Publications

Abstract Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of diagnostic significance and to use these data in real-time genomic contact tracing and surveillance. Under this paradigm, unprecedented volumes of data are generated that require rapid analysis to provide meaningful inference. We present a machine learning logistic regression pipeline that can assign classifications to genetic sequence data. The pipeline implements an intuitive and customizable approach to developing a trained prediction model that runs in linear time complexity, generating accurate output more rapidly than other classification methods. Our approach was benchmarked against porcine respiratory and reproductive syndrome virus (PRRSv) and swine H1 influenza A (IAV) datasets. Trained classifiers were tested against sequences and simulated datasets that artificially degraded sequence quality at 0, 10, 20, 30, and 40%. When applied to a poor-quality sequence data, the classifier achieved between >85% to 95% accuracy for the PRRSv and the swine H1 IAV HA dataset and this increased to near perfect accuracy when using the full dataset. The model also identifies amino acid positions used to determine genetic clade identity through a feature selection ranking within the model. These positions can be mapped onto a maximum-likelihood phylogenetic tree, allowing for the inference of clade defining mutations. Our approach is implemented as a python package with code available at https://github.com/flu-crew/classLog .

Background: The economy of Rio Grande do Sul (RS) relies majorly on agriculture; among the livestock production chains, cattle production has the largest economic, historical, and cultural importance in RS. The cattle industry is the main zootechnical activity in RS. Due to this, there is an actual need for updated characterization of the animal population, considering the population dynamics and the requirements imposed by the Official Veterinary Service (SVO) to meet certain characteristics. This would facilitate appropriate policies and measures to safeguard the health of the cattle in RS, as well as safeguard public health, and consequently avoid the economic impacts of possible health events. Materials, Methods & Results: Based on data from the livestock survey of 2013 from the Department of Animal Health (DDA), the Secretariat of Agriculture, Livestock, and Agribusiness of the State of Rio Grande do Sul (SEAPA-RS), descriptive and spatial analyses of the cattle population were performed using software R and ArcMap TM 10, respectively. It was observed that the state has more than 13 million cattle distributed over approximately 346,000 farms. The majority of the bovine population consists of females over the age of 36 months. The predominant function of these farms is a complete cycle (breeding to fattening). Beef production is the predominant activity, followed by a mix of beef production and dairy production, and then sole dairy production. These characteristics differ depending on the state’s region. Regarding the number of animals per property, 88% of properties are small having up to 50 cattle, and about 1% of properties have more than 500 animals. The general average in the state for the proportion of T:V (calf: cow) is 57 calves per 100 cows, and this is close to the national average. Discussion: About 60.62% of cattle herds consisted of animals aged over 24 months, and most of this group were females over 36 months of age (38.95%). About 50% of properties have up to 10 animals, demonstrating a large proportion of small farms. RS has an imbalance in its production system, with a large number of breeding females for the activity of beef production. The cattle in RS are mostly bred for the production of beef in a full cycle system (with all stages of production on the property), and only 10% of cattle raised in RS are bred solely for milk production. With regard to the proportion of T:V, we concluded that the state’s beef production shows modest productivity and needs to improve production rates to increase financial returns for producers and enable competitiveness in the domestic and international markets. Furthermore, this information correlates with previous studies that have reported that farms in the business of beef production use low technology and low performance animals. Dairy farming, in contrast with beef farming, has been modernizing and developing in recent years by increasing co-operatives and agribusinesses, which has led to greater knowledge through technical assistance to the farms. Extensive farming is dependent on field areas and is historically associated with the natural fields in the campaign region, since dairy farming is dependent on areas where there is a supply of specialized food. Thus, despite the state having a greater concentration of animals in the south-southwest, production indices are similar to other regions, and the type of farming undertaken exerts a great influence on the regional animal population structure.

