 268 DM1 subjects aged >18 years, who had recently performed spirometric tests were included; restrictive syndrome was diagnosed if forced vital capacity (FVC) <80% of predicted. This cut-off was used for statistical univariate and multivariate analysis. Results: 51.9% patients showed a restrictive syndrome, and half of them had indication to non-invasive ventilation (NIV), yet only 50% resulted compliant to NIV. CTG expansion size in leukocytes, clinical muscle severity, most functional parameters of respiratory muscle involvement, presence of cardiac conduction disturbances, pacemaker (PMK), exertion dyspnea, obstructive sleep apnea, and indication and compliance to NIV were all significantly associated with restrictive syndrome at the univariate analysis; in the multivariate model only the first two factors resulted independent predictors. Discussion: A high prevalence of restrictive syndrome in our DM1 cohort, mainly due to respiratory muscles weakness, was observed and documented; the severity of muscle impairment and the CTG expansion size confirmed to be independent predictors of respiratory restriction. Our data suggest that optimization of respiratory therapeutic management, particularly regarding launching of NIV, might help to reduce the rate of deaths due to respiratory complications in DM1

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

The rapid spread of SARS-COV-2 Omicron variant in Italy reflected early through wastewater surveillance

The SARS-CoV-2 Omicron variant emerged in South Africa in November 2021, and has later been identified worldwide, raising serious concerns. A real-time RT-PCR assay was designed for the rapid screening of the Omicron variant, targeting characteristic mutations of the spike gene. The assay was used to test 737 sewage samples collected throughout Italy (19/21 Regions) between 11 November and 25 December 2021, with the aim of assessing the spread of the Omicron variant in the country. Positive samples were also tested with a real-time RT-PCR developed by the European Commission, Joint Research Centre (JRC), and through nested RT-PCR followed by Sanger sequencing. Overall, 115 samples tested positive for Omicron SARS-CoV-2 variant. The first occurrence was detected on 7 December, in Veneto, North Italy. Later on, the variant spread extremely fast in three weeks, with prevalence of positive wastewater samples rising from 1.0% (1/104 samples) in the week 5-11 December, to 17.5% (25/143 samples) in the week 12-18, to 65.9% (89/135 samples) in the week 19-25, in line with the increase in cases of infection with the Omicron variant observed during December in Italy. Similarly, the number of Regions/Autonomous Provinces in which the variant was detected increased from one in the first week, to 11 in the second, and to 17 in the last one. The presence of the Omicron variant was confirmed by the JRC real-time RT-PCR in 79.1% (91/115) of the positive samples, and by Sanger sequencing in 66% (64/97) of PCR amplicons. In conclusion, we designed an RT-qPCR assay capable to detect the Omicron variant, which can be successfully used for the purpose of wastewater-based epidemiology. We also described the history of the introduction and diffusion of the Omicron variant in the Italian population and territory, confirming the effectiveness of sewage monitoring as a powerful surveillance tool

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration