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For background, Hirsutella sinensis, the only anamorphic fungus considered an effective substitute for Cordyceps sinensis, possesses immunoregulatory properties. However, the specific mechanism underlying the immunoregulatory function of Hirsutella sinensisremains unclear. The purpose is to investigate the therapeutic effects of Hirsutella sinensisalcohol extract (HSAE) on immune dysregulation and elucidate the underlying mechanisms involved. For methods, we established inflammatory and immunosuppression models in vitro and in vivo to evaluate the bidirectional immunoregulatory function of HSAE via qRT-PCR and immunoblotting. We also studied its potential mechanism via RNA sequencing and transcriptional analysis. We further established M1 and M2 cell models to explore the effect of HSAE on M1/M2 polarization using qRT-PCR, immunoblotting, and flow cytometry. For results, our data demonstrated enhanced proliferation, phagocytosis, and antipathogenic activities of macrophages. Treatment with HSAE led to increases in the proportions of CD3+and CD4+immune cells in cyclophosphamide-induced immunosuppressed mice. Additionally, HSAE reduced the lipopolysaccharide (LPS)-induced expression of Il1b, Il6, Ifnb1, and Cxcl10by inhibiting the activation of the NF-κB and MAPK pathways in vitro and improved mouse survival by reducing the proportion of M1/M2 macrophages in septic mice. Finally, we found that HSAE inhibited M1 polarization by decreasing the expression of iNOS and CD86 and promoted M2 polarization by increasing the expression of ARG1 and CD206. For conclusions, our study provides evidence that HSAE has the potential to enhance immune responses and suppress excessive inflammation. These effects were realized by modulating macrophage polarization, providing novel insights into the fundamental mechanism underlying the bidirectional immunomodulatory effect of HSAE.

Periodontitis is a common condition characterized by a bacterial infection and the disruption of the body’s immune-inflammatory response, which causes damage to the teeth and supporting tissues and eventually results in tooth loss. Current therapy involves the systemic and local administration of antibiotics. However, the existing treatments cannot exert effective, sustained release and maintain an effective therapeutic concentration of the drug at the lesion site. Hydrogels are used to treat periodontitis due to their low cytotoxicity, exceptional water retention capability, and controlled drug release profile. Hydrogels can imitate the extracellular matrix of periodontal cells while offering suitable sites to load antibiotics. This article reviews the utilization of hydrogels for periodontitis therapy based on the pathogenesis and clinical manifestations of the disease. Additionally, the latest therapeutic strategies for smart hydrogels and the main techniques for hydrogel preparation have been discussed. The information will aid in designing and preparing future hydrogels for periodontitis treatment.

The monitoring and protection of the power core lithium battery of electric vehicles is closely related to whether the lithium battery can output energy efficiently. To predict the charging state of lithium batteries, this study determined the online identification method, namely Recursive Least Square Method with Forcing Fact (FRLS), for model parameters based on the equivalent circuit model of lithium batteries, namely Thevenin. The overall prediction error of SVD-UKF is lower than that of Adaptive Extended Kalman Filter (AEKF) and Iterative Extended Kalman Filter (IEKF), which are about 20% and 30%, respectively. FRLS&Singular Value Decomposition-Unscented Kalman Filter (FRLS&SVD-UKF) has low prediction error of lithium battery load state under the same working condition and temperature, and the prediction error of lithium battery load state under the same working condition shows a gradually increasing trend with the increase of temperature. The FRLS&SVD-UKF joint prediction model can accurately predict the load state of lithium battery in electric vehicles in real time, and can improve the recycling performance of lithium battery.

DC series arc fault is one of the main causes of low-voltage dc distribution system fire accident. Traditional methods use time-frequency domain features to make judgments directly or use machine learning to further classify them. In this article, a method is proposed to simplify the feature extraction process while ensuring accuracy. First, a fully automated process is used to establish dc arc datasets. A composite bandpass filter is designed to extract the typical frequency segment of dc arc. Besides, an arc detection neural network based on temporal convolution network is proposed to extract current waveform features. Principal component analysis is used to process these features to reduce correlation. Finally, a single hidden layer neural network is used as classifier. The database is collected from different scenarios and working conditions. By measuring the dc raw current, the arc fault detector can achieve a test set accuracy of 99.88% at a sampling rate of 250 kHz. The model is also deployed on Jetson Nano with an average real-time detection of 0.15 s/sample.

