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The emergence of new SARS-CoV-2 variants poses challenges to global surveillance efforts, necessitating swift actions in their detection, evaluation, and management. Among the most recent variants, Omicron BA.2.86 and its sub-lineages have gained attention due to their potential immune evasion properties. This study describes the development of a digital PCR assay for the rapid detection of BA.2.86 and its descendant lineages,...
Cognition-oriented treatments (COTs) are a group of non-pharmacological treatments aimed at maintaining or improving cognitive functioning. Specific recommendations on the use of these interventions in people living with dementia (PLwD) are included in the Italian Guideline on the Diagnosis and Treatment of Dementia and Mild Cognitive Impairment, developed by the Italian National Institute of Health. This systematic review and...
Bioaccessible arsenic in soil of thermal areas of Viterbo, Central Italy: implications for human health riskNARA Subscribed
Thermal waters near the city of Viterbo (Central Italy) are known to show high As contents (up to 600 µg/l). Travertine is precipitated by these waters, forming extended plateau. In this study, we determine the As content, speciation and bioaccessibility in soil and travertine samples collected near a recreational area highly frequented by local inhabitants and tourists to investigate the risk of As exposure through accidental...
The diagnosis of Not Otherwise Specified (NOS) headaches in the Emergency Department (ED) is frequent despite many specialist visits performed. The aim of the study was to examine specialist visits carried out in the patients discharged from ED with diagnosis of NOS headache to evaluate discrepancies between specialist and ED diagnosis at discharge. We retrospectively (1.6.2018–31.12.2018) analyzed all the patients admitted wi...
Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severityNARA Subscribed
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the pr...