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Distributed Source Coding (DSC), a scheme that encodes multiple correlated sources separately while decoding their bitstreams jointly, is an important branch of network information theory. Due to the advantages of shifting complexity burden from the encoder to the decoder and canceling the flow of data across terminals, DSC has potential applications in many scenarios, e.g., wireless sensor network, distributed genome data compression, etc. There are two forms (lossless and lossy) of DSC. Overlapped arithmetic codes, featured by overlapped intervals, are a variant of arithmetic codes that can implement distributed lossless compression, or the so-called Slepian-Wolf coding. For uniform binary sources, an overlapped arithmetic code is essentially a nonlinear many-to-one mapping that partitions source space into unequal-sized cosets. To analyze overlapped arithmetic codes, two theoretical tools have been proposed, i.e., Coset Cardinality Spectrum (CCS) and Hamming Distance Spectrum (HDS). The former describes how source space is partitioned into cosets (equally or unequally), and the latter describes how codewords are structured within each coset (densely or sparsely). However, until now, these two tools are almost parallel to each other, and it seems that there is no intersection between them. The main contribution of this paper is tightly bridging HDS with CCS. Specifically, HDS can be quickly and accurately calculated with CCS in some cases. In addition, the paper also proves the necessary and sufficient condition for the convergence of HDS and reveals the close relation between divergent HDS and polynomial division. All theoretical analyses are verified by experimental results.

As a host for exchange bias (EB), van der Waals (vdW) magnetic materials have exhibited intriguing and distinct functionalities from conventional magnetic materials. The EB in most vdW systems is far below room temperature, which poses a challenge for practical applications. Here, by using Kerr microscopy, we demonstrate a record-high blocking temperature that approaches room temperature and a huge positive EB field that nears 2 kOe at 100 K in naturally oxidized two-dimensional (2D) vdW ferromagnetic Fe3GaTe2nanoflakes. Moreover, we realized a reversible manipulation of both the presence/absence and positive/negative signs of EB via a training magnetic field without multiple field cooling processes. Thus, our study clearly reveals the robust, sizable, and sign-tunable EB in vdW magnetic materials up to near room temperature, thereby establishing Fe3GaTe2as an emerging room-temperature-operating vdW material and paving the way for designing practical 2D spintronic devices.

Garsorasib (D-1553; InventisBio, Shangai, China), a potent KRASG12Cinhibitor, has shown promising antitumour activity in patients with KRASG12C-mutated (ie, Gly12Cys) non-small-cell lung cancer (NSCLC) in a phase 1 study. We report results from a phase 2 study conducted to evaluate the efficacy and safety of garsorasib in patients with locally advanced or metastatic KRASG12C-mutated NSCLC.

Two selenium (Se)-containing peptides from Se-enriched rice, TSeMMM and SeMDPGQQ, possess neuroprotective potency against lead (Pb2+)-induced cytotoxicity. However, the crosstalk between mRNA and microRNAs (miRNA) involved in the neuroprotection mechanism remains to be elucidated. In this study, RNA-sequencing and miRNA-sequencing were used to independently identify differentially expressed mRNAs and small RNAs profiles in Pb2+-treated primary fetal rat cortical neurons and then the correlated miRNA‑mRNA target pairs were obtained. It was found that 34 mRNAs related to oxidative phosphorylation could be reversed by pretreatment of TSeMMM and SeMDPGQQ. The protective effect of TSeMMM and SeMDPGQQ was mediated by upregulation of miR-107-3p, which downregulates the ATPase H+ transporting V0 subunit e1 (Atp6v0e1) mRNA level. A zebrafish model was applied to verify the relevance between the targeted mRNA and miRNA by real-time quantitative PCR. The results indicated that miR-107-3p was a potential therapeutic target to achieve neuroprotection of Se-containing peptides via stimulation of Atp6v0e1.

CAR-T cell therapies hold great potential in achieving long-term remission in patients suffering from malignancies. However, their efficacy in treating solid tumors is impeded by challenges such as limited infiltration, compromised cancer recognition, decreased cytotoxicity, heightened exhaustion, absence of memory phenotypes, and inevitable toxicity. To surmount these obstacles, researchers are exploring innovative strategies, including the integration of CAR-T cells with targeted inhibitors. The combination of CAR-T therapies with specific targeted drugs has shown promise in enhancing CAR-T cell infiltration into tumor sites, boosting their tumor recognition capabilities, strengthening their cytotoxicity, alleviating exhaustion, promoting the development of a memory phenotype, and reducing toxicity. By harnessing the synergistic potential, a wider range of patients with solid tumors may potentially experience favorable outcomes. To summarize the current combined strategies of CAR-T therapies and targeted therapies, outline the potential mechanisms, and provide insights for future studies, we conducted this review by collecting existing experimental and clinical evidence.

Countries have formulated different transformation plans due to differences in resource endowments, energy strategies, and technological levels. Among them, the Chinese government has proposed continuing to increase the proportion of renewable energy generation in the field of power supply, especially the proportion of wind power, to achieve energy transition. Northern China is rich in wind energy resources, and the demand for heating in autumn and winter is high, providing favorable conditions for promoting wind power heating from the perspective of energy supply and demand. However, the costs and benefits of wind power heating for each participant greatly differ at various stages, and thus, it greatly affects their enthusiasm for participating in wind power heating projects, resulting in great difficulties in promoting and developing wind power heating. Therefore, this study takes Zhangjiakou, a pilot city of wind power heating in northern China, as an example to explore the cost allocation mechanism of wind power heating in China. First, the corresponding costs and benefits for the main participants in wind power heating are analyzed. Second, to consider the impact of the carbon emission reduction benefits and investment payback period on the cost allocation of wind power heating, four scenarios are constructed. Third, based on a cooperative game model, a new cost allocation design for the main participants is developed. Fourth, the key policy factors of the wind power heating trading mechanism and urban heating planning are analyzed. Finally, some suggestions for the promotion and sustainable development of wind power heating are proposed.