ObjectivesChronic hepatitis B (CHB) caused by HBV infection greatly increases the risk of liver cirrhosis and hepatocellular carcinoma. Hepatitis B surface antigen (HBsAg) plays critical roles in the pathogenesis of CHB. HBsAg loss is the key indicator for cure of CHB, but is rarely achieved by current approved anti-HBV drugs. Therefore, novel anti-HBV strategies are urgently needed to achieve sustained HBsAg loss.DesignWe developed multiple chimeric antigen receptors (CARs) based on single-chain variable fragments (scFvs, namely MA18/7-scFv and G12-scFv), respectively, targeting HBV large and small envelope proteins. Their impacts on HBsAg secretion and HBV infection, and the underlying mechanisms, were extensively investigated using various cell culture models and HBV mouse models.ResultsAfter secretory signal peptide mediated translocation into endoplasmic reticulum (ER) and secretory pathway, MA18/7-scFv and CARs blocked HBV infection and virion secretion. G12-scFv preferentially inhibited virion secretion, while both its CAR formats and crystallisable fragment (Fc)-attached versions blocked HBsAg secretion. G12-scFv and G12-CAR arrested HBV envelope proteins mainly in ER and potently inhibited HBV budding. Furthermore, G12-scFv-Fc and G12-CAR-Fc strongly suppressed serum HBsAg up to 130-fold in HBV mouse models. The inhibitory effect lasted for at least 8 weeks when delivered by an adeno-associated virus vector.ConclusionCARs possess direct antiviral activity, besides the well-known application in T-cell therapy. Fc attached G12-scFv and G12-CARs could provide a novel approach for reducing circulating HBsAg.

ABSTRACTThere have been limited studies on the hardening of cement containing different heavy metals owing to differences in solidification effect. The leachability, setting time, and compressive strength of sulfoaluminate cement [...]

The increasingly complex transmission lines can no longer rely on a single manual inspection method to monitor the health of equipment. Considering the actual needs and conditions, online monitoring of transmission lines can make up for the shortcomings of traditional detection methods. In order to reduce the manual workload and improve the accuracy and efficiency of detection, this article introduces the application of self-powered sensors in the transmission line equipment health state depth sensing system. The research considers that the sensor is the important sensor module foundation of the online monitoring system. The characteristics of sensor cells used for solar energy conversion are analyzed. The self-powered sensor is introduced into the transmission line equipment health depth sensing system, and the transmission line network model and the data transmission compression algorithm are optimized. The experimental results show that photovoltaic cells can effectively provide stable and relatively sufficient power for sensors and prolong the service life of nodes. This improves the utilization of node resources, effectively reduces latency and energy consumption, and effectively extends the application life cycle of the sensor system.

Traditional support vector machines (SVMs) play an important role in the classification of precise data. However, due to various reasons, available data are sometimes imprecise. In this paper, uncertain variables are adopted to describe the imprecise data, and an uncertain support vector machine (USVM) is built for linearly α-nonseparable sets based on soft margin method, where a penalty coefficient is utilized as the trade-off between the maximum margin and the sum of slack variables. Then the equivalent crisp model is derived based on the inverse uncertainty distributions. Numerical experiments are designed to illustrate the application of the soft margin USVM. Finally, metrics, such as accuracy, precision, and recall are used to evaluate the robustness of the proposed model.

The lightweight design of the hood is crucial for the structural optimization of an entire vehicle. However, traditional high-fidelity-based lightweight methods are time-consuming due to the complex structures of the hood, and the lightweight results heavily rely on engineering experiences. To this end, an improved adaptive marine predator algorithm (AMPA) is proposed to solve this problem. Compared to the original marine predator algorithm (MPA), the proposed AMPA adapts to optimization problems through three enhancements, including chaotic theory-based initialization, a mixed search strategy, and dynamic partitioning of iteration phases. Experimental comparisons of AMPA, MPA, and eight state-of-the-art algorithms are conducted on IEEE CEC2017 benchmark functions. AMPA outperforms the others in both 30- and 50-dimensional experiments. Friedman and Wilcoxon’s sign-rank tests further confirm AMPA’s superiority and statistical significance. An implicit parametric model of the hood is generated, and the critical design variables are determined through global sensitivity analysis to realize hood lightweight. The stacking method is employed to construct a surrogate meta-model of the hood to accelerate the optimization efficiency of the vehicle hood. Utilizing the meta-model and the proposed AMPA, the hood mass is reduced by 7.43% while all six static and dynamic stiffness metrics are enhanced. The effectiveness of the proposed optimization method is validated through finite element analysis.Graphical Abstract

