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)

Field Plant Monitoring from Macro to Micro Scale: Feasibility and Validation of Combined Field Monitoring Approaches from Remote to in Vivo to Cope with Drought Stress in Tomato

Monitoring plant growth and development during cultivation to optimize resource use efficiency is crucial to achieve an increased sustainability of agriculture systems and ensure food security. In this study, we compared field monitoring approaches from the macro to micro scale with the aim of developing novel in vivo tools for field phenotyping and advancing the efficiency of drought stress detection at the field level. To this end, we tested different methodologies in the monitoring of tomato growth under different water regimes: (i) micro-scale (inserted in the plant stem) real-time monitoring with an organic electrochemical transistor (OECT)-based sensor, namely a bioristor, that enables continuous monitoring of the plant; (ii) medium-scale (<1 m from the canopy) monitoring through red–green–blue (RGB) low-cost imaging; (iii) macro-scale multispectral and thermal monitoring using an unmanned aerial vehicle (UAV). High correlations between aerial and proximal remote sensing were found with chlorophyll-related indices, although at specific time points (NDVI and NDRE with GGA and SPAD). The ion concentration and allocation monitored by the index R of the bioristor during the drought defense response were highly correlated with the water use indices (Crop Water Stress Index (CSWI), relative water content (RWC), vapor pressure deficit (VPD)). A high negative correlation was observed with the CWSI and, in turn, with the RWC. Although proximal remote sensing measurements correlated well with water stress indices, vegetation indices provide information about the crop’s status at a specific moment. Meanwhile, the bioristor continuously monitors the ion movements and the correlated water use during plant growth and development, making this tool a promising device for field monitoring.The research activities were supported by projects POSITIVE (Regione EmiliaRomagna ERDF project 2014–2020), and by the Project PON «R&I» 2014–2020—Azione II—“E-crops—Technologies for Digital and Sustainable Agriculture” funded by the Italian Ministry of University and Research (MUR) under the PON Agrifood Program (Contract ARS01_01136).info:eu-repo/semantics/publishedVersio

Laboratori verso la resilienza

Partendo dalle agende urbane per la sostenibilità, il Rapporto sulle Città cerca di tratteggiare un percorso con il quale i centri urbani possano proporsi quali luoghi privilegiati per l’avvio di una non più procrastinabile transizione verso nuovi modelli di sviluppo economico e rinnovate forme di convivenza e cittadinanza

State of the art and latest advances in exploring business models for nature-based solutions

Nature-based solutions (NBS) offer multiple solutions to urban challenges simultaneously, but realising funding for NBS remains a challenge. When the concept of NBS for societal challenges was first defined by the EC in 2017, financing was recognised as one of the major challenges to its mainstreaming. The complexity of NBS finance has its origin in the multiple benefits/stakeholders involved, which obscures the argument for both public and private sector investment. Since 2017, subsequent waves of EU research-and innovation-funded projects have substantially contributed to the knowledge base of funding and business models for NBS, particularly in the urban context. Collaborating and sharing knowledge through an EU Task Force, this first set of EU projects laid important knowledge foundations, reviewing existing literature, and compiling empirical evidence of different financing approaches and the business models that underpinned them. The second set of EU innovation actions advanced this knowledge base, developing and testing new implementation models, business model tools, and approaches. This paper presents the findings of these projects from a business model perspective to improve our understanding of the value propositions of NBS to support their mainstreaming

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

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

: The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10-8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10-8). A total of 113 variants were associated with survival at P-value < 1.0 × 10-5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways

Pathogen-sugar interactions revealed by universal saturation transfer analysis

Many pathogens exploit host cell-surface glycans. However, precise analyses of glycan ligands binding with heavily modified pathogen proteins can be confounded by overlapping sugar signals and/or compounded with known experimental constraints. Universal saturation transfer analysis (uSTA) builds on existing nuclear magnetic resonance spectroscopy to provide an automated workflow for quantitating protein-ligand interactions. uSTA reveals that early-pandemic, B-origin-lineage severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike trimer binds sialoside sugars in an “end-on” manner. uSTA-guided modeling and a high-resolution cryo–electron microscopy structure implicate the spike N-terminal domain (NTD) and confirm end-on binding. This finding rationalizes the effect of NTD mutations that abolish sugar binding in SARS-CoV-2 variants of concern. Together with genetic variance analyses in early pandemic patient cohorts, this binding implicates a sialylated polylactosamine motif found on tetraantennary N-linked glycoproteins deep in the human lung as potentially relevant to virulence and/or zoonosis