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This cross-sectional multicenter study was performed aimed at describing the clinical characteristics of women with COPD attended in routine daily practice in Spain. Of a total of 1610 consecutive patients diagnosed with COPD recruited in primary care centers and pneumology services throughout Spain over a 90-day period, 17.9% (n=286) were women, with a median age of 62 years. Differences in COPD phenotypes by sex were statistically significant ( = 0.002). Males as compared with females showed a higher prevalence of non-exacerbator (47.9% vs 42.2%) and exacerbator with chronic bronchitis (22.9% vs 18.8%) phenotypes, whereas the ACOS phenotype was more common among females (21.7% vs 12.9%). The mean (SD) CAT score was similar in men than in women (20.8 [9.0] vs 21.2 [8.7], = 0.481), as well as the impact of the disease on the quality of life according to CAT scores of <5 (no impact), 5-9 (low), 10-20 (medium), >20 (high), and >30 (very high). Sex-related differences according to smoking status were statistically significant ( < 0.001), with a higher percentage of men as compared with women in the groups of current smokers and ex-smokers; never-smokers were higher in women (9.1%) than in men (0.6%). The mean number of comorbidities was 2.01 (1.43) (95% CI 1.93-2.09) in males and 1.99 (1.42) (95% CI 1.83-2.16) ( = 0.930) in females, but cardiovascular diseases (hypertension, ischemic heart disease, chronic heart failure) were more frequent in men, whereas metabolic disorders (osteoporosis) were more frequent in women. This study highlights the impact of COPD in women and the importance of continuing sex-based research in tobacco-related respiratory diseases.

COPD assessment test (CAT) is a short, easy-to-complete health status tool that has been incorporated into the multidimensional assessment of COPD in order to guide therapy; therefore, it is important to understand the factors determining CAT scores. This is a post hoc analysis of a cross-sectional, observational study conducted in respiratory medicine departments and primary care centers in Spain with the aim of identifying the factors determining CAT scores, focusing particularly on the cognitive status measured by the Mini-Mental State Examination (MMSE) and levels of depression measured by the short Beck Depression Inventory (BDI). A total of 684 COPD patients were analyzed; 84.1% were men, the mean age of patients was 68.7 years, and the mean forced expiratory volume in 1 second (%) was 55.1%. Mean CAT score was 21.8. CAT scores correlated with the MMSE score (Pearson's coefficient =-0.371) and the BDI ( =0.620), both <0.001. In the multivariate analysis, the usual COPD severity variables (age, dyspnea, lung function, and comorbidity) together with MMSE and BDI scores were significantly associated with CAT scores and explained 45% of the variability. However, a model including only MMSE and BDI scores explained up to 40% and BDI alone explained 38% of the CAT variance. CAT scores are associated with clinical variables of severity of COPD. However, cognitive status and, in particular, the level of depression explain a larger percentage of the variance in the CAT scores than the usual COPD clinical severity variables.

The purpose of this study was to assess the prevalence of COPD phenotypes at a national level and to determine their geographic distribution among different autonomous communities in Spain. A total of 1,610 patients (82% men, median age 67 years) recruited in primary care centers and pneumology services participated in an observational, cross-sectional, and multicenter study. Phenotypes evaluated were the non-exacerbator phenotype, the asthma-COPD overlap syndrome (ACOS), the exacerbator phenotype with emphysema, and the exacerbator phenotype with chronic bronchitis. The non-exacerbator phenotype was the most common (46.7%) followed by exacerbator with chronic bronchitis (22.4%) and exacerbator with emphysema (16.4%). The ACOS phenotype accounted for the lowest rate (14.5%). For each phenotype, the highest prevalence rates were concentrated in two or three autonomous communities, with relatively similar rates for the remaining regions. Overall prevalence rates were higher for the non-exacerbator and the exacerbator with chronic bronchitis phenotypes than for ACOS and the exacerbator with chronic bronchitis phenotypes. Differences in the distribution of COPD phenotypes according to gender, age, physician specialty, smoking habit, number of comorbidities, quality of life assessed with the COPD Assessment Test, and BODEx index (body mass index, airflow obstruction, dyspnea, and exacerbations) were all statistically significant. Differences in the prevalence rates of COPD phenotypes among the Spanish autonomous communities have been documented. Mapping the distribution of COPD phenotypes is useful to highlight regional differences as starting point for comparisons across time. This geographic analysis provides health-care planners a valuable platform to assess changes in COPD burden at nationwide and regional levels.

