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Glioma is a common cancer in the central system. Exosomes play a key role in malignancies. This study mainly investigates the effect and mechanism of microRNA-1246 from self-derived exosomes on the apoptotic activities of astroglioma cells. Samples of malignant glioma were collected to measure microRNA-1246 expression. The glioma cells were cultured and their secreted exosomes were collected. Cells were randomized into NC group, miRNA-1246-mimic group and miRNA-1246-inhibitor group followed by analysis of invasion capability, expression of miR-1246 and CAMD1 gene, and AMD1 and apoptosis-related proteins expression by Western-blot as well as the relationship between miRNA-1246 and CAMD1. Under electron microscope, exosomes exhibited round shapes with a diameter of 50–290 nm and a positive expression of CD9 and CD63. miRNA-1246 was upregulated in exosomes from astroglioma patients. miRNA-1246 downregulated CADMI and apoptosis-related protein Bcl-2, but upregulated Caspase-3 and pro-apoptosis proteins in glioma cells. Moreover, miRNA-1246 facilitates astroglioma cells invasion while restraining apoptotic activities. CADM1 was confirmed to be a target of miRNA-1246. In conclusion, miR-1246 is highly expressed in exosomes that originated from astroglioma cells and suppressed the apoptosis of glioma cells via targeting CAMD1 genes.

The Yangtze River Basin, one of China’s five major watersheds and a primary source of drinking water for the country, is experiencing serious environmental pollution as heavy metals are discharged into its rivers. To evaluate the water quality of the river, determined water quality parameters were compared with the maximum permissible limit values recommended by the World Health Organization and Chinese drinking water standards. Physical and chemical analyses were conducted on water samples taken from 19 locations along the river’s path. The study quantified the contents of sodium (Na), magnesium (Mg), calcium (Ca), strontium (Sr), barium (Ba), lithium (Li), cobalt (Co), copper (Cu), iron (Fe), manganese (Mn), scandium (Sc) and mercury (Hg). The results show that the average values of Mg, Sr, Co, Cu, Fe, Mn and Sc are higher than the historical background values. Moreover, through a correlation analysis it was concluded that these nutrients and trace metals have high values due to anthropogenic pollution in the study area. The computed WQI values range between 9.59 and 20.26, indicating excellent water quality in the river basin. Finally, hazard quotient (HQ) values show that exposure to the detected pollutants will have no adverse effects on human health and does not pose a potential non-carcinogenic risk.

Developing efficient strategies for searching larger Bayesian networks in exact structure learning is an open challenge. In this study, ancestral and heuristic partition constraints are proposed to develop a series of exact learning algorithms, in which an ancestral partition is used to prune the order graph of a Bayesian network, and a heuristic partition is utilized to improve the tightness of the heuristic function. Algorithms for calculating these two types of constraints are established through thorough theoretical proof. Comparative experiments have been undertaken with state-of-the-art algorithms. It has been demonstrated that an algorithm improved with the proposed ancestral partition or combined ancestral and heuristic partition outperforms the algorithm in its original form, and it can have lower running time, fewer expanded states, and higher accuracy, as well as the ability to search larger networks within 100 nodes.

Microglia are innate immune cells of the central nervous system. After the onset of Ischemic stroke, excessive neuroinflammation would cause further damage to brain tissue, which is characterized by microglial activation and the release of inflammatory cytokines. Earlier studies have shown that SENP3 is raised in the brain tissue of ischemic stroke animals. We further demonstrated that SENP3 induced TLR activation and the downstream production of proinflammatory mediators, such as TNF-a, IL-1β, and iNOS. Our study of the mechanism suggested that knocking down SENP3 in microglia significantly would decreased the deSUMOylating of MKK7 and the phosphorylation of JNK in TLR4 signaling pathway, inhibited TLR4 activation and the downstream production of proinflammatory mediators. This pathway could represent a potential therapeutic target for cerebral hypoxic diseases associated with microglial activation and the inflammatory response.

The good consistency of acoustic emission sensor sensitivity is the premise to ensure accurate and reliable acoustic emission detection. To facilitate the sensitivity consistency test of acoustic emission sensors, a set of acoustic emission sensor sensitivity consistency test platform was built in this paper. The key parameters of the test device and test conditions are studied through simulation analysis and actual test. The research results show that the pulse signal excitation of the transducer can provide a stable excitation source for the test. The propagation of the acoustic signal in the test block is affected by its diameter and thickness. The acoustic signal propagation is relatively stable in a steel plate with a diameter of 600 mm and a thickness of 8 mm. The test position is related to the size of the test block. This study provides a convenient device and specific method for the sensitivity consistency test of acoustic emission sensors.