Clogging is a major geohazards risk in mechanized tunnelling through cohesive soils. Clay clogging results from the high adhesion between the clay and metal. Based on the water film theory and Reynolds fluid equation, the interfacial adhesion between metal and soil is simplified in this study as viscous hydrodynamic behavior between planes. Considering the influence of capillary force and the viscous force of water film at the interface between metal and soil, a theoretical calculation model of interfacial adhesion between metal and soil is established. The influence of water film thickness and separation rate on the interfacial adhesion between metal and soil is qualitatively analyzed. Then, the adhesion stress between the clay and the metal surface was tested with a pullout test and the influence of moisture content, pullout rates and types of clay minerals on the adhesion stress was analyzed. Finally, the calculation model of adhesion force was compared with the experimental results. The calculation model of soil adhesion stress established in this paper can quantitatively describe the relationship between soil adhesion force and moisture content and can also qualitatively reveal the influence mechanism of soil moisture content on adhesion stress.

Byline: Xin. Ye, Weijun. Fan, Zhongmin. Wang, Junjie. Wang, Hui. Wang, Lizhi. Niu, Yong. Fang, Shanzhi. Gu, Lingxiao. Liu, Baodong. Liu, Yiping. Zhuang, Zhigang. Wei, Xiao. Li, Xiaoguang. Li, Yuliang. [...]

Oncolytic viruses (OVs) are emerging as a potentially useful treatment for malignancies due to the capabilities of direct oncolysis and immune induction. Improving the replication of OVs is an effective approach to enhance the oncolytic effects. Here, we observed that cancer cells with deficiencies in JAK-STAT pathway showed greater sensitivity to oncolytic adenovirus (oAd), and JAK inhibitor could enhance the replication of oAd. Therefore, we constructed a novel oAd expressing SOCS3, a major negative regulator of JAK-STAT pathway, and confirmed that oAd-SOCS3 exhibited a more significant antitumor effect than oAd-Ctrl both in vitro and in vivo. Mechanistically, SOCS3 inhibited the activation of JAK-STAT pathway, resulting in stronger tumor selective replication of oAd and downregulated expression of PD-L1 on cancer cells as well. Both benefits could collectively awaken antitumor immunity. This study highlights the importance of JAK-STAT pathway in viral replication and confirms the treatment of oAd-SOCS3 in potential clinical applications.

• A novel N2S-NiFe modified by -NH 2 and -SH was designed. • The highest CO yield of N2S-NiFe reached 12412.23 μmol g−1 h−1. • Rich defect trap site caused by the introduction of amino and sulfhydryl groups obtained rapid charge transfer and effective space charge separation. • The DFT calculations revealed that ni-fe bimetallic center boosted the charge separation and CO 2 molecules are more inclined to adsorb at niov sites. In this study, a Ni-Fe metal-organic framework modified by –NH 2 and –SH was synthesized using a simple hydrothermal process for enhancing photocatalytic CO 2 reduction. As expected, the N2S-NiFe (NH 2 -BDC/H 4 DSBDC, 2:1) displayed excellent photocatalytic CO 2 reduction activity and high CO selectivity (12,412.23 μmol g−1 h−1) under visible light irradiation (λ ≥ 420 nm), which is 5 times that of NiFe-MOF. Notably, the excellent photocatalytic performance of N2S-NiFe can benefit from the rich defect trap site caused by the introduction of amino and sulfhydryl groups, accelerating charge transfer and promoting space charge separation, as supported by the photo-electrochemical properties. To better understand the CO 2 adsorption mechanism, density functional theory calculations were performed, which revealed that the Niov site has more negative adsorption energy compared with the Feov site. This study provides a simple strategy to establish efficient photocatalysts for CO 2 reduction through the modification of organic ligands. [ABSTRACT FROM AUTHOR]

In this paper, physics-informed liquid networks (PILNs) are proposed based on liquid time-constant networks (LTC) for solving nonlinear partial differential equations (PDEs). In this approach, the network state is controlled via ordinary differential equations (ODEs). The significant advantage is that neurons controlled by ODEs are more expressive compared to simple activation functions. In addition, the PILNs use difference schemes instead of automatic differentiation to construct the residuals of PDEs, which avoid information loss in the neighborhood of sampling points. As this method draws on both the traveling wave method and physics-informed neural networks (PINNs), it has a better physical interpretation. Finally, the KdV equation and the nonlinear Schrödinger equation are solved to test the generalization ability of the PILNs. To the best of the authors’ knowledge, this is the first deep learning method that uses ODEs to simulate the numerical solutions of PDEs.

As an important byproduct of rice bran in the rice milling industry, rice bran oil (RBO) has become increasingly popular in daily diets in recent years. Cadmium (Cd) is a toxic element and easily accumulates in rice bran; thus, it is of great significance to investigate Cd occurrence in RBOs for the sake of public health. In this study, an ultrasound-assisted extraction procedure method using diluted acid followed by inductively coupled plasma mass spectrometry was developed for the determination of Cd in RBOs. Key parameters that affect the ultrasound-assisted extraction of Cd, namely, ultrasonic power, acid extractant, extractant/oil ratio and sonication time, were investigated in detail. Under the optimized extraction conditions with inductively coupled plasma mass spectrometry (ICP-MS) determination, a limit of detection of 0.08 ng g−1, a precision of 5.1%, and recoveries in the range of 97–102% were achieved for the determination of Cd in RBOs. The proposed method is simple, fast and accurate and was applied to analyze RBOs available on the market. The survey showed that the Cd residue was very low, so consumption of RBOs does not pose a risk regarding Cd exposure.

