Hydrogel electrolytes have spurred the development of flexible energy storage devices by endowing them with liquid‐like ion transport and solid‐like mechanical elasticity. However, traditional ...hydrogel electrolytes always lose these functions in climate change because the internal water undergoes freezing and/or dehydration. In this work, a flexible supercapacitor (OHEC) is assembled based on the organohydrogel electrolyte (OHE) and activated carbon electrode material. The OHE is composed of PAMPS/PAAm double‐network hydrogel soaked from 4 m LiCl/ethylene glycol and exhibits good conductivities (1.9 and 22.9 mS cm−1 at −20 and 25 °C, respectively). The OHEC exhibits broad temperature adaptability (from −20 to 80 °C) and extraordinary resistance to mechanical damage (above 100 kg crushing). The OHEC avoids the polarization at low temperatures and retains 77.8% capacitance retention after storage at −20 °C for 30 days. Without extra sealed packaging, the OHEC maintains remarkable cycling stability (only 8.7% capacitance decay after 10 000 cycles) and retains 77.3% capacitance at 80 °C after 56 h. The outstanding anti‐drying performance and improved interfacial compatibility of OHEC account for the good durability in the high‐temperature environments. Additionally, other salts (such as LiClO4, NaCl, and KCl) with favorable solubility in ethylene glycol can also serve in OHEs for wide temperature range supercapacitors.
A flexible organohydrogel electrolyte‐based supercapacitor (OHEC) is assembled with a PAMPS/PAAm double‐network organohydrogel and activated carbon. Compared to the hydrogel electrolyte‐based supercapacitor, the OHEC exhibits broad temperature adaptability (from −20 to 80 °C) due to the improvement of interfacial compatibility as well as the inhibition of electrochemical polarization and water evaporation.
Current cancer therapy is seriously challenged by tumor metastasis and recurrence. One promising solution to these problems is to build antitumor immunity. However, immunotherapeutic efficacy is ...highly impeded by the immunosuppressive state of the tumors. Here a new strategy is presented, catalytic immunotherapy based on artificial enzymes. Cu2−xTe nanoparticles exhibit tunable enzyme‐mimicking activity (including glutathione oxidase and peroxidase) under near‐infrared‐II (NIR‐II) light. The cascade reactions catalyzed by the Cu2−xTe artificial enzyme gradually elevates intratumor oxidative stress to induce immunogenic cell death. Meanwhile, the continuously generated oxidative stress by the Cu2−xTe artificial enzyme reverses the immunosuppressive tumor microenvironment, and boosts antitumor immune responses to eradicate both primary and distant metastatic tumors. Moreover, immunological memory effect is successfully acquired after treatment with the Cu2−xTe artificial enzyme to suppress tumor relapse.
Stressed out: Cu2−xTe nanoparticles are presented as a new artificial multienzyme with enzymatic activity reinforced by near‐infrared‐II (NIR‐II) light. Cu2−xTe catalyzes cascade reactions continuously and elevates intratumor oxidative stress, which not only eradicates primary tumors, but also reverses the tumor immunosuppressive (cold) state into a proinflammatory (hot) state to combat tumor metastasis and recurrence.
A black phosphorus (BP)‐based drug delivery system for synergistic photodynamic/photothermal/chemotherapy of cancer is constructed. As a 2D nanosheet, BP shows super high drug loading capacity and ...pH‐/photoresponsive drug release. The intrinsic photothermal and photodynamic effects of BP enhance the antitumor activities. The synergistic photodynamic/photothermal/chemotherapy makes BP‐based drug delivery system a multifunctional nanomedicine platform.
Iron, nitrogen‐codoped carbon (Fe−N−C) nanocomposites have emerged as viable electrocatalysts for the oxygen reduction reaction (ORR) due to the formation of FeNxCy coordination moieties. In this ...study, results from first‐principles calculations show a nearly linear correlation of the energy barriers of key reaction steps with the Fe magnetic moment. Experimentally, when single Cu sites are incorporated into Fe−N−C aerogels (denoted as NCAG/Fe−Cu), the Fe centers exhibit a reduced magnetic moment and markedly enhanced ORR activity within a wide pH range of 0–14. With the NCAG/Fe−Cu nanocomposites used as the cathode catalyst in a neutral/quasi‐solid aluminum–air and alkaline/quasi‐solid zinc–air battery, both achieve a remarkable performance with an ultrahigh open‐circuit voltage of 2.00 and 1.51 V, large power density of 130 and 186 mW cm−2, and good mechanical flexibility, all markedly better than those with commercial Pt/C or Pt/C‐RuO2 catalysts at the cathode.
