Inspired by mussel-adhesion phenomena in nature, we present a simple, mild and green method to prepare polystyrene/Ag (PS/Ag) nanocomposite particles with enhanced antibacterial activities. In this approach, monodisperse polystyrene particles are used as template spheres, which are then coated with polydopamine (PDA) through the self-polymerization of dopamine in a weakly alkaline aqueous environment (pH ¼ 8.5). Silver precursor-[Ag(NH 3 ) 2 ] + ions are added and absorbed onto the surfaces of the PS/PDA composite spheres by the active catechol and amine groups of the polydopamine coating. Meanwhile, these adsorbed [Ag(NH 3 ) 2 ] + ions are in situ reduced into metallic silver nanoparticles by the "bridge" of the polydopamine coating, and the formed Ag nanoparticles are home positioned. As polydopamine is an environmentally friendly reagent with abilities as a universal adhesive to any surface and as a mild reductant for noble metal salts, because of its abundant active catechol and amine groups, neither additional reducing and toxic reagents nor special surface modifications of the template are needed in this procedure. Moreover, preliminary antibacterial assays indicate that these PS/Ag nanocomposite particles show enhanced antibacterial activities against Escherichia coli (Gram-negative bacteria) and Staphylococcus aureus (Gram-positive bacteria), while they do not show significant in vitro cytotoxicity against HEK293T human embryonic kidney cells. These results suggest that these PS/Ag nanocomposite particles could be promising antibacterial materials for future biomedical applications.

Maize (Zea mays) is an important C 4 plant due to its widespread use as a cereal and energy crop. A second-generation genomescale metabolic model for the maize leaf was created to capture C 4 carbon fixation and investigate nitrogen (N) assimilation by modeling the interactions between the bundle sheath and mesophyll cells. The model contains gene-protein-reaction relationships, elemental and charge-balanced reactions, and incorporates experimental evidence pertaining to the biomass composition, compartmentalization, and flux constraints. Condition-specific biomass descriptions were introduced that account for amino acids, fatty acids, soluble sugars, proteins, chlorophyll, lignocellulose, and nucleic acids as experimentally measured biomass constituents. Compartmentalization of the model is based on proteomic/transcriptomic data and literature evidence. With the incorporation of information from the MetaCrop and MaizeCyc databases, this updated model spans 5,824 genes, 8,525 reactions, and 9,153 metabolites, an increase of approximately 4 times the size of the earlier iRS1563 model. Transcriptomic and proteomic data have also been used to introduce regulatory constraints in the model to simulate an N-limited condition and mutants deficient in glutamine synthetase, gln1-3 and gln1-4. Model-predicted results achieved 90% accuracy when comparing the wild type grown under an N-complete condition with the wild type grown under an N-deficient condition.

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