Rebuilding motor function of the spinal cord based on functional electrical stimulation

Rebuilding the damaged motor function caused by spinal cord injury is one of the most serious challenges in clinical neuroscience.The function of the neural pathway under the damaged sites can be rebuilt using functional electrical stimulation technology.In this study,the locations of motor function sites in the lumbosacral spinal cord were determined with functional electrical stimulation technology.A three-dimensional map of the lumbosacral spinal cord comprising the relationship between the motor function sites and the corresponding muscle was drawn.Based on the individual experimental parameters and normalized coordinates of the motor function sites,the motor function sites that control a certain muscle were calculated.Phasing pulse sequences were delivered to the determined motor function sites in the spinal cord and hip extension,hip flexion,ankle plantarflexion,and ankle dorsiflexion movements were successfully achieved.The results show that the map of the spinal cord motor function sites was valid.This map can provide guidance for the selection of electrical stimulation sites during the rebuilding of motor function after spinal cord injury.

DeepNitro: Prediction of Protein Nitration and Nitrosylation Sites by Deep Learning

Protein nitration and nitrosylation are essential post-translational modifications （PTMs）involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are linked to numerous chronic diseases.Therefore, the identification of substrates that undergo such modifications in a site-specific manner is an important research topic in the community and will provide candidates for targeted therapy. In this study, we aimed to develop a computational tool for predicting nitration and nitrosylation sites in proteins. We first constructed four types of encoding features, including positional amino acid distributions, sequence contextual dependencies, physicochemical properties, and position-specific scoring features, to represent the modified residues. Based on these encoding features, we established a predictor called DeepNitro using deep learning methods for predicting protein nitration and nitrosylation. Using n-fold cross-validation, our evaluation shows great AUC values for DeepNitro, 0.65for tyrosine nitration, 0.80 for tryptophan nitration, and 0.70 for cysteine nitrosylation, respectively,demonstrating the robustness and reliability of our tool. Also, when tested in the independent dataset, DeepNitro is substantially superior to other similar tools with a 7%à42%improvement in the prediction performance. Taken together, the application of deep learning method and novel encoding schemes, especially the position-specific scoring feature, greatly improves the accuracy of nitration and nitrosylation site prediction and may facilitate the prediction of other PTM sites. DeepNitro is implemented in JAVA and PHP and is freely available for academic research at http：//deepnitro.renlab.org.

Recent strategies to improve the electroactivity of metal-organic frameworks for advanced electrocatalysis

Metal-organic frameworks(MOFs)have emerged as promising materials in the realm of electrocatalysis due to their high surface area,tunable porosity,and versatile chemical functionality.However,their practical application has been hampered by inherent limitations such as low electrical conductivity and a limited number of active metal sites.Researchers addressed these challenges through various strategies,including enhancing conductivity by incorporating conductive materials and metal nanoparticles,modifying the structure and composition of MOFs by replacing metal nodes and functionalizing linkers,and preparing MOFs catalysts through thermal processes such as decarburization and con-version into metal oxides,phosphides(MPs),and sulfides(MSs).This review provided a comprehensive summary of the strategies that were employed to enhance the electroactivity of MOFs for improved electrocatalytic performance in recent years.It also explored future directions and potential innovations in the design and synthesis of MOF‐based electrocatalysts,offering valuable insights for advancing their application in sustainable energy technologies.

Metal-Decorated Porous Organic Polymers:Bridged the Gap between Organic and Inorganic Scaffolds

Comprehensive Summary Advanced functionalization-decorated porous organic polymers(POPs)are emerging as a prominent research focus,spanning from their construction to applications in gas storage and separation,catalysis,energy storage,electrochemistry,and other areas.Furthermore,the inherent organic nature,tailored pore structures,and adjustable chemical components of POPs offer a versatile platform for the incorporation of various metal active sites.Meticulously designed molecular building blocks can serve as organic ligands uniformly distributed throughout POPs,leading to the effective isolation of inorganic metal active sites at the molecular level.In this manner,POPs containing active metal centers bridge the gap between organic and inorganic scaffolds.This review aims to provide an overview of recent research progress on metal-decorated POPs,focusing on strategies for incorporating metal active sites into POPs and their applications in adsorption,separation,catalysis,and photoelectrochemistry.Finally,current challenges and future prospects are discussed for further research.

