Our results support that H5N6 virus could potentially be a major public health threat, and suggest it is possible that the earlier acquisition of cellular immunity and lower concentrations of cytokines/chemokines contributed to survival in our patient. Analysis of more patient samples will be needed to draw concrete conclusions.
We report the first imported case of Rift Valley fever (RVF) in China. The patient returned from Angola, a non-epidemic country, with an infection of a new reassortant from different lineages of Rift Valley fever viruses (RVFVs). The patient developed multiorgan dysfunction and gradually recovered with continuous renal replacement therapy and a short regimen of methylprednisolone treatment. The disordered cytokines and chemokines in the plasma of the patient revealed hypercytokinemia, but the levels of protective cytokines were low upon admission and fluctuated as the disease improved. Whole-genome sequencing and phylogenetic analysis revealed that the imported strain was a reassortant comprising the L and M genes from lineage E and the S gene from lineage A. This case highlights that RVFV had undergone genetic reassortment, which could potentially alter its biological properties, cause large outbreaks and pose a serious threat to global public health as well as the livestock breeding industry.
We propose a general learning based framework for solving nonsmooth and nonconvex image reconstruction problems. We model the regularization function as the composition of the l2,1 norm and a smooth but nonconvex feature mapping parametrized as a deep convolutional neural network. We develop a provably convergent descent-type algorithm to solve the nonsmooth nonconvex minimization problem by leveraging the Nesterov's smoothing technique and the idea of residual learning, and learn the network parameters such that the outputs of the algorithm match the references in training data. Our method is versatile as one can employ various modern network structures into the regularization, and the resulting network inherits the guaranteed convergence of the algorithm. We also show that the proposed network is parameter-efficient and its performance compares favorably to the state-of-the-art methods in a variety of image reconstruction problems in practice.
The H5N1 avian influenza virus causes severe disease and high mortality, making it a major public health concern worldwide. The virus uses the host cellular machinery for several steps of its life cycle. In this report, we observed overexpression of the ubiquitin-like protein FAT10 following live H5N1 virus infection in BALB/c mice and in the human respiratory epithelial cell lines A549 and BEAS-2B. Further experiments demonstrated that FAT10 increased H5N1 virus replication and decreased the viability of infected cells. Total RNA extracted from H5N1 virus–infected cells, but not other H5N1 viral components, upregulated FAT10, and this process was mediated by the retinoic acid–induced protein I-NF-κB signaling pathway. FAT10 knockdown in A549 cells upregulated type I IFN mRNA expression and enhanced STAT1 phosphorylation during live H5N1 virus infection. Taken together, our data suggest that FAT10 was upregulated via retinoic acid–induced protein I and NF-κB during H5N1 avian influenza virus infection. And the upregulated FAT10 promoted H5N1 viral replication by inhibiting type I IFN.
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