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Recently, highly active, easy-to-make, and efficient bifunctional electrocatalysts have attracted tremendous attention because of their potential applications in clean energy. Herein, we report a simple, one-step approach for fabricating three-dimensional (3D) Ni–P nanorod arrays by direct phosphorization of commercial nickel foam (Ni foam) with different times. When used as a 3D electrode for oxygen evolution reaction, the obtained Ni–P nanorods with two hours of phosphatization treatment display high activity with an overpotential of 270 mV required to generate a current density of 30 mA/cm2 and excellent stability in 1.0 M KOH. Additionally, the Ni–P nanorod arrays are also highly active for electrocatalyzing the hydrogen evolution reaction in the alkaline media. As a result, the bifunctional Ni–P catalysts enabled a highly performed overall water splitting, in which a low applied external potential of 1.6 V led to a stabilized catalytic current density of 10 mA/cm2 over 12 h.

Developing a cost-effective electrocatalyst with high activity and excellent stability is very significant to nonenzymatic glucose detection. Herein, we have constructed 3D NiCo/NiCoOx nanocluster electrode modified by amorphous FeOOH nanosheets owing to the similar electrocatalytic activity of FeOOH to natural peroxidases. The NiCo nanoclusters can provide an excellent conductivity and high active surface areas, while the amorphous two-dimensional ultrathin structure of FeOOH stimulates more open metal sites for glucose oxidation. Besides, the strong synergetic effects among ternary Fe, Ni and Co are beneficial to the transport of charge. Though comprehensive electrochemical measurements, it is found that the as-prepared electrode possesses the prominent activity toward glucose oxidation with high sensitivity of 7138 µA mM−1 cm−2, a wide linear range of 1 µM and 8 mM, a low detection limit of 0.82 µM, good selectivity and excellent stability, all of which is mainly derived from the more active sites, rapid mass transport and superior electron transfer. This research provides a model system for developing more available electrocatalysts for glucose detection.

By combining the unique features of the quantum cutting luminescence and long persistent luminescence, we design a new concept called “near-infrared quantum cutting long persistent luminescence (NQPL)”, which makes it possible for us to obtain highly efficient (>100%) near-infrared long persistent luminescence in theory. Guided by the NQPL concept, we fabricate the first NQPL phosphor Ca 2 Ga 2 GeO 7 :Pr 3+ ,Yb 3+ . It reveals that both the two-step energy transfer of model (I) and the one-step energy transfer of model (IV) occur in 3 P 0 levels of Pr 3+ . Although the actual efficiency is not sufficient for the practical application at this primitive stage, this discovery and the associated materials are still expected to have important implications for several fields such as crystalline Si solar cells and bio-medical imaging.

Developing highly efficient electrocatalysts for the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) is critical to enable electrical‐to‐hydrogen energy conversion technologies to reality. Herein, zinc‐doped cobalt sulfide‐modified nickel sulfide (ZCNS) heteronanorod hybrid electrocatalysts are prepared through a facile hydrothermal method to enhance the electrocatalytic performance of cobalt‐nickel sulfide. The doping of Zn optimizes the electronic structure of cobalt‐nickel sulfide thus improving the conductivity and charge transfer ability of cobalt‐nickel sulfide. In addition, benefiting from the hierarchical structure of one‐dimensional nanorods and three‐dimensional Ni foam, abundant catalytically active sites and fast ion and charge transportation are obtained. As a result, the optimal zinc doped cobalt‐nickel sulfide hybrid presents overpotentials of 138 and 235 mV to achieve a current density of 10 mA/cm2 in 1.0 M KOH for HER and OER, respectively. Assembled as an electrolyzer for overall water splitting using the heteronanorod hybrids as both anode and cathode catalysts, the low cell voltage of 1.56 V at 10 mA/cm2 is achieved, which is similar to that of the IrO2‐Pt/C couple.

