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Yue-Hua Guo,Fu-Rong Li,Shi-Yun Bao,Tao Han,Jun-Jian Cao,Han-Xin Zhou 한국물리학회 2007 Current Applied Physics Vol.7 No.s1
The present work is intended to set up the optimal carboplatin-Fe@C-loaded chitosan nanoparticles method and to compare andassess carboplatin-Fe@C-loaded with carboplatin-Fe-loaded chitosan nanoparticles. Both kinds of nanoparticles were prepared by areverse microemulsion method. The carboplatin-Fe@C-loaded chitosan nanoparticles consisted of Fe@C nanopowder with the adsorbeddrug as the magnetic core, chitosan as the matrix and carboplatin as the model drug. The core of the carboplatin-Fe-loaded chitosannanoparticles was pure iron nanopowder, which was unable to adsorb a drug. The characteristics of both kinds of nanoparticles weredetermined and compared. The results showed that both kinds of nanoparticles were spherical in shape with an average size of210 nm ± 26 nm (size range 150300 nm) and a good magnetic responsivity. The drug content of the nanoparticles wasrespectively. The cumulative release percentages of carboplatin-Fe@C-loaded chitosan nanoparticles in vitro in 1d, 2d, 3d, 4d were60%, 74%, 84%, and 92%, respectively, and those of carboplatin-Fe-loaded chitosan nanoparticles in 1d, 2d were 81% and 91%. Thus,the carboplatin-Fe@C-loaded chitosan nanoparticles with dual physical drug-loaded mechanisms (physical encapsulation and adsorp-tion of active carbon) possessed a higher drug content and showed more sustained releasing. The cooperation of multiple mechanismswas a promising feature to improve the properties of nanoparticles.
Yue-Hua Han,Wen-Zhong Liu,Yao-Zhou Shi,Li-Qiong Lu,Shudong Xiao,Qing-Hua Zhang,Guo-Ping Zhao 한국미생물학회 2007 The journal of microbiology Vol.45 No.1
In order to search for specific genotypes related to this unique phenotype, we used whole genomic DNA microarray to characterize the genomic diversity of Helicobacter pylori (H. pylori) strains isolated from clinical patients in China.The open reading frame (ORF) fragments on our microarray were generated by PCR using gene-specific primers. Genomic DNA of H. pylori 26695 and J99 were used as templates. Thirty-four H. pylori isolates were obtained from patients in Shanghai. Results were judged based on ln(x) transformed and normalized Cy3/Cy5 ratios. Our microarray included 1882 DNA fragments corresponding to 1636 ORFs of both sequenced H. pylori strains. Cluster analysis, revealed two diverse regions in the H. pylori genome that were not present in other isolates. Among the 1636 genes, 1091 (66.7%) were common to all H. pylori strains, representing the functional core of the genome. Most of the genes found in the H. pylori functional core were responsible for metabolism, cellular processes, transcription and biosynthesis of amino acids, functions that are essential to H. pylori’s growth and colonization in its host. In contrast, 522(31.9%) genes were strain-specific genes that were missing from at least one strain of H. pylori. Strainspecific genes primarily included restriction modification system components, transposase genes, hypothetical proteins and outer membrane proteins. These strain-specific genes may aid the bacteria under specific circumstances during their long-term infection in genetically diverse hosts. Our results suggest 34 H. pylori clinical strains have extensive genomic diversity. Core genes and strain-specific genes both play essential roles in H. pylori propagation and pathogenesis. Our microarray experiment may help select relatively significant genes for further research on the pathogenicity of H. pylori and development of a vaccine for H. pylori.
Gene Expression Profile of Helicobacter pylori in Response to Growth Temperature Variation
Yue-hua Han,Wen-zhong Liu,Yao-zhou Shi,Li-qiong Lu,Shu-dong Xiao,Qing-hua Zhang 한국미생물학회 2009 The journal of microbiology Vol.47 No.4
A Helicobacter pylori whole-genome DNA microarray was constructed to study expression profiles of H. pylori in response to a sudden temperature transfer from 37°C to 20°C. The expression level of the genome at each of four time points (15, 30, 60, and 120 min) after temperature downshift was compared with that just before cold treatment. Globally, 10.2% (n=167) of the total predicted H. pylori genes (n=1636) represented on the microarray were significantly differentially expressed (p<0.05) over a 120 min period after shift to low temperature. The expression profiles of the differentially expressed genes were grouped, and their expression patterns were validated by quantitative real-time PCR. Up-regulated genes mainly included genes involved in energy metabolism and substance metabolism, cellular processes, protein fate, ribosomal protein genes, and hypothetical protein genes, which indicate the compensational responses of H. pylori to temperature downshift. Those genes play important roles in adaption to temperature downshift of H. pylori. Down-regulation of DNA metabolism genes and cell envelope genes and cellular processes genes may reflect damaged functions under low temperature, which is unfavorable to bacterial infection and propagation. Overall, this time-course study provides new insights into the primary response of H. pylori to a sudden temperature downshift, which allow the bacteria to survive and adapt to the new host environment.
Yue-Hua Cheng,Bin Jiang,Huan Li,Xiao-dong Han 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.4
For the on-orbit reconfiguration problem of spacecraft attitude control systems under multi-mission constraints, the idea of a reinforcement-learning algorithm is adopted, and an adaptive dynamic programming algorithm for on-orbit reconfiguration decision-making that is based on a dual optimization index is proposed. Two optimization objectives, total mission reward and total control cost (energy consumption), are defined to obtain the optimal reconfiguration policy of the spacecraft attitude control system reconfiguration, and the on-orbit reconfiguration model for multi-mission constraints is established. Then, based on the Bellman optimality principle, the optimal reconfiguration policy formulated by the discrete HJB equation is obtained. Since the HJB equation is difficult to solve accurately, a method of bi-objective adaptive dynamic programming is proposed to obtain the optimal reconfiguration policy. This method constructs a mission network and an energy network. The method then adopts a Q-learning-based algorithm to train the networks to estimate the values of total mission reward and total control cost to achieve the on-orbit optimal reconfiguration decision under multi-mission constraints. Simulation results for different cases demonstrate the validity and rationality of the proposed method.