Gravity is the most important load source in mining and geotechnical engineering, which causes both the stress level and stress gradient inside geomaterials. Different from the stress level, the influence of gravity-induced stress gradient on the behaviour of the material is still unknown. An in-deep study on it will help to promote the understanding of material behaviour, especially for those cases related to unconventional gravity such as terrestrial ng physical modelling and extraterrestrial resource exploitation (g is the terrestrial gravitational acceleration). In this study, a high-order homogenization for granular materials is proposed at first, in which the stress gradient is drawn into the constitutive representation by adopting a representative volume element (RVE). The consolidation and shear strength behaviour of RVE are then investigated by performing numerical biaxial tests. The results show that all the compressibility, shear strength, shear stiffness, volumetric deformation, and critical state behaviour show a stress gradient dependence. A coupling between stress gradient, stress level, and material properties is also observed. These observations suggest that, besides the stress level, extra attention needs to be paid to material responses related to stress gradient during engineering practices.

Tracking maneuvering target in real time autonomously and accurately in an uncertain environment is one of the challenging missions for unmanned aerial vehicles (UAVs). In this paper, aiming to address the control problem of maneuvering target tracking and obstacle avoidance, an online path planning approach for UAV is developed based on deep reinforcement learning. Through end-to-end learning powered by neural networks, the proposed approach can achieve the perception of the environment and continuous motion output control. This proposed approach includes: (1) A deep deterministic policy gradient (DDPG)-based control framework to provide learning and autonomous decision-making capability for UAVs; (2) An improved method named MN-DDPG for introducing a type of mixed noises to assist UAV with exploring stochastic strategies for online optimal planning; and (3) An algorithm of task-decomposition and pre-training for efficient transfer learning to improve the generalization capability of UAV’s control model built based on MN-DDPG. The experimental simulation results have verified that the proposed approach can achieve good self-adaptive adjustment of UAV’s flight attitude in the tasks of maneuvering target tracking with a significant improvement in generalization capability and training efficiency of UAV tracking controller in uncertain environments.

River–lake interaction is important for maintaining biodiversity, yet it is vulnerable to hydrological alteration. The connectivity of the channel connecting Poyang Lake and the Yangtze River not only ensures the regular migration of fish but also makes Poyang Lake a feeding and fattening ground for them. Unfortunately, human activities have dramatically changed the hydrodynamic conditions of Poyang Lake, which is experiencing severe drought due to the obvious decline in the water level in autumn and winter, especially since 2003. However, the possible impacts of the changes in the water level on the habitats of migratory fish remain unclear due to the limitation of traditional techniques in spatiotemporal analysis. Here, we combined a hydrodynamic model and habitat suitability model to simulate variations in the suitable habitat area and their connectivity under different water-level conditions. The conditions for the migration pathway of the target fish were obtained by a hydroacoustic survey using the Simrad EY60 echosounder. The results showed that the change in water level will significantly affect the spatiotemporal change in the suitable habitats and their connectivity. In particular, we found the existence of two thresholds that play a dominant role in illuminating the connectivity of effective suitable habitats (HC). Firstly, the maximum value of the weighted usable area (WUA) and HC can be achieved when the water level is more than 16 m. Secondly, when the water level is between 10 and 16 m, the changes in the HC are sensitive and rapid, and the area flooded at this stage is called the sensitive area. HC is a crucial element in fish migration and habitat conditions. Under the condition of continuous drought in the middle reaches of the Yangtze River, our research contributes to clarifying the influence of water level on key habitats for fish and optimizes the practice of river–lake ecological management.

