Adipose tissue macrophages as potential targets for obesity and metabolic diseases

Macrophage infiltration into adipose tissue is a key pathological factor inducing adipose tissue dysfunction and contributing to obesity-induced inflammation and metabolic disorders. In this review, we aim to present the most recent research on macrophage heterogeneity in adipose tissue, with a focus on the molecular targets applied to macrophages as potential therapeutics for metabolic diseases. We begin by discussing the recruitment of macrophages and their roles in adipose tissue. While resident adipose tissue macrophages display an anti-inflammatory phenotype and promote the development of metabolically favorable beige adipose tissue, an increase in pro-inflammatory macrophages in adipose tissue has negative effects on adipose tissue function, including inhibition of adipogenesis, promotion of inflammation, insulin resistance, and fibrosis. Then, we presented the identities of the newly discovered adipose tissue macrophage subtypes (e.g. metabolically activated macrophages, CD9+ macrophages, lipid-associated macrophages, DARC+ macrophages, and MFehi macrophages), the majority of which are located in crown-like structures within adipose tissue during obesity. Finally, we discussed macrophage-targeting strategies to ameliorate obesity-related inflammation and metabolic abnormalities, with a focus on transcriptional factors such as PPARγ, KLF4, NFATc3, and HoxA5, which promote macrophage anti-inflammatory M2 polarization, as well as TLR4/NF-κB-mediated inflammatory pathways that activate pro-inflammatory M1 macrophages. In addition, a number of intracellular metabolic pathways closely associated with glucose metabolism, oxidative stress, nutrient sensing, and circadian clock regulation were examined. Understanding the complexities of macrophage plasticity and functionality may open up new avenues for the development of macrophage-based treatments for obesity and other metabolic diseases

Scour protection of submarine pipelines using rubber plates underneath the pipes

YesThis paper presents the results from laboratory experiments to investigate the protection of scour around submarine pipelines under unidirectional flow using a rubber plate placed underneath the pipes. The pressure difference on the two sides of the pipeline is the driving force to initiate the movement of sediment particles and can be obtained by force balance analysis. Experiments covering a wide range of incoming flow velocity, pipe diameter and plate length show that there exists a critical pressure difference over which the movement of sediment and, thus, scour takes place. Analysis of the experimental results demonstrates that this critical pressure difference is related to the pressure difference of the axial points between upstream and downstream of the pipe, which can be easily determined. This critical pressure difference is used to develop an empirical formula for estimating the critical length of the rubber plate, over which the sediment movement and scour will not take place. Good agreement between the experiments and calculated critical plate length using the proposed formula is obtained.National High-Tech Research and Development program of China (863 Program, Grant No.2008AA09Z309), National Nature Science Fund of China (Grant No.50879084, 51279071 and 51279189), the Open Funding from the State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University (SKLH-OF-1306

Social recommendation model based on user interaction in complex social networks.

The user interaction in online social networks can not only reveal the social relationships among users in e-commerce systems, but also imply the social preferences of a target user for recommendation services. However, the current research has rarely explored the impact of social interaction on recommendation performance, especially now that recommender systems face increasing challenges and suffer from poor efficiency due to social data overload. Therefore, applied research on user interaction has become increasingly necessary in the field of social recommendation. In this paper, we develop a novel social recommendation method based on the user interaction in complex social networks, called the SRUI model, to present a basis for improving the efficiency of the recommender systems. Specifically, a weighted social interaction network is first mapped to represent the interactions among social users according to the gathered information about historical user behavior. Thereafter, the complete path set is mined by the complete path mining (CPM) algorithm to find social similar neighbors with tastes similar to those of the target user. Finally, the social similar tendencies of the users on the complete paths are obtained to predict the final ratings of items through the SRUI model. A series of experimental results based on two real public datasets show that our approach performs better than other state-of-the-art methods in terms of recommendation performance

Edge-Assisted Distributed DNN Collaborative Computing Approach for Mobile Web Augmented Reality in 5G Networks

