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  1. Article ; Online: Perillaldehyde ameliorates lipopolysaccharide-induced acute lung injury via suppressing the cGAS/STING signaling pathway.

    Wei, Jiahui / Liu, Zhengjia / Sun, Hongbin / Xu, Lei

    International immunopharmacology

    2024  Volume 130, Page(s) 111641

    Abstract: Acute lung injury (ALI) is a common life-threatening illness characterized by a lung inflammatory response and oxidative stress, and effective agent therapies are currently lacking. mtDNA can be recognized by cGAS/STING, the dysregulation of which leads ... ...

    Abstract Acute lung injury (ALI) is a common life-threatening illness characterized by a lung inflammatory response and oxidative stress, and effective agent therapies are currently lacking. mtDNA can be recognized by cGAS/STING, the dysregulation of which leads to inflammatory diseases, such as ALI. Perillaldehyde(PAH), one of the major active components of traditional Chinese medicine made from Perilla frutescens, has antioxidant and antiinflammatory effects. The aim of this study was to explore whether PAH can protect against lipopolysaccharide (LPS)-induced ALI and whether its protective effect is exerted through the regulation of cGAS/STING signaling. We found that PAH significantly inhibited lung histological changes, inflammatory cell infiltration, and the overproduction of inflammatory cytokines induced by LPS. Moreover, PAH inhibited LPS-induced oxidative stress, as shown by the deceases in superoxide dismutase (SOD) and glutathione(GSH) levels and increased in malondialdehyde (MDA) and lactate dehydrogenase (LDH) levels. In addition, PAH markedly downregulated the expression of cGAS, STING, p-TBK, p-IRF3, p-P65, and p-IκB, and pharmacological inhibition of cGAS/STING inhibited ALI- induced by LPS. Furthermore, the levels of mitochondrial ROS (mROS) and mtDNA were increased, and cGAS/STING-mediated IRF3/NF-κB signaling was activated during the inflammatory response- induced by LPS in RAW264.7 cells. In addition, pretreatment with the STING activator partially abolished the inhibitory effect of PAH on the inflammation and activation of STING-mediated IRF3/NF-κB signaling induced by LPS. Overall, the results revealed that PAH can effectively alleviate ALI by inhibiting cGAS/STING-mediated IRF3/NF-κB signaling, and that PAH may be a potential candidate agent for the treatment of ALI.
    MeSH term(s) Humans ; NF-kappa B/metabolism ; Lipopolysaccharides/pharmacology ; Acute Lung Injury/chemically induced ; Acute Lung Injury/drug therapy ; Acute Lung Injury/metabolism ; Signal Transduction ; Nucleotidyltransferases/metabolism ; DNA, Mitochondrial ; Monoterpenes
    Chemical Substances NF-kappa B ; Lipopolysaccharides ; perillaldehyde (6EQL0XA86G) ; Nucleotidyltransferases (EC 2.7.7.-) ; DNA, Mitochondrial ; Monoterpenes
    Language English
    Publishing date 2024-02-18
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2043785-7
    ISSN 1878-1705 ; 1567-5769
    ISSN (online) 1878-1705
    ISSN 1567-5769
    DOI 10.1016/j.intimp.2024.111641
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  2. Article ; Online: Enterprise Information Security Management Using Internet of Things Combined with Artificial Intelligence Technology.

    Sun, Hongbin / Bai, Shizhen

    Computational intelligence and neuroscience

    2022  Volume 2022, Page(s) 7138515

    Abstract: This work is conducted to deal with the information security of enterprise management under the background of current global informatization, popularize the modern Internet of Things (IoT) management technology of enterprises, and maintain the ... ...

    Abstract This work is conducted to deal with the information security of enterprise management under the background of current global informatization, popularize the modern Internet of Things (IoT) management technology of enterprises, and maintain the information security of enterprises and provide modern upgrading means for enterprise management. In this work, it firstly introduces the application scenarios of current Internet and Artificial Intelligence (AI) technology and expounds the IoT technology. Secondly, the enterprise management platform is designed, the requirements of enterprise modern management are analyzed, and then the design requirements of system functions and the design of the information security architecture of the IoT are proposed. Furthermore, an enterprise information security management platform is designed, which covers four parts: IoT data mining management, equipment management, key management, and database management. In addition, the performance of the security management platform is tested from four parts: concurrency testing, stress testing, large data volume testing, and security testing. The research results show that the IoT-based enterprise information security management platform designed in this work under the background of AI has perfect functions and stable performance of each module. Concurrency testing, stress testing, large data volume testing, and stability testing are performed on it, and the success rate of the platform in each task reaches 100%. The average response time of concurrent testing and stress testing is about 0.13 seconds, and that of the event entry events is 0.25 seconds. The central processing unit (CPU) occupancy rate in each monitoring task is always lower than 20%. Therefore, it is determined that the performance of the IoT-based enterprise information security management platform designed in this work is sufficient to meet the daily management of enterprises. This work can provide a guarantee for enterprise information security management using AI technology, setting an example for future related research.
    MeSH term(s) Artificial Intelligence ; Computer Security ; Forecasting ; Internet ; Internet of Things ; Technology
    Language English
    Publishing date 2022-06-14
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2388208-6
    ISSN 1687-5273 ; 1687-5273
    ISSN (online) 1687-5273
    ISSN 1687-5273
    DOI 10.1155/2022/7138515
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  3. Article ; Online: Statistical Machine Learning for Power Flow Analysis Considering the Influence of Weather Factors on Photovoltaic Power Generation.