In recent years, a variety of supervised manifold learning techniques have been proposed to outperform their unsupervised alternative versions in terms of classification accuracy and data structure capturing. Some dissimilarity measures have been used in these techniques to guide the dimensionality reduction process. Their good performance was empirically demonstrated; however, the relevant analysis is still missing. This paper contributes to a theoretical analysis on a) how dissimilarity measures affect maintaining manifold neighbourhood structure and b) how supervised manifold learning techniques could contribute to the reduction of classification error. This paper also provides a cross-comparison between supervised and unsupervised manifold learning approaches in terms of structure capturing using Kendall’s Tau coefficients and co-ranking matrices. Four different metrics (including three dissimilarity measures and Euclidean distance) have been considered along with manifold learning methods such as Isomap, ${t}$ -Stochastic Neighbour Embedding ( ${t}$ -SNE), and Laplacian Eigenmaps (LE), in two datasets: Breast Cancer and Swiss-Roll. This paper concludes that although the dissimilarity measures used in the manifold learning techniques can reduce classification error, they do not learn well or preserve the structure of the hidden manifold in the high dimensional space, but instead, they destroy the structure of the data. Based on the findings of this paper, it is advisable to use supervised manifold learning techniques as a pre-processing step in classification. In addition, it is not advisable to apply supervised manifold learning for visualization purposes since the two-dimensional representation using supervised manifold learning does not improve the preservation of data structure.

The synthesis, spectroscopy, crystal structure, and electrochemical behavior of cis-β-RuII(CO)2, cis-β-RuII(CO)(H2O), and cis-β-RuII(CO)(carbene) complexes supported by sterically bulky salen ligan...

Aiming at the problem of strong subjectivity and insufficient data utilisation in the traditional ship formation combat effectiveness analysis method, this study proposes a performance analysis fitting model based on deep belief network (DBN), which effectively reconstructs the combat model and improves the accuracy of the effectiveness analysis of the combat system. Firstly, the ship formation air defence effectiveness analysis index system is constructed, and then the structure and training method of the performance analysis fitting model are introduced. Finally, based on the formation of air defence combat, the performance analysis fitting model based on DBN and its comparative experiments are simulated and analysed. Simulation results verify the applicability and effectiveness of the model and method.

Real-time resource allocation is crucial for phased array radars to undertake multi-task with limited resources such as in the situation of multi-target tracking, in which targets need to be prioritized so that resources can be allocated accordingly and effectively. In this paper, a three-way decision-based model is proposed for adaptive scheduling of phased radar dwell time. Using the model, the threat posed by a target is measured by an evaluation function, and therefore, a target is assigned to one of the three possible decision regions, i.e., positive region, negative region, and boundary region. A different region has a various priority in terms of resource demand, and as such, a different radar resource allocation decision is applied to each region to satisfy different tracking accuracy of multi-target. In addition, the dwell time scheduling model can be further optimized by implementing a strategy for determining a proper threshold of three-way decision making to optimize the thresholds adaptively in real-time. The advantages and the performance of the proposed model has been verified by experimental simulations with comparison to the traditional two-way decision model and the three-way decision model without threshold optimization. The experiential results have demonstrated that the performance of the proposed model has a certain advantage in detecting high threat targets. 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

In order to solve the problems of existing threat assessment algorithms, a threat assessment method based on intuitionistic fuzzy three-way decision method is proposed. Firstly, the indexes are described by theory of intuitionistic fuzzy sets on the basis of that the threat assessment index system is established. Then, TOPSIS method is used to calculate the target threat. Finally, the targets are classified by three-way decision method according to the result of target threat. It is proved that it is feasible to introduce three-way decision method into threat assessment. At the same time, an improved algorithm for calculating the threshold of three-way decision is proposed. Experiments show that the improved algorithm has stable results and good classification effect.

The South China tiger (Panthera tigris amoyensis, SCT) is the most critically endangered subspecies of tiger due to functional extinction in the wild. Inbreeding depression is observed among the captive population descended from six wild ancestors, resulting in high juvenile mortality and low reproduction. We assembled and characterized the first SCT genome and an improved Amur tiger (P. t. altaica, AT) genome named AmyTig1.0 and PanTig2.0. The two genomes are the most continuous and comprehensive among any tiger genomes yet reported at the chromosomal level. By using the two genomes and resequencing data of 15 SCT and 13 AT individuals, we investigated the genomic signature of inbreeding depression of the SCT. The results indicated that the effective population size of SCT experienced three phases of decline, ~5.0-1.0 thousand years ago, 100 years ago, and since captive breeding in 1963. We found 43 long runs of homozygosity fragments that were shared by all individuals in the SCT population and covered a total length of 20.63% in the SCT genome. We also detected a large proportion of identical-by-descent segments across the genome in the SCT population, especially on ChrB4. Deleterious nonsynonymous single nucleotide polymorphic sites and loss-of-function mutations were found across genomes with extensive potential influences, despite a proportion of these loads having been purged by inbreeding depression. Our research provides an invaluable resource for the formulation of genetic management policies for the South China tiger such as developing genome-based breeding and genetic rescue strategy.