Objective To explore the influence of protein arginine methyltransferase 8 (PRMT8) regulating glial cell‐derived neurotrophic factor (GDNF) on neuron ferroptosis and macrophage polarization in spinal cord injury (SCI). Methods A rat model of SCI was established through an injury induced by an external force. Basso, Beattie, and Bresnahan score, hematoxylin and eosin staining, and immunofluorescence were used, respectively, to detect changes in rat locomotion, spinal cord histopathology, and NeuN expression in the spinal cord. Iron content in the spinal cord and levels of malondialdehyde and glutathione were measured using detection kits. Transmission electron microscopy was used to reveal the morphological characteristics of mitochondria. Western blotting was performed to detect PRMT8, GDNF, cystine/glutamate transporter XCT, glutathione peroxidase 4, 4‐hydroxynonenal, heme oxygenase‐1, inducible nitric oxide synthase (iNOS), CD16, and arginase 1 (Arg1). The expression levels of iNOS and Arg1 in the spinal cord were visualized by immunofluorescence. ELISA was performed to measure the expression levels of IL‐6, IL‐1β, and TNF‐α. Rat dorsal root ganglion (DRG) neurons and RMa‐bm rat macrophages were treated with lipopolysaccharide under hypoxic conditions. The viability and iron content of the neurons were detected using Cell Counting Kit‐8 and a specific probe, respectively. Flow cytometry and immunofluorescence were used to assess macrophage polarization. Chromatin immunoprecipitation was used to identify the binding of PRMT8 to the GDFN promoter. Results Neuronal ferroptosis and M1 macrophage polarization were promoted, and PRMT8 expression was downregulated in SCI. PRMT8 overexpression exerted therapeutic effects on injured DRG neurons and RMa‐bm cells. Moreover, PRMT8 overexpression inhibited ferroptosis and M1 macrophage polarization in rats with SCI. PRMT8 promoted GDNF expression by catalyzing H3K4 methylation. Knockdown of GDNF counteracted the therapeutic effects of PRMT8 overexpression. Conclusion Overexpression of PRMT8 may inhibit ferroptosis and M1 macrophage polarization by increasing GDNF expression, thereby alleviating SCI. Low PRMT8 expression inhibits GDNF transcriptional expression by reducing H3K4 methylation, thereby promoting ferroptosis and M2 macrophage polarization in SCI rats.

HighlightsThe latest progress of emerging smart flexible sensing systems driven by brain-inspired artificial intelligence (AI) from both the algorithm (machine learning) and the framework (artificial synapses) level is reviewed.New enabling features such as powerful data analysis and intelligent decision-making resulting from the fusion of AI technology with flexible sensors are discussed.Promising application prospects of AI-driven smart flexible sensing systems such as more intelligent monitoring for human activities, more humanoid feeling by artificial sensory organs, and more autonomous action of soft robotics are demonstrated.The recent wave of the artificial intelligence (AI) revolution has aroused unprecedented interest in the intelligentialize of human society. As an essential component that bridges the physical world and digital signals, flexible sensors are evolving from a single sensing element to a smarter system, which is capable of highly efficient acquisition, analysis, and even perception of vast, multifaceted data. While challenging from a manual perspective, the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm (machine learning) and the framework (artificial synapses) level. This review presents the recent progress of the emerging AI-driven, intelligent flexible sensing systems. The basic concept of machine learning and artificial synapses are introduced. The new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed, which significantly advances the applications such as flexible sensory systems, soft/humanoid robotics, and human activity monitoring. As two of the most profound innovations in the twenty-first century, the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.