    Fu, Xueqian / Zhang, Chunyu / Xu, Yan / Zhang, Youmin / Sun, Hongbin

    IEEE transactions on neural networks and learning systems

    2024  Volume PP

    Abstract: It is generally accepted that the impact of weather variation is gradually increasing in modern distribution networks with the integration of high-proportion photovoltaic (PV) power generation and weather-sensitive loads. This article analyzes power flow ...

    Abstract It is generally accepted that the impact of weather variation is gradually increasing in modern distribution networks with the integration of high-proportion photovoltaic (PV) power generation and weather-sensitive loads. This article analyzes power flow using a novel stochastic weather generator (SWG) based on statistical machine learning (SML). The proposed SML model, which incorporates generative adversarial networks (GANs), probability theory, and information theory, enables the generation and evaluation of simulated hourly weather data throughout the year. The GAN model captures various weather variation characteristics, including weather uncertainties, diurnal variations, and seasonal patterns. Compared to shallow learning models, the proposed deep learning model exhibits significant advantages in stochastic weather simulation. The simulated data generated by the proposed model closely resemble real data in terms of time-series regularity, integrity, and stochasticity. The SWG is applied to model PV power generation and weather-sensitive loads. Then, we actively conduct a power flow analysis (PFA) on a real distribution network in Guangdong, China, using simulated data for an entire year. The results provide evidence that the GAN-based SWG surpasses the shallow machine learning approach in terms of accuracy. The proposed model ensures accurate analysis of weather-related power flow and provides valuable insights for the analysis, planning, and design of distribution networks.
    Language English
    Publishing date 2024-04-08
    Publishing country United States
    Document type Journal Article
    ISSN 2162-2388
    ISSN (online) 2162-2388
    DOI 10.1109/TNNLS.2024.3382763
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Robust expansion planning and hardening strategy of meshed multi-energy distribution networks for resilience enhancement

    Li, Tingjun / Han, Xiaoqing / Wu, Wenchuan / Sun, Hongbin

    Applied Energy. 2023 July, v. 341 p.121066-

    2023  

    Abstract: As an integrated energy system (IES) incorporated with electricity, gas, and heating networks, the meshed multi-energy distribution network (MMDN) can operate more economically with higher energy utilization efficiency. To achieve high reliability, MMDN ... ...

    Abstract As an integrated energy system (IES) incorporated with electricity, gas, and heating networks, the meshed multi-energy distribution network (MMDN) can operate more economically with higher energy utilization efficiency. To achieve high reliability, MMDN is mesh-constructed and radial-operated, complicating the operation scenarios involved in planning. Existing coordinated planning models seldom consider network reconfiguration and hardening strategies collaboratively for extreme contingencies, which is not consistent with actual conditions. In addition, considering the multi-stage discreteness of the expansion planning problem, the existing robust algorithms may feedback invalid cuts. The neglect of such issues could introduce a momentous impact on the optimality of solutions. This paper presents a resiliency-oriented expansion planning and hardening model of MMDN, and the hierarchical algorithm is developed. Specifically, the model is formulated as a min–max-min optimization problem including investment and operation levels. The investment level problem optimizes planning schemes constrained with the robustness verification of the operation level problem. The operation level problem examines the operational cost and feeds back iterative information to the investment level. An additional cuts generation method is developed in the operation level, which effectively deals with invalid feedback information caused by the existing binary variable parameterization. Furthermore, accelerating strategies including infeasible region reduction, multi-cut feedback, and contingency set reduction are developed. To be solved by off-the-shelf solvers, the model is cast as a mixed-integer linear programming (MILP) problem by adopting the convex hull relaxation and linearization techniques for operational constraints with high accuracy. Numerical test results justify the effectiveness of the model.
    Keywords algorithms ; electricity ; energy ; models ; operating costs ; system optimization ; Expansion planning ; Robust optimization ; Network hardening ; Multi-energy distribution network ; Resilience
    Language English
    Dates of publication 2023-07
    Publishing place Elsevier Ltd
    Document type Article ; Online
    ZDB-ID 2000772-3
    ISSN 0306-2619
    ISSN 0306-2619
    DOI 10.1016/j.apenergy.2023.121066
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  5. Article ; Online: Potential Therapeutic Value of the STING Inhibitors.

