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目的在“心与小肠相表里”中医理论指导下，探讨阿尔茨海默病（AD）模型小鼠全肠道菌群移植，是否对正常小鼠回肠肠道微环境的影响更显著。方法将14只6月龄无特定病原体的雄性APP/PS1双转基因AD模型小鼠的全肠道菌群，移植至6只混合抗生素处理过的同月龄同背景正常C57BL/6J小鼠肠道内，移植14 d后再定殖14 d，观察小鼠回肠和结肠组织病理变化，并采用16S核糖体RNA（16S rRNA）基因测序技术分析小鼠回肠和结肠菌群。结果AD小鼠全肠道菌群移植到正常小鼠后，病理分析表明仅回肠组织出现粘膜层破坏和隐窝腺上皮细胞变性、坏死脱落；测序分析发现，仅回肠菌群的种类数量（PPP

BACKGROUND: Several studies have found that the total flavonoids of rhizome drynariae can promote neovascularization in the induced membrane, improve the biological properties of the induced membrane, and accelerate bone remodeling in the induced membrane, but the related molecular mechanisms still need to be further explored. OBJECTIVE: To explore the effect of total flavonoids of rhizome drynariae on bone remodeling in rat femoral Masquelet-induced membrane model by regulating H-type blood vessels. METHODS: Thirty-six male Sprague-Dawley rats were stratified by body mass and then randomly divided into blank group, model group and traditional Chinese medicine group, with 12 rats in each group. A 4-mm femoral bone defect model was established in all the rats. Bone defects in the model group and traditional Chinese medicine group were filled with polymethylmethacrylate bone cement. At 6 weeks after modeling, the tail bone of the rats was implanted in the blank group, as well as in the other two groups after removal of bone cement. The traditional Chinese medicine group was given 157.5 mg/kg per day of total flavonoids of rhizome drynariae at 3 days after bone implantation, while the model and blank groups were given the same amount of saline by gavage until the 8th week after bone implantation. Bone graft samples were taken for relevant testing at 8 weeks after implantation. RESULTS AND CONCLUSION: X-ray films showed that in the blank group, the fracture line in the defect area was clear, and only a small amount of bone callus formed; in the model group, the bone defect area still existed, where discontinuous cortical bone was visible; in the traditional Chinese medicine group, the defect area was filled with newborn bone tissues, the bone marrow cavity and part of the cortical bone formed, and the fracture line disappeared. Micro-CT scans showed that the amount of new bone in the defect area was low in the blank group, the number of bone trabeculae in the defect area was significantly increased in the model group, and a large amount of new bone tissue was filled in the bone defect area in the traditional Chinese medicine group. Hematoxylin-eosin staining results showed that in the blank group, only a small amount of new bone formed in the defect area and the quality of osteogenesis was poor; in the model group, there was more new bone tissue in the defect area, but some fibrous connective tissues were interspersed within the bone tissue; and in the traditional Chinese medicine group, a large amount of new bone formed in the defect area and the quality of osteogenesis was the best. CD31/Emcn immunofluorescence double-labeling staining results showed that the number of H-type blood vessels in the newborn bone tissue in the bone defect area of the blank group was sparse and sparsely distributed; compared with the blank group, there were more H-type blood vessels in the bone tissue in the bone defect area of the model group, and the blood vessels were distributed in relatively regular strips; the number of H-type blood vessels in the bone defect area of the traditional Chinese medicine group was the highest and the blood vessels were densely distributed. To conclude, the total flavonoids of rhizoma drynariae can upregulate the expression of H-type blood vessels to enhance the angiogenic-osteogenic effect, improve the osteogenic efficiency of the rat femoral Masquelet induced membrane model, and promote bone remodeling. [ABSTRACT FROM AUTHOR]

