Research into lactylation modifications across various target organs in both health and disease has gained significant attention.Many essential life processes and the onset of diseases are not only related to protein ...Research into lactylation modifications across various target organs in both health and disease has gained significant attention.Many essential life processes and the onset of diseases are not only related to protein abundance but are also primarily regulated by various post-translational protein modifications.Lactate,once considered merely a byproduct of anaerobic metabolism,has emerged as a crucial energy substrate and signaling molecule involved in both physiological and pathological processes within the nervous system.Furthermore,recent studies have emphasized the significant role of lactate in numerous neurological diseases,including Alzheimer's disease,Parkinson's disease,acute cerebral ischemic stroke,multiple sclerosis,Huntington's disease,and myasthenia gravis.The purpose of this review is to synthesize the current research on lactate and lactylation modifications in neurological diseases,aiming to clarify their mechanisms of action and identify potential therapeutic targets.As such,this work provides an overview of the metabolic regulatory roles of lactate in various disorders,emphasizing its involvement in the regulation of brain function.Additionally,the specific mechanisms of brain lactate metabolism are discussed,suggesting the unique roles of lactate in modulating brain function.As a critical aspect of lactate function,lactylation modifications,including both histone and non-histone lactylation,are explored,with an emphasis on recent advancements in identifying the key regulatory enzymes of such modifications,such as lactylation writers and erasers.The effects and specific mechanisms of abnormal lactate metabolism in diverse neurological diseases are summarized,revealing that lactate acts as a signaling molecule in the regulation of brain functions and that abnormal lactate metabolism is implicated in the progression of various neurological disorders.Future research should focus on further elucidating the molecular mechanisms underlying lactate and lactylation modifications and exploring their potential as therapeutic targets for neurological diseases.展开更多
Following injury,tissue autonomously initiates a complex repair process,resulting in either partial recovery or regeneration of tissue architecture and function in most organisms.Both the repair and regeneration proce...Following injury,tissue autonomously initiates a complex repair process,resulting in either partial recovery or regeneration of tissue architecture and function in most organisms.Both the repair and regeneration processes are highly coordinated by a hierarchy of interplay among signal transduction pathways initiated by different growth factors,cytokines and other signaling molecules under normal conditions.However,under chronic traumatic or pathological conditions,the reparative or regenerative process of most tissues in different organs can lose control to different extents,leading to random,incomplete or even flawed cell and tissue reconstitution and thus often partial restoration of the original structure and function,accompanied by the development of fibrosis,scarring or even pathogenesis that could cause organ failure and death of the organism.Ample evidence suggests that the various combinatorial fibroblast growth factor(FGF)and receptor signal transduction systems play prominent roles in injury repair and the remodeling of adult tissues in addition to embryonic development and regulation of metabolic homeostasis.In this review,we attempt to provide a brief update on our current understanding of the roles,the underlying mechanisms and clinical application of FGFs in tissue injury repair.展开更多
The Dynamic Time Warping(DTW)algorithm is widely used in finding the global alignment of time series.Many time series data mining and analytical problems can be solved by the DTW algorithm.However,using the DTW algori...The Dynamic Time Warping(DTW)algorithm is widely used in finding the global alignment of time series.Many time series data mining and analytical problems can be solved by the DTW algorithm.However,using the DTW algorithm to find similar subsequences is computationally expensive or unable to perform accurate analysis.Hence,in the literature,the parallelisation technique is used to speed up the DTW algorithm.However,due to the nature of DTW algorithm,parallelizing this algorithm remains an open challenge.In this paper,we first propose a novel method that finds the similar local subsequence.Our algorithm first searches for the possible start positions of subsequence,and then finds the best-matching alignment from these positions.Moreover,we parallelize the proposed algorithm on GPUs using CUDA and further propose an optimization technique to improve the performance of our parallelization implementation on GPU.We conducted the extensive experiments to evaluate the proposed method.Experimental results demonstrate that the proposed algorithm is able to discover time series subsequences efficiently and that the proposed GPU-based parallelization technique can further speedup the processing.展开更多
