Cells sense various in vivo mechanical stimuli, which initiate downstream signaling to mechanical forces. While a body of evidences is presented on the impact of limited mechanical regulators in past decades, the mech...Cells sense various in vivo mechanical stimuli, which initiate downstream signaling to mechanical forces. While a body of evidences is presented on the impact of limited mechanical regulators in past decades, the mechanisms how biomechanical responses globally affect cell function need to be addressed. Complexity and diversity of in v/vo mechanical clues present dis- tinct patterns of shear flow, tensile stretch, or mechanical compression with various parametric combination of its magnitude, duration, or frequency. Thus, it is required to understand, from the viewpoint of mechanobiology, what mechanical features of cells are, why mechanical properties are different among distinct cell types, and how forces are transduced to down- stream biochemical signals. Meanwhile, those in vitro isolated mechanical stimuli are usually coupled together in vivo, suggesting that the different factors that are in effect individually could be canceled out or orchestrated with each other. Evidently, omics analysis, a powerful tool in the field of system biology, is advantageous to combine with mechanobiology and then to map the fullset of mechanically sensitive proteins and transcripts encoded by its genome. This new emerging field, namely mechanomics, makes it possible to elucidate the global responses under systematically-varied mechanical stimuli. This review discusses the current advances in the related fields of mechanomics and elaborates how cells sense external forces and activate the biological responses.展开更多
Medicago polymorpha is a nutritious and palatable forage and vegetable plant that also fixes nitrogen.Here,we reveal the chromosome-scale genome sequence of M.polymorpha using an integrated approach including Illumina...Medicago polymorpha is a nutritious and palatable forage and vegetable plant that also fixes nitrogen.Here,we reveal the chromosome-scale genome sequence of M.polymorpha using an integrated approach including Illumina,PacBio and Hi-C technologies.We combined PacBio full-length RNA-seq,metabolomic analysis,structural anatomy analysis and related physiological indexes to elucidate the important agronomic traits of M.polymorpha for forage and vegetable usage.The assembled M.polymorpha genome consisted of 457.53Mb with a long scaffold N50 of 57.72Mb,and 92.92%(441.83Mb)of the assembly was assigned to seven pseudochromosomes.Comparative genomic analysis revealed that expansion and contraction of the photosynthesis and lignin biosynthetic gene families,respectively,led to enhancement of nutritious compounds and reduced lignin biosynthesis in M.polymorpha.In addition,we found that several positively selected nitrogen metabolism-related genes were responsible for crude protein biosynthesis.Notably,the metabolomic results revealed that a large number of flavonoids,vitamins,alkaloids,and terpenoids were enriched in M.polymorpha.These results imply that the decreased lignin content but relatively high nutrient content of M.polymorpha enhance its edibility and nutritional value as a forage and vegetable.Our genomic data provide a genetic basis that will accelerate functional genomic and breeding research on M.polymorpha as well as other Medicago and legume plants.展开更多
In this paper, a memetic algorithm with competition(MAC) is proposed to solve the capacitated green vehicle routing problem(CGVRP). Firstly, the permutation array called traveling salesman problem(TSP) route is used t...In this paper, a memetic algorithm with competition(MAC) is proposed to solve the capacitated green vehicle routing problem(CGVRP). Firstly, the permutation array called traveling salesman problem(TSP) route is used to encode the solution, and an effective decoding method to construct the CGVRP route is presented accordingly. Secondly, the k-nearest neighbor(k NN) based initialization is presented to take use of the location information of the customers. Thirdly, according to the characteristics of the CGVRP, the search operators in the variable neighborhood search(VNS) framework and the simulated annealing(SA) strategy are executed on the TSP route for all solutions. Moreover, the customer adjustment operator and the alternative fuel station(AFS) adjustment operator on the CGVRP route are executed for the elite solutions after competition. In addition, the crossover operator is employed to share information among different solutions. The effect of parameter setting is investigated using the Taguchi method of design-ofexperiment to suggest suitable values. Via numerical tests, it demonstrates the effectiveness of both the competitive search and the decoding method. Moreover, extensive comparative results show that the proposed algorithm is more effective and efficient than the existing methods in solving the CGVRP.展开更多
