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The corrosive anions (e.g., Cl − ) have been recognized as the origins to cause severe corrosion of anode during seawater electrolysis, while in experiments it is found that natural seawater (~0.41 M Cl − ) is usually more corrosive than simulated seawater (~0.5 M Cl − ). Here we elucidate that besides Cl − , Br − in seawater is even more harmful to Ni-based anodes because of the inferior corrosion resistance and faster corrosion kinetics in bromide than in chloride. Experimental and simulated results reveal that Cl − corrodes locally to form narrow-deep pits while Br − etches extensively to generate shallow-wide pits, which can be attributed to the fast diffusion kinetics of Cl − and the lower reaction energy of Br − in the passivation layer. Additionally, for the Ni-based electrodes with catalysts (e.g., NiFe-LDH) loading on the surface, Br − causes extensive spalling of the catalyst layer, resulting in rapid performance degradation. This work clearly points out that, in addition to anti-Cl − corrosion, designing anti-Br − corrosion anodes is even more crucial for future application of seawater electrolysis. It is known that chloride anions cause severe anode corrosion during seawater electrolysis. Here we found that bromide in seawater is even more harmful to Ni-based anodes, causing the spalling of the catalyst layer and the formation of shallow-wide pits on the substrate, leading to performance degradation.

The error performance of the 5G low‐density parity‐check codes is significantly impacted by the update order of layers. At present, the row degree (RD) and the number of punctured bits (PBs) are widely used to decide the update order of layers. Here, the authors propose a metric to assess the soft message recovery speed of coded bits and then suggest updating layers with the lowest RD first rather than those with the least PBs first. Besides, a new criterion is introduced to further determine the update order of layers with the same number of PBs and the same RD. The resulting reordered layered schedule yields better error performance and faster convergence speed than the prior arts. A static layered schedule for the 5G low‐density parity‐check codes is proposed here. The proposed static layered schedule provides better error performance and faster convergence speed than state‐of‐the‐art.

Background Emerging evidence indicates that Long non-coding RNAs (LncRNAs) and microRNAs (miRNAs) play crucial roles in tumor progression, including hepatocellular carcinoma (HCC). However, whether there is a crosstalk between LncRNA pituitary tumor-transforming 3 (PTTG3P) and miR-383 in HCC remains unknown. This study is designed to explore the underlying mechanism by which LncRNA PTTG3P sponges miR-383 during HCC progression. Methods qPCR and Western blot were used to analyze LncRNA PTTG3P, miR-383 and other target genes’ expression. CCK-8 assay was performed to examine cell proliferation. Annexin V-PE/PI and PI staining were used to analyze cell apoptosis and cell cycle distribution by flow cytometry, respectively. Transwell migration and invasion assays were used to examine cell migration and invasion abilities. An in vivo xenograft study was performed to detect tumor growth. Luciferase reporter assay and RNA pull-down assay were carried out to detect the interaction between miR-383 and LncRNA PTTG3P. RIP was carried out to detect whether PTTG3P and miR-383 were enriched in Ago2-immunoprecipitated complex. Results In this study, we found that PTTG3P was up-regulated in HCC tissues and cells. Functional experiments demonstrated that knockdown of PTTG3P inhibited cell proliferation, migration and invasion, and promoted cell apoptosis, acting as an oncogene. Mechanistically, PTTG3P upregulated the expression of miR-383 targets Cyclin D1 (CCND1) and poly ADP-ribose polymerase 2 (PARP2) by sponging miR-383, acting as a competing endogenous RNA (ceRNA). The PTTG3P-miR-383-CCND1/PARP2 axis modulated HCC phenotypes. Moreover, PTTG3P also affected the PI3K/Akt signaling pathway. Conclusion The data indicate a novel PTTG3P-miR-383-CCND1/PARP2 axis in HCC tumorigenesis, suggesting that PTTG3P may be used as a potential therapeutic target in HCC. Graphical Abstract

Background Glaucoma, the leading cause of irreversible blindness, is a retinal neurodegenerative disease, which results from progressive apoptotic death of retinal ganglion cells (RGCs). Although the mechanisms underlying RGC apoptosis in glaucoma are extremely complicated, an abnormal cross-talk between retinal glial cells and RGCs is generally thought to be involved. However, how interaction of Müller cells and microglia, two types of glial cells, contributes to RGC injury is largely unknown. Methods A mouse chronic ocular hypertension (COH) experimental glaucoma model was produced. Western blotting, immunofluorescence, quantitative real-time polymerase chain reaction (q-PCR), transwell co-culture of glial cells, flow cytometry assay, ELISA, Ca 2+ image, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) techniques were employed to investigate the interaction of Müller cells and microglia, and its underlying mechanisms in COH retina. Results We first showed that Müller cell activation in mice with COH induced microglia activation through the ATP/P2X7 receptor pathway. The activation of microglia resulted in a significant increase in mRNA and protein levels of pro-inflammatory factors, such as tumor necrosis factor-α and interleukin-6. These inflammatory factors in turn caused the up-regulation of mRNA expression of pro-inflammatory factors in Müller cells through a positive feedback manner. Conclusions These findings provide robust evidence, for the first time, that retinal inflammatory response may be aggravated by an interplay between activated two types of glial cells. These results also suggest that to reduce the interplay between Müller cells and microglia could be a potential effective strategy for preventing the loss of RGCs in glaucoma.

