Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.

In this work, nitrogen-doped, yolk-shell-structured CoSe/C mesoporous dodecahedra are successfully prepared by using cobalt-based metal-organic frameworks (ZIF-67) as sacrificial templates. The CoSe nanoparticles are in situ produced by reacting the cobalt species in the metal-organic frameworks with selenium (Se) powder, and the organic species are simultaneously converted into nitrogen-doped carbon material in an inert atmosphere at temperatures between 700 and 900 °C for 4 h. For the composite synthesized at 800 °C, the carbon framework has a relatively higher extent of graphitization, with high nitrogen content (17.65%). Furthermore, the CoSe nanoparticles, with a size of around 15 nm, are coherently confined in the mesoporous carbon framework. When evaluated as novel anode materials for sodium ion batteries, the CoSe/C composites exhibit high capacity and superior rate capability. The composite electrode delivers the specific capacities of 597.2 and 361.9 mA h g at 0.2 and 16 A g, respectively.

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A highly transparent and flexible percolative composite with magnetic reduced graphene oxide@nickel nanowire (mGN) fillers in EcoFlex matrix is proposed as a sensing layer to fabricate high-performance flexible piezoresistive sensors. Large excluded volume and alignment of mGN fillers contribute to low percolation threshold (0.27 vol %) of mGN-EcoFlex composites, leading to high electrical conductivity of 0.003 S m–1, optical transmittance of 71.8%, and low Young’s modulus of 122.8 kPa. Large-scale microdome templates for sensors are prepared by hot embossing technology cost-effectively and COMSOL Multiphysics is utilized to optimize the sensor performances. Piezoresistive sensors fabricated experimentally show superior average sensitivity of 1302.1 kPa–1 with a low device-to-device variation of 3.74%, which provides a new way to achieve transparent, highly sensitive, and large-scale electronic skin.

High performance flexible pressure sensors with tunable piezoresistivity are proposed with percolative composites as single sensing layer using micro-nickel (μNi) wires as conductive filler and polydimethylsiloxane (PDMS) as matrix. The...

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Porous materials have attracted great attention in recent years, and a variety of surface modification techniques have been developed. Herein, a layer of non-noble metal nickel was deposited onto mine-formaldehyde sponges by an electroless depositing process which uses poly(4-vinylpyridine) as an assisted functional layer and Ag nanoparticles as catalytic seeds for the metal growth. The hydrophobic metallized sponges can selectively adsorb oils from oil−water mixtures and achieve dynamic oil−water separation. The as-made metallized sponges also feature good mechanical stability, flexibility, and conductivity. A piezoresistive sensor based on the metallized sponges is fabricated, which exhibits excellent sensing performance with sensitivity of 212.9 kPa −1 in the range of less than 2 kPa. The sensors can be further applied to monitor dynamic postures of human body. Moreover, the metallized sponges show great potential as electromagnetic interference shielding and thermal conductive materials. This work provides a facile and efficient way to introduce a non-noble metal to porous materials toward multifunctional applications in fields of oil−water separation, wearable electronics, and electromagnetic shielding equipment.

Ni@Ag core shell nanowires (NWs) were prepared by in situ chemical reduction of Ag + around NiNWs as the inner core. Different Ni@Ag NWs with controllable morphologies were achieved through the layer-plus-island growth mode and this mechanism was confirmed by scanning electron microscopy, X-ray fluorescence, and X-ray photoelectron spectroscopy analyses. When used as a catalyst, the synthesized Ni@Ag NWs exhibited high reduction efficiency by showing a high reaction rate constant k of 0.408 s −1 in reducing 4-nitrophenol at room temperature. Besides, combining the magnetic property, including high saturation magnetization and low coercivity, the magnetic NiNW core contributes to excellent recyclability and long-term stability with only a 2.2% performance loss after 10 recycles by magnets. The Ni@Ag NWs proposed here show unprecedentedly high potential in applications requiring high efficiency and a recyclable catalyst.