The optimization of imaging reconnaissance constellation is of great significance for reconnaissance timeliness. At present, evolutionary algorithms based on Pareto are often used in the optimization of reconnaissance constellation. In order to solve the problems of insufficient selection pressure and poor diversity of such algorithms in the optimization of reconnaissance constellation whose objective function dimension is greater than three, the improved particle swarm optimization algorithm based on relative entropy of fuzzy sets(IFREM-PSO) is proposed. The algorithm improves the adaptive inertial weight strategy and enhances the convergence speed and accuracy. The introduction of variation strategy is conducive to jumping out of the local optimal solution. Improve external archive maintenance policy to enhance diversity. Based on the design and optimization of regional target-oriented visible light reconnaissance constellation, MOPSO, FREM-PSO and the IFREM-PSO are used to optimize the reconnaissance constellation. The experimental results show that the algorithm based on fuzzy relative entropy has a better performance in this problem, and compared with FREM-PSO algorithm, IFREM-PSO algorithm has a significant improvement in convergence speed, and a better performance in convergence effect and diversity. [ABSTRACT FROM AUTHOR]

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Copyright of Chinese Journal of Tissue Engineering Research / Zhongguo Zuzhi Gongcheng Yanjiu is the property of Chinese Journal of Tissue Engineering Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: To identify characteristic genes of rheumatoid arthritis （RA） by artificial neural network and to analyze role of immune cells in RA related microenvironment. Methods: GSE1919 and GSE77298 chips were from GEO database. Two chips were combined and batch corrected using R language to obtain a new data set, and difference was analyzed. Metascape enrichment analysis and GO and KEGG enrichment analysis were conducted for differential expressed genes （DEGs）. "randomForest" package in R software was used to screen characteristic genes of RA under random forest （RF） algorithm, and artificial neural network model was constructed according to gene score. Top 4 genes （HubGene） were extracted for subsequent analysis. Single sample gene set enrichment analysis （ssGSEA） was used to calculate abundance of immune cells in samples and carry out a series of correlation analysis. Results: Top 15 genes were selected as characteristic genes of RA through artificial neural network model: STAT1, RUNX3, AR, CDH11, LMO4, TIMP1, PLXNC1, CAP2, PRKAA2, VDR, SPP1, HCK, EPHB2, KCNAB1, ITGB7. STAT1, RUNX3 and CDH11 were up-regulated in RA synovial tissue, while AR was down-regulated in RA synovial tissue. Immune cell infiltration results showed that RA had the most significant correlation with activated CD4 T cells. Number of immune cells significantly related to RUNX3 was the largest. RUNX3 was significant positive correlated with activated B cells, activated CD4 T cells, activated CD8 T cells, central memory CD4+T cells, effector memory CD8 T cells, regulatory T cells, γδT cells and macrophages, while significant negative correlated with NK cells. Conclusion: Fifteen characteristic genes related to RA are identified through artificial neural network, among which STAT1, RUNX3, AR and CDH11 are top 4 genes. It emphasizes activation of CD4 T cells, regulatory T cells, γδT cells, macrophages, NK cells, activated B cells and other immune cells are important in pathogenesis of RA, providing new insights for diagnosis of RA and study of molecular mechanism of immune cells. [ABSTRACT FROM AUTHOR]

"Demand traction, technology promotion" is the main rule of the development of equipment system construction. This paper focuses on the analysis of system requirements, and puts forward the process of system requirements analysis on the basis of analyzing the basic connotation of system requirements analysis, combining the advantages of threat and capability; aiming at the key technical problems such as capability gap measurement and mapping analysis in system requirements analysis. The capacity gap measurement model is established, and the QFD method is used to realize the mapping between the capability requirement-system requirement-technology requirement, and the analysis of the typical space target monitoring system is taken as an example to verify the system demand analysis method proposed in this paper, which provides a theoretical basis for carrying out the system demand analysis. [ABSTRACT FROM AUTHOR]

