Multi Target Research Articles

A Network Pharmacological Study of Qianjin Sanhuang Decoction in the Treatment of Osteoarthritic Knee Disease

Objective: To predict the action targets of Qianjin Sanhuang decoction in the treatment of knee osteoarthritis through network pharmacology, to explore its potential multi component, multi target, multi, pathway mechanism of action, and to elaborate the relationship between the pharmacological effects of the drug and the disease from the perspective of molecular mechanism. Methods: The Chinese herbal composition of Qianjin Sanhuang decoction was determined by reading ancient texts and reviewing data, and the chemical components of Qianjin Sanhuang decoction were collected through the Traditional Chinese Medicine Systematic Pharmacology Database and Analysis Platform (TCMSP), and the active ingredients of the drug were obtained after oral utilization (OB) and drug-like properties (DL) screening, and the active ingredient target prediction was performed, while the active ingredient targets were retrieved from GeneCards, OMIM, and DisGeNet database to retrieve knee osteoarthritis-related targets. After taking the intersecting targets, a software called cytoscape 3.9.0 was used for mapping, with the goal of constructing a component-target network map, followed by a string database for mapping, with the goal of making a network map of target protein-target protein interactions, and finally, a gene ontology (GO) enrichment analysis and a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, this analysis process was performed in the metascape database. Results: A total of 1272 targets related to osteoarthritis of the knee were collected in this study, 89 active ingredients of Qianjin Sanhuang decoction, involving 267 targets, and 121 therapeutic targets involving osteoarthritis of the knee, and the results of GO enrichment analysis showed that it involved the response to inorganic substances, positive regulation of cell migration, response to oxygen content, response to lipopolysaccharide, response to peptides, regulation of cell adhesion, response to extracellular stimuli, negative regulation of cell differentiation, positive regulation of cell death, glandular development, regulation of apoptotic signaling pathways, development of reproductive structures, response to trauma, response to growth factors, regulation of inflammatory response, cellular response to organic recycling compounds, regulation of proteolysis, etc. After KEGG analysis, the results showed that signaling pathways such as AGE-RAGE pathway and HIF-1 pathway were involved. Conclusion: Qianjin Sanhuang decoction can improve the inflammatory response of knee osteoarthritis through potential multi-pathways, multi-targets and multi-pathways, and can have potential therapeutic effects on osteoarthritis.

Phytoconstituents of Citrus limon (Lemon) as Potential Inhibitors Against Multi Targets of SARS-CoV-2 by Use of Molecular Modelling and In Vitro Determination Approaches.

In the present work, phytoconstituents from Citrus limon are computationally tested against SARS-CoV-2 target protein such as Mpro - (5R82.pdb), Spike - (6YZ5.pdb) &RdRp - (7BTF.pdb) for COVID-19. Docking was done by glide model, QikProp was performed by in silico ADMET screening & Prime MM-GB/SA modules were used to define binding energy. When compared with approved COVID-19 drugs such as Remdesivir, Ritonavir, Lopinavir, and Hydroxychloroquine, plant-based constituents such as Quercetin, Rutoside, Naringin, Eriocitrin, and Hesperidin. bind with significant G-scores to the active SARS-CoV-2 place. The constituents Rutoside and Eriocitrin were studied in each MD simulation in 100 ns against 3 proteins 5R82.pdb, 6YZ5.pdb and 7BTF.pdb.We performed an assay with significant natural compounds from contacts and in silico results (Rutin, Eriocitrin, Naringin, Hesperidin) using 3CL protease assay kit (B.11529 Omicron variant). This kit contained 3CL inhibitor GC376 as Control. The IC50 value of the test compound was found to be Rutin -17.50 μM, Eriocitrin-37.91 μM, Naringin-39.58 μM, Hesperidine-140.20 μM, the standard inhibitory concentration of GC376 was 38.64 μM. The phytoconstituents showed important interactions with SARS-CoV-2 targets, and potential modifications could be beneficial for future development.

