Spinal cord injuries impose a notably economic burden on society,mainly because of the severe after-effects they cause.Despite the ongoing development of various therapies for spinal cord injuries,their effectiveness ...Spinal cord injuries impose a notably economic burden on society,mainly because of the severe after-effects they cause.Despite the ongoing development of various therapies for spinal cord injuries,their effectiveness remains unsatisfactory.However,a deeper understanding of metabolism has opened up a new therapeutic opportunity in the form of metabolic reprogramming.In this review,we explore the metabolic changes that occur during spinal cord injuries,their consequences,and the therapeutic tools available for metabolic reprogramming.Normal spinal cord metabolism is characterized by independent cellular metabolism and intercellular metabolic coupling.However,spinal cord injury results in metabolic disorders that include disturbances in glucose metabolism,lipid metabolism,and mitochondrial dysfunction.These metabolic disturbances lead to corresponding pathological changes,including the failure of axonal regeneration,the accumulation of scarring,and the activation of microglia.To rescue spinal cord injury at the metabolic level,potential metabolic reprogramming approaches have emerged,including replenishing metabolic substrates,reconstituting metabolic couplings,and targeting mitochondrial therapies to alter cell fate.The available evidence suggests that metabolic reprogramming holds great promise as a next-generation approach for the treatment of spinal cord injury.To further advance the metabolic treatment of the spinal cord injury,future efforts should focus on a deeper understanding of neurometabolism,the development of more advanced metabolomics technologies,and the design of highly effective metabolic interventions.展开更多
High-throughput phenotyping system has become more and more popular in plant science research.The data analysis for such a system typically involves two steps:plant feature extraction through image processing and stat...High-throughput phenotyping system has become more and more popular in plant science research.The data analysis for such a system typically involves two steps:plant feature extraction through image processing and statistical analysis for the extracted features.The current approach is to perform those two steps on different platforms.We develop the package“implant”in R for both robust feature extraction and functional data analysis.For image processing,the“implant”package provides methods including thresholding,hidden Markov random field model,and morphological operations.For statistical analysis,this package can produce nonparametric curve fitting with its confidence region for plant growth.A functional ANOVA model to test for the treatment and genotype effects on the plant growth dynamics is also provided.展开更多
基金supported by the National Natural Science Foundation of China,No.82202681(to JW)the Natural Science Foundation of Zhejiang Province,Nos.LZ22H090003(to QC),LR23H060001(to CL).
文摘Spinal cord injuries impose a notably economic burden on society,mainly because of the severe after-effects they cause.Despite the ongoing development of various therapies for spinal cord injuries,their effectiveness remains unsatisfactory.However,a deeper understanding of metabolism has opened up a new therapeutic opportunity in the form of metabolic reprogramming.In this review,we explore the metabolic changes that occur during spinal cord injuries,their consequences,and the therapeutic tools available for metabolic reprogramming.Normal spinal cord metabolism is characterized by independent cellular metabolism and intercellular metabolic coupling.However,spinal cord injury results in metabolic disorders that include disturbances in glucose metabolism,lipid metabolism,and mitochondrial dysfunction.These metabolic disturbances lead to corresponding pathological changes,including the failure of axonal regeneration,the accumulation of scarring,and the activation of microglia.To rescue spinal cord injury at the metabolic level,potential metabolic reprogramming approaches have emerged,including replenishing metabolic substrates,reconstituting metabolic couplings,and targeting mitochondrial therapies to alter cell fate.The available evidence suggests that metabolic reprogramming holds great promise as a next-generation approach for the treatment of spinal cord injury.To further advance the metabolic treatment of the spinal cord injury,future efforts should focus on a deeper understanding of neurometabolism,the development of more advanced metabolomics technologies,and the design of highly effective metabolic interventions.
文摘High-throughput phenotyping system has become more and more popular in plant science research.The data analysis for such a system typically involves two steps:plant feature extraction through image processing and statistical analysis for the extracted features.The current approach is to perform those two steps on different platforms.We develop the package“implant”in R for both robust feature extraction and functional data analysis.For image processing,the“implant”package provides methods including thresholding,hidden Markov random field model,and morphological operations.For statistical analysis,this package can produce nonparametric curve fitting with its confidence region for plant growth.A functional ANOVA model to test for the treatment and genotype effects on the plant growth dynamics is also provided.