First‐principles calculations show a nearly linear correlation of the energy barriers of critical oxygen reduction reaction (ORR) steps with the Fe magnetic moment of Fe‐N‐C composites. This is indeed observed when single Cu sites are incorporated into Fe−N−C aerogels, where the interactions between adjacent Fe−Cu 3d electrons result in a reduced magnetic moment of the Fe center and hence enhanced ORR activity.
Traditional saliency models usually adopt hand-crafted image features and human-designed mechanisms to calculate local or global contrast. In this paper, we propose a novel computational saliency ...model, i.e., deep spatial contextual long-term recurrent convolutional network (DSCLRCN), to predict where people look in natural scenes. DSCLRCN first automatically learns saliency related local features on each image location in parallel. Then, in contrast with most other deep network based saliency models which infer saliency in local contexts, DSCLRCN can mimic the cortical lateral inhibition mechanisms in human visual system to incorporate global contexts to assess the saliency of each image location by leveraging the deep spatial long short-term memory (DSLSTM) model. Moreover, we also integrate scene context modulation in DSLSTM for saliency inference, leading to a novel deep spatial contextual LSTM (DSCLSTM) model. The whole network can be trained end-to-end and works efficiently when testing. Experimental results on two benchmark datasets show that DSCLRCN can achieve state-of-the-art performance on saliency detection. Furthermore, the proposed DSCLSTM model can significantly boost the saliency detection performance by incorporating both global spatial interconnections and scene context modulation, which may uncover novel inspirations for studies on them in computational saliency models.
Piezoelectric materials, with their unique ability for mechanical‐electrical energy conversion, have been widely applied in important fields such as sensing, energy harvesting, wastewater treatment, ...and catalysis. In recent years, advances in material synthesis and engineering have provided new opportunities for the development of bio‐piezoelectric materials with excellent biocompatibility and piezoelectric performance. Bio‐piezoelectric materials have attracted interdisciplinary research interest due to recent insights on the impact of piezoelectricity on biological systems and their versatile biomedical applications. This review therefore introduces the development of bio‐piezoelectric platforms from a broad perspective and highlights their design and engineering strategies. State‐of‐the‐art biomedical applications in both biosensing and disease treatment will be systematically outlined. The relationships between the properties, structure, and biomedical performance of the bio‐piezoelectric materials are examined to provide a deep understanding of the working mechanisms in a physiological environment. Finally, the development trends and challenges are discussed, with the aim to provide new insights for the design and construction of future bio‐piezoelectric materials.
Bio‐piezoelectric platforms with the ability for mechanical–electrical energy conversion exhibit great potential in the biomedical field. The latest developments in bio‐piezoelectric platforms are introduced, their design and engineering strategies are highlighted, and the current state‐of‐the‐art in biomedical applications is systematically outlined. One closely combines the range of materials structures with their biomedical performance, aiming to provide insights for their design and construction in the future.
Nanodrug‐based cancer therapy has been actively developed in the past decades. The main challenges faced by nanodrugs include poor drug loading capacity, rapid clearance from blood circulation, and ...low antitumor efficiency with high risk of recurrence. In this work, red blood cell (RBC) membrane camouflaged hollow mesoporous Prussian blue nanoparticles (HMPB@RBC NPs) are fabricated for combination therapy of cancer. The stability, immune evading capacity, and blood retention time of HMPB@RBC NPs are significantly enhanced compared with those of bare HMPB NPs. Doxorubicin (DOX), as a model drug is encapsulated within HMPB@RBC NPs with loading capacity up to 130% in weight. In addition, DOX loaded HMPB@RBC NPs show pH‐/photoresponsive release. The in vivo studies demonstrate the outstanding performance of DOX@HMPB@RBC NPs in synergistic photothermal‐/chemotherapy of cancer.
Red blood cell (RBC) membrane camouflaged hollow mesoporous Prussian blue nanoparticles (HMPB@RBC NPs) are fabricated. With RBC membrane cloaking technique, the stability, immune evading, and blood retention time of HMPB@RBC NPs are significantly increased. Doxorubicin loaded HMPB@RBC NPs show pH‐/photoresponsive release properties. The in vivo studies demonstrate that HMPB@RBC NP is a stealthy system for synergistic photothermal‐/chemotherapy of cancer.