Abstract: The objective of this work was to analyze transformation and excretion of β-asarone in rabbits with gas chromatography–mass spectrometry (GC–MS). The rabbits were administered IV at a dose of 30 mg/kg body weight β-asarone–water–propylene glycol (6:34:60, v/v/v), and urine and feces were collected within 6, 12 and 24 h. At 24 h, the animals were killed and bile was collected. Urine (2 mL) and bile (2 mL) samples were extracted with ether (4 mL), and the feces samples (2 g) were prepared by making an ether-feces (2:1, v/w) homogenate. Ether phase was evaporated and 25 µL psoralen–ether (2.95:1 w/v) was added. All samples were measured with GC–MS. β-Asarone was excreted in urine, feces and bile, and the excretion efficiency was about 62% in urine, 22% in feces, and 16% in bile. About 22% β-asarone was converted into α-asarone. Most β-asarone were excreted in 12 h. Gender differences accounted for no significant influence on the transformation and excretion of β-asarone.

This paper proposes a joint design strategy for enhancing individual user rates in a multi-user system by optimizing both the programmable reflecting elements (PREs) of an active reconfigurable intelligent surface (aRIS) and the transmit beamforming at a base station. Given that the aRIS's PREs are bound by discrete constraints due to low-resolution quantization, this design approach relies on large-scale mixed discrete-continuous problems, which are addressed through a new universal penalised optimization reformulations. Initially, we develop iterations based on convex quadratic solvers (CQ) to tackle the problem of maximizing the users' minimum rate (MR). Given that the computational complexity of these CQs is cubic, leading to high costs in large-scale computations, we introduce a pair of surrogate objectives. These objectives are designed in a way that their constrained optimization can be efficiently managed through iterations of closed-form expressions with scalable complexity, rendering them practical for large-scale computations. This pair of surrogate objectives comprises the maximization of the geometric mean of users' rates (GM-rate maximization) and the soft-maximization of users' MR (soft max-min rate optimization). Remarkably, they not only enhance MR but also contribute to the improvement of the sum-rate (SR). Building upon the GM-rate optimization, we further propose addressing the energy efficiency problem, which achieves a high ratio of SR to power consumption and MR to power dissipation through closed-form expressions. Comprehensive simulations are conducted to validate the efficacy of the proposed solutions.

In this letter, we investigate the mobile edge computing framework with unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS) collaboration, in which a dedicated non-orthogonal multiple access (NOMA) based protocol is introduced for task offloading. In the model, the UAV acts as a relay node and computation server to support multiple ground users for offloading computation tasks to remote access point with the assistance of the RIS. To explore the impact of the joint UAV and RIS design with NOMA on computation performance, the sum computation bits maximization problem is formulated by optimizing computation and offloading bits, RIS phase shift design, UAV trajectory and bandwidth allocation. In order to obtain the solution, the original problem is decomposed into three more tractable subproblems, which can be solved by applying semidefinite relaxation method and successive convex approximation technique. Finally, the numerical solution demonstrates that our proposed algorithm achieves improvements on computation capacity compared with the benchmark and outperforms considerably the scheme without collaboration of the UAV and RIS.

ObjectiveTo investigate the clinical characteristics of children with traumatic spinal cord injury (SCI) admitted to a research rehabilitation center between 2011 and 2020, with a view to generate crucial data for understanding and prevention of pediatric traumatic SCI.DesignRetrospective cohort study.SettingThe National Rehabilitation Research Center of China, Beijing, China.ParticipantsMedical records and imaging data of children with traumatic SCI admitted to the rehabilitation research center from 2011 to 2020.InterventionsNot applicable.Outcome MeasuresData on age, sex, cause of injury, neurological level of injury, impairment scale of SCI and details of spine fracture or dislocation were all collected and analyzed.ResultsA total of 351 patients were included in the study, including 133 males (37.9%) and 218 females (62.1%). There were 231 cases (65.8%) without spine fracture or dislocation. SCI without fracture or dislocation (SCIWORA) was the most common in children between the age of 5 and 14 years (77.9%), and injuries caused by sports were the most common in girls (90.8%). Among sports injuries, those due to a special dance movement called “Xia-Yao” in Chinese, which involves hyperextension of the trunk, constituted the majority, with the neurological level of injuries located predominantly in the middle (34.6%) and lower (44.2%) thoracic levels.ConclusionGirls between the ages of 5 and 14 years constituted the majority of SCIWORA injuries at the thoracic levels, which were caused mainly by “Xia-Yao”. Overall, careful attention should be paid to prevent this kind of injury in children.

Byline: Xin. Ye, Weijun. Fan, Zhongmin. Wang, Junjie. Wang, Hui. Wang, Jun. Wang, Chuntang. Wang, Lizhi. Niu, Yong. Fang, Shanzhi. Gu, Hui. Tian, Baodong. Liu, Lingxiao. Liu, Lou. Zhong, Yiping. [...]

Guillain–Barré syndrome (GBS) is an acute inflammatory polyradiculoneuropathy; a disease involving the peripheral nervous system which is the most common cause of acute flaccid paralysis worldwide. So far, it is still lack of a comprehensive overview and understanding of the national epidemiological, clinical characteristics, and the risk factors of GBS in China, as well as differences between China and other countries and regions in these respects. With the global outbreak of the coronavirus disease 2019 (COVID-19), an epidemiological or phenotypic association between severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and GBS has attracted great attention. In this review, we outlined the current clinical data of GBS in China by retrieving literature, extracting and synthesizing the data of GBS in China from 2010 to 2021. Besides, we compared the characteristics of epidemiology, preceding events and clinical profiles of GBS between China and other countries and regions. Furthermore, in addition to conventional intravenous immunoglobulin (IVIG) and plasma exchange (PE) therapy, the potential therapeutic effects with novel medications in GBS, such as complement inhibitors, etc., have become the research focus in treatments. We found that epidemiological and clinical findings of GBS in China are approximately consistent with those in the International GBS Outcome Study (IGOS) cohort. We provided an overall picture of the present clinical status of GBS in China and summarized the global research progress of GBS, aiming to further understand the characteristics of GBS and improve the future work of GBS worldwide, especially in countries with the middle and low incomes.