    Zhang, Shangran / Zheng, Runan / Pan, Yanhong / Sun, Hongbin

    Molecules (Basel, Switzerland)

    2023  Volume 28, Issue 7

    Abstract: The stimulator of interferon genes (STING) is a critical protein in the activation of the immune system in response to DNA. It can participate the inflammatory response process by modulating the inflammation-preferred translation program through the ... ...

    Abstract The stimulator of interferon genes (STING) is a critical protein in the activation of the immune system in response to DNA. It can participate the inflammatory response process by modulating the inflammation-preferred translation program through the STING-PKR-like endoplasmic reticulum kinase (PERK)-eIF2α pathway or by inducing the secretion of type I interferons (IFNs) and a variety of proinflammatory factors through the recruitment of TANK-binding kinase 1 (TBK1) and interferon regulatory factor 3 (IRF3) or the regulation of the nuclear factor kappa-B (NF-κB) pathway. Based on the structure, location, function, genotype, and regulatory mechanism of STING, this review summarizes the potential value of STING inhibitors in the prevention and treatment of infectious diseases, psoriasis, systemic lupus erythematosus, non-alcoholic fatty liver disease, and other inflammatory and autoimmune diseases.
    MeSH term(s) Humans ; Signal Transduction ; Membrane Proteins/metabolism ; NF-kappa B/metabolism ; Inflammation/drug therapy ; Inflammation/metabolism ; DNA ; Interferon Regulatory Factor-3/metabolism ; Immunity, Innate
    Chemical Substances Membrane Proteins ; NF-kappa B ; DNA (9007-49-2) ; Interferon Regulatory Factor-3
    Language English
    Publishing date 2023-03-31
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 1413402-0
    ISSN 1420-3049 ; 1431-5165 ; 1420-3049
    ISSN (online) 1420-3049
    ISSN 1431-5165 ; 1420-3049
    DOI 10.3390/molecules28073127
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  6. Article ; Online: Barium-induced lattice expansion of Ni(OH)

    Du, Cengceng / Wang, Zhenyu / Wang, Yiming / Xu, Wenjuan / Huo, Yuqiu / Sun, Hongbin / Xu, Guangwen

    Dalton transactions (Cambridge, England : 2003)

    2024  

    Abstract: Constructing an environmentally friendly and efficient electrocatalyst holds important and profound significance for energy-efficient hydrogen production. Replacing the oxygen evolution reaction with a lower potential urea oxidation reaction (UOR) may ... ...

    Abstract Constructing an environmentally friendly and efficient electrocatalyst holds important and profound significance for energy-efficient hydrogen production. Replacing the oxygen evolution reaction with a lower potential urea oxidation reaction (UOR) may save energy in water electrolysis to produce hydrogen. The UOR is characterized by its high energy barrier, which results in slow reaction kinetics. In this study, we introduced Ba(OH)
    Language English
    Publishing date 2024-05-10
    Publishing country England
    Document type Journal Article
    ZDB-ID 1472887-4
    ISSN 1477-9234 ; 1364-5447 ; 0300-9246 ; 1477-9226
    ISSN (online) 1477-9234 ; 1364-5447
    ISSN 0300-9246 ; 1477-9226
    DOI 10.1039/d4dt00595c
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  7. Article: An efficient optimal energy flow model for integrated energy systems based on energy circuit modeling in the frequency domain

    Chen, Binbin / Wu, Wenchuan / Guo, Qinglai / Sun, Hongbin

    Applied energy. 2022 Nov. 15, v. 326

    2022  

    Abstract: With more energy networks being interconnected to form integrated energy systems (IESs), the optimal energy flow (OEF) problem has drawn increasing attention. Extant studies on OEF models mostly utilize the finite difference method (FDM) to address ... ...