In this study, ultrasonic pulse velocity (UPV) and ultrasonic shear-wave tomography are combined to measure the residual compressive strength (RCS) of small-scale lining concrete blocks and to detect inner defects in the lining structure. The characteristics of and variations in the RCS of test blocks after being exposed to elevated temperatures (200–800 °C) and constant heating times (2 h, 3 h, and 4 h) were studied. At 800 °C, the RCS values reduced by 64.4%, 69.2%, and 74.6% at heating times of 2 h, 3 h, and 4 h. Scanning electron microscopy (SEM) was used for the micro-phase analysis of the samples that had been exposed to high temperatures. The heating time and RCS as well as the SEM micro-structure relationship were compared. Finally, a tunnel lining slab sample was designed to simulate the post-fire damage inside the blocks. Additionally, shear-wave tomography with 32 probes was able to detect the ϕ10 mm void defects at a depth of 200 mm.

To observe the effect of systematic graded rewarming measures on body temperature and prognosis of patients with moderate and severe trauma [revised trauma score (RTS)12] requiring emergency operation.A prospective randomized double-blind controlled study was conducted. From January 2020 to January 2021, 104 patients who underwent emergency trauma surgery in the Second Affiliated Hospital of Wenzhou Medical University were selected as the research object. According to random number table method, the patients were divided into traditional rewarming group and systematic graded rewarming group, with 52 cases in each group. Patients in traditional rewarming group (only record the body temperature without intervention, and start the rewarming process when the body temperature at any time was less than 36 centigrade); the patients in the system graded rewarming group start the preventive measures as soon as they were admitted to the hospital, and record the body temperature. When the body temperature at any time was less than 36 centigrade, start the graded rewarming process. Observe the rewarming effect, coagulation function, blood gas analysis and postoperative anesthesia recovery time of the two groups and final outcome.With the extension of time, the body temperature of the two groups increased gradually. The body temperature of the systematic grade rewarming group was significantly higher than that of the traditional rewarming group at 2 hours after rewarming and at discharge (centigrade: 36.23±0.77 vs. 35.84±0.93 at 2 hours after rewarming, 36.54±0.87 vs. 35.82±0.92 at discharge, both P0.05). The incidence of subsequent hypothermia was significantly lower than that in the traditional rewarming group [7.7% (4/52) vs. 25.0% (13/52), P0.05]. The postoperative activated partial thromboplastin time (APTT) of the two groups was significantly shorter than that at admission (s: 35.74±8.05 vs. 45.55±28.02 in the systematic rewarming group, P0.05; 38.35±6.48 vs. 42.40±13.18 in the traditional rewarming group, P0.05); the intraoperative and postoperative pH values in the systematic rewarming group were significantly higher than those at admission (7.33±0.05, 7.36±0.06 vs. 7.30±0.07, both P0.05), while there was no significant difference between the intraoperative and postoperative pH values in the traditional rewarming group and those at admission (7.31±0.06, 7.33±0.06 vs. 7.31±0.05, both P0.05). The postoperative prothrombin time (PT) and anesthesia recovery time in the systematic graded rewarming group were significantly shorter than those in the traditional rewarming group [PT (s): 15.05±2.44 vs. 17.94±3.48, anesthesia recovery time (hours): 14.40±11.76 vs. 17.35±10.51, all P0.05], and the pH value was significantly higher than that in the traditional rewarming group (7.36±0.06 vs. 7.33±0.06, P0.05). The systematic graded rewarming group had higher improvement rate and lower disability rate than the traditional rewarming group (76.9% vs. 65.4% and 17.3% vs. 25.0%, both P0.05).Systematic graded rewarming measures can improve the hypothermia of emergency trauma patients who received surgery, reduce the incidence of subsequent hypothermia of trauma patients, shorten the time of postoperative resuscitation, improve the coagulation function and blood gas indexes, improve the treatment rate, and reduce the incidence of disability.