Transition‐metal dyshomeostasis is recognized as a critical pathogenic factor at the onset and progression of neurodegenerative disorder (ND). Excess transition‐metal ions such as Cu2+ can catalyze ...the generation of cytotoxic reactive oxygen species and thereafter induce neuronal cell apoptosis. Exploring new chelating agents, which are not only capable of capturing excess redox‐active metal, but can also cross the blood–brain barrier (BBB), are highly desired for ND therapy. Herein, it is demonstrated that 2D black phosphorus (BP) nanosheets can capture Cu2+ efficiently and selectively to protect neuronal cells from Cu2+‐induced neurotoxicity. Moreover, both in vitro and in vivo studies show that the BBB permeability of BP nanosheets is significantly improved under near‐infrared laser irradiation due to their strong photothermal effect, which overcomes the drawback of conventional chelating agents. Furthermore, the excellent biocompatibility and stability guarantee the biosafety of BP in future clinical applications. Therefore, these features make BP nanosheets have the great potential to work as an efficient neuroprotective nanodrug for ND therapy.
Black phosphorus (BP) nanosheets, having the capability of capturing Cu2+ efficiently and selectively, can not only act as an antioxidant to extenuate cellular oxidative stress and inhibit cell apoptosis, but also improve the blood–brain barrier permeability under near‐infrared laser irradiation through the photothermal effect. These properties of BP nanosheets make them an efficient neuroprotective nanodrug for neurodegenerative disorder therapy.
Fabrication of clinically translatable nanoparticles (NPs) as photothermal therapy (PTT) agents against cancer is becoming increasingly desirable, but still challenging, especially in facile and ...controllable synthesis of biocompatible NPs with high photothermal efficiency. A new strategy which uses protein as both a template and a sulfur provider is proposed for facile, cost‐effective, and large‐scale construction of biocompatible metal sulfide NPs with controlled structure and high photothermal efficiency. Upon mixing proteins and metal ions under alkaline conditions, the metal ions can be rapidly coordinated via a biuret‐reaction like process. In the presence of alkali, the inert disulfide bonds of S‐rich proteins can be activated to react with metal ions and generate metal sulfide NPs under gentle conditions. As a template, the protein can confine and regulate the nucleation and growth of the metal sulfide NPs within the protein formed cavities. Thus, the obtained metal sulfides such as Ag2S, Bi2S3, CdS, and CuS NPs are all with small size and coated with proteins, affording them biocompatible surfaces. As a model material, CuS NPs are evaluated as a PTT agent for cancer treatment. They exhibit high photothermal efficiency, high stability, water solubility, and good biocompatibility, making them an excellent PTT agent against tumors. This work paves a new avenue toward the synthesis of structure‐controlled and biocompatible metal sulfide NPs, which can find wide applications in biomedical fields.
Metal sulfide nanoparticles (NPs) with ultrasmall size, and good biocompatibility are facilely obtained via alkali‐driven transformation of S‐rich protein–metal complexes. Proteins work as both a sulfur resource and a template, where disulfide bonds are activated to react with metal ions and form metal sulfide NPs in situ, which are proved to be an excellent theranostic platform for cancer therapy.
Traditional salient object detection models often use hand-crafted features to formulate contrast and various prior knowledge, and then combine them artificially. In this work, we propose a novel ...end-to-end deep hierarchical saliency network (DHSNet) based on convolutional neural networks for detecting salient objects. DHSNet first makes a coarse global prediction by automatically learning various global structured saliency cues, including global contrast, objectness, compactness, and their optimal combination. Then a novel hierarchical recurrent convolutional neural network (HRCNN) is adopted to further hierarchically and progressively refine the details of saliency maps step by step via integrating local context information. The whole architecture works in a global to local and coarse to fine manner. DHSNet is directly trained using whole images and corresponding ground truth saliency masks. When testing, saliency maps can be generated by directly and efficiently feed forwarding testing images through the network, without relying on any other techniques. Evaluations on four benchmark datasets and comparisons with other 11 state-of-the-art algorithms demonstrate that DHSNet not only shows its significant superiority in terms of performance, but also achieves a real-time speed of 23 FPS on modern GPUs.
PDF
