Flexible Cationic Nanoparticles with Photosensitizer Cores for Multifunctional Biomedical Applications

One challenge for multimodal therapy is to develop appropriate multifunctional agents to meet the requirements of potential applications. Photodynamic therapy (PDT) is proven to be an effective way to treat cancers. Diverse polycations, such as ethylenediamine‐functionalized poly(glycidyl methacrylate) (PGED) with plentiful primary amines, secondary amines, and hydroxyl groups, demonstrate good gene transfection performances. Herein, a series of multifunctional cationic nanoparticles (PRP) consisting of photosensitizer cores and PGED shells are readily developed through simple dopamine‐involving processes for versatile bioapplications. A series of experiments demonstrates that PRP nanoparticles are able to effectively mediate gene delivery in different cell lines. PRP nanoparticles are further validated to possess remarkable capability of combined PDT and gene therapy for complementary tumor treatment. In addition, because of their high dispersities in biological matrix, the PRP nanoparticles can also be used for in vitro and in vivo imaging with minimal aggregation‐caused quenching. Therefore, such flexible nanoplatforms with photosensitizer cores and polycationic shells are very promising for multimodal tumor therapy with high efficacy.     

Peptidyl Virus-Like Nanovesicles as Reconfigurable “Trojan Horse” for Targeted siRNA Delivery and Synergistic Inhibition of Cancer Cells

The self-assembly of peptidyl virus-like nanovesicles (pVLNs) composed of highly ordered peptide bilayer membranes that encapsulate the small interfering RNA (siRNA) is reported. The targeting and enzyme-responsive sequences on the bilayer's surface allow the pVLNs to enter cancer cells with high efficiency and control the release of genetic drugs in response to the subcellular environment. By transforming its structure in response to the highly expressed enzyme matrix metalloproteinase 7 (MMP-7) in cancer cells, it helps the siRNA escape from the lysosomes, resulting in a final silencing efficiency of 92%. Moreover, the pVLNs can serve as reconfigurable “Trojan horse” by transforming into membranes triggered by the MMP-7 and disrupting the cytoplasmic structure, thereby achieving synergistic anticancer effects and 96% cancer cell mortality with little damage to normal cells. The pVLNs benefit from their biocompatibility, targeting, and enzyme responsiveness, making them a promising platform for gene therapy and anticancer therapy.     

碳酸双（三氯甲酯）的合成和应用

综述了碳酸双（三氯甲酯）（ＢＴＣ）的制法、性质及其应用。     

Clustering of temporal gene expression data by regularized spline regression and an energy based similarity measure

Clustering analysis of temporal gene expression data is widely used to study dynamic biological systems, such as identifying sets of genes that are regulated by the same mechanism. However, most temporal gene expression data often contain noise, missing data points, and non-uniformly sampled time points, which imposes challenges for traditional clustering methods of extracting meaningful information. In this paper, we introduce an improved clustering approach based on the regularized spline regression and an energy based similarity measure. The proposed approach models each gene expression profile as a B-spline expansion, for which the spline coefficients are estimated by regularized least squares scheme on the observed data. To compensate the inadequate information from noisy and short gene expression data, we use its correlated genes as the test set to choose the optimal number of basis and the regularization parameter. We show that this treatment can help to avoid over-fitting. After fitting the continuous representations of gene expression profiles, we use an energy based similarity measure for clustering. The energy based measure can include the temporal information and relative changes of the time series using the first and second derivatives of the time series. We demonstrate that our method is robust to noise and can produce meaningful clustering results.     

基于单调邻域粗糙集的特征基因提取

为了避免连续数据离散化处理时造成的信息损失,降低样本属性邻域求解的复杂度,提高特征基因提取的效率。该文在单调度量空间上,提出了一种基于单调邻域粗糙集的特征基因提取方法。并在两个标准的基因表达数据上进行了实验,结果证明该方法是有效可行的。     

Cascade of genetic algorithm and decision tree for cancer classification on gene expression data

Abstract: Cancer classification, through gene expression data analysis, has produced remarkable results, and has indicated that gene expression assays could significantly aid in the development of efficient cancer diagnosis and classification platforms. However, cancer classification, based on DNA array data, remains a difficult problem. The main challenge is the overwhelming number of genes relative to the number of training samples, which implies that there are a large number of irrelevant genes to be dealt with. Another challenge is from the presence of noise inherent in the data set. It makes accurate classification of data more difficult when the sample size is small. We apply genetic algorithms (GAs) with an initial solution provided by t statistics, called t‐GA, for selecting a group of relevant genes from cancer microarray data. The decision‐tree‐based cancer classifier is built on the basis of these selected genes. The performance of this approach is evaluated by comparing it to other gene selection methods using publicly available gene expression data sets. Experimental results indicate that t‐GA has the best performance among the different gene selection methods. The Z‐score figure also shows that some genes are consistently preferentially chosen by t‐GA in each data set.     

miRNA检测技术进展

miRNA做为一种非常重要的非编码蛋白的RNA.广泛存在于植物、病毒、哺乳动物当中.因其在细胞增殖、细胞死亡、肿瘤发生和哺乳动物细胞生长中重要的调节功能,其检测技术也受到越来越多的关注,很多关键的检测技术,比如印迹技术,阵列杂交技术,反转录PCR技术等等都在miRNA的检测中发挥了巨大的实用价值.该文基于此对miRNA近几年的检测技术进行了具体的综述.     

基于弹簧模型的基因表达数据可视化聚类

依据基因表达数据的特点,提出一种基于弹簧模型的基因表达数据可视化聚类方法,将多维空间的基因表达数据映射到二维空间中,较好地保持了原始多维数据间的时空相似性。实验结果表明,该方法能发现基因表达数据集中隐含的类簇结构以及共表达基因模式。