Identification of candidate genes associated with bacterial and viral infections in wild boars hunted in Tuscany (Italy).

Wild boar (Sus scrofa L.) is one of the large mammals most spread worldwide, highly adaptable, and its population rapidly increased in many areas in Europe, including Italy, where Tuscany is considered particularly suitable for wild boar. Wild boars are potential hosts for different etiological agents, such as Brucella spp., Leptospira spp. and Pseudorabies virus and they can contribute to maintain and/or to disseminate some bacterial or viral pathogens to humans and domestic animals, above all-in free-range farms. In order to identify hypothetical genomic regions associated with these infection diseases, 96 samples of wild boars hunted in Tuscany during the 2018-2019 and 2019-2020 hunting seasons were considered. Diagnosis was achieved by serological tests and 42 Pseudorabies, 31 Leptospira and 15 Brucella positive animals were identified. All animals were genotyped with Geneseek Genomic Profiler Porcine HD (70 k) and a genome-wide scan was then performed. Significant markers were highlighted for Pseudorabies (two SNPs), Brucella (seven SNPs), and Leptospira (four SNPs) and they were located within, or nearby, 29 annotated genes on chromosome 6, 9, 12, 13, 14 and 18. Eight genes are implicated in viral (SEC14L1, JMJD6, SRSF2, TMPRSS2, MX1, MX2) or bacterial (COL8A1, SPIRE1) infections, seven genes (MFSD11, METTL23, CTTNBP2, BACE2, IMPA2, MPPE1 and GNAL) are involved in mental disorders and one gene (MGAT5B) is related to the Golgi complex. Results presented here provide interesting starting points for future research, validation studies and fine mapping of candidate genes involved in bacterial and viral infections in wild boar.

Structured reporting of chest CT in COVID-19 pneumonia: a consensus proposal.

OBJECTIVES: The need of a standardized reporting scheme and language, in imaging of COVID-19 pneumonia, has been welcomed by major scientific societies. The aim of the study was to build the reporting scheme of chest CT in COVID-19 pneumonia. METHODS: A team of experts, of the Italian Society of Medical and Interventional Radiology (SIRM), has been recruited to compose a consensus panel. They used a modified Delphi process to build a reporting scheme and expressed a level of agreement for each section of the report. To measure the internal consistency of the panelist ratings for each section of the report, a quality analysis based on the average inter-item correlation was performed with Cronbach's alpha (Cα) correlation coefficient. RESULTS: The overall mean score of the experts and the sum of score were 3.1 (std.dev. ± 0.11) and 122 in the second round, and improved to 3.75 (std.dev. ± 0.40) and 154 in the third round. The Cronbach's alpha (Cα) correlation coefficient was 0.741 (acceptable) in the second round and improved to 0.789 in the third round. The final report was built in the management of radiology report template (MRRT) and includes n = 4 items in the procedure information, n = 5 items in the clinical information, n = 16 in the findings, and n = 3 in the impression, with overall 28 items. CONCLUSIONS: The proposed structured report could be of help both for expert radiologists and for the less experienced who are faced with the management of these patients. The structured report is conceived as a guideline, to recommend the key items/findings of chest CT in COVID-19 pneumonia.