Web-based DNNs provide accurate object recognition to the mobile Web AR, which is newly emerging as a lightweight mobile AR solution. Webbased DNNs are attracting a great deal of attention. However, balancing the UX against the computing cost for DNN-based object recognition on the Web is difficult for both self-contained and cloud-based offloading approaches, as it is a latency-sensitive service but also has high requirements in terms of computing and networking abilities. Fortunately, the emerging 5G networks promise not only bandwidth and latency improvement but also the pervasive deployment of edge servers which are closer to the users. In this article, we propose the first edge-based collaborative object recognition solution for mobile Web AR in the 5G era. First, we explore the finegrained and adaptive DNN partitioning for the collaboration between the cloud, the edge, and the mobile Web browser. Second, we propose a differentiated DNN computation scheduling approach specially designed for the edge platform. On one hand, performing part of DNN computations on mobile Web without decreasing the UX (i.e., keep response latency below a specific threshold) will effectively reduce the computing cost of the cloud system; on the other hand, performing the remaining DNN computations on the cloud (including remote and edge cloud) will also improve the inference latency and thus UX when compared to the self-contained solution. Obviously, our collaborative solution will balance the interests of both users and service providers. Experiments have been conducted in an actually deployed 5G trial network, and the results show the superiority of our proposed collaborative solution.</p

Crystal structure and electrochemical properties of [Ni(bztmpen)(CH3CN)](BF4)2 {bztmpen is N-benzyl-N,N′,N′-tris[(6-methylpyridin-2-yl)methyl]ethane-1,2-diamine}

The mononuclear nickel title complex (acetonitrile-κN){N-benzyl-N,N′,N′-tris[(6-methylpyridin-2-yl)methyl]ethane-1,2-diamine}nickel(II) bis(tetrafluoridoborate), [Ni(C30H35N5)(CH3CN)](BF4)2, was prepared from the reaction of Ni(BF4)2·6H2O with N-benzyl-N,N′,N′-tris[(6-methylpyridin-2-yl)methyl]ethane-1,2-diamine (bztmpen) in acetonitrile at room temperature. With an open site occupied by the acetonitrile molecule, the nickel(II) atom is chelated by five N-atom sites from the ligand and one N atom from the ligand, showing an overall octahedral coordination environment. Compared with analogues where the 6–methyl substituent is absent, the bond length around the Ni2+ cation are evidently longer. Upon reductive dissociation of the acetronitrile molecule, the title complex has an open site for a catalytic reaction. The title complex has two redox couples at −1.50 and −1.80 V (versus Fc+/0) based on nickel. The F atoms of the two BF4− counter-anions are split into two groups and the occupancy ratios refined to 0.611 (18):0.389 (18) and 0.71 (2):0.29 (2)

Crystal structure of [Cu(tmpen)](BF4)2 {tmpen is N,N,N′,N′-tetrakis[(6-methylpyridin-2-yl)methyl]ethane-1,2-diamine}

The mononuclear copper title complex {N,N,N′,N′-tetrakis[(6-methylpyridin-2-yl)methyl]ethane-1,2-diamine-κ6N}copper(II) bis(tetrafluoridoborate), [Cu(C30H36N6)](BF4)2, is conveniently prepared from the reaction of Cu(BF4)2·6H2O with N,N,N′,N′-tetrakis[(6-methylpyridin-2-yl)methyl]ethane-1,2-diamine (tmpen) in acetonitrile at room temperature in air. The complex shows a distorted octahedral environment around the CuII cation (site symmetry 2) and adopts the centrosymmetric space group C2/c. The presence of the 6-methyl substituent hinders the approach of the pyridine group to the CuII core. The bond lengths about the CuII atom are significantly longer than those of analogues without the 6-methyl substituents

CO₂ Diffusion in Various Carbonated Beverages: A Molecular Dynamics Study

Carbonated beverages are widely enjoyed in spare time, yet there remain many physical and chemical processes clouded at the molecular level. In this report, we employ molecular dynamics simulations to estimate the diffusion coefficients of CO₂ and the molecular origin of its variations in three model systems with characteristic features of champagnes, sugar-based cola drinks, and club sodas. The computed diffusion coefficients of CO₂ are in good agreement with experimental data. Analyses of hydrogen bonding and the solvent’s structural and dynamic properties reveal that the change of CO₂ diffusion coefficient is closely associated with the diffusional behavior of the solvent water itself, as a result of changes in the number and strength of hydrogen bonding interactions among the species and solvent

Edge-Assisted Distributed DNN Collaborative Computing Approach for Mobile Web Augmented Reality in 5G Networks

