Robust small area prediction for counts

A new semiparametric approach to model-based small area prediction for counts is proposed and used for estimating the average number of visits to physicians for Health Districts in Central Italy. The proposed small area predictor can be viewed as an outlier robust alternative to the more commonly used empirical plug-in predictor that is based on a Poisson generalized linear mixed model with Gaussian random effects. Results from the real data application and from a simulation experiment confirm that the proposed small area predictor has good robustness properties and in some cases can be more efficient than alternative small area approaches

A transitional non-parametric maximum pseudo-likelihood estimator for disease mapping

Abstract Non-parametric maximum likelihood estimators of relative risk have been proposed as an alternative to empirical Bayes or full Bayes approaches to disease mapping. They have the advantage of being relatively simple, the EM algorithm assures convergence and area classiÿcation is straightforward. However, they do not take into account spatial autocorrelation and have higher mean square error when the true underlying risk pattern is strongly spatially structured. Furthermore, the EM algorithm is sensible to starting values and could converge to local maxima. We review the transitional generalized linear models and propose a transitional non-parametric maximum pseudo-likelihood estimator for disease mapping. The usual kernel likelihood of the mixture models is replaced by the conditional density of the observed response for a single area given the values observed in adjacent areas. The estimation of the parameters is based on the EM algorithm, appropriately modiÿed to handle the problem of local maxima and to estimate the number of components of the mixture. A simulation study shows that the transitional non-parametric maximum pseudo-likelihood estimator performs similarly to full Bayes estimators

Bithiazole Inhibitors of Phosphatidylinositol 4-Kinase (PI4KIIIβ) as Broad-Spectrum Antivirals Blocking the Replication of SARS-CoV-2, Zika Virus, and Human Rhinoviruses

Over half a century since the description of the first antiviral drug, “old” re-emerging viruses and “new” emerging viruses still represent a serious threat to global health. Their high mutation rate and rapid selection of resistance toward common antiviral drugs, together with the increasing number of co-infections, make the war against viruses quite challenging. Herein we report a host-targeted approach, based on the inhibition of the lipid kinase PI4KIIIβ, as a promising strategy for inhibiting the replication of multiple viruses hijacking this protein. We show that bithiazole inhibitors of PI4KIIIβ block the replication of human rhinoviruses (hRV), Zika virus (ZIKV) and SARS-CoV-2 at low micromolar and sub-micromolar concentrations. However, while the anti-hRV/ZIKV activity can be directly linked to PI4KIIIβ inhibition, the role of PI4KIIIβ in SARS-CoV-2 entry/replication is debated

Multitarget CFTR Modulators Endowed with Multiple Beneficial Side Effects for Cystic Fibrosis Patients: Toward a Simplified Therapeutic Approach

Cystic fibrosis (CF) is a multiorgan disease caused by mutations of the cystic fibrosis transmembrane conductance regulator (CFTR). In addition to respiratory impairment due to mucus accumulation, viruses and bacteria trigger acute pulmonary exacerbations, accelerating disease progression and mortality rate. Treatment complexity increases with patients’ age, and simplifying the therapeutic regimen represents one of the key priorities in CF. We have recently reported the discovery of multitarget compounds able to “kill two birds with one stone” by targeting F508del-CFTR and PI4KIIIβ and thus acting simultaneously as CFTR correctors and broad-spectrum enterovirus (EV) inhibitors. Starting from these preliminary results, we report herein a hit-to-lead optimization and multidimensional structure–activity relationship (SAR) study that led to compound 23a. This compound showed good antiviral and F508del-CFTR correction potency, additivity/synergy with lumacaftor, and a promising in vitro absorption, distribution, metabolism, and excretion (ADME) profile. It was well tolerated in vivo with no sign of acute toxicity and histological alterations in key biodistribution organs

A New Strategy for Glioblastoma Treatment: In Vitro and In Vivo Preclinical Characterization of Si306, a Pyrazolo[3,4-d]Pyrimidine Dual Src/P-Glycoprotein Inhibitor

20siopenOverexpression of P-glycoprotein (P-gp) and other ATP-binding cassette (ABC) transporters in multidrug resistant (MDR) cancer cells is responsible for the reduction of intracellular drug accumulation, thus decreasing the efficacy of chemotherapeutics. P-gp is also found at endothelial cells' membrane of the blood-brain barrier, where it limits drug delivery to central nervous system (CNS) tumors. We have previously developed a set of pyrazolo[3,4-d]pyrimidines and their prodrugs as novel Src tyrosine kinase inhibitors (TKIs), showing a significant activity against CNS tumors in in vivo. Here we investigated the interaction of the most promising pair of drug/prodrug with P-gp at the cellular level. The tested compounds were found to increase the intracellular accumulation of Rho 123, and to enhance the efficacy of paclitaxel in P-gp overexpressing cells. Encouraging pharmacokinetics properties and tolerability in vivo were also observed. Our findings revealed a novel role of pyrazolo[3,4-d]pyrimidines which may be useful for developing a new effective therapy in MDR cancer treatment, particularly against glioblastoma.openFallacara, Anna Lucia; Zamperini, Claudio; Podolski-Renić, Ana; Dinić, Jelena; Stanković, Tijana; Stepanović, Marija; Mancini, Arianna; Rango, Enrico; Iovenitti, Giulia; Molinari, Alessio; Bugli, Francesca; Sanguinetti, Maurizio; Torelli, Riccardo; Martini, Maurizio; Maccari, Laura; Valoti, Massimo; Dreassi, Elena; Botta, Maurizio; Pešić, Milica; Schenone, SilviaFallacara, Anna Lucia; Zamperini, Claudio; Podolski-Renić, Ana; Dinić, Jelena; Stanković, Tijana; Stepanović, Marija; Mancini, Arianna; Rango, Enrico; Iovenitti, Giulia; Molinari, Alessio; Bugli, Francesca; Sanguinetti, Maurizio; Torelli, Riccardo; Martini, Maurizio; Maccari, Laura; Valoti, Massimo; Dreassi, Elena; Botta, Maurizio; Pešić, Milica; Schenone, Silvi

Applying Definitions of “Asbestos” to Environmental and “Low-Dose” Exposure Levels and Health Effects, Particularly Malignant Mesothelioma

Although asbestos research has been ongoing for decades, this increased knowledge has not led to consensus in many areas of the field. Two such areas of controversy include the specific definitions of asbestos, and limitations in understanding exposure-response relationships for various asbestos types and exposure levels and disease. This document reviews the current regulatory and mineralogical definitions and how variability in these definitions has led to difficulties in the discussion and comparison of both experimental laboratory and human epidemiological studies for asbestos. This review also examines the issues of exposure measurement in both animal and human studies, and discusses the impact of these issues on determination of cause for asbestos-related diseases. Limitations include the lack of detailed characterization and limited quantification of the fibers in most studies. Associated data gaps and research needs are also enumerated in this review

Metodi di correzione per l'effetto confine nella mappatura del rischio di malattia in epidemiologia geografica

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