A fresh look at paralytics in the critically ill: real promise and real concern.

Neuromuscular blocking agents (NMBAs), or "paralytics," often are deployed in the sickest patients in the intensive care unit (ICU) when usual care fails. Despite the publication of guidelines on the use of NMBAs in the ICU in 2002, clinicians have needed more direction to determine which patients would benefit from NMBAs and which patients would be harmed. Recently, new evidence has shown that paralytics hold more promise when used in carefully selected lung injury patients for brief periods of time. When used in early acute respiratory distress syndrome (ARDS), NMBAs assist to establish a lung protective strategy, which leads to improved oxygenation, decreased pulmonary and systemic inflammation, and potentially improved mortality. It also is increasingly recognized that NMBAs can cause harm, particularly critical illness polyneuromyopathy (CIPM), when used for prolonged periods or in septic shock. In this review, we address several practical considerations for clinicians who use NMBAs in their practice. Ultimately, we conclude that NMBAs should be considered a lung protective adjuvant in early ARDS and that clinicians should consider using an alternative NMBA to the aminosteroids in septic shock with less severe lung injury pending further studies

Ballistic electron microscopy and spectroscopy of metal and semiconductor nanostructures

Ballistic electron emission microscopy (BEEM) and its spectroscopy utilize ballistic transport of hot carriers as a versatile tool to characterize nanometer-scale structural and electronic properties of metallic and semiconducting materials and their interfaces. In this review, recent progress in experimental and theoretical aspects of the BEEM technique are covered. Emphasis is drawn to the development of BEEM in several emerging fields, including spin-sensitive hot-carrier transport through ferromagnetic thin films and multilayers, hot-electron spectroscopy and imaging of organic thin films and molecules, and hot-electron induced electroluminescence in semiconductor heterostructures. A brief discussion on BEEM of cross-sectional semiconductor heterostructures and advanced insulator films is also included

Reproduction ratio and growth rates: Measures for an unfolding pandemic

The initial exponential growth rate of an epidemic is an important measure that follows directly from data at hand, commonly used to infer the basic reproduction number. As the growth rates λ(t) of tested positive COVID-19 cases have crossed the threshold in many countries, with negative numbers as surrogate for disease transmission deceleration, lock- downs lifting are linked to the behavior of the momentary reproduction numbers r(t), often called R0. Important to note that this concept alone can be easily misinterpreted as it is bound to many internal assumptions of the underlying model and significantly affected by the assumed recovery period. Here we present our experience, as part of the Basque Coun- try Modeling Task Force (BMTF), in monitoring the development of the COVID-19 epidemic, by considering not only the behaviour of r(t) estimated for the new tested positive cases— significantly affected by the increased testing capacities, but also the momentary growth rates for hospitalizations, ICU admissions, deceased and recovered cases, in assisting the Basque Health Managers and the Basque Government during the lockdown lifting mea- sures. Two different data sets, collected and then refined during the COVID-19 responses, are used as an exercise to estimate the momentary growth rates and reproduction numbers over time in the Basque Country, and the implications of using those concepts to make deci- sions about easing lockdown and relaxing social distancing measures are discussed. These results are potentially helpful for task forces around the globe which are now struggling to provide real scientific advice for health managers and governments while the lockdown measures are relaxed.Marie Skłodowska-Curie grant agreement No 79249

Scaling of stochasticity in dengue hemorrhagic fever epidemics

In this paper we analyze the stochastic version of a minimalistic multi-strain model, which captures essential differences between primary and secondary infections in dengue fever epidemiology, and investigate the interplay between stochasticity, seasonality and import. The introduction of stochasticity is needed to explain the fluctuations observed in some of the available data sets, revealing a scenario where noise and complex deterministic skeleton strongly interact. For large enough population size, the stochastic system can be well described by the deterministic skeleton gaining insight on the relevant parameter values purely on topological information of the dynamics, rather than classical parameter estimation of which application is in general restricted to fairly simple dynamical scenarios

The role of mild and asymptomatic infections on COVID-19 vaccines performance: A modeling study

Introduction: Different COVID-19 vaccine efficacies are reported, with remarkable effectiveness against severe disease. The so called sterilizing immunity, occurring when vaccinated individuals cannot transmit the virus, is still being evaluated. It is also unclear to what extent people with no symptoms or mild infection transmit the disease, and estimating their contribution to outbreaks is challenging. Objective: With an uneven roll out of vaccination, the purpose of this study is to investigate the role of mild and asymptomatic infections on COVID-19 vaccine performance as vaccine efficacy and vaccine coverage vary. Methods: We use an epidemiological SHAR (Susceptible-Hospitalized-Asymptomatic-Recovered) model framework to evaluate the effects of vaccination in different epidemiological scenarios of coverage and efficacy. Two vaccination models, the vaccine V1 protecting against severe disease, and the vaccine V2, protecting against infection as well as severe disease, are compared to evaluate the reduction of overall infections and hospitalizations. Results: Vaccine performance is driven by the ability of asymptomatic or mild disease cases transmitting the virus. Vaccines protecting against severe disease but failing to block transmission might not be able to reduce significantly the severe disease burden during the initial stage of a vaccination roll out programme, with an eventual increase on the number of overall infections in a population. Conclusion: The different COVID-19 vaccines currently in use have features placing them closer to one or the other of these two extreme cases, V1 and V2, and insights on the importance of asymptomatic infection in a vaccinated population are of a major importance for the future planning of vaccination programmes. Our results give insights on how to best combine the use of the available COVID-19 vaccines, optimizing the reduction of hospitalizations