Argonaute proteins generally play regulatory roles by forming complexes with the corresponding small RNAs (sRNAs). An expanded Argonaute family with 20 potentially functional members has been identified in Caenorhabditis elegans. Canonical sRNAs in C. elegansare miRNAs, small interfering RNAs including 22G-RNAs and 26G-RNAs, and 21U-RNAs, which are C. eleganspiRNAs. Previous studies have only covered some of these Argonautes for their sRNA partners, and thus, a systematic study is needed to reveal the comprehensive regulatory networks formed by C. elegansArgonautes and their associated sRNAs. We obtained in situknockin (KI) strains of all C. elegansArgonautes with fusion tags by CRISPR/Cas9 technology. RNA immunoprecipitation against these endogenously expressed Argonautes and high-throughput sequencing acquired the sRNA profiles of individual Argonautes. The sRNA partners for each Argonaute were then analyzed. We found that there were 10 Argonautes enriched miRNAs, 17 Argonautes bound to 22G-RNAs, 8 Argonautes bound to 26G-RNAs, and 1 Argonaute PRG-1 bound to piRNAs. Uridylated 22G-RNAs were bound by four Argonautes HRDE-1, WAGO-4, CSR-1, and PPW-2. We found that all four Argonautes played a role in transgenerational epigenetic inheritance. Regulatory roles of the corresponding Argonaute-sRNA complex in managing levels of long transcripts and interspecies regulation were also demonstrated. In this study, we portrayed the sRNAs bound to each functional Argonaute in C. elegans. Bioinformatics analyses together with experimental investigations provided perceptions in the overall view of the regulatory network formed by C. elegansArgonautes and sRNAs. The sRNA profiles bound to individual Argonautes reported here will be valuable resources for further studies.

Biomass carbon materials with high rate capacity have great potential to boost supercapacitors with cost effective, fast charging–discharging performance and high safety requirements, yet currently suffers from a lack of targeted preparation methods. Here we propose a facile FeCl3assisted hydrothermal carbonization strategy to prepare ultra-high rate biomass carbon from apple residues (ARs). In the preparation process, ARs were first hydrothermally carbonized into a porous precursor which embedded by Fe species, and then synchronously graphitized and activated to form biocarbon with a large special surface area (2159.3 m2g−1) and high degree of graphitization. The material exhibited a considerable specific capacitance of 297.5 F g−1at 0.5 A g−1and outstanding capacitance retention of 85.7% at 10 A g−1in 6 M KOH, and moreover, achieved an energy density of 16.2 Wh kg−1with the power density of 350.3 W kg−1. After 8000 cycles, an initial capacitance of 95.2% was maintained. Our findings provide a new idea for boosting the rate capacity of carbon-based electrode materials.

For the demand of high reliability in the aerospace field, multi-phase electric machines have become a research hotspot for the fault-tolerant ability. Inter-turn short-circuit fault is one of the main fault forms in the electric machine. The fault mechanism, diagnosis method and fault-tolerant control strategy of inter-turn short-circuit fault of the open-winding five-phase permanent-magnet synchronous machine that is used as the starter/generator system are studied in this paper. Firstly, the fault mechanism of the inter-turn short-circuit fault (ITSCF) is analyzed. The characteristics of phase voltage, inter-turn short-circuit current and torque ripple are compared using the phase winding open-circuit method and the phase winding short-circuit method. Secondly, a fault diagnosis method based on the information fusion is proposed, which determines the fault phase firstly and then identifies the inter-turn short-circuit ratio. According to the fault mechanism, a fault-tolerant control method is proposed, in which the accurate inter-turn short-circuit ratio and inter-turn short-circuit current are not required. The proposed fault-tolerant control method has similar torque ripple compared with the control method using accurate inter-turn short-circuit ratio and inter-turn short-circuit current. Finally, the effectiveness of the proposed fault-tolerant control method has been verified by experimental results.