Smoking can affect both the phenotypic expression of COPD and factors such as disease severity, quality of life, and comorbidities. Our objective was to evaluate if the impact of active smoking on these factors varies according to the disease phenotype. This was a Spanish, observational, cross-sectional, multicenter study of patients with a diagnosis of COPD. Smoking rates were described among four different phenotypes (non-exacerbators, asthma-COPD overlap syndrome [ACOS], exacerbators with emphysema, and exacerbators with chronic bronchitis), and correlated with disease severity (body mass index, obstruction, dyspnea and exacerbations [BODEx] index and dyspnea grade), quality of life according to the COPD assessment test (CAT), and presence of comorbidities, according to phenotypic expression. In total, 1,610 patients were recruited, of whom 46.70% were classified as non-exacerbators, 14.53% as ACOS, 16.37% as exacerbators with emphysema, and 22.40% as exacerbators with chronic bronchitis. Smokers were predominant in the latter 2 groups (58.91% and 57.67%, respectively, =0.03). Active smoking was significantly associated with better quality of life and a higher dyspnea grade, although differences were observed depending on clinical phenotype. Active smoking is more common among exacerbator phenotypes and appears to affect quality of life and dyspnea grade differently, depending on the clinical expression of the disease.

Background: COPD assessment test (CAT) is a short, easy-to-complete health status tool that has been incorporated into the multidimensional assessment of COPD in order to guide therapy; therefore, it is important to understand the factors determining CAT scores. Methods: This is a post hoc analysis of a cross-sectional, observational study conducted in respiratory medicine departments and primary care centers in Spain with the aim of identifying the factors determining CAT scores, focusing particularly on the cognitive status measured by the Mini-Mental State Examination (MMSE) and levels of depression measured by the short Beck Depression Inventory (BDI). Results: A total of 684 COPD patients were analyzed; 84.1% were men, the mean age of patients was 68.7 years, and the mean forced expiratory volume in 1 second (%) was 55.1%. Mean CAT score was 21.8. CAT scores correlated with the MMSE score (Pearson's coefficient r=-0.371) and the BDI (r=0.620), both p<0.001. In the multivariate analysis, the usual COPD severity variables (age, dyspnea, lung function, and comorbidity) together with MMSE and BDI scores were significantly associated with CAT scores and explained 45% of the variability. However, a model including only MMSE and BDI scores explained up to 40% and BDI alone explained 38% of the CAT variance. Conclusion: CAT scores are associated with clinical variables of severity of COPD. However, cognitive status and, in particular, the level of depression explain a larger percentage of the variance in the CAT scores than the usual COPD clinical severity variables. Keywords: COPD, CAT, Mini-Mental State Examination, MMSE, Beck Depression Inventory, BDI

