Severe asthma: One disease and multiple definitions

Introduction: There is, so far, no universal definition of severe asthma. This definition usually relies on: number of exacerbations, inhaled therapy, need for oral corticosteroids, and respiratory function. The use of such parameters varies in the different definitions used. Thus, according to the parameters chosen, each patient may result in having severe asthma or not. The aim of this study was to evaluate how the choice of a specific definition of severe asthma can change the allocation of patients. Methods: Data collected from the Severe Asthma Network Italy (SANI) registry were analyzed. All the patients included were then reclassified according to the definitions of U-BIOPRED, NICE, WHO, ATS/ERS, GINA, ENFUMOSA, and TENOR. Results: 540 patients, were extracted from the SANI database. We observed that 462 (86%) met the ATS/ERS criteria as well as the GINA criteria, 259 (48%) the U-Biopred, 222 (41%) the NICE, 125 (23%) the WHO, 313 (58%) the Enfumosa, and 251 (46%) the TENOR criteria. The mean eosinophil value were similar in the ATS/ERS, U-Biopred, and Enfumosa (528, 532 and 516 cells/mcl), higher in WHO and Tenor (567 and 570 cells/mcl) and much higher in the NICE classification (624 cells/mcl). Lung function tests resulted similarly in all groups, with WHO (67%) and ATS/ERS-GINA (73%), respectively, showing the lower and upper mean FEV1 values. Conclusions: The present observations clearly evidence the heterogeneity in the distribution of patients when different definitions of severe asthma are used. However, the recent definition of severe asthma, provided by the GINA document, is similar to that indicated in 2014 by ATS/ERS, allowing mirror reclassification of the patients examined. This lack of homogeneity could complicate the access to biological therapies. The definition provided by the GINA document, which reflects what suggested by ATS/ERS, could partially overcome the problem

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: A systematic analysis for the Global Burden of Disease Study 2015

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods: We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings: Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation: Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding: Bill & Melinda Gates Foundation

Scintillator ageing of the T2K near detectors from 2010 to 2021

The T2K experiment widely uses plastic scintillator as a target for neutrino interactions and an active medium for the measurement of charged particles produced in neutrino interactions at its near detector complex. Over 10 years of operation the measured light yield recorded by the scintillator based subsystems has been observed to degrade by 0.9–2.2% per year. Extrapolation of the degradation rate through to 2040 indicates the recorded light yield should remain above the lower threshold used by the current reconstruction algorithms for all subsystems. This will allow the near detectors to continue contributing to important physics measurements during the T2K-II and Hyper-Kamiokande eras. Additionally, work to disentangle the degradation of the plastic scintillator and wavelength shifting fibres shows that the reduction in light yield can be attributed to the ageing of the plastic scintillator. The long component of the attenuation length of the wavelength shifting fibres was observed to degrade by 1.3–5.4% per year, while the short component of the attenuation length did not show any conclusive degradation

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Severe asthma: One disease and multiple definitions