Electric vehicles are powered by battery packs, which are usually composed of hundreds of units in series or in parallel. For power battery pack performance evaluation, many literatures have been published, including online performance assessment, life prediction and offline performance evaluation. Nevertheless, performance evaluation strategies that include both online and offline have not attracted sufficient attention. In this paper, we propose a performance evaluation method based on MCPE-DEKF, which can solve the problem of consistency analysis and sort of battery cells offline, as well as, implementing battery pack state estimation online. MCPE-DEKF is designed to enhanced the accuracy and adaptability for power battery pack SOC estimation. The pack SOC online estimation value from cells means model and the standard deviation of SOC estimation are combined with MCPE to determine their aggregation weights. An offline evaluation framework for cells grading and sorting problem is solved by MCPE methods. As the results show that, the RMSE of the online estimation for the battery pack is less than 2% and 7 mV for the SOC and the terminal voltage, respectively. The RMSE of the cell estimation is less than 0.3% and 6 mV, respectively. In terms of offline evaluation approaches for cells, we propose an approach with a fusion method to improve the reliability of sorting by integrating method 1 and method 4 (the second-best sorting method).

With the vigorous development of mobile Internet technology and the popularization of smart devices, while the amount of multimedia data has exploded, its forms have become more and more diversified. People’s demand for information is no longer satisfied with single-modal data retrieval, and cross-modal retrieval has become a research hotspot in recent years. Due to the strong feature learning ability of deep learning, cross-modal deep hashing has been extensively studied. However, the similarity of different modalities is difficult to measure directly because of the different distribution and representation of cross-modal. Therefore, it is urgent to eliminate the modal gap and improve retrieval accuracy. Some previous research work has introduced GANs in cross-modal hashing to reduce semantic differences between different modalities. However, most of the existing GAN-based cross-modal hashing methods have some issues such as network training is unstable and gradient disappears, which affect the elimination of modal differences. To solve this issue, this paper proposed a novel Semantic-guided Autoencoder Adversarial Hashing method for cross-modal retrieval (SAAH). First of all, two kinds of adversarial autoencoder networks, under the guidance of semantic multi-labels, maximize the semantic relevance of instances and maintain the immutability of cross-modal. Secondly, under the supervision of semantics, the adversarial module guides the feature learning process and maintains the modality relations. In addition, to maintain the inter-modal correlation of all similar pairs, this paper use two types of loss functions to maintain the similarity. To verify the effectiveness of our proposed method, sufficient experiments were conducted on three widely used cross-modal datasets (MIRFLICKR, NUS-WIDE and MS COCO), and compared with several representatives advanced cross-modal retrieval methods, SAAH achieved leading retrieval performance.

Background: Hepatocellular Carcinoma (HCC), the second leading cause of cancer-related mortality with over half a million new cases diagnosed annually in the world, accounts for nearly 70% of cancer deaths in parts of Asia and Africa. Podophyllum, one of the important members of the lignane class of natural products derived from plants in Podophyllum peltatum L., has been shown to suppress tumor growth in various cancers. However, the effects of Podophyllum compounds on HCC and the mechanisms for its tumor-suppressive function remain unknown. Methods: A molecular docking study was employed to the analysis of the interaction between compounds and their targeted proteins. Cell proliferation was measured by MTT assay. Western blot analysis was used to evaluate protein expression. qRT-PCR was performed to assess RNA expression. Results: Molecular docking analysis was consistent with the beneficial effect of fluorine atom substituent in the 3-position of 2-aminopyridine in our previous study. Also, P-3F and D-3F displayed the most potent cytotoxicities against PLC/PRF/5 with p53-R249S and weakest inhibition of L02 (normal liver cell) growth. However, these derivatives had no effect on the suppression of HepG2 (wild-type p53) and Hep3B (p53-null) proliferation significantly. Further study showed that both compounds increase γ-H2AX expression in PLC/PRF/5 cell, along with repression of the c-Myc activation, purportedly by induction of p53 level and transcriptional activation. Conclusion: The results suggested that podophyllum derivatives containing fluorine atom in the 3-position of 2- aminopyridine could inhibit the growth of HCC harboring p53-R249S by restoring the activity of p53 with decreasing the level of c-Myc.