Atmospheric marine aerosol particles impact Earth's albedo and climate. These particles can be primary or secondary and come from a variety of sources, including sea salt, dissolved organic matter, volatile organic compounds, and sulfur-containing compounds. Dimethylsulfide (DMS) marine emissions contribute greatly to the global biogenic sulfur budget, and its oxidation products can contribute to aerosol mass, specifically as sulfuric acid and methanesulfonic acid (MSA). Further, sulfuric acid is a known nucleating compound, and MSA may be able to participate in nucleation when bases are available. As DMS emissions, and thus MSA and sulfuric acid from DMS oxidation, may have changed since pre-industrial times and may change in a warming climate, it is important to characterize and constrain the climate impacts of both species. Currently, global models that simulate aerosol size distributions include contributions of sulfate and sulfuric acid from DMS oxidation, but to our knowledge, global models typically neglect the impact of MSA on size distributions. In this study, we use the GEOS-Chem-TOMAS (GC-TOMAS) global aerosol microphysics model to determine the impact on aerosol size distributions and subsequent aerosol radiative effects from including MSA in the size-resolved portion of the model. The effective equilibrium vapor pressure of MSA is currently uncertain, and we use the Extended Aerosol Inorganics Model (E-AIM) to build a parameterization for GC-TOMAS of MSA's effective volatility as a function of temperature, relative humidity, and available gas-phase bases, allowing MSA to condense as an ideally nonvolatile or semivolatile species or too volatile to condense. We also present two limiting cases for MSA's volatility, assuming that MSA is always ideally nonvolatile (irreversible condensation) or that MSA is always ideally semivolatile (quasi-equilibrium condensation but still irreversible condensation). We further present simulations in which MSA participates in binary and ternary nucleation with the same efficacy as sulfuric acid whenever MSA is treated as ideally nonvolatile. When using the volatility parameterization described above (both with and without nucleation), including MSA in the model changes the global annual averages at 900 hPa of submicron aerosol mass by 1.2 %, N3 (number concentration of particles greater than 3 nm in diameter) by −3.9 % (non-nucleating) or 112.5 % (nucleating), N80 by 0.8 % (non-nucleating) or 2.1 % (nucleating), the cloud-albedo aerosol indirect effect (AIE) by −8.6 mW m−2 (non-nucleating) or −26 mW m−2 (nucleating), and the direct radiative effect (DRE) by −15 mW m−2 (non-nucleating) or −14 mW m−2 (nucleating). The sulfate and sulfuric acid from DMS oxidation produces 4–6 times more submicron mass than MSA does, leading to an ∼10 times stronger cooling effect in the DRE. But the changes in N80 are comparable between the contributions from MSA and from DMS-derived sulfate/sulfuric acid, leading to comparable changes in the cloud-albedo AIE. Model–measurement comparisons with the Heintzenberg et al. (2000) dataset over the Southern Ocean indicate that the default model has a missing source or sources of ultrafine particles: the cases in which MSA participates in nucleation (thus increasing ultrafine number) most closely match the Heintzenberg distributions, but we cannot conclude nucleation from MSA is the correct reason for improvement. Model–measurement comparisons with particle-phase MSA observed with a customized Aerodyne high-resolution time-of-flight aerosol mass spectrometer (AMS) from the ATom campaign show that cases with the MSA volatility parameterizations (both with and without nucleation) tend to fit the measurements the best (as this is the first use of MSA measurements from ATom, we provide a detailed description of these measurements and their calibration). However, no one model sensitivity case shows the best model–measurement agreement for both Heintzenberg and the ATom campaigns. As there are uncertainties in both MSA's behavior (nucleation and condensation) and the DMS emissions inventory, further studies on both fronts are needed to better constrain MSA's past, current, and future impacts upon the global aerosol size distribution and radiative forcing.

Native mass spectrometry (native-MS) of membrane proteins typically requires a detergent screening protocol, protein solubilization in the preferred detergent, followed by protein liberation from the micelle by collisional activation. Here, submicrometer nano-ESI emitter tips are used for native-MS of membrane proteins solubilized in both nonionic and ionic detergent solutions. With the submicrometer nano-ESI emitter tips, resolved charge-state distributions of membrane protein ions are obtained from a 150 mM NaCl, 25 mM Tris-HCl with 1.1% octyl glucoside solution. The relative abundances of NaCl and detergent cluster ions at high m  / z are significantly reduced with the submicrometer emitters compared with larger nano-ESI emitters that are commonly used. This technique is beneficial for significantly decreasing the abundances (by two to three orders of magnitude compared with the larger tip size: 1.6 μm) of detergent cluster ions formed from aqueous ammonium acetate solutions containing detergents that can overlap with the membrane protein ion signal. Resolved charge-state distributions of membrane protein ions from aqueous ammonium acetate solutions containing ionic detergents were obtained with the submicrometer nano-ESI emitters; this is the first report of native-MS of membrane proteins solubilized by ionic detergents. Graphical Abstract

