Detection of Hepatitis E Virus Antibodies in Domestic and Wild Animal Species in Central Italy

Hepatitis E virus (HEV) is known for its zoonotic potential. Although several mammalian species have been indicated as possible viral reservoir, the host range of the infection is partially defined. In this work serum samples collected from wild brown hares, red deer, wild rabbits, cattle living in semi-wild state and wild boar-hunting dogs were tested by a multi-species ELISA assay. Only sera from red deer (5.6%), wild rabbit (38.5%) and wild-boar hunting dogs (14.3%) scored positive. The investigation indicated the circulation and the high endemicity of HEV in various animal species in Central Italy, and the importance that these species can play in the epidemiology of infection

A new software toolkit for optical apportionment of carbonaceous aerosol

Instruments measuring aerosol light absorption, such as the Aethalometer and the Multi-Wavelength Absorbance Analyzer (MWAA), have been extensively used to characterize optical absorption of atmospheric particulate matter. Data retrieved with such instruments can be analysed with mathematical models to apportion different aerosol sources (Aethalometer model) and components (MWAA model). In this work we present an upgrade to the MWAA optical apportionment model. In addition to the apportionment of the absorption coefficient b abs in its components (black carbon and brown carbon) and sources (fossil fuels and wood burning), the extended model allows for the retrieval of the absorption Ångström exponent of each component and source, thereby avoiding initial assumptions regarding these parameters. We also present a new open-source software toolkit, the MWAA model toolkit (MWAA_MT), written in both Python and R, that performs the entire apportionment procedure

Experiences and Lessons Learned from the SIGMOD Entity Resolution Programming Contests

We report our experience in running three editions (2020, 2021, 2022) of the SIGMOD programming contest, a well-known event for students to engage in solving exciting data management problems. During this period we had the opportunity of introducing participants to the entity resolution task, which is of paramount importance in the data integration community. We aim at sharing the executive decisions, made by the people co-authoring this report, and the lessons learned

New distributional data for the Mediterranean medicinal leech Hirudo verbana Carena, 1820 (Hirudinea, Hirudinidae) in Italy, with a note on its feeding on amphibians

Scarce data are currently available about the distribution of the Mediterranean medicinal leech Hirudo verbana in Italy, and most of the known occurrence localities are based on records collected in the nineteenth and the first half of the twentieth century, which were not confirmed in the last decades, mostly due to a lack of surveys. Accordingly, the available knowledge on the distribution of the species is far from being updated and representative, although a significant negative trend of H. verbana throughout the country is supposed. The lack of sound distribution data is a significant shortfall, which hinders the implementation of the monitoring of the species as required by the Article 17 of the “Habitats Directive” on the species of Union concern. To provide recent, validated distributional data for the Mediterranean medicinal leech in Italy to be used as baseline data for further surveys and monitoring, we present herein a set of unpublished observations collected in the last decades in peninsular Italy, Sicily, and Sardinia. Moreover, we report observation of H. verbana feeding on amphibians, a feeding habit to date poorly documented for the Mediterranean medicinal leech. Based on both published and novel data, H. verbana is characterised by a large but fragmented distribution in Italy. Therefore, dedicated monitoring programs and the collection of validated occasional observations are highly desirable to get a clearer picture of the real distribution of the species

An Observational Study to Develop a Predictive Model for Bacterial Pneumonia Diagnosis in Severe COVID-19 Patients-C19-PNEUMOSCORE

In COVID-19 patients, antibiotics overuse is still an issue. A predictive scoring model for the diagnosis of bacterial pneumonia at intensive care unit (ICU) admission would be a useful stewardship tool. We performed a multicenter observational study including 331 COVID-19 patients requiring invasive mechanical ventilation at ICU admission; 179 patients with bacterial pneumonia; and 152 displaying negative lower-respiratory samplings. A multivariable logistic regression model was built to identify predictors of pulmonary co-infections, and a composite risk score was developed using β-coefficients. We identified seven variables as predictors of bacterial pneumonia: vaccination status (OR 7.01; 95% CI, 1.73-28.39); chronic kidney disease (OR 3.16; 95% CI, 1.15-8.71); pre-ICU hospital length of stay ≥ 5 days (OR 1.94; 95% CI, 1.11-3.4); neutrophils ≥ 9.41 × 1

Effectiveness and Safety of Biosimilars in Pediatric Non-infectious Uveitis: Real-Life Data from the International AIDA Network Uveitis Registry

IntroductionSince many biological drug patents have expired, biosimilar agents (BIOs) have been developed; however, there are still some reservations in their use, especially in childhood. The aim of the current study is to evaluate the efficacy and safety of tumor necrosis factor (TNF) inhibitors BIOs as treatment for pediatric non-infectious uveitis (NIU).MethodsData from pediatric patients with NIU treated with TNF inhibitors BIOs were drawn from the international AutoInflammatory Disease Alliance (AIDA) registries dedicated to uveitis and Behcet's disease. The effectiveness and safety of BIOs were assessed in terms of frequency of relapses, risk for developing ocular flares, best-corrected visual acuity (BCVA), glucocorticoids (GCs)-sparing effect, drug survival, frequency of ocular complications, and adverse drug event (AE).ResultsForty-seven patients (77 affected eyes) were enrolled. The BIOs employed were adalimumab (ADA) (89.4%), etanercept (ETA) (5.3%), and infliximab (IFX) (5.3%). The number of relapses 12 months prior to BIOs and at last follow-up was 282.14 and 52.43 per 100 patients/year. The relative risk of developing ocular flares before BIOs introduction compared to the period following the start of BIOs was 4.49 (95% confidence interval [CI] 3.38-5.98, p = 0.004). The number needed to treat (NNT) for ocular flares was 3.53. Median BCVA was maintained during the whole BIOs treatment (p = 0.92). A significant GCs-sparing effect was observed throughout the treatment period (p = 0.002). The estimated drug retention rate (DRR) at 12-, 24-, and 36-month follow-up were 92.7, 83.3, and 70.8%, respectively. The risk rate for developing structural ocular complications was 89.9/100 patients/year before starting BIOs and 12.7/100 patients/year during BIOs treatment, with a risk ratio of new ocular complications without BIOs of 7.1 (CI 3.4-14.9, p = 0.0003). Three minor AEs were reported.ConclusionsTNF inhibitors BIOs are effective in reducing the number of ocular uveitis relapses, preserving visual acuity, allowing a significant GCs-sparing effect, and preventing structural ocular complications.Trial RegistrationClinicalTrials.gov ID NCT05200715

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