Numerous natural products originated from Chinese herbal medicine exhibit anti-cancer activities, including anti-proliferative, pro-apoptotic, anti-metastatic, anti-angiogenic effects, as well as regulate autophagy, reverse multidrug resistance, balance immunity, and enhance chemotherapy in vitro and in vivo. To provide new insights into the critical path ahead, we systemically reviewed the most recent advances (reported since 2011) on the key compounds with anti-cancer effects derived from Chinese herbal medicine (curcumin, epigallocatechin gallate, berberine, artemisinin, ginsenoside Rg3, ursolic acid, silibinin, emodin, triptolide, cucurbitacin B, tanshinone I, oridonin, shikonin, gambogic acid, artesunate, wogonin, β-elemene, and cepharanthine) in scientific databases (PubMed, Web of Science, Medline, Scopus, and Clinical Trials). With a broader perspective, we focused on their recently discovered and/or investigated pharmacological effects, novel mechanism of action, relevant clinical studies, and their innovative applications in combined therapy and immunomodulation. In addition, the present review has extended to describe other promising compounds including dihydroartemisinin, ginsenoside Rh2, compound K, cucurbitacins D, E, I, tanshinone IIA and cryptotanshinone in view of their potentials in cancer therapy. Up to now, the evidence about the immunomodulatory effects and clinical trials of natural anti-cancer compounds from Chinese herbal medicine is very limited, and further research is needed to monitor their immunoregulatory effects and explore their mechanisms of action as modulators of immune checkpoints.

The battery system, as the core energy storage device of new energy vehicles, faces increasing safety issues and threats. An accurate and robust fault diagnosis technique is crucial to guarantee the safe, reliable, and robust operation of lithium-ion batteries. However, in battery systems, various faults are difficult to diagnose and isolate due to their similar features and internal coupling relationships. In this paper, the current research of advanced battery system fault diagnosis technology is reviewed. Firstly, the existing types of battery faults are introduced in detail, where cell faults include progressive and sudden faults, and system faults include a sensor, management system, and connection component faults. Then, the fault mechanisms are described, including overcharge, overdischarge, overheat, overcool, large rate charge and discharge, and inconsistency. The existing fault diagnosis methods are divided into four main types. The current research and development of model-based, data-driven, knowledge-based, and statistical analysis-based methods for fault diagnosis are summarized. Finally, the future development trend of battery fault diagnosis technology is prospected. This paper provides a comprehensive insight into the fault and defect diagnosis of lithium-ion batteries for electric vehicles, aiming to promote the further development of new energy vehicles.

Exposure to a novel environment can enhance the extinction of recent contextual fear in mice. This has been explained by a tagging and capture hypothesis. Consistently, we show in mice that exposure to a novel environment before extinction training promoted the extinction of recent auditory fear. However, such a promoting effect of novelty was absent for remote memories. In the present study, we replaced the regular extinction training with a retrieval-extinction session which capitalized on a reconsolidation window. When novelty exposure was followed by a retrieval-extinction session, remote fear was distinguished more easily and permanently. We have termed it as a “novelty-retrieval-extinction” paradigm. This paradigm played a greater role in the extinction of remote fear when fear conditioning and retrieval-extinction occurred in two different contexts other than in one identical context. The mechanism underlying the facilitating effect of this paradigm might involve up-regulation of histone acetylation in the hippocampus, which has been reported to increase functional and structural neuroplasticity. The present work proposes an effective, drug-free paradigm for the extinction of remote fear, which could be easily adapted in humans with least side effects.

Pycnocline is a widespread marine phenomenon across the world, which plays an important role in ocean engineering, oceanic meteorology, and biological applications. In this study, based on actual density data, statistical characteristics of complex density profiles are analyzed. It is found that the pycnocline interval d in multilayer structures conforms to the three-parameter Weibull distribution. To describe the multilayer structure more accurately, a dimensionless parameter α is proposed, which takes into account scale effects and the relative position of layers. Then, the probability density distribution of α is analyzed, from which the clustering phenomena are found. Therefore, clustering analysis is carried out to obtain a method for determining the location of pycnocline in complex density profiles. Based on this method, the statistical research of pycnocline distribution in the northern South China Sea is carried out including the key properties of pycnocline depth, pycnocline thickness, and pycnocline intensity. The result shows that the pycnocline distribution changes periodically with seasons, in which heat flux and monsoon are the main influencing factors. As the temperature increases, the formation of the pycnocline is encouraged, with the consequent decrease in pycnocline depth and increase in pycnocline thickness and intensity, vice versa. The monsoon influences the distribution of the pycnocline by affecting vertical mixing and Ekman wind-driven mechanism.