Chapter Il fascismo ‘liberista’ e la ‘quasi abolizione’ dell’imposta di successione del 1923

In summer 1923, in the midst of the ‘fight’ to balance the budget, Minister Alberto De Stefani announced the abolition of inheritance tax, pursuant to the ‘full powers’ granted to the government by the Parliament. This abolition – possibly the most iconic act of the ‘financial restauration’ carried on by De Stefani – provoked surprise and interest in the country and abroad but was substantially overlooked by historians. This chapter – first outcome of a research in progress – offers a first historical reconstruction of this episode of early 1920s Italian economic history, by documenting both the positions of an influent advisor of De Stefani, the economist Maffeo Pantaleoni, and even more, the lobbying activity carried on by pressure groups such as the bankers’ association, an influential businessman linked to Mussolini such as Cesare Goldmann, and a young, very proactive association of notaries. Moreover, the chapter surveys the way in which both Italian and international media reported on this case of politics of inequality, offering a different perspective on a crucial period in the consolidation of Fascist power

La lutte des ouvriers de GKN Florence, entre auto-organisation ouvrière et mobilisation sociale

Cette chronique décrit la lutte des travailleurs de l’usine GKN de Florence contre sa fermeture et sa délocalisation. Après avoir rendu compte des principales étapes du conflit, l’article se penche sur trois aspects fondamentaux : l’organisation syndicale interne à l’usine et sa capacité à renforcer les ressources militantes autonomes des travailleurs, l’habileté de ces derniers à mobiliser le tissu social environnant et à nouer des alliances avec d’autres mouvements sociaux et, enfin, la contribution apportée par le monde de l’université et de la recherche dans l’élaboration d’un plan de reconversion du site

La lutte des ouvriers de GKN à Florence, entre auto-organisation ouvrière et mobilisation sociale

Cette chronique décrit la lutte des travailleurs de l’usine GKN de Florence contre sa fermeture et sa délocalisation. Après avoir rendu compte des principales étapes du conflit, l’article se penche sur trois aspects fondamentaux : l’organisation syndicale interne à l’usine et sa capacité à renforcer les ressources militantes autonomes des travailleurs, l’habileté de ces derniers à mobiliser le tissu social environnant et à nouer des alliances avec d’autres mouvements sociaux et, enfin, la contribution apportée par le monde de l’université et de la recherche dans l’élaboration d’un plan de reconversion du site

Bloodborne Viral Hepatitis Infections among Drug Users: The Role of Vaccination

Drug use is a prevalent world-wide phenomenon and hepatitis virus infections are traditionally a major health problem among drug users (DUs). HBV and HCV, and to a lesser extent HAV, are easily transmitted through exposure to infected blood and body fluids. Viral hepatitis is not inevitable for DUs. Licensed vaccines are available for hepatitis A and hepatitis B. The purpose of this overview is to show some epidemiological data about HBV and the other blood-borne viral hepatitis among DUs and to summarize and discuss use of hepatitis vaccinations in this population. Successful vaccination campaigns among DUs are feasible and well described. We try to focus on the most significant results achieved in successful vaccination programs as reported in scientific literature. Vaccination campaigns among DUs represent a highly effective form of health education and they are cost-saving

Incidence of cancer and overall risk of mortality in individuals treated with raltegravir-based and non-raltegravir-based combination antiretroviral therapy regimens

Objectives: There are currently few data on the long-term risk of cancer and death in individuals taking raltegravir (RAL). The aim of this analysis was to evaluate whether there is evidence for an association. Methods: The EuroSIDA cohort was divided into three groups: those starting RAL-based combination antiretroviral therapy (cART) on or after 21 December 2007 (RAL); a historical cohort (HIST) of individuals adding a new antiretroviral (ARV) drug (not RAL) to their cART between 1 January 2005 and 20 December 2007, and a concurrent cohort (CONC) of individuals adding a new ARV drug (not RAL) to their cART on or after 21 December 2007. Baseline characteristics were compared using logistic regression. The incidences of newly diagnosed malignancies and death were compared using Poisson regression. Results: The RAL cohort included 1470 individuals [with 4058 person-years of follow-up (PYFU)] compared with 3787 (4472 PYFU) and 4467 (10 691 PYFU) in the HIST and CONC cohorts, respectively. The prevalence of non-AIDS-related malignancies prior to baseline tended to be higher in the RAL cohort vs. the HIST cohort [adjusted odds ratio (aOR) 1.31; 95% confidence interval (CI) 0.95–1.80] and vs. the CONC cohort (aOR 1.89; 95% CI 1.37–2.61). In intention-to-treat (ITT) analysis (events: RAL, 50; HIST, 45; CONC, 127), the incidence of all new malignancies was 1.11 (95% CI 0.84–1.46) per 100 PYFU in the RAL cohort vs. 1.20 (95% CI 0.90–1.61) and 0.83 (95% CI 0.70–0.99) in the HIST and CONC cohorts, respectively. After adjustment, there was no evidence for a difference in the risk of malignancies [adjusted rate ratio (RR) 0.73; 95% CI 0.47–1.14 for RALvs. HIST; RR 0.95; 95% CI 0.65–1.39 for RALvs. CONC] or mortality (adjusted RR 0.87; 95% CI 0.53–1.43 for RALvs. HIST; RR 1.14; 95% CI 0.76–1.72 for RALvs. CONC). Conclusions: We found no evidence for an oncogenic risk or poorer survival associated with using RAL compared with control groups.Peer reviewe

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as “Respiratory or thoracic disease”, supporting their link with COVID-19 severity outcome