As the use of electric self-balancing scooters (ESSs) increases, so does the number of related traffic accidents. Because of the special control method, mechanical structure and driving posture, ESSs are prone to various single-vehicle accidents, such as collisions with fixed obstacles and falls due to mechanical failures. In various ESS accident scenarios, the rider's head injury is the most frequent injury type. In this study, several typical single-ESS accident scenarios are reconstructed via computational methods, and the risk of riders' head/brain injury is assessed in depth using various injury criteria. Results showed that two types of ESSs (solo- and two-wheeler) do not have clear differences in head kinematics and head injury risks; the head kinematics (or falling posture) and ESS accident scenario exhibit a distinct effect on the head injury responses; half of the analysed ESS riders have a 50% probability of skull fracture, a few riders have a 50% risk of abbreviated injury scale (AIS) 4+ brain injury, and none has a diffuse axonal injury; the ESS speed plays an important role in producing the head/brain injury in ESS riders, and generally, higher ESS speed generates higher level of predicted head injury parameters. These findings will provide theoretical support for preventing head injury among ESS riders and data support for developing and legislating ESSs.

The ‘support – surrounding rock’ mechanical model has been set up to solve the stability control problem of fully mechanized working face (FMWF) with big dip angle. By the mechanical analysis of SSIDD of working face with big dip angle (WFBDA) in a free state, operating state and special state, we have found the mechanical relationship of critical topple/slip angle with support height, width, resistance and friction coefficient. With the research results applied to #115011 FMWF of Wangwa No. 2 coal mine, the following data have been figured out: in a free state, the critical topple/slip angle of the support are 21.51° and 4.88°. In a special state, the two figures are respectively 64.61° and 39.94°. Thus, the critical support resistance required for the support not to topple or slip is 4,855 kN and 6,591 kN respectively. By movable side guide plate and other technical measures, we realize the safe and efficient production of working face.

A deep eutectic solvent (DES) is a promising electrolyte choice for lithium metal batteries. However, the DES liquid electrolyte causes safety concerns and side reactions with the lithium anode. Therefore, it is necessary to solidify the DES-based electrolyte and enhance its electrochemical stability. Herein, we present a novel DES-based rapid self-healing gel electrolyte, which is able to self-smooth its surface cracks in only 30 min. The electrolyte exhibits noncombustibility (SET = 4 s g–1), high ionic conductivity (1.1 × 10–3S cm–1at 25 °C), and a wide electrochemical voltage window (4.5 V vs Li/Li+). As a result, the solid-state lithium batteries coupling the gel electrolyte with the Li anode and LiFePO4cathode deliver a high specific capacity of 135.4 mA h g–1with durable cyclic stability (>1200 h). This work provides valuable insights for design of fire-resistant and high-energy solid-state lithium batteries.

Ultramicropores and inner space of a novel graphene block are well-characterized by CO2adsorption-desorption method, showing a high capacitive Na+storage ability when certain potential is applied to allow Na+passing through the ultramicropores.

The impact of policies on cultivated land and food security has received global attention, especially in Central Asia, which underwent drastic transformations in land policies during the post-socialist era. Therefore, this study focused on the impacts of policies on the quantity and quality of cultivated land and food security in Central Asia from 1992 to 2015. The results showed that although different land policy reforms were implemented by five Central Asian countries, the cultivated land areas tended to be stable after 2010. The cultivated land increased by approximately 7.02 × 104 km2in Central Asia. After 2000, cultivated land slowly increased and the degree of land degradation rapidly decreased, illustrating that the turning point for the quantity and quality of cultivated land change caused by these policies occurred in 2000. In addition, changes in cotton and grain cultivation occurred in response to the policies of Central Asian countries. Grain per capita increased in land nationalization countries, whereas it decreased in land privatization countries. Thus, driven by policies, the cultivated land use mode in Central Asia was gradually replacing the mode used by the Soviet Union and has been moving toward sustainable development. Some Central Asian countries, however, still face food insecurity.