Aims:Extracellular vesicles from Lacticaseibacillus paracaseiPC-H1 have antiproliferative activity of colon cells, but the effect on glycolytic metabolism of cancer cell remains enigmatic. The authors investigated how Lacticaseibacillus paracaseiextracellular vesicles (LpEVs) inhibit the growth of colon cancer cells by affecting tumor metabolism. Materials & methods:HCT116 cells were treated with LpEVs and then differentially expressed genes were analyzed by transcriptome sequencing, the sequencing results were confirmed in vivoand in vitro. Results:LpEVs entered colon cancer cells and inhibited their growth. Transcriptome sequencing revealed differentially expressed genes were related to glycolysis. Lactate production, glucose uptake and lactate dehydrogenase activity were significantly reduced after treatment. LpEVs also reduced HIF-1α, GLUT1 and LDHA expression. Conclusion:LpEVs exert their antiproliferative activity of colon cancer cells by decreasing HIF-1α-mediated glycolysis.

With the rapid development of urbanization in the world, it has brought enormous pressure on urban traffic management and control such as traffic congestion. An excellent urban traffic management and control system consists of three critical aspects: obtaining traffic parameters, developing traffic control scheme, and evaluating traffic control scheme. Intersection signal timing is one of the most important parts in urban traffic control. This paper proposed an intersection signal timing system based on traffic video which consists of three parts: acquisition of video-based traffic parameters, calculation of traffic flow-based signal timing scheme, and evaluation of intersection signal timing scheme. In the first part, we used advanced techniques such as deep learning and image processing to obtain traffic parameters such as traffic flow, vehicle type, composition of different vehicle types, and speed of vehicles passing through a scene in a traffic video. In the second part, we calculated the signal timing scheme of the video at the traffic scene through the obtained traffic flow information with Webster method. In the third part, the detailed traffic parameters and signal timing scheme were input into the VISSIM software for traffic microscopic simulation, which was used to evaluate the signal timing scheme. The experimental results show that the accuracy of the detailed traffic flow information obtained by the proposed system can reach more than 90%, the accuracy of composition of different vehicle types can be achieved more than 98%, and the vehicle speed accuracy can reach more than 95%. Therefore, the system improves the reliability and adaptability of the whole signal timing network. At the same time, the simulation results show that the proposed system integrates the acquisition of traffic parameters and the calculation and evaluation of signal timing schemes, and provides a good solution for solving research problems and actual needs such as signal timing optimization.

Vaccination is the best way to build an immune barrier to control a new infectious disease. Considering the limited production capacity at the initial stage of vaccine production, the problem of multistage vaccine production and allocation is studied under the policy of free treatment for infected patients by the government. Given the population and infection rates of different regions and the vaccine production capacity of each stage, an integer programming model is established to minimize the sum of production-and-vaccination cost and treatment cost of infected patients, which is solved by the GUROBI solver. The correctness of the model is verified by simulation, and the necessity of considering the treatment cost of infected patients in the objective function is further analyzed, which confirmed the correctness of the free treatment policy for patients in China. A heuristic algorithm is designed to solve the large-scale problem and numerical experiments are conducted to verify the efficiency of this algorithm. Furthermore, based on the sensitivity analysis results of parameters, the optimal vaccine production and allocation strategy are proposed, which provide the decision basis for the government departments to make reasonable vaccine production and vaccination plan.

Non-orthogonal multiple access (NOMA) is regarded as a promising solution to improve the energy efficiency and reduce the latency of the unmanned aerial vehicle (UAV)-aided networks. In this letter, we consider an energy-efficient multi-UAV incorporating hybrid NOMA data collection system. Explicitly, the optimization problem of joint trajectory design and power allocation is formulated for maximizing energy utilization of the system. The optimization problem is a mixed integer non-convex problem and involves continuous variables. To tackle this challenging problem, we utilize a multi-agent deep reinforcement learning (MADRL) approach, i.e., multi-agent Twin Delayed Deep Deterministic Policy Gradient (MATD3), which introduces clipped double Q-learning and deep networks to reduce overestimation bias. Furthermore, a reward shaping method is applied to speed up the learning efficiency and convergence. Corroborated by extensive experiments, the proposed hybrid NOMA enhanced multi-UAV outperforms pure NOMA and OMA cases.

In recent years, the energy consumption structure has been accelerating towards clean and low-carbon globally, and China has also set positive goals for new energy development, vigorously promoting the development and utilization of renewable energy, accelerating the implementation of renewable energy substitution actions, and focusing on improving the consumption capacity of new energy. However, due to the intermittent and unstable characteristics of renewable energy, it is difficult to meet the demands of the power load side in practical applications. Energy storage is an important link for the grid to efficiently accept new energy, which can significantly improve the consumption of new energy electricity such as wind and photovoltaics by the power grid, ensuring the safe and reliable operation of the grid system, but energy storage is a high-cost resource. Therefore, this paper focuses on the energy storage scenarios for a big data industrial park and studies the energy storage capacity allocation plan and business model of big data industrial park. Firstly, based on the characteristics of the big data industrial park, three energy storage application scenarios were designed, which are grid center, user center, and market center. On this basis, an optimal energy storage configuration model that maximizes total profits was established, and financial evaluation methods were used to analyze the corresponding business models. Finally, taking an actual big data industrial park as an example, the economic viability of energy storage configuration schemes under two scenarios was discussed, and an energy storage system construction plan was proposed to promote the zero-carbon target of the big data industrial park.