Licochalcone A (Lico A), isolated from Xinjiang licorice Glycyrrhiza inflate, has been shown to have antioxidative potential via the activation of nuclear factor-erythroid 2-related factor 2 (Nrf2) activation, which is involved in the prevention of acetaminophen-induced hepatotoxicity. The purpose of the current study was to further explore the protective effect of Lico A against lipopolysaccharide/d-galactosamine (LPS/GalN)-induced acute liver injury (ALI) and its underlying molecular mechanisms. Our results found that treatment with Lico A significantly reduced in LPS/GalN-induced hepatotoxicity by lessening lethality, alleviating histopathological liver changes, decreasing the alanine transaminase, and aspartate aminotransferase levels, attenuating the secretion of inflammatory cytokines, and regulating oxidative markers. Furthermore, Lico A efficiently alleviated LPS-induced inflammatory response by inhibiting TLR4-MAPK and -NF-κB, as well as the Txnip-NLRP3 signaling pathway. Meanwhile, Lico A induced the activation of Nrf2 and QSTM1 (P62) signaling and promoted autophagy involved in AMP-activated protein kinase (AMPK)-the transcription factor EB (TFEB) signaling, which may contribute to its hepatoprotective activity. Additional mechanistic investigations to evaluate the dependence of the hepatoprotective role of Lico A on Nrf2 revealed that a lack of Nrf2 promoted Lico A-induced autophagy, which contributed to the hepatoprotective effect of Lico A in Nrf2 −/− mice. In addition, cotreatment with autophagy inhibitor (3-methyladenine, 3-MA) alleviated but did not abrogate the hepatoprotective effect of Lico A, which may be attributed to its ability to activate Nrf2. Our study firstly suggests that Lico A has protective potential against LPS/GalN-induced hepatotoxicity, which may be strongly associated with activation of Nrf2 and autophagy.

Face detection plays an important role in many artificial intelligence applications, such as identity recognition, facial expression recognition, and gender/age recognition. Recently, the development of deep learning techniques has greatly improved face detection’s performance. However, it is still ineffective and time-consuming to manually design hyperparameters of face detectors for different deployment environments with diverse distributions. Besides, due to the limited computation capability, many previous networks are hard to meet the latency requirements in deployment environments, and the improved resolution of current cameras further increases the computation burden. Motivated by the above problems, we propose a searching framework aiming to automatically search a real-time face detector architecture with a fixed complexity constraint, to adapt a specific deployment environment. We model the whole searching space into two parts, including the hyperparameters of the network and the detector. Instead of only searching the network structure, the proposed method considers the whole model’s hyperparameters space which contains the preprocessing and postprocessing parameters. The evolutionary algorithm is employed to find the optimal solution, and new evolutionary operations are proposed to explore architecture space. During the whole searching procedure, we guarantee the computation cost is under the restrictions. The advantages of the proposed framework are that it considers a hard computation cost constraint and the preprocessing and postprocessing hyperparameters, leading to a fully automatic design style and global optimization. Finally, we evaluate the proposed model on the most popular Widerface and FDDB datasets. The proposed detector significantly surpasses the existing lightweight face detectors in the comprehensive performances, and the average latency is twice as shorter as the best competitor.

Recently, the layer-wise N:M fine-grained sparse neural network algorithm (i.e., every M-weights contains N non-zero values) has attracted tremendous attention, as it can effectively reduce the computational complexity with negligible accuracy loss. However, the speed-up potential of this algorithm will not be fully exploited if the right hardware support is lacking. In this work, we design an efficient accelerator for the N:M sparse convolutional neural networks (CNNs) with layer-wise sparse patterns. First, we analyze the performances of different processing element (PE) structures and extensions to construct the flexible PE architecture. Second, the variable sparse convolutional dimensions and sparse ratios are involved in the hardware design. With a sparse PE cluster (SPEC) design, the hardware can efficiently accelerate CNNs with the layer-wise N:M pattern. Finally, we employ the proposed SPEC into the CNN accelerator with flexible network-on-chip and specially designed dataflow. We implement hardware accelerators on Xilinx ZCU102 FPGA and Xilinx VCU118 FPGA and evaluate them with classical CNNs such as Alexnet, VGG-16, and ResNet-50. Compared with existing accelerators designed for structured and unstructured pruned networks, our design achieves the best performance in terms of power efficiency.

