Ultra-deep sequencing provides insights into the virology of hepatitis C super-infections in a case of three sequential infections with different genotypes

The current epidemic of Hepatitis C infection in HIV-positive men who have sex with men is associated with increasing use of recreational drugs. Multiple HCV infections have been reported in haemophiliacs and intravenous drug users. Using ultra-deep sequencing analysis, we present the case of an HIV-positive MSM with evidence of three sequential HCV infections, each occurring during the acute phase of the preceding infection, following risk exposures. We observed rapid replacement of the original strain by the incoming genotype at subsequent time points. The impact of HCV super-infection remains unclear and UDS may provide new insights.

Are Deep Learning Approaches Suitable for Natural Language Processing?

In recent years, Deep Learning (DL) techniques have gained much at-tention from Artificial Intelligence (AI) and Natural Language Processing (NLP) research communities because these approaches can often learn features from data without the need for human design or engineering interventions. In addition, DL approaches have achieved some remarkable results. In this paper, we have surveyed major recent contributions that use DL techniques for NLP tasks. All these reviewed topics have been limited to show contributions to text understand-ing, such as sentence modelling, sentiment classification, semantic role labelling, question answering, etc. We provide an overview of deep learning architectures based on Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Recursive Neural Networks (RNNs).