In this brief, the oscillation characteristics of multilayer graphene are verified and analyzed by simulating and fabricating a multilayer graphene oscillator with low phase noise. Graphene has strong nonlinearity. Biasing can change the in-band conductivity of graphene. With electromagnetic excitation and DC bias circuit, multilayer graphene can be approximated as a series-parallel connection of multiple discrete element resistors and inductors, which can be used to make resonant circuits. In this brief, we first analyze the principle of bias voltage to change the surface conductivity of graphene, and establish a multilayer graphene Symbolically Defined Devices (G-SDD) simulation model based on the surface conductivity. When the G-SDD model is applied to the oscillator simulation circuit, the simulation results obtained are basically consistent with the experimental results. The multilayer graphene oscillator has an oscillation frequency of about 650 MHz, an output power of 6.48dBm, and a phase noise of −116.40dBc/Hz@1MHz. By comparison with other recent literature the better phase noise characteristics of this design are further highlighted.

Overall survival (OS) benefits of neoadjuvant immunotherapy remain elusive in locally advanced esophageal squamous cell carcinomas (ESCC). Here, we reported the results of a phase 1b trial of neoadjuvant PD-L1 blockade with adebrelimab in resectable ESCC. Patients received two neoadjuvant doses of adebrelimab followed by surgery. The primary endpoints were safety and feasibility; secondary endpoints included pathologic complete response (pCR) and OS. Our data showed the primary endpoints of safety and feasibility had been met. Common treatment-related adverse events were anorexia (32%) and fatigue (16%), without grade 3 or more adverse events. Of the 30 patients enrolled in the trial, 25 underwent successful resection without surgery delay and 24% had major pathologic responses including a pCR rate of 8%. The 2-year OS was 92%. Responsive patients had an immune-enriched tumor microenvironment phenotype, whereas nonresponsive patients had greater infiltration of cancer-associated fibroblasts at baseline. Clonotypic dynamics of pre-existing intratumoral T cells was a hallmark of responsive patients. These findings provide a rational for neoadjuvant anti-PD-L1 monotherapy as a therapeutic strategy for patients with resectable ESCC. ClinicalTrials.gov identifier: NCT04215471.

Byline: Yehua. Shen, Chien-shan. Cheng, Peng. Wang, Xu. Zhu, Guangyan. Lei, Yong. Fang, Hailiang. Li, Weijun. Fan, Hongming. Pan, Zhe. Tang, Kuansheng. Ma, Xiaoguang. Li, Zhengyu. Lin, Yiping. Zhuang, Xin. [...]

LZTFL1 is a tumor suppressor located in chromosomal region 3p21.3 that is deleted frequently and early in various cancer types including the kidney cancer. However, its role in kidney tumorigenesis remains unknown. Here we hypothesized a tumor suppressive function of LZTFL1 in clear cell renal cell carcinoma (ccRCC) and its mechanism of action based on extensive bioinformatics analysis of patients’ tumor data and validated it using both gain- and loss-functional studies in kidney tumor cell lines and patient-derive xenograft (PDX) model systems. Our studies indicated that LZTFL1 inhibits kidney tumor cell proliferation by destabilizing AKT through ZNRF1-mediated ubiquitin proteosome pathway and inducing cell cycle arrest at G1. Clinically, we found that LZTFL1 is frequently deleted in ccRCC. Downregulation of LZTFL1 is associated with a poor ccRCC outcome and may be used as prognostic maker. Furthermore, we show that overexpression of LZTFL1 in PDX via lentiviral delivery suppressed PDX growth, suggesting that re-expression of LZTFL1 may be a therapeutic strategy against ccRCC.

In the present study, the effects of cooked rice (CR) with added fructo-oligosaccharide (FOS) on faecal flora were studied by a simulated in vitrodigestion and fermentation method. The total carbohydrate content, pH, and short-chain fatty acids (SCFAs) were determined during in vitrodigestion and fermentation. The change in the bacterial phase distribution after the fermentation was also analysed. The results showed that the total carbohydrate content of the CR with added FOS (FCR) significantly decreased during the simulated digestion. Meanwhile, the pH of the FCR decreased and the SCFAs concentration increased significantly compared to those of the CR during the simulated fermentation. In addition, the FCR showed the advantage of promoting beneficial bacteria, such as Bifidobacteriumand Lactobacillus, and inhibiting harmful bacteria, such as Bacteroidesand Klebsiellacompared to the CR. Therefore, the FOS as a prebiotic could be recommended to produce the high-quality healthy rice food.

Vehicle-to-vehicle (V2V) communication is the most typical application of the Internet of Vehicles, and it has many envisaged applications, such as driverless driving, collision warning and addressing traffic congestion. The realization of future intelligent transportation systems (ITSs) will require V2V communication technology, which in turn relies on accurate V2V channel estimation. As the possibilities that 5G technologies can be used for V2V communications are increasingly being explored, corresponding channel models used to describe the characteristics of V2V channels are also being updated, so the new channel estimation algorithms needed to be developed. Although the channel estimation method based on Convolutional Neural Network (CNN) has achieved remarkable success in communication problems in recent years, it cannot be well adapted to V2V channels under different scenarios and different modeling methods. In this article, a method is proposed for learning and estimating the channel structure in the 5G NR downlink that can adapt to the V2V channel under multi-scenes. The inherent block sparsity characteristics of the channel structure is adopted to combine the group lasso Alternating Direction Method of Multipliers (ADMM) algorithm with CNN, and residual dense network is employed to estimate and refine the V2V channel structure. Furthermore, the classifier and interpolation with pooling method are used to estimate the V2V channel structure under multi-scene and multi-resolution. Simulation results show that the performance of this method is better than other deep learning based estimation algorithms.

