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Role of metabolic dysfunction and inflammation along the liver-brain axis in animal models with obesity-induced neurodegeneration

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Neural Regeneration Research 2025年第4期20卷 1069-1076页

作者： Evridiki Asimakidou Eka Norfaishanty Saipuljumri Chih Hung Lo jialiu zeng Department of Clinical Neurosciences University of CambridgeCambridgeUK School of Applied Science Republic PolytechnicSingaporeSingapore Lee Kong Chian School of Medicine Nanyang Technological UniversitySingaporeSingapore

The interaction between metabolic dysfunction and inflammation is central to the development of neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s ***-related conditions like type 2 diabetes and non-alcoholic fatty liver disease exacerbate this *** lipid accumulation,particularly in the liver,initiates a cascade of inflammatory processes that extend to the brain,influencing critical metabolic regulatory *** and palmitate,key lipid components,along with lipid transporters lipocalin-2 and apolipoprotein E,contribute to neuroinflammation by disrupting blood–brain barrier integrity and promoting *** insulin resistance further exacerbates brain insulin resistance and *** interventions targeting peripheral lipid metabolism and insulin signaling pathways have shown promise in reducing neuroinflammation in animal ***,translating these findings to clinical practice requires further investigation into human *** conclusion,metabolic dysfunction,peripheral inflammation,and insulin resistance are integral to neuroinflammation and *** these complex mechanisms holds potential for identifying novel therapeutic targets and improving outcomes for neurodegenerative diseases.

关键词： Alzheimer’s disease inflammatory cytokines insulin resistance lipid

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Defective lysosomal acidification:a new prognostic marker and therapeutic target for neurodegenerative diseases

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Translational Neurodegeneration 2023年第1期12卷 500-510页

作者： Chih Hung Lo jialiu zeng Lee Kong Chian School of Medicine Nanyang Technological UniversitySingapore 308232Singapore

Lysosomal acidification dysfunction has been implicated as a key driving factor in the pathogenesis of neurodegenerative diseases,including Alzheimer’s disease and Parkinson’s *** genetic factors have been linked to lysosomal de-acidification through impairing the vacuolar-type ATPase and ion channels on the organelle *** lysosomal abnormalities are also present in sporadic forms of neurodegeneration,although the underlying pathogenic mechanisms are unclear and remain to be ***,recent studies have revealed early occurrence of lysosomal acidification impairment before the onset of neurodegeneration and late-stage ***,there is a lack of methods for organelle pH monitoring in vivo and a dearth of lysosome-acidifying therapeutic ***,we summarize and present evidence for the notion of defective lysosomal acidification as an early indicator of neurodegeneration and urge the critical need for technological advancement in developing tools for lysosomal pH monitoring and detection both in vivo and for clinical *** further discuss current preclinical pharmacological agents that modulate lysosomal acidification,including small molecules and nanomedicine,and their potential clinical translation into lysosome-targeting *** timely detection of lysosomal dysfunction and development of therapeutics that restore lysosomal function represent paradigm shifts in targeting neurodegenerative diseases.

关键词： Neurodegenerative diseases Alzheimer’s disease Parkinson’s disease Lysosomal de-acidification Autophagy dysfunction Early detection Prognostic marker Small molecules Nanomedicine Nanoparticles

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Integrative multi-omics and systems bioinformatics in translational neuroscience:A data mining perspective

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Journal of Pharmaceutical Analysis 2023年第8期13卷 836-850页

作者： Lance M.O'Connor Blake A.O'Connor Su Bin Lim jialiu zeng Chih Hung Lo College of Biological Sciences University of MinnesotaMinneapolisMN55455USA School of Pharmacy University of WisconsinMadisonWI53705USA Department of Biochemistry and Molecular Biology Ajou University School of MedicineSuwon16499South Korea Lee Kong Chian School of Medicine Nanyang Technological UniversitySingapore308232Singapore

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information,with its application to neuroscience termed *** mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms,which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative ***,integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain *** this review,we first summarize data mining studies utilizing datasets from the individual type of omics analysis,including epigenetics/epigenomics,transcriptomics,proteomics,metabolomics,lipidomics,and spatial omics,pertaining to Alzheimer's disease,Parkinson's disease,and multiple *** then discuss multi-omics integration approaches,including independent biological integration and unsupervised integration methods,for more intuitive and informative interpretation of the biological data obtained across different omics *** further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain ***,we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery,therapeutic development,and elucidation of disease *** conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personaliz

关键词： Multi-omics integration Systems bioinformatics Data mining Human brain profile reconstruction Translational neuroscience

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基于改进GSA-GWO算法的含分布式电源局部电网孤岛划分策略

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可再生能源 2024年第4期42卷 538-545页

作者：张丹赛翔羽曾丕江武明康瞿佳刘云南电网有限责任公司电力调度控制中心云南昆明650217 直流输电技术国家重点实验室(南方电网科学研究院) 广东广州510663 广东省新能源电力系统智能运行与控制企业重点实验室广东广州510663

为进一步提高局部电网在故障恢复过程中的高效性和可靠性,文章提出了一种基于改进GSA-GWO算法的局部电网故障下孤岛划分策略。首先,采用最优-最劣法对负荷进行评价,得到负荷权重值,从而确定局部电网故障下孤岛划分重要负荷恢复优先级;其... 详细信息

为进一步提高局部电网在故障恢复过程中的高效性和可靠性,文章提出了一种基于改进GSA-GWO算法的局部电网故障下孤岛划分策略。首先,采用最优-最劣法对负荷进行评价,得到负荷权重值,从而确定局部电网故障下孤岛划分重要负荷恢复优先级;其次,结合负荷优先级确定负荷等级权重系数值,构建含分布式电源的局部电网孤岛划分目标函数模型;再次,为了获取更佳的目标函数求解结果,引入混沌反向学习和遗传退火算法(Genetic Simulated An-nealing,GSA)对灰狼优化算法(Grey Wolf Optimization,GWO)进行改进,以提高算法的优化性能;最后,以修改后的IEEE 69节点为例进行仿真分析,运用改进的GSA-GWO算法对局部配电网故障模型进行求解,得到更佳的孤岛划分结果。算例分析表明,文章提出的策略可准确实现局部电网故障下孤岛划分最优策略,保证了重要负荷的电力供应,验证了策略的有效性和优越性。

关键词：局部电网分布式电源孤岛划分恢复供电

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