文摘Cells sense various in vivo mechanical stimuli, which initiate downstream signaling to mechanical forces. While a body of evidences is presented on the impact of limited mechanical regulators in past decades, the mechanisms how biomechanical responses globally affect cell function need to be addressed. Complexity and diversity of in v/vo mechanical clues present dis- tinct patterns of shear flow, tensile stretch, or mechanical compression with various parametric combination of its magnitude, duration, or frequency. Thus, it is required to understand, from the viewpoint of mechanobiology, what mechanical features of cells are, why mechanical properties are different among distinct cell types, and how forces are transduced to down- stream biochemical signals. Meanwhile, those in vitro isolated mechanical stimuli are usually coupled together in vivo, suggesting that the different factors that are in effect individually could be canceled out or orchestrated with each other. Evidently, omics analysis, a powerful tool in the field of system biology, is advantageous to combine with mechanobiology and then to map the fullset of mechanically sensitive proteins and transcripts encoded by its genome. This new emerging field, namely mechanomics, makes it possible to elucidate the global responses under systematically-varied mechanical stimuli. This review discusses the current advances in the related fields of mechanomics and elaborates how cells sense external forces and activate the biological responses.
基金the Graduate Student Innovation Foundation of Jiangsu Province(No.KYCX20_2992).
文摘Medicago polymorpha is a nutritious and palatable forage and vegetable plant that also fixes nitrogen.Here,we reveal the chromosome-scale genome sequence of M.polymorpha using an integrated approach including Illumina,PacBio and Hi-C technologies.We combined PacBio full-length RNA-seq,metabolomic analysis,structural anatomy analysis and related physiological indexes to elucidate the important agronomic traits of M.polymorpha for forage and vegetable usage.The assembled M.polymorpha genome consisted of 457.53Mb with a long scaffold N50 of 57.72Mb,and 92.92%(441.83Mb)of the assembly was assigned to seven pseudochromosomes.Comparative genomic analysis revealed that expansion and contraction of the photosynthesis and lignin biosynthetic gene families,respectively,led to enhancement of nutritious compounds and reduced lignin biosynthesis in M.polymorpha.In addition,we found that several positively selected nitrogen metabolism-related genes were responsible for crude protein biosynthesis.Notably,the metabolomic results revealed that a large number of flavonoids,vitamins,alkaloids,and terpenoids were enriched in M.polymorpha.These results imply that the decreased lignin content but relatively high nutrient content of M.polymorpha enhance its edibility and nutritional value as a forage and vegetable.Our genomic data provide a genetic basis that will accelerate functional genomic and breeding research on M.polymorpha as well as other Medicago and legume plants.
基金supported by the National Science Fund for Distinguished Young Scholars of China(61525304)the National Natural Science Foundation of China(61873328)
文摘In this paper, a memetic algorithm with competition(MAC) is proposed to solve the capacitated green vehicle routing problem(CGVRP). Firstly, the permutation array called traveling salesman problem(TSP) route is used to encode the solution, and an effective decoding method to construct the CGVRP route is presented accordingly. Secondly, the k-nearest neighbor(k NN) based initialization is presented to take use of the location information of the customers. Thirdly, according to the characteristics of the CGVRP, the search operators in the variable neighborhood search(VNS) framework and the simulated annealing(SA) strategy are executed on the TSP route for all solutions. Moreover, the customer adjustment operator and the alternative fuel station(AFS) adjustment operator on the CGVRP route are executed for the elite solutions after competition. In addition, the crossover operator is employed to share information among different solutions. The effect of parameter setting is investigated using the Taguchi method of design-ofexperiment to suggest suitable values. Via numerical tests, it demonstrates the effectiveness of both the competitive search and the decoding method. Moreover, extensive comparative results show that the proposed algorithm is more effective and efficient than the existing methods in solving the CGVRP.
