Riorientare la tassazione su energia e emissioni

La fiscalità ambientale è uno strumento efficiente di policy per ridurre l’inquinamento e l’uso delle risorse naturali. Sono cinque le linee di intervento per indirizzare l’Italia verso la decarbonizzazione, tra cui l’abolizione dei sussidi ai combustibili fossili per una riforma fiscale ecologica

Politica industriale e sviluppo sostenibile

Il libro riproduce ed amplia le relazioni presentate al workshop del 3 ottobre 2014 presso il Dipartimento di Economia dell’Università di Parma, ad opera di studiosi appartenenti all’Università di Ferrara, allo Iefe-Università Bocconi di Milano, all’Università di Modena, alla Scuola Sant’Anna di Pisa, nonché alla stessa Università di Parma. I cinque contributi qui presentati fotografano cinque diversi aspetti del rapporto fra politica industriale (più in generale crescita economica diretta dalle istituzioni pubbliche) e sviluppo sostenibile: a livello nazionale, il possibile trade-off fra i due obiettivi di politica industriale e di sostenibilità ambientale nel tentativo di gerarchizzare i “settori strategici”, e la necessità che questo trade-off sia parzialmente compensato a livello di sforzo innovativo (Di Tommaso e Tassinari); a livello internazionale, la possibilità che politiche industriali nazionali non operino all’interno di un gioco a somma zero, ma diano risultati favorevoli al raggiungimento di un bene pubblico globale quale il cambiamento climatico (Fabbri e Ninni); a livello di imprese, la tendenziale riduzione delle contraddizioni fra incentivi al loro operare e “impronta” ambientale, grazie agli accordi volontari e in particolare all’importante ruolo della certificazione (Frey); a livello di istituzioni, l’esistenza di tipologie diverse di obiettivi e di strumenti a livello nazionale e a livello locale, e l’analisi in un confronto tra paesi europei delle caratteristiche delle politiche ambientali impostate a livello sub-nazionale (Croci e Molteni); a livello di mercato del lavoro, l’effetto sul tessuto industriale delle politiche di aumento della flessibilità del lavoro nella singola impresa, come aspetto particolare di una ridiscussione più ampia del concetto di sostenibilità ambientale e dei suoi rapporti con la politica nei confronti delle imprese (Giovannetti)

3D bone texture analysis as a potential predictor of radiationinduced insufficiency fractures

Background: The aim of our work is to assess the potential role of texture analysis (TA), applied to computed tomography (CT) simulation scans, in relation to the development of insuffciency fractures (IFs) in patients undergoing radiation therapy (RT) for pelvic malignancies. Methods: We analyzed patients undergoing pelvic RT from Jan-2010 to Dec-2016, 31 of whom had developed IFs of the pelvis. We analyzed CT simulation scans using LifeX Software, and in particular we selected three regions of interest (ROI): L5 body, the sacrum and both the femoral heads. The ROI were automatically contoured using the treatment planning software Raystation. TA parameters included parameters from the gray-level histogram, indices from sphericity and from the matrix of GLCM (gray level co-occurrence matrix). The IFs patients were matched (1:1 ratio) with control patients who had not developed IFs, and were matched for age, sex, type of tumor, menopausal status, RT dose and use of chemotherapy. Univariate and multivariate analyses (logistic regression) were used for statistical analysis. Results: Signifcant TA parameters on univariate analysis included both parameters from the histogram distribution, as well from the matrix of GLCM. On logistic regression analysis the signifcant parameters were L5-energy [P=0.033, odds ratio (OR): 1.997, 95% CI: 1.0593.767] and FH-Skewness (P=0.014, OR: 2.338, 95% CI: 1.1914.591), with a R2: 0.268. A ROC curve was generated from the binary logistic regression, and the AUC was 0.741 (95% CI: 0.6270.855, P=0.001, S.E.: 0.058). Conclusions: In our experience, 3D-bone CT TA can be used to stratify the risk of the patients to develop radiation-induced IFs. A prospective study will be conducted to validate these fndings

Modifications of Chest CT Body Composition Parameters at Three and Six Months after Severe COVID-19 Pneumonia: A Retrospective Cohort Study