•The ASNC-600–800 was prepared with the N, S elements co-doped and developed porous structure.•The ASNC-600–800 showed a porous structure with a large surface area.•The ASNC-600–800 electrode materials showed high specific capacity of 500.10 F/g at a current density of 1A/g.•Symmetrical supercapacitor was assembled with an extended operating voltage window of 1.8 V in 1 M Na2SO4aqueous.•The symmetrical supercapacitor device possess the specific energy of 21.15 Wh/kg at specific power of 450 W/kg.

ABSTRACTThe efficacy of PD-1/PD-L1 blockades is heterogeneous in different molecular subtypes of gastric cancer (GC). In this study, we analyzed relevant clinical trials to identify the molecular subtypes associated with the efficacy of PD-1/PD-L1 blockades, and public datasets, patient samples, and GC cell lines were used for investigating potential mechanisms. We found that GC with EBV-positive, MSI-H/dMMR, TMB-H or PIK3CA mutant subtype had enhanced efficacy of PD-L1/PD-1 blockades. Also, differentially expressed genes of these molecular subtypes shared the same gene signature and functional annotations related to immunity. Meanwhile, CIBERSORT identified that the overlapping landscapes of tumor-infiltrating immune cells in the four molecular subtypes were mainly M1-like macrophages (M1). The relationships between M1 and clinical characteristics, M1, and gene signatures associated with PD-1/PD-L1 blockades also revealed that M1 was associated with improved prognosis and required for the efficacy of PD-L1/PD-1 blockades in GC. We identified that tumor-infiltrating CD68+CD163−macrophages could represent M1 calculated by CIBERSORT in clinical application, and CXCL9, 10, 11/CXCR3 axis was involved in the mechanism of CD68+CD163−macrophages in the enhanced efficacy of PD-L1/PD-1 blockades. In conclusion, CD68+CD163−macrophages are required for the efficacy of PD-L1/PD-1 blockades and expand the applicable candidates in GC patients without the molecular subtypes.

Bioenergetic reprogramming during hypoxia adaption is critical to promote hepatocellular carcinoma (HCC) growth and progression. However, the mechanism underlying the orchestration of mitochondrial OXPHOS (oxidative phosphorylation) and glycolysis in hypoxia is not fully understood. Here, we report that mitochondrial UQCC3 (C11orf83) expression increases in hypoxia and correlates with the poor prognosis of HCC patients. Loss of UQCC3 impairs HCC cell proliferation in hypoxia in vitroand in vivo. Mechanistically, UQCC3 forms a positive feedback loop with mitochondrial reactive oxygen species (ROS) to sustain UQCC3 expression and ROS generation in hypoxic HCC cells and subsequently maintains mitochondrial structure and function and stabilizes HIF-1α expression to enhance glycolysis under hypoxia. Thus, UQCC3 plays an indispensable role for bioenergetic reprogramming of HCC cells during hypoxia adaption by simultaneously regulating OXPHOS and glycolysis. The positive feedback between UQCC3 and ROS indicates a self-modulating model within mitochondria that initiates the adaptation of HCC to hypoxic stress.

Insulin-stimulated hepatic glycogen synthesis is central to glucose homeostasis. Here, we show that PPP1R3G, a regulatory subunit of protein phosphatase 1 (PP1), is directly phosphorylated by AKT. PPP1R3G phosphorylation fluctuates with fasting-refeeding cycle and is required for insulin-stimulated dephosphorylation, i.e., activation of glycogen synthase (GS) in hepatocytes. In this study, we demonstrate that knockdown of PPP1R3G significantly inhibits insulin response. The introduction of wild-type PPP1R3G, and not phosphorylation-defective mutants, increases hepatic glycogen deposition, blood glucose clearance, and insulin sensitivity in vivo. Mechanistically, phosphorylated PPP1R3G displays increased binding for, and promotes dephosphorylation of, phospho-GS. Furthermore, PPP1R3B, another regulatory subunit of PP1, binds to the dephosphorylated GS, thereby relaying insulin stimulation to hepatic glycogen deposition. Importantly, this PP1-mediated signaling cascade is independent of GSK3. Therefore, we reveal a regulatory axis consisting of insulin/AKT/PPP1R3G/PPP1R3B that operates in parallel to the GSK3-dependent pathway, controlling glycogen synthesis and glucose homeostasis in insulin signaling.

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