Link Clustering with Extended Link Similarity and EQ Evaluation Division.

Link Clustering (LC) is a relatively new method for detecting overlapping communities in networks. The basic principle of LC is to derive a transform matrix whose elements are composed of the link similarity of neighbor links based on the Jaccard distance calculation; then it applies hierarchical clustering to the transform matrix and uses a measure of partition density on the resulting dendrogram to determine the cut level for best community detection. However, the original link clustering method does not consider the link similarity of non-neighbor links, and the partition density tends to divide the communities into many small communities. In this paper, an Extended Link Clustering method (ELC) for overlapping community detection is proposed. The improved method employs a new link similarity, Extended Link Similarity (ELS), to produce a denser transform matrix, and uses the maximum value of EQ (an extended measure of quality of modularity) as a means to optimally cut the dendrogram for better partitioning of the original network space. Since ELS uses more link information, the resulting transform matrix provides a superior basis for clustering and analysis. Further, using the EQ value to find the best level for the hierarchical clustering dendrogram division, we obtain communities that are more sensible and reasonable than the ones obtained by the partition density evaluation. Experimentation on five real-world networks and artificially-generated networks shows that the ELC method achieves higher EQ and In-group Proportion (IGP) values. Additionally, communities are more realistic than those generated by either of the original LC method or the classical CPM method

Research on the Integrated Practical Teaching Model of Cross-border E-commerce Professional Knowledge and Innovation and Entrepreneurship Education

The development of cross-border e-commerce has stimulated a growing interest in related education. In response to this trend, a practical teaching approach that merges cross-border e-commerce expertise with innovation and entrepreneurship education has arisen and gained widespread traction. This innovative approach emphasizes the cultivation of students’ innovation skills and entrepreneurial ability through task-driven teaching that integrates professional knowledge and practical training. By participating in enterprise operations and completing assignments, students are able to master both theoretical knowledge and professional skills. This paper aims to explore the effectiveness of the task-driven teaching method in the integrated practical teaching of cross-border e-commerce and innovation and entrepreneurship. Practical suggestions for teaching reform in cross-border e-commerce are provided to meet the needs of application-oriented undergraduate colleges and to cultivate the application skills that enterprises require

Composite functional module inference: detecting cooperation between transcriptional regulation and protein interaction by mantel test

<p>Abstract</p> <p>Background</p> <p>Functional modules are basic units of cell function, and exploring them is important for understanding the organization, regulation and execution of cell processes. Functional modules in single biological networks (e.g., the protein-protein interaction network), have been the focus of recent studies. Functional modules in the integrated network are composite functional modules, which imply the complex relationships involving multiple biological interaction types, and detect them will help us understand the complexity of cell processes.</p> <p>Results</p> <p>We aimed to detect composite functional modules containing co-transcriptional regulation interaction, and protein-protein interaction, in our pre-constructed integrated network of <it>Saccharomyces cerevisiae</it>. We computationally extracted 15 composite functional modules, and found structural consistency between co-transcriptional regulation interaction sub-network and protein-protein interaction sub-network that was well correlated with their functional hierarchy. This type of composite functional modules was compact in structure, and was found to participate in essential cell processes such as oxidative phosphorylation and RNA splicing.</p> <p>Conclusions</p> <p>The structure of composite functional modules containing co-transcriptional regulation interaction, and protein-protein interaction reflected the cooperation of transcriptional regulation and protein function implementation, and was indicative of their important roles in essential cell functions. In addition, their structural and functional characteristics were closely related, and suggesting the complexity of the cell regulatory system.</p

A novel ZRS variant causes preaxial polydactyly type I by increased sonic hedgehog expression in the developing limb bud.

PurposePreaxial polydactyly (PPD) is a common congenital hand malformation classified into four subtypes (PPD I-IV). Variants in the zone of polarizing activity regulatory sequence (ZRS) within intron 5 of the LMBR1 gene are linked to most PPD types. However, the genes responsible for PPD I and the underlying mechanisms are unknown.MethodsA rare large four-generation family with isolated PPD I was subjected to genome-wide genotyping and sequence analysis. In vitro and in vivo functional studies were performed in Caco-2 cells, 293T cells, and a knockin transgenic mouse model.ResultsA novel g.101779T&gt;A (reference sequence: NG_009240.2; position 446 of the ZRS) variant segregates with all PPD I-affected individuals. The knockin mouse with this ZRS variant exhibited PPD I phenotype accompanying ectopic and excess expression of Shh. We confirmed that HnRNP K can bind the ZRS and SHH promoters. The ZRS mutant enhanced the binding affinity for HnRNP K and upregulated SHH expression.ConclusionOur results identify the first PPD I disease-causing variant. The variant leading to PPD I may be associated with enhancing SHH expression mediated by HnRNP K. This study adds to the ZRS-associated syndromes classification system for PPD and clarifies the underlying molecular mechanisms

消化内科护理风险及管理对策分析

Objective: To explore the common nursing risk in department of gastroenterology and clinical nursing management strategies, in order to provide the basis for nursing in the department of gastroenterology. Methods: Analyze and discuss of the common characteristics of nursing risk in our hospital department of gastroenterology, and summarize the countermeasure and method of correlation of risk management. The implementation of risk management as the observation group and the other as the control group, and clinical nursing effect between the two groups would be compared. Moreover, nursing ability improvement circumstance for the nursing staff was compared before and after the implementation of risk management. Results: The observation group after the risk management of nursing errors, medical disputes and the patients' satisfaction were better than the control group, there is statistical significance (P&lt; 0.05). After the risk management in Department of gastroenterology, nursing work of nursing staff in various digestive operation is proficient, medical record documents writing norms, communication ability, the emergency ability is superior before the implementation of risk management, there is statistical significance (P&lt;0.05). Conclusion: In the nursing management in the Department of gastroenterology, the implementation of risk management is helpful to improve the ability of nursing and the nursing quality, reduce nursing risk in Department of gastroenterology, and improve hospital patient satisfaction.目的  探讨消化内科中常见的护理风险以及临床护理管理对策，为消化内科的安全护理提供依据。方法  对本院消化内科常见的护理风险特点进行分析讨论，总结相关风险管理的对策与方法。将未实施风险管理作为对照组，实施风险管理为观察组，比较两组临床护理效果，并对护理人员实施风险管理前、后护理能力改善情况进行对比研究。结果  观察组实施风险管理后护理差错、医疗纠纷以及患者护理满意度方面均优于对照组，比较差异有显著性（P&lt;0.05），具有统计学意义。实施风险管理后护理人员对消化内科各种护理工作操作熟练程度，病历文书书写规范性，沟通能力，应急能力等方面均优于实施风险管理前，比较差异有显著性（P&lt;0.05），具有统计学意义。结论  在消化内科的护理管理中，实施风险管理有助于提高护理能力和护理质量，降低消化内科的护理风险，提高患者的满意度

REST: A Toolkit for Resting-State Functional Magnetic Resonance Imaging Data Processing

Resting-state fMRI (RS-fMRI) has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST). REST was developed in MATLAB with graphical user interface (GUI). After data preprocessing with SPM or AFNI, a few analytic methods can be performed in REST, including functional connectivity analysis based on linear correlation, regional homogeneity, amplitude of low frequency fluctuation (ALFF), and fractional ALFF. A few additional functions were implemented in REST, including a DICOM sorter, linear trend removal, bandpass filtering, time course extraction, regression of covariates, image calculator, statistical analysis, and slice viewer (for result visualization, multiple comparison correction, etc.). REST is an open-source package and is freely available at http://www.restfmri.net