A unique 3D microporous MOF constructed by cross-linking 1D coordination polymer chains for effectively selective separation of CO_(2)/CH4 and C_(2)H_(2)/CH_(4)

Selective separation of CO_(2)/CH_(4)and C2 H_(2)/CH_(4)are promising for their high-purity industrial demand and scientific research on account of the similar molecular radius and physical properties.In this work,a unique 3 D microporous MOF material[Cu(SiF6)(sdi)2]·solvents(1,sdi=1,1’-sulfonyldiimidazole)was successfully constructed by cross-linking 1 D coordination polymer chains.The dense functional active sites on the inner walls of the channel of la can provide strong binding affinities to CO_(2),C2 H_(2),and thus effectively improve the gas separation performance of CO_(2)/CH_(4)and C2 H_(2)/CH_(4).

Impact of Web Site Functions on E-Business Success in Chinese Wholesale and Retail Industries

Web sites are very important and companies can attract customers by promoting various features of the web site. This paper presents an analysis of the relationship between web site functions and firm performance. A research model based on the DeLone and McLean （D＆M） model and customer service life cycle （CSLC） theory was used to investigate the impact of web site functions on e-business success. The research model considers web site functions, web site use, customer satisfaction, and firm performance. According to the CSLC theory, there are three stages in a customer service life cycle. Therefore, the web site functions are divided into three stages： requirements, acquisition, and ownership. The functions in each stage serve to encourage usage and thus, enhance customer satisfaction and firm performance. The theoretical model and hypotheses were tested using data collected from 72 wholesale and retail firms in China using the partial least squares （PLS） method. The results suggest that web site functions in the acquisition stage have the strongest impact on web site use and that the improvement of customer satisfaction can significantly increase firm performance.

Paralog-divergent Features May Help Reduce Off-target Effects of Drugs:Hints from Glucagon Subfamily Analysis

Side effects from targeted drugs remain a serious conccrn. One reason is the nonselective binding of a drug to unintended proteins such as its paralogs, which arc highly homologous in sequences and have similar structures and drug-binding pockets. To identify targctablc differences between paralogs, we analyzed two types （type-I and type-ll） of functional divergence between two paralogs in the known target protein receptor family G-protein coupled receptors （GPCRs） at the amino acid level. Paralogous protein receptors in glucagon-like subfamily, glucagon receptor （GCGR） and glucagon-like peptide-I receptor （GLP-I R）, exhibit divergence in ligands and are clinically validated drug targets for type 2 diabetes. Our data showed that type-ll alnino acids were significantly enriched in the binding sites of antagonist MK-0893 to GCGR. which had a radical shift in physicochemical properties between GCGR and GLP-1R. We also examined the role of type-I amino acids between GCGR and GLP-IR. The divergent features between GCGR and GLP-I R paralogs may be helpful in their discrimination, thus enabling the identification of binding sites to reduce undesirable side effects and increase the target specificity of drugs.

Scale,Site Selection and Function of Economic and Technological Development Zones

This article analyses different characteristics of scale,site selection and function of the current economic andtehnological development zones in our country.It further proposes that it is inappropriate for the economic andtechnological development zones to follow the“pattern of the special zones”,but a new pattern of“small scale,unitaryfunction and closeness to old city”should be adopted to fit in with the practical conditions in our country.The scale,landuse structure and the relations between the development zone and the old city are the basic issues in planning forthe development zones.These three essential elements constitute the pattern of planning which determines to a certainextent the success or failure of the development zones.