    Abstract With more energy networks being interconnected to form integrated energy systems (IESs), the optimal energy flow (OEF) problem has drawn increasing attention. Extant studies on OEF models mostly utilize the finite difference method (FDM) to address partial-differential-equation (PDE) constraints related to the dynamics in natural gas networks (NGNs) and district heating networks (DHNs). However, this time-domain approach suffers from a heavy computational burden with regard to achieving high finite-difference accuracy. In this paper, a novel OEF model that formulates NGN and DHN constraints in the frequency domain and corresponding model compaction techniques for efficient solving are contributed. First, an energy circuit method (ECM) that algebraizes the PDEs of NGNs and DHNs in the frequency domain is introduced. Then, an ECM-based OEF model is formulated, which contains fewer variables and constraints than an FDM-based OEF model and thereby yields better solving efficiency. Finally, variable space projection is employed to remove implicit variables, by which another constraint generation algorithm is enabled to remove redundant constraints. These two techniques further compact the OEF model and bring about a second improvement in solving efficiency. Numerical tests on actual systems indicate the final OEF model reduces variables and constraints by more than 95% and improves the solving efficiency by more than 10 times. In conclusion, the proposed OEF model and solving techniques well meet the optimization needs of large-scale IESs.
    Keywords algorithms ; energy flow ; models ; natural gas
    Language English
    Dates of publication 2022-1115
    Publishing place Elsevier Ltd
    Document type Article
    ZDB-ID 2000772-3
    ISSN 0306-2619
    ISSN 0306-2619
    DOI 10.1016/j.apenergy.2022.119923
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  8. Article ; Online: Discussion on the Analysis Method of Iodide in Natural Water Samples

    SONG Xinyi / XU Chunxue / AN Ziyi / SUN Hongbin / CHEN Zongding / LIU Wei / ZHENG Yuqi

    Yankuang ceshi, Vol 42, Iss 3, Pp 587-

    2023  Volume 597

    Abstract: BACKGROUND As the main source of iodine intake, water is of practical significance to detect the content of iodide accurately. At present, the common methods for the analysis of iodide in water samples include ion chromatography, gas chromatography, ... ...

    Abstract BACKGROUND As the main source of iodine intake, water is of practical significance to detect the content of iodide accurately. At present, the common methods for the analysis of iodide in water samples include ion chromatography, gas chromatography, colorimetry, spectrophotometry. The analysis results of different methods can be affected by the actual sample matrix and experimental conditions. Our project team organized 38 laboratories to determine the content of iodide in natural water samples by ion chromatography, starch spectrophotometry, catalytic reduction spectrophotometry, and inductively coupled plasma-mass spectrometry (ICP-MS), the results showed that there were significant differences among the measured values by different methods, and the data were obviously dispersed. OBJECTIVES To discuss the reasons for the differences between the results of different methods and give suggestions on the selection of iodide analysis methods under different conditions, based on the principles and conditions of each method. METHODS Four analysis methods, including ion chromatography, starch spectrophotometry, catalytic reduction spectrophotometry, and ICP-MS, were used to determine the content of iodide of the groundwater sample by 38 laboratories. High performance liquid chromatography-inductively coupled plasma-mass spectrometry (HPLC-ICP-MS) was used to determine the content of iodide by our own laboratory. RESULTS (1) HPLC-ICP-MS can be used to effectively separate iodide and iodate ions in water samples. Through the quality control of the experimental process by blank samples, standard reference materials and replicate samples, the analytical results of this method were accurate and reliable. The determination results of iodide in JSH-2 samples were 78.32μg/L. (2) The determination values of iodide by ion chromatography (83.38μg/L) were consistent with those by HPLC-ICP-MS (78.32μg/L). However, the data of ion chromatography between different laboratories were obviously dispersed. The determination values of ...
    Keywords iodide ; iodine speciation ; high performance liquid chromatography-inductively coupled plasma-mass spectrometry ; hplc-icp-ms ; natural water ; Geology ; QE1-996.5 ; Ecology ; QH540-549.5
    Subject code 540
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher Science Press, PR China
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Effects of magnesium valproate adjuvant therapy on patients with dementia: A systematic review and meta-analysis.

    Zhang, ChenQi / Sun, LingQi / Sun, HongBin

    Medicine

    2022  Volume 101, Issue 31, Page(s) e29642

    Abstract: Background: Current research has found contradictory results on the treatment of magnesium valproate (VPM) in patients with dementia (PwD).: Objectives: Here, we conducted a meta-analysis to evaluate the efficacy and safety of VPM in the adjuvant ... ...