Mechanistic insights into antidiabetic potential of Ficus viren against multi organ specific diabetic targets: molecular docking, MDS, MM-GBSA analysis

Ficus viren has been traditionally used to treat diabetes, and its extract inhibits carbohydrate/lipid metabolism and possesses anti-hyperglycemic potential. However, there is conflicting investigation related to F. viren extract effect on carbohydrate metabolism. Thus, bioactive and mechanism behind its antidiabetic potential is still scanty. This study explored F. viren’s anti-diabetic property by identifying potential phytoconstituents and mechanism. A sequential in-silico approach was used i.e., druglikeness, molecular docking, post-docking MM-GBSA, ADMET studies, molecular dynamic simulation (MDS), and post-MDS MM-GBSA. We screened ∼32 phytoconstituents and twelve potential organ-specific diabetic targets (O.S.D.Ts i.e., IR, DPP-4, ppar-γ, ppar-α, ppar-δ, GLP-1R, SIRT-1, AMPK, GSK-3β, RAGE, and AR). Drug likeness study identified 18 druggable candidates among 32 phytoconstituents. K3A, quercetin, scutellarein, sorbifolin, and vogeline J identified as potential ligands from druggable ligands, using IR as the standard target. Subsequently, potential ligands docked with remaining O.S.D.Ts. and data showed that K3A binds strongly with AMPK, ppar-δ, DPP-4, and GSK-3β, while scutellarein binds with AR and ppar-α. Sorbifolin, quercetin, and vogeline J binds with ppar-α, ppar-γ, and RAGE, respectively. Post-docking MM-GBSA data (∆GBind) also depicted potential ligand’s strong binding affinities with their corresponding targets. Thereafter, simulation data revealed that only scutellarein and sorbifolin showed dynamic stability with their respective targets, i.e., AR/ppar-α and ppar-α, respectively. Interestingly, post-MDS MM-GBSA revealed that only scutellarein exhibited strong ∆GBind of −55.08 kcal/mol and −75.48 kcal/mol with AR and ppar-α, respectively. Though, collective computational analysis supports antidiabetic potential of F. viren through AR and ppar-α modulation by scutellarein.

Design and Simulation of Multi Unmanned Boat Cooperative Obstacle Avoidance System Based on 5G Edge Computing

Background:: Compared to single unmanned boat, multi unmanned boats have more flexible mobility and efficient task completion capabilities, which can effectively expand the types of tasks. However, the traditional independent path planning and obstacle avoidance methods of unmanned boats are difficult to meet the requirements of collaborative operation among multiple unmanned boats due to the lack of information exchange. Objective:: According to the actual demand of multi unmanned boats' cooperative operation, a method of multi unmanned boats cooperative obstacle avoidance based on 5G edge computing is proposed to realize the unified planning and scheduling of multi unmanned boats. Methods:: Firstly, 5G technology and Kubeedge edge computing tools are used to build a multi unmanned boat collaborative obstacle avoidance system based on cloud, edge and end collaboration, and the Kubeedge edge computing platform was optimized by optimizing communication strategies, building a highly available Kubeedge cluster, building a Harbor image center, and using Web management interfaces further to improve the reliability and stability of the system. Secondly, the YOLOR-Deepport multi-target recognition and tracking algorithm based on cloud, edge and end collaborative network is used to complete the recognition and tracking tasks of obstacle targets, and a set of EECBS path planning methods based on the Kubedge centralized control platform is designed to plan collision-free and efficient paths for each unmanned boat in realtime. Finally, the effectiveness of the system was verified through simulation experiments. Results:: The experimental results show that compared to the traditional autonomous planning obstacle avoidance method for unmanned boats, the collaborative planning obstacle avoidance method proposed in this paper can exhibit excellent performance in dense and narrow scenarios, with a more reasonable navigation path, a range reduction of 20% - 50%, and higher safety. Conclusion:: The results show that the cooperative obstacle avoidance system based on 5G edge computing designed in the paper is feasible, and it can effectively realize the cooperative path planning and obstacle avoidance of multi unmanned boats.

