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MotivationThe application of machine learning (ML) techniques in the medical field has demonstrated both successes and challenges in the precision medicine era. The ability to accurately classify a subject as a potential responder versus a nonresponder to a given therapy is still an active area of research pushing the field to create new approaches for applying machine-learning techniques. In this study, we leveraged publicly available data through the BeatAML initiative. Specifically, we used gene count data, generated via RNA-seq, from 451 individuals matched with ex vivo data generated from treatment with RTK-type-III inhibitors. Three feature selection techniques were tested, principal component analysis, Shapley Additive Explanation (SHAP) technique and differential gene expression analysis, with three different classifiers, XGBoost, LightGBM and random forest (RF). Sensitivity versus specificity was analyzed using the area under the curve (AUC)-receiver operating curves (ROCs) for every model developed.ResultsOur work demonstrated that feature selection technique, rather than the classifier, had the greatest impact on model performance. The SHAP technique outperformed the other feature selection techniques and was able to with high accuracy predict outcome response, with the highest performing model: Foretinib with 89% AUC using the SHAP technique and RF classifier. Our ML pipelines demonstrate that at the time of diagnosis, a transcriptomics signature exists that can potentially predict response to treatment, demonstrating the potential of using ML applications in precision medicine efforts.Availability and implementationhttps://github.com/UD-CRPL/RCDML.Supplementary informationSupplementary data are available at Bioinformatics Advances online.

El autor cita por primera vez para la Argentina los siguientes Cladoceros: Latonopsis breviremis Daday 1905, L. fasciculata Daday 1905; Dunhevedia odonthoplax Sars 1901, Chydorus globosus Baird 1850, cap. barroisi (Richard) 1894 y cap. hybridus Daday 1905. Los géneros Latonopsis Sars 1888 y Dunhevedia King 1853 también son nuevos para Argentina y todos han sido encontrados en aguas llenas de maleza de la cuenca del Paraná medio.

Se realizaron investigaciones con el fin de establecer la existencia de migraciones verticales y horizontales de zooplancton en algunos cuerpos de agua de la cuenca del Paraná medio y si este factor afectaría las estimaciones de cultivos en pie cuando solo se toman muestras superficiales, como es habitual en aguas poco profundas. Para ello se tomaron muestras en dos cuerpos de agua de diferentes características en diferentes lugares, niveles y horas, especialmente en lo referente a su extensión, profundidad e hidrofitia. Las observaciones indican un movimiento vertical evidente e irregularidades en la distribución horizontal que deben tenerse en cuenta cuando se desean resultados cuidadosos.

Air-breathing electric propulsion has the potential to enable space missions at very low altitudes. This study introduces to a 0D hybrid formulation for describing the coupled intake and thruster physics of an air-breathing electric propulsion prototype. Model derivation is then used to formally derive main system’s key performance indicators and estimate the figure of merit for the design of rarefied flow air intakes. Achievable performance by conical intake shapes are defined and evaluated by Monte Carlo simulations. Influence of inlet flow variation is assessed by dedicated sensitivity analyses. The set of requirements and optimality conditions derived for the downstream plasma thruster suggest concept feasibility within an achievable performance range.

A taxa de mortalidade média por infarto agudo do miocárdio do sexo mascu-lino e feminino, respectivamente, é de 108 óbitos a cada 100 mil homens, e 62 mortes a cada 100 mil mulheres. Diante disso, é importante a implementação de novas aborda-gens médicas, que sejam efetivas para a diminuição desses dados estatísticos. Nesse sentido, a telemedicina, em conjunto com os meios de comunicação atuais, mostra-se como uma grande aliada na prevenção dessa cardiopatia, no que tange à prevenção da doença e aos achados clínicos antecipados. Assim, descrevera eficácia da telemedicina no tratamento e prevenção de doenças cardiogênicas através de uma revisão de litera-tura a partir de 22 artigos redigidos em língua inglesa obtidos das bases de dados do PubMed, selecionados utilizando-se os Descritores em Ciência da Saúde (DeCS): “mHealth”, “eHealth” e “heart attack”, com critério de data de publicação entre 2014 e 2019. Os resultados foram baseados nas mudanças fisiológicas e na consequente redu-ção da morbimortalidade cardiogênica quando associada à telemedicina, em compara-ção com os cuidados médicos tradicionais. Nesse contexto, vale mencionar que o mé-todo mais eficiente, no que diz respeito às vertentes da telemedicina, foi o envio de men-sagens de texto aos usuários, lembrando-os de se exercitarem, de aderirem às dietas propostas e de cessarem, gradativamente, o uso de tabaco. Tangente a isso, é impor-tante ressaltar que a inserção dessa tecnologia na rotina desses pacientes proporcionou a redução dos níveis de glicemia em jejum, diminuição dos valores de pressão arterial, bem como a normalização do Índice de Massa Corporal (IMC). Em outro viés, o eletro-cardiograma, em consonância com a telemedicina reduz em 20% o tempo de conclusão de talexame, o que aumenta as chances de um diagnóstico antecipado. Logo, diante do exposto, constatou-se que a telemedicina pode ser usada como uma alternativa inova-dora, tanto para o controle da mortalidade de cardiopatas, quanto para o aumento da qualidade de vida da sociedade, visto que também pode prevenir fisiopatologias.

Experimental chemical shifts (CS) from solution and solid state magic-angle-spinning nuclear magnetic resonance (NMR) spectra provide atomic level information for each amino acid within a protein or protein complex. However, structure determination of large complexes and assemblies based on NMR data alone remains challenging due to the complexity of the calculations. Here, we present a hardware accelerated strategy for the estimation of NMR chemical-shifts of large macromolecular complexes based on the previously published PPM_One software. The original code was not viable for computing large complexes, with our largest dataset taking approximately 14 hours to complete. Our results show that serial code refactoring and parallel acceleration brought down the time taken of the software running on an NVIDIA Volta 100 (V100) Graphic Processing Unit (GPU) to 46.71 seconds for our largest dataset of 11.3 million atoms. We use OpenACC, a directive-based programming model for porting the application to a heterogeneous system consisting of x86 processors and NVIDIA GPUs. Finally, we demonstrate the feasibility of our approach in systems of increasing complexity ranging from 100K to 11.3M atoms.

Non-O157 serogroups contribute significantly to the burden of disease caused by Shiga toxin-producing Escherichia coli (STEC) and have been underrecognized by traditional detection algorithms. We described the epidemiology of non-O157 STEC in Alberta, Canada for the period of 2018 to 2021. All non-O157 STEC isolated from clinical samples were submitted for serotyping and qPCR targeting the stx1 and stx2 genes. A total of 729 isolates were identified. Increased detection occurred over the summer months, peaking in July. Patients 18 years and younger made up 42.4% of cases, with 31.1% in those 0–9 years of age. There was a slight female predominance (399/729, 54.7%) A total of 50 different serogroups were detected; the most common were O26 (30.3%), O103 (15.9%), O111 (12.8%), O121 (11.0%), O118 (3.3%) and O71 (2.9%). These six serogroups made up 76.2% of all isolates. In total, 567 (77.8%) were positive for stx1, 114 (15.6%) were positive for stx2 and 48 (6.6%) were positive for both stx1 and stx2. A wide variety of non-O157 serogroups have been detected in Alberta, with the most frequent serogroups differing from other locations. These results highlight the need for further characterization of their virulence factors and clinical impact.