Acute respiratory distress syndrome in patients with COVID-19 vs. Non-COVID-19: clinical characteristics and outcomes in a tertiary care setting in Mexico City.

BACKGROUND: Acute Respiratory Distress Syndrome (ARDS) due tocoronavirus disease (COVID-19) infection has a unique phenotype generating a growing need to determine the existing differences that can alter existing evidence-based management strategies for ARDS. RESEARCH QUESTION: What differences does the clinical profile of patients with ARDS due to COVID 19 and Non-COVID 19 have? STUDY DESIGN AND METHODS: We conducted a comparative, observational, retrospective study in the Intensive Care Unit (ICU)of a third-level hospital in Mexico City, from March 2020 through March 2022. Clinical, echocardiographic, and laboratory variables were compared between patients with ARDS due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and those due to other etiologies. RESULTS: We enrolled 140 patients with a diagnosis of ARDS. The study group of COVID-19 etiology were younger males, higher body mass index, progressed to organ dysfunction, required more frequently renal replacement therapy, and higher SOFA score. There was no difference in rates of right ventricular dysfunction. INTERPRETATION: COVID-19 ARDS exhibit much greater severity that led to higher admission and mortality rates, whilst being younger and less comorbid.

Clinical Decision-making for Continuous Positive Airway Pressure Mask Selection.

Continuous positive airway pressure is the gold standard treatment for obstructive sleep apnea. Different interfaces with distinct characteristics, advantages, and disadvantages are available, which may influence long-term adherence. Oronasal masks have been increasingly used. However, recent evidence suggest that nasal masks are more effective when continuous positive airway pressure is used to treat obstructive sleep apnea. The main objective of this review is to describe the basis for the selection of the interface for the treatment of obstructive sleep apnea with continuous positive airway pressure.

Inq, a Modern GPU-Accelerated Computational Framework for (Time-Dependent) Density Functional Theory.

We present inq, a new implementation of density functional theory (DFT) and time-dependent DFT (TDDFT) written from scratch to work on graphic processing units (GPUs). Besides GPU support, inq makes use of modern code design features and takes advantage of newly available hardware. By designing the code around algorithms, rather than against specific implementations and numerical libraries, we aim to provide a concise and modular code. The result is a fairly complete DFT/TDDFT implementation in roughly 12 000 lines of open-source C++ code representing a modular platform for community-driven application development on emerging high-performance computing architectures.

Octopus, a computational framework for exploring light-driven phenomena and quantum dynamics in extended and finite systems.

Over the last few years, extraordinary advances in experimental and theoretical tools have allowed us to monitor and control matter at short time and atomic scales with a high degree of precision. An appealing and challenging route toward engineering materials with tailored properties is to find ways to design or selectively manipulate materials, especially at the quantum level. To this end, having a state-of-the-art ab initio computer simulation tool that enables a reliable and accurate simulation of light-induced changes in the physical and chemical properties of complex systems is of utmost importance. The first principles real-space-based Octopus project was born with that idea in mind, i.e., to provide a unique framework that allows us to describe non-equilibrium phenomena in molecular complexes, low dimensional materials, and extended systems by accounting for electronic, ionic, and photon quantum mechanical effects within a generalized time-dependent density functional theory. This article aims to present the new features that have been implemented over the last few years, including technical developments related to performance and massive parallelism. We also describe the major theoretical developments to address ultrafast light-driven processes, such as the new theoretical framework of quantum electrodynamics density-functional formalism for the description of novel light-matter hybrid states. Those advances, and others being released soon as part of the Octopus package, will allow the scientific community to simulate and characterize spatial and time-resolved spectroscopies, ultrafast phenomena in molecules and materials, and new emergent states of matter (quantum electrodynamical-materials).

Trends and Inpatient Outcomes of Venous Thromboembolism-Related Admissions in Patients with Philadelphia-Negative Myeloproliferative Neoplasms.