    Abstract Background: Current research has found contradictory results on the treatment of magnesium valproate (VPM) in patients with dementia (PwD).
    Objectives: Here, we conducted a meta-analysis to evaluate the efficacy and safety of VPM in the adjuvant treatment of PwD.
    Purpose: Current research has found contradictory results on the treatment of VPM in PwD. Here, we conducted a meta-analysis to evaluate the efficacy and safety of VPM in the adjuvant treatment of PwD.
    Methods: MEDLINE via PubMed, Cochrane Library, EBSCO, Embase, China National Knowledge (CNKI), and Wan Fang databases were researched to gather relevant data on magnesium valproate assistant therapy for patients with dementia (PwD) by using medical subject headings and term words.
    Results: After the final screening, 22 RCT studies (a total of 1899 participants) were included in this meta-analysis, which compared VPM adjuvant treatment with antidementia or psychotropic drug monotherapy. Significant differences were found in the scores on mini-mental state examination (P = .028), Alzheimer disease assessment scale cognitive subscale (P < .05), Bech-Rafaelsen Mania Rating Scale (P < .05), behavioral pathology in Alzheimer disease rating scale (P = .001), activities of daily living (P < .05), and Pittsburgh Sleep Quality Index (P < .05). Besides, the levels of inflammatory factors including IL-1β, IL-6, and TNF-α were significantly lower than those in the monotherapy group (P < .05). While there was no increase in the incidence of adverse events (P = .383), VPM as an assistant therapy is generally well tolerated in PwD.
    Conclusion: By meta-analysis, evidence was found to support VPM additional used for the treatment of cognitive function, psychiatric symptoms, or disease improvement in PwD. VPM may be a potential drug to aid in the treatment of dementia patients. However, there was lack of enough evidence to classification of dementia severity in our inclusion study. More research is still needed, including clinical trials evaluating VPM as a complementary therapy.
    MeSH term(s) Activities of Daily Living ; Alzheimer Disease/psychology ; Cognition ; Humans ; Mental Status and Dementia Tests ; Valproic Acid/adverse effects
    Chemical Substances Valproic Acid (614OI1Z5WI)
    Language English
    Publishing date 2022-08-24
    Publishing country United States
    Document type Journal Article ; Meta-Analysis ; Systematic Review
    ZDB-ID 80184-7
    ISSN 1536-5964 ; 0025-7974
    ISSN (online) 1536-5964
    ISSN 0025-7974
    DOI 10.1097/MD.0000000000029642
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  10. Article ; Online: Deep Reinforcement Learning Microgrid Optimization Strategy Considering Priority Flexible Demand Side.

    Sang, Jinsong / Sun, Hongbin / Kou, Lei

    Sensors (Basel, Switzerland)

    2022  Volume 22, Issue 6

    Abstract: As an efficient way to integrate multiple distributed energy resources (DERs) and the user side, a microgrid is mainly faced with the problems of small-scale volatility, uncertainty, intermittency and demand-side uncertainty of DERs. The traditional ... ...

    Abstract As an efficient way to integrate multiple distributed energy resources (DERs) and the user side, a microgrid is mainly faced with the problems of small-scale volatility, uncertainty, intermittency and demand-side uncertainty of DERs. The traditional microgrid has a single form and cannot meet the flexible energy dispatch between the complex demand side and the microgrid. In response to this problem, the overall environment of wind power, thermostatically controlled loads (TCLs), energy storage systems (ESSs), price-responsive loads and the main grid is proposed. Secondly, the centralized control of the microgrid operation is convenient for the control of the reactive power and voltage of the distributed power supply and the adjustment of the grid frequency. However, there is a problem in that the flexible loads aggregate and generate peaks during the electricity price valley. The existing research takes into account the power constraints of the microgrid and fails to ensure a sufficient supply of electric energy for a single flexible load. This paper considers the response priority of each unit component of TCLs and ESSs on the basis of the overall environment operation of the microgrid so as to ensure the power supply of the flexible load of the microgrid and save the power input cost to the greatest extent. Finally, the simulation optimization of the environment can be expressed as a Markov decision process (MDP) process. It combines two stages of offline and online operations in the training process. The addition of multiple threads with the lack of historical data learning leads to low learning efficiency. The asynchronous advantage actor-critic (Memory A3C, M-A3C) with the experience replay pool memory library is added to solve the data correlation and nonstatic distribution problems during training. The multithreaded working feature of M-A3C can efficiently learn the resource priority allocation on the demand side of the microgrid and improve the flexible scheduling of the demand side of the microgrid, which greatly reduces the input cost. Comparison of the researched cost optimization results with the results obtained with the proximal policy optimization (PPO) algorithm reveals that the proposed algorithm has better performance in terms of convergence and optimization economics.
    MeSH term(s) Algorithms ; Computer Simulation ; Electric Power Supplies ; Electricity ; Wind
    Language English
    Publishing date 2022-03-14
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s22062256
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