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Humidity alarm switches, smart doors, and wound healing devices based on the programmable contractile actuations of the spider silk yarns were demonstrated, which provide application scenarios for the supercontraction of spider dragline silk.The precise determination of affinity and specificity is a crucial step in the development of new protein reagents for therapy and diagnostics. Paradoxically, the selection of protein binders, e.g., antibody fragments, from large combinatorial repertoires is a rapid process compared to the subsequent characterization of selected clones. Here we demonstrate the use of suspension bead arrays (SBA) in combination with flow cytometry to facilitate the post-selection analysis of binder affinities. The array is designed to capture the proteins of interest (POIs) covalently on the surface of superparamagnetic color-coded microbeads directly from expression cell lysate, based on SpyTag-SpyCatcher coupling by isopeptide bond formation. This concept was validated by analyzing the affinities of a typical phage display output, i.e., clones consisting of single-chain variable fragment antibodies (scFvs), as SpyCatcher fusions in 12- and 24-plex SBA formats using a standard three-laser flow cytometer. We demonstrate that the equilibrium dissociation constants (Kd) obtained from multiplexed SBA assays correlate well with experiments performed on a larger scale, while the antigen consumption was reduced >100-fold compared to the conventional 96-well plate format. Protein screening and characterization by SBAs is a rapid and reagent-saving analytical format for combinatorial protein engineering to address specificity maturation and cross-reactivity profiling of antibodies.Bacterial infections have been increasingly recognized as the major reason for the failure of tissue engineering scaffolds. Therefore, there is a need for novel and multifunctional biomaterials that not only enhance tissue regeneration but also can combat infections. An antibacterial and bioactive scaffold was fabricated in this study by incorporation of honey and a nitric oxide (NO) donor, S-nitroso-N-acetyl-penicillamine (SNAP), into polylactic acid (PLA) nanofibers using a single-jet electrospinning method. The morphology of the prepared nanofibers was observed using a scanning electron microscope. PLA/honey/SNAP (PLA/HN/SNAP) nanofibers had an average diameter of 624.92 ± 137.69 nm and showed a sustained release of NO for 48 h. The scaffolds were characterized for their chemical composition via Fourier-transform infrared spectroscopy. Moreover, the tensile properties of nanofibers along with their wettability, water retention ability, and water vapor transmission rate were evaluated. The results of antibacterial studies revealed that the synergistic combination of honey and SNAP significantly reduced the viability of Gram positive Staphylococcus aureus and Gram negative Escherichia coli. In addition, qualitative and quantitative 3T3 fibroblast cell culturing experiments proved that the PLA/HN/SNAP scaffolds supported better cell attachment and proliferation compared to PLA. The promising results obtained in this study indicate that PLA/HN/SNAP nanofibrous scaffolds have great potential for tissue engineering applications.The freeze casting process has been widely used for fabricating aerogels due to its versatile and environmentally friendly nature. This process offers a variety of tools to tailor the entire micropore morphology of the final product in a monolithic fashion through manipulation of the freezing kinetics and precursor suspension chemistry. However, aerogels with nonmonolithic micropore morphologies, having pores of various sizes located in certain regions of the aerogels, are highly desired by certain applications such as controlled drug-delivery, bone tissue engineering, extracellular simulation, selective liquid sorption, immobilized catalysts, and separators. Furthermore, aerogels composed of micropores with predesigned size, shape, and location can open up a new paradigm in aerogel design and lead to new applications. selleck products In this study, a general manufacturing approach is developed to control the size, shape, and location of the pores on the aerogel surface by applying a precise control on the local thermal cond conductivity of the substrates.MXene, a new state-of-the-art two-dimensional (2D) nanomaterial, has attracted considerable interest from both industry and academia because of its excellent electrical, mechanical, and chemical properties. However, MXene-based device engineering has rarely been reported. In this study, we explored Ti3C2 MXene for digital and analog computing applications by engineering the top electrode. For this purpose, Ti3C2 MXene was synthesized by a simple chemical process, and its structural, compositional, and morphological properties were studied using various analytical tools. Finally, we explored its potential application in bipolar resistive switching (RS) and synaptic learning devices. In particular, the effect of the top electrode (Ag, Pt, and Al) on the RS properties of the Ti3C2 MXene-based memory devices was thoroughly investigated. Compared with the Ag and Pt top electrode-based devices, the Al/Ti3C2/Pt device exhibited better RS and operated more reliably, as determined by the evaluation of the charge-magnetic property and memory endurance and retention. Thus, we selected the Al/Ti3C2/Pt memristive device to mimic the potentiation and depression synaptic properties and spike-timing-dependent plasticity-based Hebbian learning rules. Furthermore, the electron transport in this device was found to occur by a filamentary RS mechanism (based on oxidized Ti3C2 MXene), as determined by analyzing the electrical fitting curves. The results suggest that the 2D Ti3C2 MXene is an excellent nanomaterial for non-volatile memory and synaptic learning applications.Polarization switching mechanisms in ferroelectric materials are fundamentally linked to local domain structure and the presence of the structural defects, which both can act as nucleation and pinning centers and create local electrostatic and mechanical depolarization fields affecting wall dynamics. However, the general correlative mechanisms between domain structure and polarization dynamics are only weakly explored, precluding insight into the associated physical mechanisms. Here, the correlation between local domain structures and switching behavior in ferroelectric materials is explored using convolutional encoder-decoder networks, enabling image to spectral (im2spec) and spectral to image (spec2im) translations via encoding of latent variables. The latter reflect the assumption that the relationship between domain structure and polarization switching is parsimonious, i.e., is based upon a small number of local mechanisms. The analysis of latent variables distributions and their real-space representations provides insight into the predictability of the local switching behavior and hence associated physical mechanisms.