Glucose enzyme biosensors have been shown useful for a range of applications from medical diagnosis, bioprocess monitoring, to beverage industry and environmental monitoring. We present here a highly sensitive glucose enzyme sensor based on Pt nanoparticles (PtNPs)-polyaniline (PAni) hydrogel heterostructures. High-density PtNPs were homogeneously loaded onto the three-dimensional (3D) nanostructured matrix of the PAni hydrogel. The PtNP/PAni hydrogel heterostructure-based glucose sensor synergizes the advantages of both the conducting hydrogel and the nanoparticle catalyst. The porous structure of the PAni hydrogel favored the high density immobilization of the enzyme and the penetration of water-soluble molecules, which helped efficiently catalyze the oxidation of glucose. In addition, the PtNPs catalyzed the decomposition of hydrogen peroxide that was generated during the enzymatic reaction. The transferred charges from these electrochemical processes were efficiently collected by the highly conducting PtNP/PAni hydrogel heterostructures. The glucose enzyme sensor based on this heterostructure exhibited unprecedented sensitivity, as high as 96.1 μA·mM(-1)·cm(-2), with a response time as fast as 3 s, a linear range of 0.01 to 8 mM, and a low detection limit of 0.7 μM.

Superhydrophobic surfaces are of immense scientific and technological interests for a broad range of applications. However, a major challenge remains in developing scalable methodologies that enable superhydrophobic coatings on versatile substrates with a combination of strong mechanical stability, optical transparency, and even stretchability. Herein, we developed a scalable methodology to versatile hydrophobic surfaces that combine with strong mechanical stability, optical transparency, and stretchability by using a self-assembled hydrogel as the template to in situ generate silica microstructures and subsequent silanization. The superhydrophobic coatings can be enabled on virtually any substrates via large-area deposition techniques like dip coating. Transparent surfaces with optical transmittance as high as 98% were obtained. Moreover, the coatings exhibit superior mechanical flexibility and robustness that it can sustain contact angles ∼ 160° even after 5000 cycles of mechanically stretching at 100% strain. The multifunctional surfaces can be used as screen filters and sponges for the oil/water separation that can selectively absorb oils up to 40× their weight.

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Organisms usually cope with change in the environment by altering the dynamic trajectory of gene expression to adjust the complement of active proteins. The identification of particular sets of genes whose expression is adaptive in response to environmental changes helps to understand the mechanistic base of gene-environment interactions essential for organismic development. We describe a computational framework for clustering the dynamics of gene expression in distinct environments through Gaussian mixture fitting to the expression data measured at a set of discrete time points. We outline a number of quantitative testable hypotheses about the patterns of dynamic gene expression in changing environments and gene-environment interactions causing developmental differentiation. The future directions of gene clustering in terms of incorporations of the latest biological discoveries and statistical innovations are discussed. We provide a set of computational tools that are applicable to modeling and analysis of dynamic gene expression data measured in multiple environments.