Study on the mechanism of hirudin multi target delaying renal function decline in chronic kidney disease based on the “gut-kidney axis” theory

The disorder of the “gut-kidney axis” exacerbates renal function decline in chronic kidney disease (CKD), and current CKD therapy is insufficient to address this issue. Hirudin has a palliative effect on the decline of renal function. However, whether hirudin can delay CKD by regulating the “intestinal renal axis” disorder remains unclear. Unilateral ureteral ligation (UUO) induced CKD rat model, and the rats were treated with bifidobacterium and hirudin for 36 days. After 14 and 36 days of modeling, kidney and colon tissues were collected for pathology, western blot (WB) assay, and quantitative real-time PCR (qPCR) detection. Serum samples were collected for renal function testing. Fecal samples were used for 16S rRNA sequencing and research on fecal bacterial transplantation. Lipopolysaccharide combine with adenosine 5’-triphosphate (LPS + ATP)-induced intestinal epithelial cell injury was treated with a nod-like receptor pyrin domain-associated protein 3 (NLRP3) inhibitor and hirudin. Protein expression was detected using WB and qPCR. The kidneys and colons of the CKD rats exhibited varying degrees of lesions. Creatinine (CRE), blood urea nitrogen (BUN), N-acetyl-β-D-glucosidase (NAG) enzyme, and serum uremic toxins were elevated. The expression of claudin-1 and occludin was decreased, NLRP3 inflammatory-related proteins were increased, and the gut microbiota was disrupted. These pathological changes were more pronounced after 36 days of modeling. Meanwhile, high-dose hirudin treatment significantly improved these lesions and restored the intestinal flora to homeostasis in CKD rats. In vitro, hirudin demonstrated comparable effects to NLRP3 inhibitors by upregulating claudin-1 and occludin expression, and downregulating NLRP3 inflammatory-related proteins expression. The dysbiosis of the gut microbiota and impaired intestinal epithelial barrier function in CKD are associated with renal dysfunction in CKD. Hirudin delays the progression of CKD by regulating the disorder of the “gut-kidney axis” and inhibiting the activation of the NLRP3-ASC-caspase-1 pathway.

Multi-Agent Distributed Optimal Control for Tracking Large-Scale Multi-Target Systems in Dynamic Environments.

This article considers the problem of motion coordination for a multiagent (MA) network whose goal is to track a large-scale multitarget (MT) system in a region populated by dynamic obstacles. We first characterize a density path which corresponds to the expected evolution of the macroscopic state of the MT system, which is represented by the probability density function (PDF) of a time-varying Gaussian mixture (GM). We compute this density path by using an adaptive optimal control method which accounts for the distribution of the (possibly moving) obstacles over the environment described by a time-varying obstacle map function. We show that each target of the MT system can find microscopic inputs that can collectively realize the density path while guaranteeing obstacle avoidance at all times. Subsequently, we propose a Voronoi distributed motion coordination algorithm which determines the individual microscopic control inputs of each agent of the MA network so that the latter can track the MT system while avoiding collisions with obstacles and their teammates. The proposed algorithm relies on a distributed move-to-centroid control law in which the density over the Voronoi cell of each agent is determined by the estimated macroscopic state evolution of the MT system. Finally, simulation results are presented to showcase the effectiveness of our proposed approach.

A random sampling method for radiobiological modeling

Various radiobiological models have been proposed to describe the clonogenic cell survival after radiation. Least square model fitting to match experimental survival data can be tedious and sometimes difficult for complex models with multiple parameters. In this work, a random sampling method is developed to optimize the model parameters automatically to achieve best fitting with the experimental data. A computer program is developed to read the experimental data and to calculate the cell survival fractions based on a given mathematical model. Model parameters are randomly sampled, and the model predictions are compared with the experimental data. The mean square error (MSE) is used as an objective function to drive the iterative process. The goodness-of-fit of the linear quadratic (LQ), multitarget (MT), universal survival curves (USC) and multimode (MM) model was compared between the new method and previous studies for melanoma and non–small-cell lung cancer (NSCLC) cell lines. Good fitting was obtained for the MM model with the NSCLC data (MSE = 0.0005), which was better than the fits to the LQ, MT and USC models (MSE = 0.0019, 0.0082, 0.0024, respectively). The parameters used for the LQ, MT and USC models were α = 0.33Gy, α/β = 10Gy, D0 = 1.25Gy, n = 4.22 and DT = 6.2Gy. The parameters for the MM model (n = 4) were D1 = 3.0Gy, D2 = 8.27Gy, and D3 = 2.93Gy and D4 = 10.6Gy. It is concluded that the random sampling method provides a useful tool for the parameterization of radiobiological models for radiation research and clinical applications.