We aimed to describe body composition changes up to 6-7 months after severe COVID-19 and to evaluate their association with COVID-19 inflammatory burden, described by the integral of the C-reactive protein (CRP) curve. The pectoral muscle area (PMA) and density (PMD), liver-to-spleen (L/S) ratio, and total, visceral, and intermuscular adipose tissue areas (TAT, VAT, and IMAT) were measured at baseline (T0), 2-3 months (T1), and 6-7 months (T2) follow-up CT scans of severe COVID-19 pneumonia survivors. Among the 208 included patients (mean age 65.6 ± 11 years, 31.3% females), decreases in PMA [mean (95%CI) -1.11 (-1.72; -0.51) cm2] and in body fat areas were observed [-3.13 (-10.79; +4.52) cm2 for TAT], larger from T0 to T1 than from T1 to T2. PMD increased only from T1 to T2 [+3.07 (+2.08; +4.06) HU]. Mean decreases were more evident for VAT [-3.55 (-4.94; -2.17) cm2] and steatosis [L/S ratio increase +0.17 (+0.13; +0.20)] than for TAT. In multivariable models adjusted by age, sex, and baseline TAT, increasing the CRP interval was associated with greater PMA reductions, smaller PMD increases, and greater VAT and steatosis decreases, but it was not associated with TAT decreases. In conclusion, muscle loss and fat loss (more apparent in visceral compartments) continue until 6-7 months after COVID-19. The inflammatory burden is associated with skeletal muscle loss and visceral/liver fat loss

A Hydrogenated amorphous silicon detector for Space Weather Applications

The characteristics of a hydrogenated amorphous silicon (a-Si:H) detector are presented here for monitoring in space solar flares and the evolution of large energetic proton events up to hundreds of MeV. The a-Si:H presents an excellent radiation hardness and finds application in harsh radiation environments for medical purposes, for particle beam characterization and in space weather science and applications. The critical flux detection threshold for solar X rays, soft gamma rays, electrons and protons is discussed in detail.Comment: 32 pages, 13 figures, submitted to Experimental Astronom

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

Carriers of ADAMTS13 Rare Variants Are at High Risk of Life-Threatening COVID-19

Thrombosis of small and large vessels is reported as a key player in COVID-19 severity. However, host genetic determinants of this susceptibility are still unclear. Congenital Thrombotic Thrombocytopenic Purpura is a severe autosomal recessive disorder characterized by uncleaved ultra-large vWF and thrombotic microangiopathy, frequently triggered by infections. Carriers are reported to be asymptomatic. Exome analysis of about 3000 SARS-CoV-2 infected subjects of different severities, belonging to the GEN-COVID cohort, revealed the specific role of vWF cleaving enzyme ADAMTS13 (A disintegrin-like and metalloprotease with thrombospondin type 1 motif, 13). We report here that ultra-rare variants in a heterozygous state lead to a rare form of COVID-19 characterized by hyper-inflammation signs, which segregates in families as an autosomal dominant disorder conditioned by SARS-CoV-2 infection, sex, and age. This has clinical relevance due to the availability of drugs such as Caplacizumab, which inhibits vWF-platelet interaction, and Crizanlizumab, which, by inhibiting P-selectin binding to its ligands, prevents leukocyte recruitment and platelet aggregation at the site of vascular damage

Gain- and Loss-of-Function CFTR Alleles Are Associated with COVID-19 Clinical Outcomes

Carriers of single pathogenic variants of the CFTR (cystic fibrosis transmembrane conductance regulator) gene have a higher risk of severe COVID-19 and 14-day death. The machine learning post-Mendelian model pinpointed CFTR as a bidirectional modulator of COVID-19 outcomes. Here, we demonstrate that the rare complex allele [G576V;R668C] is associated with a milder disease via a gain-of-function mechanism. Conversely, CFTR ultra-rare alleles with reduced function are associated with disease severity either alone (dominant disorder) or with another hypomorphic allele in the second chromosome (recessive disorder) with a global residual CFTR activity between 50 to 91%. Furthermore, we characterized novel CFTR complex alleles, including [A238V;F508del], [R74W;D1270N;V201M], [I1027T;F508del], [I506V;D1168G], and simple alleles, including R347C, F1052V, Y625N, I328V, K68E, A309D, A252T, G542*, V562I, R1066H, I506V, I807M, which lead to a reduced CFTR function and thus, to more severe COVID-19. In conclusion, CFTR genetic analysis is an important tool in identifying patients at risk of severe COVID-19

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor