ANXA2 enhances the progression of hepatocellular carcinoma via remodeling the cell motility associated structures

Hepatocellular carcinoma (HCC) ranks as the fifth most common malignancy worldwide. The detailed mechanism of signal regulation for HCC progression is still not known, and the high motility of cancer cells is known as a core property for cancer progression maintenance. Annexin A2 (ANXA2), a calcium-dependent phospholipids binding protein is highly expressed in HCC. To study the roles the excessively expressed ANXA2 during the progression of HCC, we inhibited the ANXA2 expression in SMMC-7721 cells using RNAi, followed by the analysis of cell growth, apoptosis and cell motility. To explore the relationship between the cell behaviors and its structures, the microstructure changes were observed under fluorescence microscopy, laser scanning confocal microscopy and electron microscopy. Our findings demonstrated that down-regulation of ANXA2 results in decreased the cell proliferation and motility, enhanced apoptosis, suppressed cell pseudopodia/filopodia, inhibited expression of F-actin and β-tubulin, and inhibited or depolymerized Lamin B. The cell contact inhibition was also analyzed in the paper. Take together, our results indicate that ANXA2 plays an important role to enhance the malignant behaviors of HCC cells, and the enhancement is closely based on its remodeling to cell structures.     

金属配合物作为核酸释放的载体

基因治疗是指利用一种载体将健康的基因载入细胞替换致病的基因.由基因缺陷导致的人类疾病达1200多种,最合理的选择是采用基因替换的方法进行治疗.基因治疗的关键问题是解决"使用何种载体才能安全有效地将治疗基因载入靶细胞".非病毒基因载体主要是一些有机阳离子物种,一直受到极大重视;近年来,磷酸钙、纳米粒子和金属配合物释放核酸的功能也开始受到关注.本文总结了金属配合物作为非病毒基因载体使用的研究进展,希望由此理解配合物释放核酸的优势和不足之处.     

Dendritic polyglycerol with secondary amine shell as an efficient gene delivery vector with reduced toxicity

Dendritic polycation (PG‐BEN) using polyglycerol as a core and secondary amine shell consisting of N¹,N¹¹‐bisethylnorspermine (BEN) was synthesized. Polymers containing primary amines in the shell (PG‐Nor and PG‐NH₂) were synthesized as controls to allow evaluation of the shell effect on physicochemical and transfection properties of the polymers. All studied polymers condensed DNA and formed polyplexes with sizes less than 110 nm. PG‐BEN and PG‐Nor had a similar transfection activity that was fully comparable with that of the control polyethylenimine. Amongst the studied polymers, PG‐BEN demonstrated the lowest cytotoxicity, suggesting that PG‐BEN is a promising gene delivery vector with favorable transfection/toxicity profile. Copyright © 2014 John Wiley & Sons, Ltd.     

Phospholipid–Detergent Conjugates as Novel Tools for siRNA Delivery

One of the potential benefits of drug delivery systems in medicine is the creation of nanoparticle‐based vectors that deliver a therapeutic cargo in sufficient quantity to a target site to enable a selective effect, width of the therapeutic window depending on the toxicity of the vector and the cargo. In this work, we intended to improve the siRNA delivery efficiency of a new kind of nucleic acid carrier, which is the result of the conjugation of the membrane phospholipid 1,2‐dioleoyl‐sn‐glycero‐3‐phosphocholine (DOPC) to the membrane‐active species Triton X‐100 (TX100). We hypothesized that by improving the biodegradability the cytotoxicity of the conjugate might by reduced, whereas its original transfection potential would be tentatively preserved. DOPC was conjugated to Triton X‐100 through spacers displaying various resistance to chemical hydrolysis and enzyme degradation. The results obtained through in vitro siRNA delivery experiments showed that the initial phosphoester bond can be replaced with a phospho(alkyl)enecarbonate group with no loss in the transfection activity, whereas the associated cytotoxicity was significantly decreased, as assessed by metabolic activity and membrane integrity measurements. The toxicity of the conjugates incorporating a phospho(alkyl)enesuccinnate moiety proved even lower but was clearly balanced with a reduction of the siRNA delivery efficiency. Hydrolytic stability and intracellular degradation of the conjugates were investigated by NMR spectroscopy and mass spectrometry. A general trend was that the more readily degraded conjugates were those with the lower toxicity. Otherwise, the phospho(alkyl)enecarbonate conjugates revealed some hemolytic activity, whereas the parent phosphoester did not. The reason why these conjugates behave differently with respect to hemolysis might be a consequence of unusual fusogenic properties and probably reflects the difference in the stability of the conjugates in the intracellular environment.     