Web-based DNNs provide accurate object recognition to the mobile Web AR, which is newly emerging as a lightweight mobile AR solution. Webbased DNNs are attracting a great deal of attention. However, balancing the UX against the computing cost for DNN-based object recognition on the Web is difficult for both self-contained and cloud-based offloading approaches, as it is a latency-sensitive service but also has high requirements in terms of computing and networking abilities. Fortunately, the emerging 5G networks promise not only bandwidth and latency improvement but also the pervasive deployment of edge servers which are closer to the users. In this article, we propose the first edge-based collaborative object recognition solution for mobile Web AR in the 5G era. First, we explore the finegrained and adaptive DNN partitioning for the collaboration between the cloud, the edge, and the mobile Web browser. Second, we propose a differentiated DNN computation scheduling approach specially designed for the edge platform. On one hand, performing part of DNN computations on mobile Web without decreasing the UX (i.e., keep response latency below a specific threshold) will effectively reduce the computing cost of the cloud system; on the other hand, performing the remaining DNN computations on the cloud (including remote and edge cloud) will also improve the inference latency and thus UX when compared to the self-contained solution. Obviously, our collaborative solution will balance the interests of both users and service providers. Experiments have been conducted in an actually deployed 5G trial network, and the results show the superiority of our proposed collaborative solution

A Knowledge-Guided Fusion Visualisation Method of Digital Twin Scenes for Mountain Highways

Informatization is an important trend in the field of mountain highway management, and the digital twin is an effective way to promote mountain highway information management due to the complex and diverse terrain of mountainous areas, the high complexity of mountainous road scene modeling and low visualisation efficiency. It is challenging to construct the digital twin scenarios efficiently for mountain highways. To solve this problem, this article proposes a knowledge-guided fusion expression method for digital twin scenes of mountain highways. First, we explore the expression features and interrelationships of mountain highway scenes to establish the knowledge graph of mountain highway scenes. Second, by utilizing scene knowledge to construct spatial semantic constraint rules, we achieve efficient fusion modeling of basic geographic scenes and dynamic and static ancillary facilities, thereby reducing the complexity of scene modeling. Finally, a multi-level visualisation publishing scheme is established to improve the efficiency of scene visualisation. On this basis, a prototype system is developed, and case experimental analysis is conducted to validate the research. The results of the experiment indicate that the suggested method can accomplish the fusion modelling of mountain highway scenes through knowledge guidance and semantic constraints. Moreover, the construction time for the model fusion is less than 5.7 ms; meanwhile, the dynamic drawing efficiency of the scene is maintained above 60 FPS. Thus, the construction of twinned scenes can be achieved quickly and efficiently, the effect of replicating reality with virtuality is accomplished, and the informatisation management capacity of mountain highways is enhanced

A Genetic Compensation Phenomenon and Global Gene Expression Changes in Sex-miR-2766-3p Knockout Strain of <i>Spodoptera exigua</i> Hübner (Lepidoptera: Noctuidae)

MicroRNAs (miRNAs) drive the post-transcriptional repression of target mRNAs and play important roles in a variety of biological processes. miR-2766-3p is conserved and abundant in Lepidopteran species and may be involved in a variety of biological activities. In this study, Sex-miR-2766-3p was predicted to potentially bind to the 3′ untranslated region (UTR) of cap ‘n’ collar isoform C (CncC) in Spodoptera exigua, and Sex-miR-2766-3p was confirmed to regulate the expression of SeCncC through screening with a luciferase reporter system. Although CRISPR/Cas9 has been extensively utilized to examine insect gene function, studies of miRNA function are still relatively uncommon. Thus, we employed CRISPR/Cas9 to knock out Sex-miR-2766-3p from S. exigua. However, the expression of SeCncC was not significantly altered in the knockout strain (2766-KO) compared with that of the WHS strain. This result suggested that a miRNA knockout might lack phenotypes because of genetic robustness. Additionally, we used transcriptome analysis to examine how the global gene expression patterns of the Sex-miR-2766-3p knockout strain varied. RNA-seq data revealed 1746 upregulated and 2183 downregulated differentially expressed genes (DEGs) in the 2766-KO strain, which might be the result of Sex-miR-2766-3p loss or DNA lesions as the trigger for transcriptional adaptation. GO function classification and KEGG pathway analyses showed that these DEGs were enriched for terms related to binding, catalytic activity, metabolic process, and signal transduction. Our findings demonstrated that S. exigua could compensate for the missing Sex-miR-2766-3p by maintaining the expression of SeCncC by other pathways