Nexus format phylogenetic tree. Hemagglutinin H3 Subtype Reference Sequences. Reference sequences used for determining the clade an H3 subtype hemagglutinin sequence falls into. (TXT 29 kb)

O presente artigo tem como objetivo identificar e apresentar uma solução eficiente para a problemática dos odores presentes em resinas recicladas de polipropileno (PP) utilizadas no reaproveitamento de materiais plásticos. Observa-se que o aroma característico dos componentes poliméricos se intensifica conforme aumenta o número de vezes em que o PP é submetido ao processo de reciclagem, comprometendo a qualidade sensorial do material final. Com base em pesquisas existentes e em métodos científicos descritos em outros trabalhos acadêmicos, foi conduzido um processo de minimização de odor aplicado às resinas recicladas. A metodologia adotada permitiu avaliar técnicas de redução e controle de odores, resultando em uma melhora significativa no cheiro do material obtido após o tratamento. Os resultados demonstram que a aplicação de procedimentos adequados é capaz de reduzir de forma efetiva os odores residuais no PP reciclado, contribuindo para o aprimoramento de sua qualidade e ampliando suas possibilidades de reaproveitamento. Conclui-se que a solução proposta é viável e apresenta desempenho relevante para o avanço de práticas sustentáveis no processamento de materiais plásticos.

The evolution and spread of SARS-CoV-2 variants have driven successive waves of global COVID-19 outbreaks, yet the longitudinal dynamics of intrahost variation within the same patient remain less clear. We conducted a longitudinal cohort study by deep sequencing 198 swab samples collected from COVID-19 patients with varying infection durations. Our analysis showed that prolonged infections enhanced viral genomic diversity, leading to emergence of co-occurring variants that maintained high (>20%) frequency and became dominant in virus populations. We observed heterogeneous intrahost dynamics among individual patients, 2 of whom exhibited a minor variant of the spike D614G substitution over the course of infection. The increase in intrahost variants strongly correlated with prolonged infections, highlighting the complex interplay between viral diversity and host factors. This study revealed the intricate evolutionary mechanisms driving the emergence of de novo variants and lineage dominance, which could inform development of effective vaccine candidates and strategies to protect public health.

The diversity of the 8 genes of influenza A viruses (IAV) in swine reflects introductions from nonswine hosts and subsequent antigenic drift and shift. Here, we curated a data set and present a pipeline that assigns evolutionary lineage and genetic clade to query gene segments.

Genetically distinct clades of influenza A virus (IAV) in swine undermine efforts to control the disease. Swine producers commonly use vaccines, and vaccine strains are selected by identifying the most common hemagglutinin (HA) gene from viruses detected in a farm or a region.

Foot and mouth disease (FMD) is a highly infectious disease that affects cloven-hoofed livestock and wildlife. FMD has been a problem for decades, which has led to various measures to control, eradicate and prevent FMD by National Veterinary Services worldwide. Currently, the identification of areas that are at risk of FMD virus incursion and spread is a priority for FMD target surveillance after FMD is eradicated from a given country or region. In our study, a knowledge-driven spatial model was built to identify risk areas for FMD occurrence and to evaluate FMD surveillance performance in Rio Grande do Sul state, Brazil. For this purpose, multi-criteria decision analysis was used as a tool to seek multiple and conflicting criteria to determine a preferred course of action. Thirteen South American experts analyzed 18 variables associated with FMD introduction and dissemination pathways in Rio Grande do Sul. As a result, FMD higher risk areas were identified at international borders and in the central region of the state. The final model was expressed as a raster surface. The predictive ability of the model assessed by comparing, for each cell of the raster surface, the computed model risk scores with a binary variable representing the presence or absence of an FMD outbreak in that cell during the period 1985 to 2015. Current FMD surveillance performance was assessed, and recommendations were made to improve surveillance activities in critical areas.

RESUMO: Foi realizado um levantamento nos arquivos do Laboratório de Patologia Veterinária (LPV) da Universidade Federal de Mato Grosso (UFMT) das doenças de bovinos registradas entre os anos 2005 a 2014. Foram revisados 1124 casos. Destes, 27,6% foram amostras obtidas de necropsias realizadas por técnicos do LPV-UFMT e 72,3% foram amostras encaminhadas ao LPV-UFMT por veterinários de campo. Em 49,38% dos casos (555/1124) o diagnóstico da doença foi feito através da análise morfológica de lesões e/ou através de exames complementares. Raiva foi a principal causa de morte de bovinos neste estudo (7,82%). As doenças inflamatórias e parasitárias foram as mais prevalentes sendo diagnosticadas em 27,49% dos casos, seguida das doenças tóxicas e toxiinfecções com 9,78%. As demais categorias foram distribuídas em ordem decrescente em: neoplasmas e lesões tumoriformes (4%), doenças degenerativas (3,02%), distúrbios causados por agentes físicos (2,84%), distúrbios metabólicos e nutricionais (1,42%) e outras categorias (0,71%).