Sudden cardiac death poses a unique challenge to clinicians because it may be the only symptom of an inherited heart condition. Indeed, inherited heart diseases can cause sudden cardiac death in older and younger individuals. Two groups of familial diseases are responsible for sudden cardiac death: cardiomyopathies (mainly hypertrophic cardiomyopathy, dilated cardiomyopathy, and arrhythmogenic cardiomyopathy) and channelopathies (mainly long QT syndrome, Brugada syndrome, short QT syndrome, and catecholaminergic polymorphic ventricular tachycardia). This review focuses on cardiac channelopathies, which are characterized by lethal arrhythmias in the structurally normal heart, incomplete penetrance, and variable expressivity. Arrhythmias in these diseases result from pathogenic variants in genes encoding cardiac ion channels or associated proteins. Due to a lack of gross structural changes in the heart, channelopathies are often considered as potential causes of death in otherwise unexplained forensic autopsies. The asymptomatic nature of channelopathies is cause for concern in family members who may be carrying genetic risk factors, making the identification of these genetic factors of significant clinical importance.

The study of the preparation phase of large earthquakes is essential to understand the physical processes involved, and potentially useful also to develop a future reliable short-term warning system. Here we analyse electron density and magnetic field data measured by Swarm three-satellite constellation for 4.7 years, to look for possible in-situ ionospheric precursors of large earthquakes to study the interactions between the lithosphere and the above atmosphere and ionosphere, in what is called the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC). We define these anomalies statistically in the whole space-time interval of interest and use a Worldwide Statistical Correlation (WSC) analysis through a superposed epoch approach to study the possible relation with the earthquakes. We find some clear concentrations of electron density and magnetic anomalies from more than two months to some days before the earthquake occurrences. Such anomaly clustering is, in general, statistically significant with respect to homogeneous random simulations, supporting a LAIC during the preparation phase of earthquakes. By investigating different earthquake magnitude ranges, not only do we confirm the well-known Rikitake empirical law between ionospheric anomaly precursor time and earthquake magnitude, but we also give more reliability to the seismic source origin for many of the identified anomalies.

Sudden unexplained death may be the first manifestation of an unknown inherited cardiac disease. Current genetic technologies may enable the unraveling of an etiology and the identification of relatives at risk. The aim of our study was to define the etiology of natural deaths, younger than 50 years of age, and to investigate whether genetic defects associated with cardiac diseases could provide a potential etiology for the unexplained cases. Our cohort included a total of 789 consecutive cases (77.19% males) <50 years old (average 38.6±12.2 years old) who died suddenly from non-violent causes. A comprehensive autopsy was performed according to current forensic guidelines. During autopsy a cause of death was identified in most cases (81.1%), mainly due to cardiac alterations (56.87%). In unexplained cases, genetic analysis of the main genes associated with sudden cardiac death was performed using Next Generation Sequencing technology. Genetic analysis was performed in suspected inherited diseases (cardiomyopathy) and in unexplained death, with identification of potentially pathogenic variants in nearly 50% and 40% of samples, respectively. Cardiac disease is the most important cause of sudden death, especially after the age of 40. Close to 10% of cases may remain unexplained after a complete autopsy investigation. Molecular autopsy may provide an explanation for a significant part of these unexplained cases. Identification of genetic variations enables genetic counseling and undertaking of preventive measures in relatives at risk.