The vertical-structure heterojunction has been highlighted as a promising candidate for the solar-blind ultraviolet (UV) photodetector (PD) due to the control of its channel length and the strong electric field-induced high carrier mobility. Meanwhile, carbon nanodot (CND) has drawn great attention to be playing an essential role in absorbing solar-blind UV waves as the active layer of the PD. However, CND prepared for solar-blind UV PDs, independent of sophisticated manufacturing method and extreme process conditions, has yet to be well developed. Herein, for the very first time, a vertical structure CNDs/graphene heterojunction type solar-blind UV PD is introduced, where the CND and the graphene are used as the photosensitive layer and the transparent electrode, respectively. Particularly, the CND is fabricated with a low-cost and one-step electrochemical strategy. The device realizes an optimized performance tradeoff, presenting responsivity of 76.01 mA/W, normalized detectivity of $4.17\times 10^{{10}}$ Jones, and rise/decay time of 0.54/0.27 s under the illumination of 1.47 mW/cm2 at 254-nm wavelength, along with the bias voltage of −5 V and the substrate voltage of 10 V applied. The results show that this work has unlocked the critical bottleneck of developing a graphene-based solar-blind UV PD with higher responsivity, greater detectivity, and shorter response time, unveiling the potential for missile warning, flame detection, and other areas of interest.

As an emerging carbon-based material, carbon quantum dots (CQDs) have shown unstoppable prospects in the field of bionic electronics with their outstanding optoelectronic properties and unique biocompatible characteristics. In this study, a novel CQD-based memristor is proposed for neuromorphic computing. Unlike the models that rely on the formation and rupturing of conductive filaments, it is speculated that the resistance switching mechanism of CQD-based memristors is due to the conductive path caused by the hybridization state transition of the sp2carbon domain and sp3carbon domain induced by the reversible electric field. This avoids the drawback of uncontrollable nucleation sites leading to the random formation of conductive filaments in resistive switching. Importantly, it illustrates that the coefficient of variation (CV) of the threshold voltage can be as low as −1.551% and 0.083%, which confirms the remarkable uniform switching characteristics. Interestingly, the Pavlov's dog reflection as an important biological behavior can be demonstrated by the samples. Finally, the accuracy recognition rate of MNIST handwriting can reach up to 96.7%, which is very close to the ideal number (97.8%). A carbon-based memristor based on a new mechanism presented provides new possibilities for the improvement of brain-like computing.

Distributed Arithmetic Coding (DAC) is a practical realization of Slepian-Wolf coding, one of whose properties is Coset Cardinality Spectrum (CCS). The initial CCS is especially important because it has many applications. Up to now, the initial CCS is calculable only for some discrete rates, while in general cases, the time-consuming numerical algorithm is needed. Though a polynomial approximation of the initial CCS has been proposed recently, its complexity becomes very high as code rate decreases. Hence, this letter aims at finding simpler approximations for the initial CCS at low rates by proposing two methods: interpolation approximation and bell-shaped approximation. The effectiveness of both methods is illustrated by simulation results.

Laplacian distribution is widely used to model the differences between correlated continuous or nonbinary signals, e.g., the predictive residues of videos. Usually, distributed coding of correlated nonbinary sources, e.g., distributed video coding, is implemented by binary or nonbinary Low-Density Parity-Check (LDPC) codes. In this paper, as an alternative, we attempt using nonbinary Distributed Arithmetic Coding (DAC) to implement distributed coding of uniform nonbinary sources with Laplace-distributed correlation. To analyze $Q$ -ary DAC for uniform $Q$ -ary sources, following the methodology developed in our prior work for binary DAC, we define and deduce Coset Cardinality Spectrum (CCS) from both fixed-length and variable-length perspectives, whose physical meanings are explained in detail; while for binary DAC, our prior work totally ignored the subtle difference between these two perspectives. Compared with binary DAC, an important advantage of nonbinary DAC is that, the mapping from source symbols to coding intervals is so flexible that there are many parameters that can be tuned to achieve better performance; while for binary DAC, there are very few tunable parameters, making it very hard to achieve better performance. This paper proposes a simple method to map source symbols onto coding intervals, which results in a very lightweight codec, while possessing a good Manhattan distance distribution. Then this paper deduces the formula of path metrics for decoder design by making use of CCS. All theoretical analyses are perfectly verified by simulation results. Most important, experimental results show that $Q$ -ary DAC achieves significantly better performance than LDPC codes for distributed coding of uniform $Q$ -ary sources with Laplace-distributed correlation.

The Ice, Cloud and Land Elevation Satellite (ICESat-2) offers an unprecedented high density of laser data on the Earth’s surface. Evaluation and calibration of geolocation errors are important for the scientific application of laser data. In this study, a crossover method is proposed to evaluate and calibrate errors. This method mainly relies on small-scale reference data and consistency conditions at the trajectory crossovers. By matching the profile measurements of the ascending and descending altimeter tracks to find the location where the crossover discrepancy is minimized, the geolocation errors of the wide-area laser data are estimated. Three years of ICESat-2 measurements over the Ridgecrest (CA19) in the southern United States and McMurdo Dry Valleys (MDV) in eastern Antarctica were used to test the performance of the method. It was shown that the method can be used to estimate the geolocation error of the ICESat-2 laser data, which ranged from 4.65 to 5.62 m for both sites. After calibration, the mean absolute error of the crossover discrepancies was reduced by approximately 50%. In addition, with the reference digital elevation model (DEM) as the true value, the elevation accuracy (RMSE) of the laser data at the CA19 site improved from 0.38 m before calibration to 0.34 m after calibration, and the improvement at the MDV site was even more significant, about 0.22 m. In conclusion, the proposed method is effective and feasible and can improve the consistency of long-period laser data quality in large areas.

