The influence of hepatitis B virus (HBV) genotypes in the natural history of the disease and its response to antiviral treatment have been addressed in many studies. In Brazil, studies on HBV genotype circulation have been restricted to specific population groups and states. Here, we have conducted a nationwide multicentre study with an unprecedented sample size representing all Brazilian regions in an effort to better understand the viral variants of HBV circulating among chronic carriers. Seven HBV genotypes were found circulating in Brazil. Overall, HBV/A was the most prevalent, identified in 589 (58.7 %) samples, followed by HBV/D (23.4 %) and HBV/F (11.3 %). Genotypes E, G, C and B were found in a minor proportion. The distribution of the genotypes differed markedly from the north to the south of the country. While HBV/A was the most prevalent in the North (71.6 %) and Northeast (65.0 %) regions, HBV/D was found in 78.9 % of the specimens analysed in the South region. HBV/F was the second most prevalent genotype in the Northeast region (23.5 %). It was detected in low proportions (7 to 10 %) in the North, Central-West and Southeast regions, and in only one sample in the South region. HBV/E was detected in all regions except in the South, while monoinfection with HBV/G was found countrywide, with the exception of Central-West states. Our sampling covered 24 of the 26 Brazilian states and the Federal District and is the first report of genotype distribution in seven states. This nationwide study provides the most complete overview of HBV genotype distribution in Brazil to date and reflects the origin and plurality of the Brazilian population.

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Considered a neglected pathogen until the last 2 decades, an increase in the availability of genetic data of hepatitis D virus (HDV) strains around the world has been noticed recently, resulting in the proposition of different classifications. Our study aimed to determine the molecular epidemiological profile of HDV isolates circulating in areas of endemicity and non-areas of endemicity in Brazil.

Meningiomas (MGMs) are currently classified into grades I, II, and III. High-grade tumors are correlated with decreased survival rates and increased recurrence rates. The current grading classification is based on histological criteria and determined only after surgical tumor sampling. This study aimed to identify plasma metabolic alterations in meningiomas of different grades, which would aid surgeons in predefining the ideal surgical strategy. Plasma samples were collected from 51 patients with meningioma and classified into low-grade (LG) (grade I; n = 43), and high-grade (HG) samples (grade II, n = 5; grade III, n = 3). An untargeted metabolomic approach was used to analyze plasma metabolites. Statistical analyses were performed to select differential biomarkers among HG and LG groups. Metabolites were identified using tandem mass spectrometry along with database verification. Five and four differential biomarkers were identified for HG and LG meningiomas, respectively. To evaluate the potential of HG MGM metabolites to differentiate between HG and LG tumors, a receiving operating characteristic curve was constructed, which revealed an area under the curve of 95.7%. This indicates that the five HG MGM metabolites represent metabolic alterations that can differentiate between LG and HG meningiomas. These metabolites may indicate tumor grade even before the appearance of histological features.

Dogs can be excellent models for spontaneous studies about breast cancers, presenting similarities in clinical behavior and molecular pathways of the disease. Thus, analyses of the canine transcriptome can identify deregulated genes and pathways, contributing to the identification of biomarkers and new therapeutic targets, benefiting humans and animals. In this context, this study aimed to determine the transcriptional profile of canine mammary ductal carcinoma and contribute to the clarification of the importance of deregulated molecules in the molecular pathways involved in the disease. Therefore, we used mammary ductal carcinoma tissue samples and non-tumor mammary tissue from the radical mastectomy of six female dogs. Sequencing was performed on the NextSeq-500 System platform. A comparison of carcinoma tissue and normal tissue revealed 633 downregulated and 573 upregulated genes, which were able to differentiate the groups by principal component analysis. Gene ontology analysis indicated that inflammatory, cell differentiation and adhesion, and extracellular matrix maintenance pathways were mainly deregulated in this series. The main differentially expressed genes observed in this research can indicate greater disease aggressiveness and worse prognosis. Finally, the study of the canine transcriptome indicates that it is an excellent model to generate information relevant to oncology in both species.