123noopenIntroduction: There is, so far, no universal definition of severe asthma. This definition usually relies on: number of exacerbations, inhaled therapy, need for oral corticosteroids, and respiratory function. The use of such parameters varies in the different definitions used. Thus, according to the parameters chosen, each patient may result in having severe asthma or not. The aim of this study was to evaluate how the choice of a specific definition of severe asthma can change the allocation of patients. Methods: Data collected from the Severe Asthma Network Italy (SANI) registry were analyzed. All the patients included were then reclassified according to the definitions of U-BIOPRED, NICE, WHO, ATS/ERS, GINA, ENFUMOSA, and TENOR. Results: 540 patients, were extracted from the SANI database. We observed that 462 (86%) met the ATS/ERS criteria as well as the GINA criteria, 259 (48%) the U-Biopred, 222 (41%) the NICE, 125 (23%) the WHO, 313 (58%) the Enfumosa, and 251 (46%) the TENOR criteria. The mean eosinophil value were similar in the ATS/ERS, U-Biopred, and Enfumosa (528, 532 and 516 cells/mcl), higher in WHO and Tenor (567 and 570 cells/mcl) and much higher in the NICE classification (624 cells/mcl). Lung function tests resulted similarly in all groups, with WHO (67%) and ATS/ERS-GINA (73%), respectively, showing the lower and upper mean FEV1 values. Conclusions: The present observations clearly evidence the heterogeneity in the distribution of patients when different definitions of severe asthma are used. However, the recent definition of severe asthma, provided by the GINA document, is similar to that indicated in 2014 by ATS/ERS, allowing mirror reclassification of the patients examined. This lack of homogeneity could complicate the access to biological therapies. The definition provided by the GINA document, which reflects what suggested by ATS/ERS, could partially overcome the problem.restrictedopenBagnasco D.; Paggiaro P.; Latorre M.; Folli C.; Testino E.; Bassi A.; Milanese M.; Heffler E.; Manfredi A.; Riccio A.M.; De Ferrari L.; Blasi F.; Canevari R.F.; Canonica G.W.; Passalacqua G.; Guarnieri G.; Patella V.; Maria Pia F.B.; Carpagnano G.E.; Colle A.D.; Scioscia G.; Gerolamo P.; Puggioni F.; Racca F.; Favero E.; Iannacone S.; Savi E.; Montagni M.; Camiciottoli G.; Allegrini C.; Lombardi C.; Spadaro G.; Detoraki C.; Menzella F.; Galeone C.; Ruggiero P.; Yacoub M.R.; Berti A.; Scichilone N.; Durante C.; Costantino M.T.; Roncallo C.; Braschi M.; D'Adda A.; Ridolo E.; Triggiani M.; Parente R.; Maria D.A.; Verrillo M.V.; Rolla G.; Brussino L.; Frazzetto A.V.; Cristina Z.M.; Lilli M.; Crimi N.; Bonavia M.; Corsico A.G.; Grosso A.; Del Giacco S.; Deidda M.; Ricciardi L.; Isola S.; Cicero F.; Amato G.; Vita F.; Spanevello A.; Pignatti P.; Cherubino F.; Visca D.; Massimo Ricciardolo F.L.; Anna Carriero V.M.; Bertolini F.; Santus P.; Barlassina R.; Airoldi A.; Guida G.; Eleonora N.; Aruanno A.; Rizzi A.; Caruso C.; Colantuono S.; Senna G.; Caminati M.; Arcolaci A.; Vianello A.; Bianchi F.C.; Marchi M.R.; Centanni S.; Luraschi S.; Ruggeri S.; Rinaldo R.; Parazzini E.; Calabrese C.; Flora M.; Cosmi L.; Di Pietro L.; Maggi E.; Pini L.; Macchia L.; Di Bona D.; Richeldi L.; Condoluci C.; Fuso L.; Bonini M.; Farsi A.; Carli G.; Montuschi P.; Santini G.; Conte M.E.; Turchet E.; Barbetta C.; Mazza F.; D'Alo S.; Pucci S.; Caiaffa M.F.; Minenna E.; D'Elia L.; Pasculli C.; Viviano V.; Tarsia P.; Rolo J.; Di Proietto M.; Lo Cicero S.Bagnasco, D.; Paggiaro, P.; Latorre, M.; Folli, C.; Testino, E.; Bassi, A.; Milanese, M.; Heffler, E.; Manfredi, A.; Riccio, A. M.; De Ferrari, L.; Blasi, F.; Canevari, R. F.; Canonica, G. W.; Passalacqua, G.; Guarnieri, G.; Patella, V.; Maria Pia, F. B.; Carpagnano, G. E.; Colle, A. D.; Scioscia, G.; Gerolamo, P.; Puggioni, F.; Racca, F.; Favero, E.; Iannacone, S.; Savi, E.; Montagni, M.; Camiciottoli, G.; Allegrini, C.; Lombardi, C.; Spadaro, G.; Detoraki, C.; Menzella, F.; Galeone, C.; Ruggiero, P.; Yacoub, M. R.; Berti, A.; Scichilone, N.; Durante, C.; Costantino, M. T.; Roncallo, C.; Braschi, M.; D'Adda, A.; Ridolo, E.; Triggiani, M.; Parente, R.; Maria, D. A.; Verrillo, M. V.; Rolla, G.; Brussino, L.; Frazzetto, A. V.; Cristina, Z. M.; Lilli, M.; Crimi, N.; Bonavia, M.; Corsico, A. G.; Grosso, A.; Del Giacco, S.; Deidda, M.; Ricciardi, L.; Isola, S.; Cicero, F.; Amato, G.; Vita, F.; Spanevello, A.; Pignatti, P.; Cherubino, F.; Visca, D.; Massimo Ricciardolo, F. L.; Anna Carriero, V. M.; Bertolini, F.; Santus, P.; Barlassina, R.; Airoldi, A.; Guida, G.; Eleonora, N.; Aruanno, A.; Rizzi, A.; Caruso, C.; Colantuono, S.; Senna, G.; Caminati, M.; Arcolaci, A.; Vianello, A.; Bianchi, F. C.; Marchi, M. R.; Centanni, S.; Luraschi, S.; Ruggeri, S.; Rinaldo, R.; Parazzini, E.; Calabrese, C.; Flora, M.; Cosmi, L.; Di Pietro, L.; Maggi, E.; Pini, L.; Macchia, L.; Di Bona, D.; Richeldi, L.; Condoluci, C.; Fuso, L.; Bonini, M.; Farsi, A.; Carli, G.; Montuschi, P.; Santini, G.; Conte, M. E.; Turchet, E.; Barbetta, C.; Mazza, F.; D'Alo, S.; Pucci, S.; Caiaffa, M. F.; Minenna, E.; D'Elia, L.; Pasculli, C.; Viviano, V.; Tarsia, P.; Rolo, J.; Di Proietto, M.; Lo Cicero, S