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BACKGROUND: The repair of critical size bone defects has always been a challenge clinical problem for trauma orthopedic surgeons. With the development of clinical techniques and biomaterials, Ilizarov, Masquelet and bone tissue engineering techniques are gradually replacing the traditional autologous and allogeneic bone transplantation to become the research hotspots in the field of bone repair. Among them, bone tissue engineering scaffolds have the greatest potential for development. But a lot of basic research is necessary before the formal clinical application of bone tissue engineering scaffolds, and animal experiments are the most important. Therefore, it is very important to select an appropriate animal model of critical bone defects for testing the osteogenic efficacy of bone tissue engineering scaffolds. OBJECTIVE: To systematically summarize the advantages and disadvantages of different types of animal models of critical bone defects and to evaluate the osteogenic efficacy of various types of bone tissue engineering scaffolds in the animal models of critical bone defects. METHODS: CNKI, WanFang, Web of Science, Cochrane Library, and PubMed were searched for relevant literature. Search terms included “bone defects, animal models, bone tissue engineering, scaffolds, bone repair, bone regeneration” in Chinese and English. A total of 62 articles addressing the animal models of critical bone defects and their application to evaluate the osteogenic efficacy of bone tissue engineering scaffolds were included for further review. RESULTS AND CONCLUSION: The specific definition of critical bone defects is still unclear and there is no consensus on how to establish critical defects in various animal models of bone defects. By searching the published articles about the establishment of critical bone defect animal models in mice, rats, rabbits, pigs, dogs and sheep, we found that domestic and foreign scholars basically followed the principle that the size of the bone defect that could be not self-healing during the experimental period is selected when establishing the critical bone defect model, but there were differences in the specific values. In general, rat skull, femur and rabbit femoral condyles are the more suitable sites for critical bone defect models, which are suitable for large-scale modeling because of their wide sources, low requirement of experimental environment, easy breeding, low modeling cost, and high operability. However, compared with large animals such as sheep and pigs, they have the disadvantages of small bones and the composition of bone tissue is different from that of human, which makes it difficult to fully simulate the human bone healing process. After the biocompatibility and osteogenic activity of the bone tissue engineering scaffolds are evaluated by cytological experiments, its osteogenic efficiency and biological safety in vivo can be confirmed with the help of the stable animal model of critical bone defects. The critical bone defect models of rat skull and femur and rabbit femoral condyle are respectively suitable for the preliminary evaluation of intramembranous osteogenesis and endochondral osteogenesis, while the critical bone defect models of sheep and pig tibia are ideal animal models that are recommended for preclinical evaluation. Further research on the molecular mechanism of bone tissue engineering scaffold osteogenesis is expected to help develop artificial scaffold materials that can match the osteogenesis efficiency of autogenous bone, which is of great significance for overcoming the difficult clinical problem of segmental bone defects. [ABSTRACT FROM AUTHOR]

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Aiming at the problem that LF ant colony clustering algorithm does not distinguish the importance of data set attributes, the algorithm efficiency is low and the clustering effect is unstable, this paper proposed a weighted global memory ant colony optimization (WGACO) based on entropy weight. Firstly, it calculated the entropy weight of each attribute by entropy weight method, and modified the Euclidean distance calculation formula to improve the clustering accuracy. It initialized the data object with the value of the largest weight attribute to enhance the stability of the clustering effect, and introduced the global memory matrix to reduce the invalid movement of ants and improve the efficiency of the algorithm. It added the convergence conditions of the algorithm to improve the practicability of the algorithm. Selecting seven real data sets and three artificially generated data sets in UCI database for numerical experiments, and compared WGACO with GMACO,SMACC and ILFACC three improved LF algorithms. The experimental results show that WGACO has a relatively good improvement in accuracy, algorithm efficiency and stability, and also has a good performance in processing high-dimensional data. Finally, WGACO has performed well in the segmentation of mall member users, reflecting its practical value. [ABSTRACT FROM AUTHOR]

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In order to solve the problem of dynamic evaluation of operational effectiveness of space-based information support equipment system, this paper presents a method of operational effectiveness evaluation of space-based information support equipment system based on dynamic Bayesian network. Firstly, the data samples are obtained by the operational effectiveness evaluation model of system dynamics, then the dynamic network is established based on the static Bayesian network operational effectiveness evaluation model, and the dynamic Bayesian network operational effectiveness evaluation model is established by EM parameter learning algorithm. Finally, the operational effectiveness of space-based information support equipment system is analyzed. Through this model, the relationship and influence degree of many influencing factors in the space- based information support equipment system are deeply analyzed in the battle scenario of attacking moving ship targets in the sea direction. At the same time, simulation experiments verify the effectiveness and feasibility of this method in the operational effectiveness evaluation of space-based information support equipment system, which can provide solid technical support for the operational effectiveness evaluation of space-based information support equipment system. [ABSTRACT FROM AUTHOR]

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