Background: The purpose of this randomized controlled trial was to determine if enhanced recovery after surgery (ERAS) would improve outcomes for three-stage minimally invasive esophagectomy (MIE). Methods: Patients with esophageal cancer undergoing MIE between March 2016 and August 2018 were consecutively enrolled, and were randomly divided into 2 groups: ERAS+group that received a guideline-based ERAS protocol, and ERAS- group that received standard care. The primary endpoint was morbidity after MIE. The secondary endpoints were the length of stay (LOS) and time to ambulation after the surgery. The perioperative results including the Surgical Apgar Score (SAS) and Visualized Analgesia Score (VAS) were also collected and compared. Results: A total of 60 patients in the ERAS+ group and 58 patients in the ERAS- group were included. Postoperatively, lower morbidity and pulmonary complication rate were recorded in the ERAS+ group (33.3% vs. 51.7%; p= 0.04, 16.7% vs. 32.8%; p= 0.04), while the incidence of anastomotic leakage remained comparable (11.7% vs. 15.5%; p= 0.54). There was an earlier ambulation (3 [2–3] days vs. 3 [3–4] days, p= 0.001), but comparable LOS (10 [9–11.25] days vs. 10 [9–13] days; p= 0.165) recorded in ERAS+ group. The ERAS protocol led to close scores in both SAS (7.80 ± 1.03 vs. 8.07 ± 0.89, p= 0.21) and VAS (1.74 ± 0.85 vs. 1.78 ± 1.06, p= 0.84). Conclusions: Implementation of an ERAS protocol for patients undergoing MIE resulted in earlier ambulation and lower pulmonary complications, without a change in anastomotic leakage or length of hospital stay. Further studies on minimizing leakage should be addressed in ERAS for MIE.

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[Display omitted] • The hacker group identification method based on heterogeneous graph. • Web attack chain structure representation model called Web attack heterogeneous information network (WAHIN). • Hacker group feature extraction method based on heterogeneous graph attention network (HAN). • The experiments show that HGHAN method perform better than other heterogeneous graph algorithm in WAHIN. The hacker group identification is an important pre-work for tasks such as hacking tracing, criminal portraits. The current hacker identification mainly relies on fingerprints and clue collection. However, the increasing complexity of organizational attacks makes cyber-attacks no longer a single action, but a hierarchical attack chain. It is indeed a big challenge of portraying the complete attack chain and correlating multiple attack records. In addition, extracting feature information of hacker groups from the attack chain requires a novel solution to optimize the conventional identification. This paper proposes a novel method HGHAN for hacker group identification based on the heterogeneous graph. The core of HGHAN is the heterogeneous graph attention network. It extracts the hacker group feature from the Web attack heterogeneous information network, which models the Web attack chain of hacker groups. Through experiments on Web attack data from the Zone-H.org site, the results prove that the HAN algorithm improves the performance of hacker group identification, and has a better identification effect than other heterogeneous graph node embedding algorithms. [ABSTRACT FROM AUTHOR]

This paper develops an arithmetic coding algorithm based on delta recurrent neural network for edge computing devices called DRAC. Our algorithm is implemented on a Xilinx Zynq 7000 Soc board. We evaluate DRAC with four datasets and compare it with the state-of-the-art compressor DeepZip. The experimental results show that DRAC outperforms DeepZip and achieves 5X speedup ratio and 20X power consumption saving.

This paper considers the Cohen-Grossberg BAM neural networks (CG-BAMNNs) on time scale, which can unify and generalize the continuous and discrete systems. First, the criteria for the existence and uniqueness of the equilibrium of CG-BAMNNs are derived on time scale. Then based on that, the authors give the criteria for the stability and estimation of equilibrium of the CG-BAMNNs on time scale. The method proposed in this paper unifies and generalizes the continuous and discrete CG-BAMNNs systems, and is applicable to some other neural network systems on time scale with practical meaning. The effectiveness of the proposed criteria for delayed CG-BAMNNs is demonstrated by numerical simulation.

This paper is concerned with distributed consensus control of unknown multiagent systems. As the system’s dynamics is unknown, an adaptive Fourier decomposition (AFD) based iterative learning control (ILC) dynamics adaptive matching method in frequency domain is put forward to deal with it. First, large amounts of input and output measurement data are used to estimate the frequency domain characteristics of the system by Takenaka-Malmquist functions. Second, convert the traditional time domain ILC to the frequency domain to establish a matching relationship with the estimated frequency domain features. Then, an adaptive iterative learning rate is constructed to achieve the optimal convergence at each sampling point. The feasibility of the proposed algorithm is guaranteed by the convergence of AFD in Hardy space $H^{2}(\mathbb {D})$ under the maximum selection principle. Compared with the reinforcement learning data-driven control scheme, the method proposed in this paper has obvious advantages in the control accuracy and convergence efficiency. In addition, this paper takes two kinds of denoising algorithms based on unwinding AFD to deal with the multi-agent systems with channel noise. Finally, the feasibility and effectiveness of the developed method are verified by a series of simulations. [ABSTRACT FROM AUTHOR]

ABSTRACTSince circCDR1 was abnormally expressed in esophageal squamous cell cancer (ESCC), the current study explored whether circCDR1 affected ESCC. Detailedly, circCDR1 expression in ESCC and linear isoform and stability of circCDR1 were detected by RT-qPCR. The location of circCDR1 was detected by fluorescence in situhybridization (FISH). After transfection, the cell biological functions were detected by wound-healing, CCK-8, colony formation, and flow cytometry assays. The target of circCDR1 was predicted by bioinformatics, FISH, RNA pull-down, and dual-luciferase reporter assays. The correlation between circCDR1 and miR-1290 was analyzed by Pearson’s correlation analysis. A subcutaneous-xenotransplant tumor model in BALB/c nude mice was established and the levels of circCDR1, miR-1290, and apoptosis/metastasis/proliferation-related factors in the cancer cells and tissues were detected by immunohistochemical analysis, western blot, or RT-qPCR. As a result, circCDR1 was low-expressed in ESCC tissues and cells, while miR-1290 was high-expressed. CircCDR1 was regulated and was negatively correlated with miR-1290. CircCDR1, located in cytoplasm, inhibited the viability, proliferation, migration, and invasion of the cancer cells and the expressions of Bcl-2, N-cadherin, and Vimentin, but enhanced cell apoptosis and the expressions of C caspase-3, Bax, E-cadherin, IGFBP4, LHX6 and NFIX. In vivo, circCDR1 promoted xenotransplanted tumor weight and volume, and the expressions of C caspase-3 and Bax yet suppressed the levels of Bcl-2, miR-1290, and Ki-67 in tumor tissues. The effects of circCDR1 on both cancer cells and tissues were opposite to and reversed by miR-1290 mimic. Collectively, circCDR1 sponged miR-1290 to regulate the progression of ESCC both in vitroand in vivo.