Design, synthesis, in vitro and in silico evaluations of new isatin-triazine- aniline hybrids as potent anti- Alzheimer multi-target directed lead compounds

Multi target directed ligands (MTDLs) are one of the promising tools for treatment of complex disease like Alzheimer’s disease (AD). In this study, using rational design, we synthesized new 15 hybrids of the s-triazine, isatin and aniline derivatives as anti- AD compounds. The design was as way as that new compounds could had anti cholinesterase (ChE), antioxidant and biometal chelation ability. In vitro biological evaluation against ChE enzymes showed that these molecules were excellent inhibitors with IC50 values ranging from 0.2 nM to 734.5 nM for acetylcholinesterase (AChE), and 0.02 μM to 1.92 μM for butyrylcholinesterase (BChE). Among these compounds, 8 l with IC50 AChE = 0.7 nM, IC50 BChE = 0.09 μM and 8n with IC50 AChE = 0.2 nM, IC50 BChE = 0.03 μM were the most potent compounds. In silico studies showed that these molecules had key and effective interactions with the corresponding enzymes residues. The molecules with hydroxyl group on aniline moiety had also good antioxidant activity with EC50 values ranging from 64.2 μM to 103.6 μM. The UV–Vis spectroscopy study revealed that molecule 8n was also able to chelate biometals such as Zn2+, Cu2+and Fe2+ properly. It was concluded that these molecules could be excellent lead compounds for future studies.

A network pharmacological approach for the identification of potential therapeutic targets of Brahmi Nei – a complex traditional Siddha formulation

Brahmi Nei (BN), a traditional Indian polyherbal formulation has been described in classical texts for the treatment of anxiety and depression, as well as to fortify the immune system. The individual herbs of BN have been used for treatment of wide range of disorders including cognition, inflammation, skin ailments and cancer etc., This diverse basket of therapeutic activity suggests that BN may possess therapeutic benefits to other disorders. So, the present study aims to identify the potential therapeutic targets of BN using a network pharmacological approach to comprehend the multi target action of its multiple phytoconstituents. We have employed Randić Index for the first time to calculate the contribution score of module segregated targets towards diseases. Our results suggests that BN targets could also be effective in other diseases such as lysosomal storage disorders, respiratory disorders etc., apart from neurological disorders. The key targets with highest topological measures of Targets-(Pathway)-Targets network were identified as potential therapeutic targets of BN. And the top hit target PTGS2, a gene encoding for cyclooxygenase-2 was further evaluated using molecular docking, molecular dynamic simulation and in vitro studies. Our findings open up new therapeutic facets for BN that can be explored systematically in future. Communicated by Ramaswamy H. Sarma

Research Progress on the Mechanism of PI3K/AKT/mTOR Signaling Pathway in Multiple Myeloma --Review

PI3K/AKT/mTOR signaling pathway is of great significance in the development and prognosis of tumors, and is closely related to the pathogenesis of multiple myeloma (MM). PI3K/AKT/mTOR signaling pathway can participate in the regulation of MM through multichannel and multitarget, such as regulating the tumor microenvironment of MM cells survival, affecting tumor development and migration, regulating the proliferation, apoptosis and autophagy of MM cells. It have shown that after the PI3K/AKT/mTOR signaling pathway is inhibited, the apoptosis and autophagy of MM cells are activated, which promote the death of MM cells and inhibit the metastasis and recurrence of MM cells. Therefore, indepth study of the mechanism of PI3K/AKT/mTOR signaling pathway in MM is helpful to elucidate the pathogenesis and prognosis of MM.