Mercury (Hg) is a global environmental contaminant, and excessive mercury levels in water can adversely affect the growth of fish. Silver carp (Hypophthalmichthys molitrix) is one of the important freshwater aquaculture fish in China, and its natural resources have been critically declining. However, the effects of Hg

Promoting blood-spinal cord barrier (BSCB) repair at the early stage plays a crucial role in treatment of spinal cord injury (SCI). Excessive activation of autophagy can prevent recovery of BSCB after SCI. Basic fibroblast growth factor (bFGF) has been shown to promote BSCB repair and locomotor function recovery in SCI. However, the therapeutic effect of bFGF

In order to investigate the influence of the high-altitude aquatic environment on indigenous fish metabolites, metabolomics studies were applied in this study. Widespread throughout the main stem of the Nujiang River of Schizothorax nukiangensis, we established sampling sites at high (3890 m) and low (2100 m) altitudes and selected six S. nukiangensis at each location, each weighing approximately 150 g and looking healthy. Then, metabolomics analysis was performed to compare the various metabolites of the two groups. Low concentrations of amino acids, dipeptides, eicosapentaenoic acid, docosahexaenoic acid, pentadecanoic acid, Thioetheramide-PC, 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine, 1-Stearoyl-sn-glycerol-3-phosphocholine, 1-Myristoyl-sn-glycero-3-phosphocholine and 1-Palmitoyl-sn-glycero-3-phosphocholine, high concentrations in S-Methyl-5’-thioadenosine, creatine, D-mannose-6-phosphate, D-mannose-1-phosphate, oleic acid and myristoleic acid were found in high-altitude fish liver. These differentially accumulated metabolites were involved in oxidative stress, energy metabolism, carbohydrate metabolism and lipid metabolism. mTOR signaling pathway, apoptosis and lysosome were the KEGG pathways that were enriched between different groups to ensure energy supply and limit tissue damage of fish at high altitudes. All these results contributed to the understanding of the high-altitude adaptation of S. nukiangensis in the Nujiang River. Nicotine and methoprene, two organic pollutants, performed differently in fish at different altitudes. Overall, our findings advanced the fundamental understanding of fish responses to high-altitude environments, adaptive mechanisms and organic contaminants pollution in the Nujiang River.

Background: The Coronavirus pandemic has resulted in an extreme challenge for humanity in recent times, like the challenges faced during World War II. Its origin has been pointed out, and the speculation made on its source directly points towards Wuhan in China. Since then, it has spread across the globe. The pandemic has resulted in more than one million deaths, which is a considerable challenge for humanity. Objective: With the pandemic of COVID-19, prevention of patient infection is crucial. This research focused on the orthopedic operating room nursing model effect based on evidence-based nursing and PDCA (Plan-Do-Check-act) cycle during the COVID-19 outbreak. Materials and Methods: From February 2020 to May 2020, 146 patients were admitted and received orthopedic surgery at Xuanwu Chunshu Hospital, Beijing, China, these admissions were grouped into control and intervention groups, which was based on the treatment provided. Satisfaction, time to bed and hospitalization, postoperative incision infection, and the occurrence of deep venous thrombosis of lower extremities, pain degree score, surgical treatment effect, anxiety, and depression scores were compared for all the admissions between the control and intervention groups. Results: In the control group, nursing satisfaction was less than in the intervention group. The time of getting out of bed and hospitalization was less in the intervention group; The total incidence of postoperative incision infection and lower limb deep vein thrombosis in the intervention group decreased. In the first postoperative day, the pain level in the intervention group was less than the control group. The effectiveness rate in the observation group is higher than that of the control group. Anxiety and depression scores of both groups tended to decrease with time and there was an interactive effect between grouping and time, where these differences were found to be statistically significant (P-value

The morphologies of individual particles vary greatly, which intimately affect the physical and mechanical properties of granular assemblies. In this paper, a modified morphology quantification and generation method of granular particles based on two-dimensional images is proposed. By defining the ratio of the long axis and the short axis of the least-squares fitting ellipse of the particle contour as the aspect ratio, we characterize the deviations between the particle contour and the least-squares fitting ellipse as the angularity. Meanwhile, the surface texture is calculated by using the locally weighted regression smoothing method. Five types of particles are used to verify the quantization method, and the results demonstrate a comprehensive description of particle morphology. As the inversion of the quantification, a generation method of granular particles is further introduced and then compared with the traditional Fourier generation algorithm. The algorithms proposed in this work are computationally efficient and could be used for rapid quantification and generation of particle morphology in particulate matter research.