Gut microbes are closely related with human health,but remain much to learn.Clostridium symbiosum is a conditionally pathogenic human gut bacterium and regarded as a potential biomarker for early diagnosis of intestin...Gut microbes are closely related with human health,but remain much to learn.Clostridium symbiosum is a conditionally pathogenic human gut bacterium and regarded as a potential biomarker for early diagnosis of intestinal tumors.However,the absence of an efficient toolbox that allows diverse genetic manipulations of this bacterium limits its in-depth studies.Here,we obtained the complete genome sequence of C.symbiosum ATCC 14940,a representative strain of C.symbiosum.On this basis,we further developed a series of genetic manipulation methods for this bacterium.Firstly,following the identification of a functional replicon pBP1 in C.symbiosum ATCC 14940,a highly efficient conjugative DNA transfer method was established,enabling the rapid introduction of exogenous plasmids into cells.Next,we constructed a dual-plasmid CRISPR/Cas12a system for genome editing in this bacterium,reaching over 60% repression for most of the chosen genes as well as efficient deletion(>90%)of three target genes.Finally,this toolbox was used for the identification of crucial functional genes,involving growth,synthesis of important metabolites,and virulence of C.symbiosum ATCC 14940.Our work has effectively established and optimized genome editing methods in intestinal C.symbiosum,thereby providing strong support for further basic and application research in this bacterium.展开更多
在开展数学教学时,因数学课件缺乏交互性,使得课件变成了课本的"投影展示",影响教学效果。概述了VBA语言及PowerPoint Control Toolbox,通过对高中数学"三视图"及"不等关系"等知识点使用PowerPoint Contr...在开展数学教学时,因数学课件缺乏交互性,使得课件变成了课本的"投影展示",影响教学效果。概述了VBA语言及PowerPoint Control Toolbox,通过对高中数学"三视图"及"不等关系"等知识点使用PowerPoint Control Toolbox的组件进行交互设计,增强了数学课件的交互性。展开更多
This paper presents a method for dynamically predicting gas emission quantity based on the wavelet neural network （WNN） toolbox. Such a method is able to predict the gas emission quantity in adjacent subsequent time...This paper presents a method for dynamically predicting gas emission quantity based on the wavelet neural network （WNN） toolbox. Such a method is able to predict the gas emission quantity in adjacent subsequent time intervals through training the WNN with even time-interval samples. The method builds successive new model with the width of sliding window remaining invariable so as to obtain a dynamic prediction method for gas emission quantity. Furthermore, the method performs prediction by a self-developed WNN toolbox. Experiments indicate that such a model can overcome the deficiencies of the traditional static prediction model and can fully make use of the feature extraction capability of wavelet base function to reflect the geological feature of gas emission quantity dynamically. The method is characterized by simplicity, flexibility, small data scale, fast convergence rate and high prediction precision. In addition, the method is also characterized by certainty and repeatability of the predicted results. The effectiveness of this method is confirmed by simulation results. Therefore, this method will exert practical significance on promoting the application of WNN.展开更多
基金supported by the National Key R&D Program of China(2018YFA0901500)Science and Technology Commission of Shanghai Municipality(21DZ1209100)+1 种基金DNL Cooperation Fund,CAS(DNL202013)Tianjin Synthetic Biotechnology Innovation Capacity Improvement Project(TSBICIP-KJGG-016).
文摘Gut microbes are closely related with human health,but remain much to learn.Clostridium symbiosum is a conditionally pathogenic human gut bacterium and regarded as a potential biomarker for early diagnosis of intestinal tumors.However,the absence of an efficient toolbox that allows diverse genetic manipulations of this bacterium limits its in-depth studies.Here,we obtained the complete genome sequence of C.symbiosum ATCC 14940,a representative strain of C.symbiosum.On this basis,we further developed a series of genetic manipulation methods for this bacterium.Firstly,following the identification of a functional replicon pBP1 in C.symbiosum ATCC 14940,a highly efficient conjugative DNA transfer method was established,enabling the rapid introduction of exogenous plasmids into cells.Next,we constructed a dual-plasmid CRISPR/Cas12a system for genome editing in this bacterium,reaching over 60% repression for most of the chosen genes as well as efficient deletion(>90%)of three target genes.Finally,this toolbox was used for the identification of crucial functional genes,involving growth,synthesis of important metabolites,and virulence of C.symbiosum ATCC 14940.Our work has effectively established and optimized genome editing methods in intestinal C.symbiosum,thereby providing strong support for further basic and application research in this bacterium.
文摘在开展数学教学时,因数学课件缺乏交互性,使得课件变成了课本的"投影展示",影响教学效果。概述了VBA语言及PowerPoint Control Toolbox,通过对高中数学"三视图"及"不等关系"等知识点使用PowerPoint Control Toolbox的组件进行交互设计,增强了数学课件的交互性。
文摘This paper presents a method for dynamically predicting gas emission quantity based on the wavelet neural network （WNN） toolbox. Such a method is able to predict the gas emission quantity in adjacent subsequent time intervals through training the WNN with even time-interval samples. The method builds successive new model with the width of sliding window remaining invariable so as to obtain a dynamic prediction method for gas emission quantity. Furthermore, the method performs prediction by a self-developed WNN toolbox. Experiments indicate that such a model can overcome the deficiencies of the traditional static prediction model and can fully make use of the feature extraction capability of wavelet base function to reflect the geological feature of gas emission quantity dynamically. The method is characterized by simplicity, flexibility, small data scale, fast convergence rate and high prediction precision. In addition, the method is also characterized by certainty and repeatability of the predicted results. The effectiveness of this method is confirmed by simulation results. Therefore, this method will exert practical significance on promoting the application of WNN.