Phytocompounds-based therapeutic approach: Investigating curcumin and green tea extracts on MCF-7 breast cancer cell line

BackgroundBreast cancer (BC) has transcended lung cancer as the most common cancer in the world. Due to the disease's aggressiveness, rapid growth, and heterogeneity, it is crucial to investigate different therapeutic approaches for treatment. According to the World Health Organization (WHO), Plant-based therapeutics continue to be utilized as safe/non-toxic complementary or alternative treatments for cancer, even in developed countries, regardless of how cutting-edge conventional therapies are. Despite their low bioavailability, curcumin (CUR) and green tea (GT) represent safer therapeutic options. Due to their potent molecular-modulating properties on various cancer-related molecules and signaling pathways, they are considered gold-standard therapeutic agents and have been incorporated into the development of one or more therapeutic strategies of BC treatment. MethodsWe investigated the modulatory role of CUR and GT extracts on significant multi molecular targets in MCF-7 BC cell line to assess their potential as BC multi-targeting agents. We analyzed the phytocompounds in GT leaves using High-performance liquid chromatography (HPLC) and Gas chromatography-mass spectrometry (GC-MS) techniques. The mRNA expression levels of Raf-1, Telomerase, Tumor necrosis factor alpha (TNF-α) and Interleukin-8 (IL-8) genes in MCF-7 cells were quantified using quantitative real-time PCR (qRT-PCR). The cytotoxicity of the extracts was assessed by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and the released Lactate dehydrogenase (LDH), a valuable marker for identifying the programmed necrosis (necroptosis). Additionally, the concentrations of the necroptosis-related proinflammatory cytokines (TNF-α and IL-8) were measured using enzyme-linked immunosorbent assay (ELISA). ResultsIn contrast to the GT, the results showed the anticancer and cytotoxic properties of CUR against MCF-7 cells, with a relatively higher level of released LDH. The CUR extract downregulated the oncogenic Raf-1, suppressed the Telomerase and upregulated the TNF-α and IL-8 genes. Results from the ELISA showed a notable increase in IL-8 and TNF-α cytokines levels after CUR treatment, which culminated after 72 h. ConclusionsAmong both extracts, only CUR effectively modulated the understudy molecular targets, achieving multi-targeting anticancer activity against MCF-7 cells. Moreover, the applied dosage significantly increased levels of the proinflammatory cytokines, which represent a component of the cytokines-targeting-based therapeutic strategy. However, further investigations are recommended to validate this therapeutic approach.

An Improved Multi Target Ship Recognition Model Based on Deep Convolutional Neural Network

Deep learning is the major technique used to identify objects in images captured by the synthetic aperture radar (SAR). While SAR images can be used to identify ships in general, detecting multiple ships or small vessels in these images in complex contexts remains an outstanding challenge. This study proposes a model of detection based on the improved PP-YOLO deep convolutional neural network that can identify multiple ships as well as small vessels in complex scenarios from SAR images. The histogram equalization algorithm is first used to preprocess the SAR images, and then the initial anchor box is optimized by using the shape similarity distance-based K-means clustering algorithm. Following this, the accuracy of the training network is improved based on the feature pyramid network and an attention mechanism. The experimental results show that the average accuracy (average precision) of the model was 94.25% at 41.63 frames per second on the GF-3 and the Sentinel-1 SAR datasets, superior to those of YOLOv3 (Darknet), YOLOv7, FPN (VGG), SSD, Faster R-CNN, and PP-YOLO (RestNet50-vd). The model also satisfies the demands of real-time detection.