基金supported by Applied Basic Research Joint Fund Project of Yunnan Province,No.202301AY070001-200Middle-aged Academic and Technical Training Project for High-Level Talents,No.202105AC160065+1 种基金Yunnan Clinical Medical Center for Neurological and Cardiovascular Diseases,No.YWLCYXZX2023300077Key Clinical Specialty of Neurology in Yunnan Province,No.300064(all to CL)。
文摘Research into lactylation modifications across various target organs in both health and disease has gained significant attention.Many essential life processes and the onset of diseases are not only related to protein abundance but are also primarily regulated by various post-translational protein modifications.Lactate,once considered merely a byproduct of anaerobic metabolism,has emerged as a crucial energy substrate and signaling molecule involved in both physiological and pathological processes within the nervous system.Furthermore,recent studies have emphasized the significant role of lactate in numerous neurological diseases,including Alzheimer's disease,Parkinson's disease,acute cerebral ischemic stroke,multiple sclerosis,Huntington's disease,and myasthenia gravis.The purpose of this review is to synthesize the current research on lactate and lactylation modifications in neurological diseases,aiming to clarify their mechanisms of action and identify potential therapeutic targets.As such,this work provides an overview of the metabolic regulatory roles of lactate in various disorders,emphasizing its involvement in the regulation of brain function.Additionally,the specific mechanisms of brain lactate metabolism are discussed,suggesting the unique roles of lactate in modulating brain function.As a critical aspect of lactate function,lactylation modifications,including both histone and non-histone lactylation,are explored,with an emphasis on recent advancements in identifying the key regulatory enzymes of such modifications,such as lactylation writers and erasers.The effects and specific mechanisms of abnormal lactate metabolism in diverse neurological diseases are summarized,revealing that lactate acts as a signaling molecule in the regulation of brain functions and that abnormal lactate metabolism is implicated in the progression of various neurological disorders.Future research should focus on further elucidating the molecular mechanisms underlying lactate and lactylation modifications and exploring their potential as therapeutic targets for neurological diseases.
基金supported by start-up funds from Wenzhou Medical University and The First Affiliated Hospital to YL,and Chinese Academy of Medical Sciences(CAMS)Innovation Fund for Medical Sciences(2019-I2M-5-028)to XL.
文摘Following injury,tissue autonomously initiates a complex repair process,resulting in either partial recovery or regeneration of tissue architecture and function in most organisms.Both the repair and regeneration processes are highly coordinated by a hierarchy of interplay among signal transduction pathways initiated by different growth factors,cytokines and other signaling molecules under normal conditions.However,under chronic traumatic or pathological conditions,the reparative or regenerative process of most tissues in different organs can lose control to different extents,leading to random,incomplete or even flawed cell and tissue reconstitution and thus often partial restoration of the original structure and function,accompanied by the development of fibrosis,scarring or even pathogenesis that could cause organ failure and death of the organism.Ample evidence suggests that the various combinatorial fibroblast growth factor(FGF)and receptor signal transduction systems play prominent roles in injury repair and the remodeling of adult tissues in addition to embryonic development and regulation of metabolic homeostasis.In this review,we attempt to provide a brief update on our current understanding of the roles,the underlying mechanisms and clinical application of FGFs in tissue injury repair.
基金supported by the National Natural Science Foundation of China(No.61602215)the Science Foundation of Jiangsu Province(No.BK20150527)the EU Horizon 2020—Marie Sklodowska-Curie Actions through the project entitled Computer Vision Enabled Multimedia Forensics and People Identification(Project No.690907,Acronym:IDENTITY).
文摘The Dynamic Time Warping(DTW)algorithm is widely used in finding the global alignment of time series.Many time series data mining and analytical problems can be solved by the DTW algorithm.However,using the DTW algorithm to find similar subsequences is computationally expensive or unable to perform accurate analysis.Hence,in the literature,the parallelisation technique is used to speed up the DTW algorithm.However,due to the nature of DTW algorithm,parallelizing this algorithm remains an open challenge.In this paper,we first propose a novel method that finds the similar local subsequence.Our algorithm first searches for the possible start positions of subsequence,and then finds the best-matching alignment from these positions.Moreover,we parallelize the proposed algorithm on GPUs using CUDA and further propose an optimization technique to improve the performance of our parallelization implementation on GPU.We conducted the extensive experiments to evaluate the proposed method.Experimental results demonstrate that the proposed algorithm is able to discover time series subsequences efficiently and that the proposed GPU-based parallelization technique can further speedup the processing.