Background Patients with Philadelphia-negative myeloproliferative neoplasms (MPNs), including polycythemia vera (PV), essential thrombocytosis (ET), and primary myelofibrosis (MF), have a significant risk of venous thromboembolism (VTE). We aim to determine the trends in annual rates of VTE-related admissions, associated cost, length of stay (LOS), and in-hospital mortality in patients with MPN. Methods We identified patients with PV, ET, and MF from the Nationwide Inpatient Sample (NIS) database from 2006 to 2014 using ICD-9CM coding. Hospitalizations where VTE was among the top-three diagnoses were considered VTE-related. We compared in-hospital outcomes between VTE and non-VTE hospitalizations using chi-square and Mann-Whitney U -test and used linear regression for trend analysis. Results We identified 1,046,666 admissions with a diagnosis of MPN. Patients were predominantly white (65.6%), females (52.7%), with a median age of 66 years (range: 18-108). The predominant MPN was ET (54%). There was no difference in in-hospital mortality between groups (VTE: 3.4% vs. non-VTE: 3.2%; p = 0.12); however, VTE admissions had a longer LOS (median: 6 vs. 5 days; p < 0.01) and higher cost (median: VTE US$32,239 vs. 28,403; p ≤ 0.01). The annual rate of VTE admissions decreased over time (2006: 3.94% vs. 2014: 2.43%; p ≤ 0.01), compared with non-VTE-related admissions. Conclusion In our study, VTE-related admissions had similar in-hospital mortality as compared with non-VTE-related admissions. The rates of hospitalizations due to VTE have decreased over time but are associated with a higher cost and LOS. Newer risk assessment tools may assist in preventing VTE in high-risk patients and optimizing resource utilization.

Primary Liver Diffuse Large B-Cell Lymphoma following Complete Response for Hepatitis C Infection after Direct Antiviral Therapy.

INTRODUCTION: Hepatitis C infection is highly prevalent worldwide and has a well-known association with B-cell lymphoid malignancies. Antiviral therapy has successfully decreased the rate of liver cirrhosis and improved the outcome in patients with hepatitis C-associated lymphomas. However, although there are a few case reports of aggressive lymphomas after successful hepatitis C therapy, the mechanism behind this association remains unclear. CASE PRESENTATION: We present the case of a 55-year-old man with chronic hepatitis C infection and liver cirrhosis who received antiviral therapy with sofosbuvir and ribavirin and achieved a sustained complete virological response. One year after successful therapy, there was an unexplained decline of his liver function and atypical liver nodularity, which led to the diagnosis of a primary liver diffuse large B-cell lymphoma. DISCUSSION: We review the evidence supporting possible mechanisms of lymphomagenesis after successful hepatitis C therapy, particularly involving late "second-hit" mutations after viral-induced DNA damage and antiviral therapy facilitating the emergence of latent malignant B-cell clones by decreasing local inflammation and immune surveillance. More reports may help elucidate any association between hepatitis C antiviral therapy and late lymphoid malignancies.

Validation of a Patient-Completed Caprini Risk Assessment Tool for Spanish, Arabic, and Polish Speakers.

Targeted prophylaxis for venous thromboembolism (VTE) using the Caprini risk score (CRS) is effective reducing postoperative VTE. Despite its availability as preventive strategy, risk scoring remains underutilized. Critics to the CRS contend the time it takes to complete, and its limitation to English language. Aim is to create and validate patient-completed CRS tools for Spanish, Arabic, and Polish speakers. We translated the first patient-completed CRS to Spanish, Arabic, and Polish. We conducted a pilot study followed by the validation study. Using PASS version 11, we determined that a sample size of 37 achieved a power of 80%, to detect a difference of 0.1 between the null hypothesis correlation of 0.5 and the alternative hypothesis correlation of 0.7 using a 2-sided hypothesis test, significance level of .05. We tabulated and categorized scores using SPSS version 23 to estimate κ, linear correlation, and Bland Altman test. κ value >0.8 was defined as "almost perfect agreement." From 129 recruited patients, 50 (39%) spoke Spanish, 40 (31%) spoke Arabic, and 39 (30%) spoke Polish; average age 51 (16.69) years, 58 (45%) were men, with less than college education (67%). Mean (standard deviation) CRS was 5 (3.90), the majority (63%) above moderate VTE risk. We report excellent agreement comparing physician and patient results (κ = 0.93) and high correlation 0.97 ( P < .01) for the overall score. Bland Altman did not show trend for extreme values. We created and validated the first Spanish, Arabic, and Polish versions of the patient-completed CRS, with excellent correlation and agreement when compared to CRS-trained physician-completed form. Based on these results, the physician needs to calculate the body mass index. Completing the form was not time-consuming.

Insights into colour-tuning of chlorophyll optical response in green plants.

First-principles calculations within the framework of real-space time-dependent density functional theory have been performed for the complete chlorophyll (Chl) network of the light-harvesting complex from green plants, LHC-II. A local-dipole analysis method developed for this work has made possible the studies of the optical response of individual Chl molecules subjected to the influence of the remainder of the chromophore network. The spectra calculated using our real-space TDDFT method agree with previous suggestions that weak interaction with the protein microenvironment should produce only minor changes in the absorption spectrum of Chl chromophores in LHC-II. In addition, relative shifting of Chl absorption energies leads the stromal and lumenal sides of LHC-II to absorb in slightly different parts of the visible spectrum providing greater coverage of the available light frequencies. The site-specific alterations in Chl excitation energies support the existence of intrinsic energy transfer pathways within the LHC-II complex.

Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems.

Real-space grids are a powerful alternative for the simulation of electronic systems. One of the main advantages of the approach is the flexibility and simplicity of working directly in real space where the different fields are discretized on a grid, combined with competitive numerical performance and great potential for parallelization. These properties constitute a great advantage at the time of implementing and testing new physical models. Based on our experience with the Octopus code, in this article we discuss how the real-space approach has allowed for the recent development of new ideas for the simulation of electronic systems. Among these applications are approaches to calculate response properties, modeling of photoemission, optimal control of quantum systems, simulation of plasmonic systems, and the exact solution of the Schrödinger equation for low-dimensionality systems.

Compressed Sensing for the Fast Computation of Matrices: Application to Molecular Vibrations.

This article presents a new method to compute matrices from numerical simulations based on the ideas of sparse sampling and compressed sensing. The method is useful for problems where the determination of the entries of a matrix constitutes the computational bottleneck. We apply this new method to an important problem in computational chemistry: the determination of molecular vibrations from electronic structure calculations, where our results show that the overall scaling of the procedure can be improved in some cases. Moreover, our method provides a general framework for bootstrapping cheap low-accuracy calculations in order to reduce the required number of expensive high-accuracy calculations, resulting in a significant 3× speed-up in actual calculations.

A survey of the parallel performance and accuracy of Poisson solvers for electronic structure calculations.

We present an analysis of different methods to calculate the classical electrostatic Hartree potential created by charge distributions. Our goal is to provide the reader with an estimation on the performance-in terms of both numerical complexity and accuracy-of popular Poisson solvers, and to give an intuitive idea on the way these solvers operate. Highly parallelizable routines have been implemented in a first-principle simulation code (Octopus) to be used in our tests, so that reliable conclusions about the capability of methods to tackle large systems in cluster computing can be obtained from our work.

Real-Space Density Functional Theory on Graphical Processing Units: Computational Approach and Comparison to Gaussian Basis Set Methods.

We discuss the application of graphical processing units (GPUs) to accelerate real-space density functional theory (DFT) calculations. To make our implementation efficient, we have developed a scheme to expose the data parallelism available in the DFT approach; this is applied to the different procedures required for a real-space DFT calculation. We present results for current-generation GPUs from AMD and Nvidia, which show that our scheme, implemented in the free code Octopus, can reach a sustained performance of up to 90 GFlops for a single GPU, representing a significant speed-up when compared to the CPU version of the code. Moreover, for some systems, our implementation can outperform a GPU Gaussian basis set code, showing that the real-space approach is a competitive alternative for DFT simulations on GPUs.

Application of compressed sensing to the simulation of atomic systems.

Compressed sensing is a method that allows a significant reduction in the number of samples required for accurate measurements in many applications in experimental sciences and engineering. In this work, we show that compressed sensing can also be used to speed up numerical simulations. We apply compressed sensing to extract information from the real-time simulation of atomic and molecular systems, including electronic and nuclear dynamics. We find that, compared to the standard discrete Fourier transform approach, for the calculation of vibrational and optical spectra the total propagation time, and hence the computational cost, can be reduced by approximately a factor of five.

Time-dependent density-functional theory in massively parallel computer architectures: the OCTOPUS project.

Octopus is a general-purpose density-functional theory (DFT) code, with a particular emphasis on the time-dependent version of DFT (TDDFT). In this paper we present the ongoing efforts to achieve the parallelization of octopus. We focus on the real-time variant of TDDFT, where the time-dependent Kohn-Sham equations are directly propagated in time. This approach has great potential for execution in massively parallel systems such as modern supercomputers with thousands of processors and graphics processing units (GPUs). For harvesting the potential of conventional supercomputers, the main strategy is a multi-level parallelization scheme that combines the inherent scalability of real-time TDDFT with a real-space grid domain-partitioning approach. A scalable Poisson solver is critical for the efficiency of this scheme. For GPUs, we show how using blocks of Kohn-Sham states provides the required level of data parallelism and that this strategy is also applicable for code optimization on standard processors. Our results show that real-time TDDFT, as implemented in octopus, can be the method of choice for studying the excited states of large molecular systems in modern parallel architectures.

Compressed Sensing for Multidimensional Spectroscopy Experiments.

Compressed sensing is a processing method that significantly reduces the number of measurements needed to accurately resolve signals in many fields of science and engineering. We develop a two-dimensional variant of compressed sensing for multidimensional spectroscopy and apply it to experimental data. For the model system of atomic rubidium vapor, we find that compressed sensing provides an order-of-magnitude (about 10-fold) improvement in spectral resolution along each dimension, as compared to a conventional discrete Fourier transform, using the same data set. More attractive is that compressed sensing allows for random undersampling of the experimental data, down to less than 5% of the experimental data set, with essentially no loss in spectral resolution. We believe that by combining powerful resolution with ease of use, compressed sensing can be a powerful tool for the analysis and interpretation of ultrafast spectroscopy data.