• The progress in building electromagnetic waves absorbing materials is reviewed. • We classify electromagnetic waves absorbing materials from building angles. • The challenges of building electromagnetic waves absorbing materials are analyzed. • The future research direction is analyzed systematically and comprehensively. Healthy and livable living environments, as well as anti-electromagnetic (EM) radiation buildings, are the long-term goals of human beings. The introduction of advanced EM wave absorbing materials into buildings is one of the most feasible ways to address the increasing EM pollution in building spaces. High-efficiency, broadband, low-cost and good building performance EM wave absorbing materials, as an important support in the field of sustainable building, has gradually become the hotspot research. Here, we review the research progress of building materials with EM wave absorption functions, and comb their classification, including cement, concrete, ceramics, and prefabs, especially highlighting the advanced coating materials. We objectively outline and evaluate the latest technology of building materials with EM wave absorption performance, and discuss the main problems and bottlenecks, highlighting potential research opportunities. [ABSTRACT FROM AUTHOR]

Background: The aim of the study was to investigate whether the expression of CD27−CD38+in interferon (IFN)-γ+CD4+T cells stimulated by the specific antigen early secreted antigenic target-6 (ESAT-6)/culture filter protein-10 (CFP-10) could be a potential new therapeutic evaluation indicator for anti-tuberculosis (TB) treatment. Methods: Newly diagnosed active pulmonary TB patients, latent TB infection (LTBI) and healthy controls were enrolled from January 2021 to December 2021. PTB patients were treated by standard anti-TB regimen 2HREZ/4HR (2 months of isoniazid (H), rifampin (R), ethambutol (E), and pyrazinamide (Z) followed by 4 months of isoniazid (H) and rifampin (R)). The difference of CD27−CD38+expression in IFN-γ+CD4+T cells before treatment, 2 months after treatment, and 6 months after treatment were compared. Results: Total 45 PTB patients, 38 LTBI cases and 43 healthy controls were enrolled. The expression of CD27−CD38+decreased significantly after anti-TB treatment and was comparable with that in LTBI and healthy controls when the 6-month anti-TB treatment course was completed. The decline rate of CD27−CD38+between 6 months after treatment and baseline was positively correlated with erythrocyte sedimentation rate (r= 0.766, P< 0.0001), C-reactive protein (r= 0.560, P= 0.003) and chest computerized tomography severity score (r= 0.632, P= 0.0005). The area under receiver operator characteristic curve of CD27−CD38+in distinguish pulmonary TB patients before and after treatment was 0.779. Conclusion: The expression of CD27−CD38+in ESAT-6/CFP-10 stimulated IFN-γ+CD4+T cells can well reflect the changes of the disease before and after anti-TB treatment, which is expected to be a potential new therapeutic evaluation index.

The TSeMMM and SeMDPGQQ, two selenium-containing peptides derived from Se-enriched rice protein hydrolysates, have previously been demonstrated to show neuroprotective properties against high-dose lead exposure. However, the potential toxicological effects of these functional peptides on low-dose lead-induced neurotoxicity remain poorly understood. The present study aimed to investigate the protective mechanism of two selenium-containing peptides in mitigating low-dose Pb2+-induced damage in HT22 cells. Results showed that treatment with 40 μmol/L Pb2+significantly reduced cell viability and increased apoptosis, both of which were alleviated by 40 μmol/L TSeMMM and SeMDPGQQ treatment. Furthermore, two peptides exhibited antioxidant potentials by reducing reactive oxygen species levels to 32.19% and 79.29% of the model group, respectively. They also enhanced antioxidant enzyme activities and mitigated oxidative stress through activation of the Keap1/Nrf2 pathway. Additionally, two peptides improved mitochondrial function by elevating mitochondrial membrane potential, ATP production while dramatically reducing reactive oxygen species levels. Interestingly, TSeMMM exhibited superior neurointerventional effects compared to SeMDPGQQ. The RNA sequencing analysis revealed that TSeMMM modulated gene expressions related to oxidative stress and neuroprotective function. The study provides insights into the protective mechanism underlying selenium-containing peptides for mitigating neuronal damage.

Despite the strong light absorption and high efficiency of multiple carrier generation and collection of carbon dots (CDs), little attention has been paid to the field of photodetection. Herein, CDs are synthesized through a green and facile strategy, which only uses graphite rods and distilled water. It is found that the oxygen content and the optical properties of CDs could be modulated by the voltage applied between the two graphite rods. A series of tests reveal that the excitation-independent blue photoluminescence (PL) emission of as-prepared CDs is related to the topological defects. And the oxygen-containing groups would bring new energy levels between the band gaps of CDs, which enhanced the excitation-dependent yellow-green PL emission and the absorption from the near-ultraviolet (UV) to the visible range. The CDs with fewer oxygen-containing groups show strong UV absorption and short cutoff wavelength, and they are utilized to fabricate solar-blind UV photodetectors. Tested under 254 nm UV illumination, the detectors exhibit a high photoresponsivity (1.14 mA/W) and highly characteristic wavelength-dependent response (R254/R365= 115). This study provides a deeper understanding of the relationships between optical properties and the structure/composition of CDs. More importantly, the solution processability of CDs paves the way for future high-performance, low-cost solar-blind photodetectors.