ANÁLISE GENÔMICA DE ACINETOBACTER BAUMANII RESISTENTE AOS CARBAPENÊMICOS ISOLADOS NA REGIÃO AMAZÔNICA: RESULTADOS DA PLATAFORMA GENERATE

Introdução: Acinetobacter baumannii resistentes aos Carbapenêmicos (CRAB) é atualmente um dos principais problemas de saúde pública do mundo, e é considerado pela Organização Mundial da Saúde (OMS) como um patógeno prioritário para pesquisa e desenvolvimento de novos antimicrobianos. Frente a isso, é importante compreender as características genômicas dessas linhagens que estão circulando nos hospitais. No Brasil, ainda existe uma escassez desses dados, principalmente na região norte do país. Diante disso, está sendo criada a plataforma GENERATE que tem como objetivo disponibilizar dados genômicos de bacilos gram-negativos multirresistentes do Brasil. Diante disso o objetivo do trabalho foi analisar as características genômicas de isolados de CRAB isolados no estado de Rondônia incluídos no projeto GENERATE. Metodologia: Nove isolados de CRAB recuperados de hemocultura (n=4) e aspirado traqueal (n=5) de dois hospitais de Porto Velho – RO foram sequenciados utilizando Illumina HiSeq 2500. A montagem e anotação de novo foram realizadas usando os softwares SPAdes e Prokka, respectivamente. O Sequence Type (ST) e análise filogenética foi realizada na plataforma CGE e o resistoma foi obtido no CARD. Resultados: Nossas análises identificaram a presença de cinco STs, sendo eles: ST79 (n=3), ST160 (n=1), ST8554(n=1), ST1 (n=1), e ST2 (n=1). Além disso, dois isolados apresentaram novos STs. Também foi verificado a presença de genes de conferem resistência aos β-lactâmicos (blaTEM-1, blaADC-Like, blaOXA-51-Like, blaOXA-23, blaGES-5), aminoglicosídeos (aac(6’)-ib’, ant(2’’)-Ia, ant(3’’)IIc, aph(3’)-Via, aph(3’’)-Ib, aph(6)Id, aadA, armA), trimetoprima (dfrA1), macrolídeos (mphE, msrE), anfenicóis (florR, catB8), tetraciclinas (tet(B)) e mutações que conferem resistências as quinolonas (gyrA S81L; parC S84L, V104I, D105E). Todos os CRAB possuíam OXA-23, e curiosamente, um isolado também carreava o gene codificador da carbapenemase GES-5, sendo esse até onde sabemos, o segundo relato no mundo. A análise filogenética mostrou que os três isolados ST79 estavam intimamente relacionados, assim como os dois isolados que pertencem a um novo ST. Conclusão: Os dados aqui apresentados revelam uma diversidade de genes que conferem resistência a diversas classes de antimicrobianos. Além disso, identificamos a presença do ST2 que não é muito frequente no Brasil e uma linhagem ST1 co-abrigando blaOXA-23 e blaGES-5. Esses dados reforçam a variabilidade genética de CRAB na Amazôni

Rectal cancer survival in a Brazilian Cancer Reference Unit

ABSTRACT Colorectal cancer is one of the most common malign tumors in men and women all over the world. In spite of prevention advances in the last few years, worldwide incidence remains significant, about one million per year. Objectives: Evaluate rectal cancer survival in patients diagnosed and surgically treated at the Cancer Reference Unit at Rio Grande do Norte State, Brazil. Methods: Observational retrospective study composed by 135 patients assisted from 2007 to 2014 at Doctor Luiz Antonio Hospital, Natal, Brazil. Data were collected from the patient records revision and survival rates were calculated and analyzed by non-parametric Kaplan-Meier and Wilcoxon tests, respectively. All patients were submitted to surgical treatment, chemotherapy and/or radiotherapy. Results: Overall survival was 62% in seven years, while disease-free survival in one, three and five years was 91.7%, 75.5% and 72.1%, respectively. Conclusion: Overall survival and disease-free survival remained enhanced until the end of the study, suggesting that the treatment protocols used in the institution have shown to be effective

Structural Health Monitoring of Dams Based on Acoustic Monitoring, Deep Neural Networks, Fuzzy Logic and a CUSUM Control Algorithm

Internal erosion is the most important failure mechanism of earth and rockfill dams. Since this type of erosion develops internally and silently, methodologies of data acquisition and processing for dam monitoring are crucial to guarantee a safe operation during the lifespan of these structures. In this context, artificial intelligence techniques show up as tools that can simplify the analysis and verification process not of the internal erosion itself, but of the effects that this pathology causes in the response of the dam to external stimuli. Therefore, within the scope of this paper, a methodological framework for monitoring internal erosion in the body of earth and rockfill dams will be proposed. For that, artificial intelligence methods, especially deep neural autoencoders, will be used to treat the acoustic data collected by geophones installed on a dam. The sensor data is processed to identify patterns and anomalies as well as to classify the dam’s structural health status. In short, the acoustic dataset is preprocessed to reduce its dimensionality. In this process, for each second of acquired data, three parameters are calculated (Hjorth parameters). For each parameter, the data from all the available sensors are used to calibrate an autoencoder. Then, the reconstruction error of each autoencoder is used to monitor how far from the original (normal) state the acoustic signature of the dam is. The time series of reconstruction errors are combined with a cumulative sum (CUSUM) algorithm, which indicates changes in the sequential data collected. Additionally, the outputs of the CUSUM algorithms are treated by a fuzzy logic framework to predict the status of the structure. A scale model is built and monitored to check the effectiveness of the methodology hereby developed, showing that the existence of anomalies is promptly detected by the algorithm. The framework introduced in the present paper aims to detect internal erosion inside dams by combining different techniques in a novel context and methodological workflow. Therefore, this paper seeks to close gaps in prior studies, which mostly treated just parts of the data acquisition–processing workflow