Two-surface wave decay: improved analytical theory and effects on electron acceleration

Two-surface wave decay (TSWD), i.e. the parametric excitation of electron surface waves, was recently proposed as an absorption mechanism in the interaction of ultrashort, intense laser pulses with solid targets. We present an extension of the fluid theory of TSWD to a warm plasma which treats boundary effects consistently. We also present test-particle simulations showing localized enhancement of electron acceleration by TSWD fields; this effect leads to a modulation of the current density entering into the target and may seed current filamentation instabilities.Comment: 4 figures, submitted to Appl.Phys.B (special issue from HFSW X conference, Biarritz, France, Oct 12-15 2003); slightly revised tex

Biomolecular Corona Associated with Nanostructures: The Potentially Disruptive Role of Raman Microscopy

When nanostructures and other materials are exposed to biological fluids, they are immediately covered by a layer of biological molecules, which is typically referred to as a “biomolecular corona” (BC). This represents the first component of a material that interacts with biological systems, so characterizing the composition and the dynamic evolution of BC is essential for predicting the interactions of materials and living organisms. This review provides an analysis of current BC characterization techniques, with particular attention to nanostructures involved in biomedical applications. The influence on cell–nanostructure interactions is assessed and the advantages and limitations of each technique are discussed and compared. An in-depth analysis of Raman microscopy, a relatively unexploited tool with great potential in the characterization of BC, is then conducted. Raman microscopy can be used to analyze a vast amount of specimens without the need for staining, and can provide analysis on a spatial scale of hundreds of nanometers: it may thus represent a potentially disruptive tool for the characterization of BC, as it overcomes many of the limitations posed by current techniques

Estimating weekly excess mortality at sub-national level in Italy during the COVID-19 pandemic

In this study we present the first comprehensive analysis of the spatio-temporal differences in excess mortality during the COVID-19 pandemic in Italy. We used a population-based design on all-cause mortality data, for the 7,904 Italian municipalities. We estimated sex-specific weekly mortality rates for each municipality, based on the first four months of 2016-2019, while adjusting for age, localised temporal trends and the effect of temperature. Then, we predicted all-cause weekly deaths and mortality rates at municipality level for the same period in 2020, based on the modelled spatio-temporal trends. Lombardia showed higher mortality rates than expected from the end of February, with 23,946 (23,013 to 24,786) total excess deaths. North-West and North-East regions showed one week lag, with higher mortality from the beginning of March and 6,942 (6,142 to 7,667) and 8,033 (7,061 to 9,044) total excess deaths respectively. We observed marked geographical differences also at municipality level. For males, the city of Bergamo (Lombardia) showed the largest percent excess, 88.9% (81.9% to 95.2%), at the peak of the pandemic. An excess of 84.2% (73.8% to 93.4%) was also estimated at the same time for males in the city of Pesaro (Central Italy), in stark contrast with the rest of the region, which does not show evidence of excess deaths. We provided a fully probabilistic analysis of excess mortality during the COVID-19 pandemic at sub-national level, suggesting a differential direct and indirect effect in space and time. Our model can be used to help policy-makers target measures locally to contain the burden on the health-care system as well as reducing social and economic consequences. Additionally, this framework can be used for real-time mortality surveillance, continuous monitoring of local temporal trends and to flag where and when mortality rates deviate from the expected range, which might suggest a second wave of the pandemic

Estimating weekly excess mortality at sub-national level in Italy during the COVID-19 pandemic

In this study we present the first comprehensive analysis of the spatio-temporal differences in excess mortality during the COVID-19 pandemic in Italy. We used a population-based design on all-cause mortality data, for the 7,904 Italian municipalities. We estimated sex-specific weekly mortality rates for each municipality, based on the first four months of 2016-2019, while adjusting for age, localised temporal trends and the effect of temperature. Then, we predicted all-cause weekly deaths and mortality rates at municipality level for the same period in 2020, based on the modelled spatio-temporal trends. Lombardia showed higher mortality rates than expected from the end of February, with 23,946 (23,013 to 24,786) total excess deaths. North-West and North-East regions showed one week lag, with higher mortality from the beginning of March and 6,942 (6,142 to 7,667) and 8,033 (7,061 to 9,044) total excess deaths respectively. We observed marked geographical differences also at municipality level. For males, the city of Bergamo (Lombardia) showed the largest percent excess, 88.9% (81.9% to 95.2%), at the peak of the pandemic. An excess of 84.2% (73.8% to 93.4%) was also estimated at the same time for males in the city of Pesaro (Central Italy), in stark contrast with the rest of the region, which does not show evidence of excess deaths. We provided a fully probabilistic analysis of excess mortality during the COVID-19 pandemic at sub-national level, suggesting a differential direct and indirect effect in space and time. Our model can be used to help policy-makers target measures locally to contain the burden on the health-care system as well as reducing social and economic consequences. Additionally, this framework can be used for real-time mortality surveillance, continuous monitoring of local temporal trends and to flag where and when mortality rates deviate from the expected range, which might suggest a second wave of the pandemic