Modelling COVID 19 in the Basque Country from introduction to control measure response

In March 2020, a multidisciplinary task force (so‐called Basque Modelling Task Force, BMTF) was created to assist the Basque health managers and Government during the COVID‐19 responses. BMTF is a modelling team, working on different approaches, including stochastic processes, statistical methods and artificial intelligence. Here we describe the efforts and challenges to develop a flexible modeling framework able to describe the dynamics observed for the tested positive cases, including the modelling development steps. The results obtained by a new stochastic SHARUCD model framework are presented. Our models differentiate mild and asymptomatic from severe infections prone to be hospitalized and were able to predict the course of the epidemic, providing important projections on the national health system’s necessities during the increased population demand on hospital admissions. Short and longer‐term predictions were tested with good results adjusted to the available epidemiological data. We have shown that the partial lockdown measures were effective and enough to slow down disease transmission in the Basque Country. The growth rate was calculated from the model and from the data and the implications for the reproduction ratio r are shown. The analysis of the growth rates from the data led to improved model versions describing after the exponential phase also the new information obtained during the phase of response to the control measures. This framework is now being used to monitor disease transmission while the country lockdown was gradually lifted, with insights to specific programs for a general policy of “social distancing” and home quarantining.Marie Skłodowska-Curie Grant Agreement No. 79249

Manipulation of subsurface carbon nanoparticles in Bi2Sr2CaCu2O8+δ using a scanning tunneling microscope

We present evidence that subsurface carbon nanoparticles in Bi2Sr2CaCu2O8+δ can be manipulated with nanometer precision using a scanning tunneling microscope. High-resolution images indicate that most of the carbon particles remain subsurface after transport observable as a local increase in height as the particle pushes up on the surface. Tunneling spectra in the vicinity of these protrusions exhibit semiconducting characteristics with a band gap of approximately 1.8 eV, indicating that the incorporation of carbon locally alters the electronic properties near the surface

Critical fluctuations in epidemic models explain COVID‑19 post‑lockdown dynamics

As the COVID-19 pandemic progressed, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading. The momentary reproduction ratio r(t) of an epidemic is used as a public health guiding tool to evaluate the course of the epidemic, with the evolution of r(t) being the reasoning behind tightening and relaxing control measures over time. Here we investigate critical fluctuations around the epidemiological threshold, resembling new waves, even when the community disease transmission rate β is not signifcantly changing. Without loss of generality, we use simple models that can be treated analytically and results are applied to more complex models describing COVID-19 epidemics. Our analysis shows that, rather than the supercritical regime (infectivity larger than a critical value, β>βc) leading to new exponential growth of infection, the subcritical regime (infectivity smaller than a critical value, β<βc) with small import is able to explain the dynamic behaviour of COVID-19 spreading after a lockdown lifting, with r(t) ≈ 1 hovering around its threshold value.BMTF “Mathematical Modeling Applied to Health” Project European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 79249

Electronic structure changes of Si(001)-(2x1) from subsurface Mn observed by STM

The deposition of Mn atoms onto the Si(001)-(2x1) reconstructed surface has been studied using scanning tunneling microscopy (STM) and first-principles electronic structure calculations. Room-temperature deposition of 0.1 ML (monolayer) of Mn gives rise to a disordered surface structure. After in situ annealing between 300 and 700 °C, most of the Mn is incorporated into three-dimensional manganese silicide islands, and Si dimer rows reappear in the STM images on most of the substrate surface. At the same time, rowlike structures are visible in the atomic-scale STM images. A comparison with calculated STM images provides evidence that Mn atoms are incorporated into the row structures in subsurface interstitial sites, which are the lowest-energy position for Mn on Si(001). The subsurface Mn alters the height and local density of states of the Si dimer atoms, causing them to appear 0.6 Å higher than a neighboring Si dimer with no Mn below. This height difference that allows the detection the subsurface Mn results from a subtle interplay of geometrical and electronic effects

Changes in Social and Clinical Determinants of COVID-19 Outcomes Achieved by the Vaccination Program: A Nationwide Cohort Study

Background: The objective of this study was to assess changes in social and clinical determinants of COVID-19 outcomes associated with the first year of COVID-19 vaccination rollout in the Basque population. Methods: A retrospective study was performed using the complete database of the Basque Health Service (n = 2,343,858). We analyzed data on age, sex, socioeconomic status, the Charlson comorbidity index (CCI), hospitalization and intensive care unit (ICU) admission, and COVID-19 infection by Cox regression models and Kaplan–Meier curves. Results: Women had a higher hazard ratio (HR) of infection (1.1) and a much lower rate of hospitalization (0.7). With older age, the risk of infection fell, but the risks of hospitalization and ICU admission increased. The higher the CCI, the higher the risks of infection and hospitalization. The risk of infection was higher in high-income individuals in all periods (HR = 1.2–1.4) while their risk of hospitalization was lower in the post-vaccination period (HR = 0.451). Conclusion: Despite the lifting of many control measures during the second half of 2021, restoring human mobility patterns, the situation could not be defined as syndemic, clinical determinants seeming to have more influence than social ones on COVID-19 outcomes, both before and after vaccination program implementation