In this study, an organic semiconducting pro‐nanostimulant (OSPS) with a near‐infrared (NIR) photoactivatable immunotherapeutic action for synergetic cancer therapy is presented. OSPS comprises a semiconducting polymer nanoparticle (SPN) core and an immunostimulant conjugated through a singlet oxygen (1O2) cleavable linkers. Upon NIR laser irradiation, OSPS generates both heat and 1O2 to exert combinational phototherapy not only to ablate tumors but also to produce tumor‐associated antigens. More importantly, NIR irradiation triggers the cleavage of 1O2‐cleavable linkers, triggering the remote release of the immunostimulants from OSPS to modulate the immunosuppressive tumor microenvironment. Thus, the released tumor‐associated antigens in conjunction with activated immunostimulants induce a synergistic antitumor immune response after OSPS‐mediated phototherapy, resulting in the inhibited growth of both primary/distant tumors and lung metastasis in a mouse xenograft model, which is not observed for sole phototherapy.

Federated learning, as a promising machine learning approach, has emerged to leverage a distributed personalized dataset from a number of nodes, e.g., mobile devices, to improve performance while simultaneously providing privacy preservation for mobile users. In the federated learning, training data is widely distributed and maintained on the mobile devices as workers. A central aggregator updates a global model by collecting local updates from mobile devices using their local training data to train the global model in each iteration. However, unreliable data may be uploaded by the mobile devices (i.e., workers), leading to frauds in tasks of federated learning. The workers may perform unreliable updates intentionally, e.g., the data poisoning attack, or unintentionally, e.g., low-quality data caused by energy constraints or high-speed mobility. Therefore, finding out trusted and reliable workers in federated learning tasks becomes critical. In this article, the concept of reputation is introduced as a metric. Based on this metric, a reliable worker selection scheme is proposed for federated learning tasks. Consortium blockchain is leveraged as a decentralized approach for achieving efficient reputation management of the workers without repudiation and tampering. By numerical analysis, the proposed approach is demonstrated to improve the reliability of federated learning tasks in mobile networks.

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Alzheimer’s disease (AD) is a common age-related neurodegenerative disease characterized by progressive cognitive dysfunction and behavioral impairment. The typical pathological characteristics of AD are extracellular senile plaques composed of amyloid ß (Aβ) protein, intracellular neurofibrillary tangles formed by the hyperphosphorylation of the microtubule-associated protein tau, and neuron loss. In the past hundred years, although human beings have invested a lot of manpower, material and financial resources, there is no widely recognized drug for the effective prevention and clinical cure of AD in the world so far. Therefore, evaluating and exploring new drug targets for AD treatment is an important topic. At present, researchers have not stopped exploring the pathogenesis of AD, and the views on the pathogenic factors of AD are constantly changing. Multiple evidence have confirmed that chronic neuroinflammation plays a crucial role in the pathogenesis of AD. In the field of neuroinflammation, the nucleotide-binding oligomerization domain-like receptor pyrin domain-containing 3 (NLRP3) inflammasome is a key molecular link in the AD neuroinflammatory pathway. Under the stimulation of Aβ oligomers and tau aggregates, it can lead to the assembly and activation of NLRP3 inflammasome in microglia and astrocytes in the brain, thereby causing caspase-1 activation and the secretion of IL-1β and IL-18, which ultimately triggers the pathophysiological changes and cognitive decline of AD. In this review, we summarize current literatures on the activation of NLRP3 inflammasome and activation-related regulation mechanisms, and discuss its possible roles in the pathogenesis of AD. Moreover, focusing on the NLRP3 inflammasome and combining with the upstream and downstream signaling pathway-related molecules of NLRP3 inflammasome as targets, we review the pharmacologically related targets and various methods to alleviate neuroinflammation by regulating the activation of NLRP3 inflammasome, which provides new ideas for the treatment of AD.

Electrocatalytic water splitting for industrial hydrogen production at large current densities requests highly active and cost‐effective catalysts with long‐term stability. Here, conductive nickel foam is proposed to be used as a substrate to support (Fe,Ni)(OH)2 nanosheet arrays and a reducing agent to reduce Ru3+ ions to metallic Ru. The formed 3D self‐supported Ru/(Fe,Ni)(OH)2/NF (denoted as RFNOH) with a superhydrophilic surface and high conductivity ensures rapid release of gases and efficient electron transportation and mass transfer at a high current density. The resultant RFNOH requires an overpotential of only 152 mV to achieve a current density of 1 A cm−2 for hydrogen evolution reaction in 1 m KOH solution, along with excellent stability at high current density. Meanwhile, density functional theory calculations suggest that (Fe,Ni)(OH)2 promotes the dissociation of water molecules considerably, which plays a critical role in enhancing the generation of molecular hydrogen on Ru nanoparticles. Furthermore, the proposed dual‐active site mechanism solves the problem of low water‐dissociation efficiency faced by noble metal‐based catalysts under alkaline media. This study provides a new route for the practical production of large quantities of hydrogen via electrochemical water splitting.

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Purpose -The purpose of this paper is to report a new direct metal manufacturing method which integrates freeform deposition process and micro rolling process, introduce the manufacturing principle and show the advantages of this method. Design/methodology/approach -This paper introduces the hybrid manufacturing principle and devices first. Then, the key parameters of hybrid manufacturing process are studied by contrast experiments. The results of comparisons of manufacturing accuracy, microstructure and tensile test between freeform fabricated parts and hybrid manufactured parts show the advantages of this new direct manufacturing method. Findings -The experiments results show that the accuracy of hybrid manufacturing method is improved obviously comparing with arc-based freeform deposition manufacturing method; the microstructure of the hybrid manufacturing part turns into cellular crystal instead of dendrite; the tensile strength of the part increases by 33 percent and the tensile deformation improved more than two times. Originality/value -The paper presents a new hybrid direct metal manufacturing method for the first time. The hybrid manufacturing devices are developed. The experiments results show that the hybrid manufacturing method can be used on directly fabricating large metal components with outstanding quality, efficiency and low cost. The application prospect is great.