Does forest damage have an economic impact? A case study from the Italian Alps

The aim of this paper is to take stock of the situation regarding the main types of damage to forests and their respective economic consequences, with reference to a case study in the Italian Alps (Trentino province). Each kind of damage (wind and snow, defoliation, fire and tillage) has been analysed in terms of its impact on four forest functions (production, protection, tourism-recreation and carbon sequestration) and evaluated in monetary terms. Market value was used to estimate the production and carbon sequestration functions, replacement cost method for protection, and contingent valuation for tourism-recreation. Applying desk research on damage caused by the main biotic and abiotic factors to this particular case study led to estimate a annual damage of about € 1,633,595 equal to € 4.73 per hectar. This can be considered a lower bound estimate of possibly greater damage. Another interesting result emerged from the evaluation exercise is that the wealth of information produced through monitoring and scientific research in the last twenty years does not readily lend itself to economic analysis.forest damage, forest functions, interaction between damage and functions, economic valuation, Alpine forests

Consumer Preferences for Fruit and Vegetables with Credence-Based Attributes: A Review

credence goods, consumer preferences and attitudes, sustainable fruit and vegetables, consumer research., Agricultural Finance, Consumer/Household Economics, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, Institutional and Behavioral Economics, Marketing, Productivity Analysis,

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

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

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

Do ‘locally grown’ claims influence artisanal food purchase? Evidence from a natural field experiment.

We conducted a natural field experiment in an artisanal sit-down ice-cream shop in Italy to investigate whether consumer choices are affected by information regarding locally grown products. Two aspects of locally grown products are investigated: (i) quality due to terroir (i.e., quality with a link to the territory) and (ii) reduced carbon emissions due to short transportation distance. Contrary to the evidence emerging from the majority of the stated-preference literature, our results suggest that consumer behavior is not significantly affected by information regarding quality due to terroir. We also find that consumers positively respond to information concerning reduced carbon emissions, although the estimated average WTP is small (10 Euro cents). Finally, we offer a contribution to the literature on sustainable food consumption by documenting a gender gap and a cohort effect and by providing evidence that social pressure, as proxied by the size of the party and the presence of kids at the table, fosters environmentally friendly consumption

Exploiting cut-off information to incorporate context effect: a discrete choice experiment on small fruits in a Alpine region

Crop Production/Industries, Demand and Price Analysis,