Background Neuroinflammation plays an important role in the pathogenesis of glaucoma. Tumor necrosis factor-alpha (TNF-α) is a major pro-inflammatory cytokine released from activated retinal glial cells in glaucoma. Here, we investigated how TNF-α induces retinal ganglion cell (RGC) hyperexcitability and injury. Methods Whole-cell patch-clamp techniques were performed to explore changes in spontaneous firing and evoked action potentials, and Na + currents in RGCs. Both intravitreal injection of TNF-α and chronic ocular hypertension (COH) models were used. Western blotting, immunofluorescence, quantitative real-time polymerase chain reaction (q-PCR), and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) techniques were employed to investigate the molecular mechanisms of TNF-α effects on RGCs. Results Intravitreal injection of soluble TNF-α significantly increased the spontaneous firing frequencies of RGCs in retinal slices. When the synaptic transmissions were blocked, more than 90% of RGCs still showed spontaneous firing; both the percentage of cells and firing frequency were higher than the controls. Furthermore, the frequency of evoked action potentials was also higher than the controls. Co-injection of the TNF-α receptor 1 (TNFR1) inhibitor R7050 eliminated the TNF-α-induced effects, suggesting that TNF-α may directly act on RGCs to induce cell hyperexcitability through activating TNFR1. In RGCs acutely isolated from TNF-α-injected retinas, Na + current densities were upregulated. Perfusing TNF-α in RGCs of normal rats mimicked this effect, and the activation curve of Na + currents shifted toward hyperpolarization direction, which was mediated through p38 MAPK and STAT3 signaling pathways. Further analysis revealed that TNF-α selectively upregulated Nav1.6 subtype of Na + currents in RGCs. Similar to observations in retinas of rats with COH, intravitreal injection of TNF-α upregulated the expression of Nav1.6 proteins in both total cell and membrane components, which was reversed by the NF-κB inhibitor BAY 11-7082. Inhibition of TNFR1 blocked TNF-α-induced RGC apoptosis. Conclusions TNF-α/TNFR1 signaling induces RGC hyperexcitability by selectively upregulating Nav1.6 Na + channels, thus contributing to RGC apoptosis in glaucoma.

In gift-giving, it violates social norms for recipients to explicitly deliver negative evaluations of gifts, potentially causing emotional or psychological harm to givers, which raises ethical concerns. However, recent research indicates that this behavior is surprisingly not rare. While substantial research has focused on instances where recipients are dissatisfied with gifts, little attention has been given to the unique emotional harm experienced by givers and the underlying psychological processes involved. This study addresses this gap from the perspective of social exclusion and examines how givers’ feelings of social exclusion differ between close and distant relationships. We argue that givers tend to devote more effort to selecting gifts for close (vs. distant) recipients, leading them to hold higher expectations of gifting success in close relationships. Instead, when givers get negative feedback from close recipients, they perceive a higher level of expectancy violation, which, in turn, backfires on their perceived threats to the relationship and arouses stronger feelings of social exclusion than in distant relationships. Results from three experiments substantiate our theoretical claims based on the expectancy-violation theory. Further, we apply neuroscience technology (event-related potentials, ERPs) to capture the cognitive characteristics of givers’ emotional experiences, offering additional evidence and insights into givers’ feelings of social exclusion. This research contributes to a deeper understanding of the emotional harm givers experience when their gifts are unappreciated, highlighting the ethical aspect of gift-giving.

Background Fc gamma receptor IIb (FcγRIIb) is an important inhibitory receptor that plays vital roles in regulating various immune response processes and the pathogenesis of many infectious diseases. The purpose of our research was to evaluate FcγRIIb expression in serum and liver biopsy specimens from hepatitis B virus (HBV)-infected patients and to explore the association of FcγRIIb with chronic HBV infection. Methods Enzyme-linked immunosorbent assay (ELISA) was adopted to measure the serum FcγRIIb levels in 119 HBV-infected patients and 24 healthy controls. An immunohistochemical method was then employed to identify FcγRIIb expression in biopsy specimens from patients with chronic hepatitis B (CHB). The integrated optical density (IOD) value was measured to represent FcγRIIb expression levels. Results Serum FcγRIIb levels were decreased in CHB patients compared to controls (P < 0.001). The FcγRIIb levels in the CHB patient group were remarkably lower than those in the HBV carrier group (P < 0.001). In addition, FcγRIIb levels were negatively associated with AST and ALT (r = −0.3936, P = 0.0063; r = −0.3459, P = 0.0097, respectively). The IOD values of FcγRIIb expression in the moderate and severe CHB groups were significantly lower than those in the control group (P = 0.006 and P < 0.001, respectively). The FcγRIIb level tended to be lower with pathological changes related to hepatitis. Furthermore, correlation analysis revealed that FcγRIIb had negative correlations with AST and ALT (r = −0.688, P = 0.0016; r = −0.686, P = 0.0017, respectively) but a positive association with the platelet count (r = 0.6464, P = 0.0038). Conclusions FcγRIIb levels are significantly related to chronic HBV infection and the progression of CHB. Changes in FcγRIIb may affect the progression of liver inflammation and fibrosis in CHB patients.