Effect of Terbinafin and DMSO on The Gene Expression Level of Squalene Synthase (Sqs) and Amorpha-4,11-Diene Synthase (Ads) in Artemisia Annua L

Artemisinin, a secondary metabolite from Artemisia annua L. is a sesquiterpene lactone that has antimalaria activity but produced at low quantities by the plant. Low levels of artemisinin in the plant is related to the biosynthetic pathways influenced by specific enzymes that play role in the formation of artemisinin. Farnesyl diphosphate (FDP), which is the main precursor of artemisinin, also known as the precursor for the formation of sterols. Compared with the other compounds, sterol biosynthetic pathway is the biggest competitor of the artemisinin production since sterols are needed by plants to regulate membrane fluidity and permeability. This research aimed to study the effect of terbinafin and DMSO as sterol synthesis inhibitors on the regulation of the artemisinin biosynthetic pathway by analyzing the expression level of two genes linked, squalene synthase (SQS) and amorpha-4,11-diene synthase (ADS) using quantitative PCR (qPCR) and the amount of artemisinin is determined using high performance liquid chromatography (HPLC). The results showed that at mRNA levels, terbinafin 30 μM had no significant effect on SQS and ADS expression levels, but it increased the amount of artemisinin at 50 hours incubation up to 1.36 times higher than control. DMSO increased the expression level of ADS up to 3-4 times and increased the content of artemisinin up to 2.42 times higher than control at 50 hours incubation time     

Clustering gene expression data analysis using an improved EM algorithm based on multivariate elliptical contoured mixture models

Clustering gene expression data is an important research topic in bioinformatics because knowing which genes act similarly can lead to the discovery of important biological information. Many clustering algorithms have been used in the field of gene clustering. The multivariate Gaussian mixture distribution function was frequently used as the component of the finite mixture model for clustering, however the clustering cannot be restricted to the normal distribution in the real dataset. In order to make the cluster algorithm strong adaptability, this paper proposes a new scheme for clustering gene expression data based on the multivariate elliptical contoured mixture models (MECMMs). To solve the problem of over-reliance on the initialization, we propose an improved expectation maximization (EM) algorithm by adding and deleting initial value for the classical EM algorithm, and the number of clusters can be treated as a known parameter and inferred with the QAIC criterion. The improved EM algorithm based on the MECMMs is tested and compared with some other clustering algorithms, the performance of our clustering algorithm has been extensively compared over several simulated and real gene expression datasets. Our results indicated that improved EM clustering algorithm is superior to the classical EM algorithm and the support vector machines (SVMs) algorithm, and can be widely used for gene clustering.     

Clustering approaches for dealing with multiple DNA microarray datasets

This paper centres on clustering approaches that deal with multiple DNA microarray datasets. Four clustering algorithms for deriving a clustering solution from multiple gene expression matrices studying the same biological phenomenon are considered: two unsupervised cluster techniques based on information integration, a hybrid consensus clustering method combining Particle Swarm Optimization and k-means that can be referred to supervised clustering, and a supervised consensus clustering algorithm enhanced by Formal Concept Analysis (FCA), which initially produces a list of different clustering solutions, one per each experiment and then these solutions are transformed by portioning the cluster centres into a single overlapping partition, which is further analyzed by employing FCA. The four algorithms are evaluated on gene expression time series obtained from a study examining the global cell-cycle control of gene expression in fission yeast Schizosaccharomyces pombe.     

A Novel DNA‐Enrichment Technology Based on Amino‐Modified Functionalized Silica Nanoparticles

Abstract

In this paper we report a novel DNA‐enrichment technology based on amino‐modified functionalized silica nanoparticles. The approach takes advantage of the amino‐modified silica nanoparticles that have been prepared in one step by the controlled synchronous hydrolysis of tetraethoxysilane and N‐(β‐amimoethyl)‐γ‐aminopropyltriethoxysilane in water nanodroplets of water‐in‐oil microemulsions. The functionalized silica nanoparticles display a positive surface charge at neutral pH due to the presence of amino groups on the surface of these nanoparticles. DNA‐enrichment has been realized in the form of nanoparticle–DNA complexes that is accomplished through electrostatic binding between the positive charge of the amino group and the negative charge of the phosphate groups of the nucleic acid. These nanoparticles have high affinity to bind DNA. The results show that 1 mg of nanoparticles can bind 97.2 µg of plasmid DNA with 4.3 kb. This novel DNA‐enrichment technology has been used successfully in gene delivery.