Prediction of the derivative discontinuity in density functional theory from an electrostatic description of the exchange and correlation potential.

We propose an approach to approximate the exchange and correlation (XC) term in density functional theory. The XC potential is considered as an electrostatic potential, generated by a fictitious XC density, which is in turn a functional of the electronic density. We apply the approach to develop a correction scheme that fixes the asymptotic behavior of any approximated XC potential for finite systems. Additionally, the correction procedure gives the value of the XC derivative discontinuity; therefore, it can directly predict the fundamental gap as a ground-state property.

Basis set effects on the hyperpolarizability of CHCl3: Gaussian-type orbitals, numerical basis sets and real-space grids.

Calculations of the hyperpolarizability are typically much more difficult to converge with basis set size than the linear polarizability. In order to understand these convergence issues and hence obtain accurate ab initio values, we compare calculations of the static hyperpolarizability of the gas-phase chloroform molecule (CHCl(3)) using three different kinds of basis sets: Gaussian-type orbitals, numerical basis sets, and real-space grids. Although all of these methods can yield similar results, surprisingly large, diffuse basis sets are needed to achieve convergence to comparable values. These results are interpreted in terms of local polarizability and hyperpolarizability densities. We find that the hyperpolarizability is very sensitive to the molecular structure, and we also assess the significance of vibrational contributions and frequency dispersion.

Towards a gauge invariant method for molecular chiroptical properties in TDDFT.

We present an efficient scheme to calculate the chiroptical response of molecular systems within time dependent density functional theory using either a real-time propagation or a frequency-dependent Sternheimer method. The scheme avoids the commonly used sum over empty orbitals and has a very favorable scaling with system size. Moreover, the method is general and can be easily implemented. In the present work, we implemented it using a real-space pseudo-potential representation of the wave-functions and Hamiltonian. The specific use of non-local pseudo-potentials implies that a gauge correction term in the angular momentum operator must be included to ensure that the total scheme is fully gauge invariant. Applications to small organic chiral molecules are shown and discussed, addressing some deficiencies of present exchange-correlation functionals to describe the absolute position of the excitations. However, the shape or sign of the dichroism spectra comes out in excellent agreement with available experiments.

Optical and magnetic properties of boron fullerenes.

We report linear response properties of the recently proposed boron fullerenes [N. Gonzalez Szwacki et al., Phys. Rev. Lett., 2007, 98, 166804]: magnetic susceptibilities, static dipole polarizabilities and dynamical polarizabilities (i.e. optical and near ultraviolet absorption spectra), calculated from first principles within the (time-dependent) density-functional theory framework. We find that all clusters except B80 are diamagnetic. The strong cancellation between diamagnetic and paramagnetic currents in B80 leads to a very small value for its susceptibility that turns out to be slightly paramagnetic. Static polarizabilities increase linearly with the number of B atoms. Furthermore, the absorption spectrum of B80 is very different from the one of its carbon counterpart C60, exhibiting a low absorption threshold of about 1.5 eV and many peaks in the visible and near ultraviolet. This can be understood by the analysis of the wavefunctions involved in the low energy transitions.

Modified Ehrenfest Formalism for Efficient Large-Scale ab initio Molecular Dynamics.

We present in detail the recently derived ab initio molecular dynamics (AIMD) formalism [Alonso et al. Phys. Rev. Lett. 2008, 101, 096403], which due to its numerical properties, is ideal for simulating the dynamics of systems containing thousands of atoms. A major drawback of traditional AIMD methods is the necessity to enforce the orthogonalization of the wave functions, which can become the bottleneck for very large systems. Alternatively, one can handle the electron-ion dynamics within the Ehrenfest scheme where no explicit orthogonalization is necessary, however the time step is too small for practical applications. Here we preserve the desirable properties of Ehrenfest in a new scheme that allows for a considerable increase of the time step while keeping the system close to the Born-Oppenheimer surface. We show that the automatically enforced orthogonalization is of fundamental importance for large systems because not only it improves the scaling of the approach with the system size but it also allows for an additional very efficient parallelization level. In this work, we provide the formal details of the new method, describe its implementation, and present some applications to some test systems. Comparisons with the widely used Car-Parrinello molecular dynamics method are made, showing that the new approach is advantageous above a certain number of atoms in the system. The method is not tied to a particular wave function representation, making it suitable for inclusion in any AIMD software package.