Coxsackievirus A6 (CVA6) has emerged as a major pathogen causing hand, foot and mouth disease (HFMD) outbreaks worldwide. The CVA6 epidemic poses a new challenge in HFMD control since there is currently no vaccine available against CVA6 infections. The Vero cell line has been widely used in vaccine production, particularly in the preparation of viral vaccines, including poliovirus vaccines and EV71 vaccines.
View Article and Find Full Text PDFA previous study classifies solid tumors based on collagen deposition and immune infiltration abundance, identifying a refractory subtype termed armored & cold tumors, characterized by elevated collagen deposition and diminished immune infiltration. Beyond its impact on immune infiltration, collagen deposition also influences tumor angiogenesis. This study systematically analyzes the association between immuno-collagenic subtypes and angiogenesis across diverse cancer types.
View Article and Find Full Text PDFCofactors are non-protein entities necessary for proteins to operate. They provide "functional groups" beyond those of the 20 canonical amino acids and enable proteins to carry out more diverse functions. Such a viewpoint is rarely mentioned, if at all, when it comes to natural products and is the theme of this Concept.
View Article and Find Full Text PDFThe global quest for clean energy and sustainable processes makes advanced membrane extremely attractive for energy-intensive industrial gas separations. Here, we disclosed a series of ultra-high-performance gas separation membranes (PIM-3D-TB) from novel network polymers of intrinsic microporosity (PIM) that combine the advantages of solution processible PIM and small pore size distribution (PSD) of porous organic polymers (POP), which was synthesized by in situ copolymerization of triptycene-2,6-diamine as linear part and triptycene-2,6,13(14)-triamine (TTA) as crosslinker. The resulting PIM-3D-TB membranes demonstrated outstanding separation properties that outperformed the latest trade-off lines for H/CH and O/N.
View Article and Find Full Text PDFHigh-performance strain and corresponding fermentation process are essential for achieving efficient biomanufacturing. However, conventional offline detection methods for products are cumbersome and less stable, hindering the "Test" module in the operation of "Design-Build-Test-Learn" cycle for strain screening and fermentation process optimization. This study proposed and validated an innovative research paradigm combining computer vision with deep learning to facilitate efficient strain selection and effective fermentation process optimization.
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