Target Detection in Martial Arts Competition Video using Kalman Filter Algorithm Based on Multi target Tracking

Target Detection in Martial Arts Competition Video using Kalman Filter Algorithm Based on Multi target Tracking

Multi targets of cannabidiol (CBD) on skeletal mammalian and avian neuromuscular preparations

Cannabidiol (CBD) has been used in diseases that affect the central nervous system. Its effects on the peripheral synapses are of great interest, since endocannabinoid receptors are expressed in muscles. CBD (0.3 mM) was analysed using mammalian and avian neuromuscular preparations, through myographic techniques in complementary protocols. Mammalian cells were examined by light microscopy while exogenous acetylcholine (40 µM) and potassium chloride (100 mM) were added into avian preparations, before and at the end of experiments. Pharmacological tools such as atropine (2 µM), polyethylene glycol (PEG 400, 20 µM), Ca2+ (1.8 mM), F55-6 (20 µg/mL), and nifedipine (1.3 mM) were assessed with CBD. In mice, CBD causes a facilitatory effect and paralysis, whereas in avian, paralysis. Concluding, CBD is responsible for activated or inhibited channels, for ACh release via muscarinic receptor modulation, and by the inhibition of nicotinic receptors leading to neuromuscular blockade, with no damage to striated muscle cells.

Macrophage Membrane-Modified MoS2 Quantum Dots as a Nanodrug for Combined Multi-Targeting of Alzheimer's Disease.

The complex pathological mechanism of Alzheimer's disease (AD) limits the efficacy of simple drug therapy, and drugs are difficult to penetrate the blood-brain barrier (BBB). Therefore, it is a breakthrough to enhance the therapeutic effect of AD by rationally using multiple therapeutic strategies to inhibit multiple pathological targets. In this study, macrophage membrane (MM) with active targeting inflammation function is used to functionalize molybdenum disulfide quantum dots (MoS2 QDs) with the properties of elimination of reactive oxygen species (ROS) and anti-Aβ1-42 deposition to form the nano drug (MoS2 QDs/MM), and play the role of multi-target combined therapy with NIR. The results show that MoS2 QDs/MM has a targeted therapeutic effect on ROS elimination and anti-deposition of Aβ1-42 . In addition, the combined therapy group effectively reduced Aβ1-42 mediated cytotoxicity. The modification of MM could effectively target the brain, and NIR irradiation could actively increase the cross of BBB of materials. In vivo behavioral study also show that APP/PS1 mice in the combined treatment group showed the similar exploration desire and learning ability to mice in the group of WT. MoS2 QDs/MM is an excellent nano drug with multiple effects, which has advantages in the field of neurological diseases with crisscross pathogenesis.

Multi target tracking algorithm based on anchor free detection

In order to alleviate the problems of frequent identity label switching caused by mutual occlusion between targets and missed detection caused by small target sizes in multi-target tracking, this paper proposes a multi-target tracking algorithm based on anchor-free detection. This algorithm first uses YOLOX for detection and embeds the ReID algorithm to enhance pedestrian recognition. Then, it uses the DeepSORT algorithm for tracking and correcting abnormal trajectory algorithms for occluded targets. Finally, experiments are conducted on both the MOT16 dataset and the self-made dataset. This algorithm has higher tracking accuracy than other algorithms, and its tracking performance for small targets has also been effectively improved.

Evaluating the anti-urolithiasis potential of Ficus religiosa seed GC MS evaluated phytoconstituents based on their in-vitro antioxidant properties and in-silico ADMET and molecular docking studies

BackgroundUrolithiasis, the deposit of stones in the urinary tract is a pertinent clinical issue in daily practice that imposes a burden on the human health system. Ficus religiosa plant has historically been useful in preventing urolithiasis. There is currently no information on phytochemical profiling that specifies the precise phytochemicals in the seed that are active against urolithiasis.MethodsF. religiosa seeds were extracted with different solvents in increasing order of their polarity by Soxhlet extraction. All the extracts were evaluated for their antioxidant potential. GC–MS profiling of the most potent antioxidant F. religiosa seed extract was done to evaluate the phytoconstituents. To evaluate the pharmacokinetics and drug-likeness properties of these compounds in silico ADMET analysis was done. To comprehend the binding potential of the best ADMET evaluated phytochemicals contained in the F. religiosa seed extract against the several protein targets (matrix metalloproteinases (MMP-2, MMP-9), and Human calcium-sensing receptor (CaSR)) and antioxidant enzymes (Glutathione S-transferase (GST), glutathione-disulfide reductase (GR), glutathione peroxidase (GPX), and superoxide dismutase (SOD)) involved in urolithiasis, multi targets based virtual screening tests were done using Autodock Vina tool.ResultsGC–MS profiling revealed the presence of 53 different compounds. Of all these compounds, based on ADMET analysis 2-Methoxy-4-vinylphenol; 3,5-Di-tert-butylphenol; diethyl benzene-1,2-dicarboxylate; 4-hydroxy-3,5-dimethoxybenzaldehyde; 2-methoxy-4-prop-2-enylphenol; and bis (2-methyl propyl) benzene-1,2-dicarboxylate were found to have best pharmacokinetics and drug-likeness properties. In the autodocking studies, 3,5-Di-tert-butyl phenol is proved to be the best of all in terms of binding energies with the selected targets.ConclusionThe findings of this study suggest a framework for employing F. religiosa seed ethyl acetate extract as a potent herbal treatment for urolithiasis.

