Activated Random Walkers: Facts, Conjectures and Challenges

We study a particle system with hopping (random walk) dynamics on the integer lattice $\mathbb Z^d$. The particles can exist in two states, active or inactive (sleeping); only the former can hop. The dynamics conserves the number of particles; there is no limit on the number of particles at a given site. Isolated active particles fall asleep at rate $\lambda > 0$, and then remain asleep until joined by another particle at the same site. The state in which all particles are inactive is absorbing. Whether activity continues at long times depends on the relation between the particle density $\zeta$ and the sleeping rate $\lambda$. We discuss the general case, and then, for the one-dimensional totally asymmetric case, study the phase transition between an active phase (for sufficiently large particle densities and/or small $\lambda$) and an absorbing one. We also present arguments regarding the asymptotic mean hopping velocity in the active phase, the rate of fixation in the absorbing phase, and survival of the infinite system at criticality. Using mean-field theory and Monte Carlo simulation, we locate the phase boundary. The phase transition appears to be continuous in both the symmetric and asymmetric versions of the process, but the critical behavior is very different. The former case is characterized by simple integer or rational values for critical exponents ($\beta = 1$, for example), and the phase diagram is in accord with the prediction of mean-field theory. We present evidence that the symmetric version belongs to the universality class of conserved stochastic sandpiles, also known as conserved directed percolation. Simulations also reveal an interesting transient phenomenon of damped oscillations in the activity density

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

The Gene-Environment Interactions in Respiratory Diseases (GEIRD) Project

The role of genetic and environmental factors, as well as their interaction, in the natural history of asthma, allergic rhinitis and chronic obstructive pulmonary disease (COPD) is largely unknown. This is mainly due to the lack of large-scale analytical epidemiological/genetic studies aimed at investigating these 3 respiratory conditions simultaneously. The GEIRD project is a collaborative initiative designed to collect information on biomarkers of inflammation and oxidative stress, individual and ecological exposures, diet, early-life factors, smoking habits, genetic traits and medication use in large and accurately defined series of asthma, allergic rhinitis and COPD phenotypes. It is a population-based multicase-control design, where cases and controls are identified through a 2-stage screening process (postal questionnaire and clinical examination) in pre-existing cohorts or new samples of subjects. It is aimed at elucidating the role that modifiable and genetic factors play in the occurrence, persistence, severity and control of inflammatory airway diseases, by way of the establishment of a historical multicentre standardized databank of phenotypes, contributed by and openly available to international epidemiologists. Researchers conducting population-based surveys with standardized methods may contribute to the public-domain case-control database, and use the resulting increased power to answer their own scientific questions.</jats:p

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