Abnormal Detection Method of Transship Based on Marine Target Spatio-Temporal Data

<p>Marine target situational awareness is developing towards intelligence. The practical application of marine law enforcement, route control, fishery supervision and other fields makes marine ship track mining and anomaly analysis a hot direction of technology development. At present, most of the research focuses on the feature recognition of single target or single target signal, while the research on correlation anomaly detection based on multi target or multi target signal is relatively less. In this paper, based on the large spatio-temporal data of ocean targets such as radar and AIS track, the corresponding recognition algorithm is designed for the abnormal transport behavior. The real-time batch detection of illegal transshipment is realized, which verifies the effectiveness of the algorithm and shows good performance in practical application scenarios.</p> <p> </p>

Activity of Citrus aurantium and Lavandula angustifolia in Alzheimer’s Disease Symptoms in Male Wistar Rats

Background: Alzheimer's Disease (AD) is one of the most prevalent chronic neurodegenerative disorders. The present study aims to better understand the mechanism by which Citrus aurantium (C. aurantium) and Lavandula angustifolia (L. angustifolia) hydro–alcoholic extracts were used to treat AD and anti­–oxidant issues in a laboratory model.
 Methods: 15 male Wistar rats, weighing 250±20 gr, aged 6–8 weeks, were used. Amyloids in the brain were found and identified using the shuttle box and Congo red test. ELISA testing for norepinephrine and serotonin, Superoxide Dismutase (SOD), Malon-dialdehyde (MDA), and Real–time PCR for expression of the APP and GLT1 genes were done.
 Results: The shuttle box test demonstrated that AD produces behavioral harm, since it significantly reduces passive avoidance learning. The Congo red test revealed that the AD models had much more amyloid beta in their brain tissue than the control. Norepinephrine levels were also decreased by using both extracts in test group. Treatment with both extracts led to a substantial rise in SOD activity and fall in MDA concentration.
 Conclusion: The gene expression data indicated that the relative expression of the APP and GLT1 genes was shown to be lower in the groups treated with both extracts. C. aurantium and L. angustifolia may therefore offer a multi–target treatment strategy for AD, which calls for more research in this area.

Omni-Directional Capture for Multi-Drone Based on 3D-Voronoi Tessellation

This paper addresses the multi-drone formation capture in three-dimensional (3D) environments. The omni-directional minimum volume (ODMV) 3D-Voronoi diagram algorithm is proposed for the first time to achieve the two goals of (1) forming and keeping a capture and (2) planning the control action within its safe, collision region for each drone. First, we extend the traditional 2D Voronoi diagram to the 3D environment and use the non-overlapping spatial division property of 3D Voronoi diagram to inherently avoid the collision between drones. Second, we make improvements to the problem of capture angle in our minimum area strategy and propose an omni-directional minimum volume strategy to accomplish the effective capture of a target by constraining the capture angle. Finally, the wolf pack algorithm (WPA) with variable step size is introduced to provide a movement strategy for multi-drone formations. Thus, the proposed ODMV can also achieve dynamic target and multi target capture in environments with obstacles. The Optitrack motion capture system and Crazyflie drones are used to conduct the multi-drone capture experiment. Both simulation and experimental results are included to demonstrated the effectiveness of the proposed ODMV method.