Core-Shell Assisted Bimetallic Assembly of Pt and Ru Nanoparticles by DNA Hybridization

We have discovered that the current protocols to assemble Au nanoparticles based on DNA hybridization do not work well with the small metal nanoparticles (e.g. 5 nm Au, 3.6 nm Pt and 3.2 nm Ru particles). Further investigations revealed the presence of strong interaction between the oligonucleotide backbone and the surface of the small metal nanoparticles. The oligonucleotides in this case are recumbent on the particle surface and are therefore not optimally oriented for hybridization. The nonspecific adsorption of oligonucleotides on small metal nanoparticles must be overcome before DNA hybridization can be accepted as a general assembly method. Two methods have been suggested as possible solutions to this problem. One is based on the use of stabilizer molecules which compete with the oligonucleotides for adsorption on the metal nanoparticle surface. Unfortunately, the reported success of this approach in small Au nanoparticles (using K₂BSPP) and Au films (using 6-mercapto-1-hexanol) could not be extended to the assembly of Pt and Ru nanoparticles by DNA hybridization. The second approach is to simply use larger metal particles. Indeed most reports on the DNA hybridization induced assembly of Au nanoparticles have made use of relatively large particles (>10 nm), hinting at a weaker non-specific interaction between the oligonucleotides and large Au nanoparticles. However, most current methods of nanoparticle synthesis are optimized to produce metal nanoparticles only within a narrow size range. We find that core-shell nanoparticles formed by the seeded growth method may be used to artificially enlarge the size of the metal particles to reduce the nonspecific binding of oligonucleotides. We demonstrate herein a core-shell assisted growth method to assemble Pt and Ru nanoparticles by DNA hybridization. This method involves firstly synthesizing approximately 16 nm core-shell Ag-Pt and 21 nm core-shell Au-Ru nanoparticles from 9.6 nm Ag seeds and 17.2 nm Au seeds respectively by the seed-mediated growth method. The core-shell nanoparticles were then functionalized by complementary thiolated oligonucleotides followed by aging in 0.2 M PBS buffer for 6 hours. The DNA hybridization induced bimetallic assembly of Pt and Ru nanoparticles could then be carried out in 0.3 M PBS buffer for 10 hours.

UV Embossed Plastic Chip for Protein Separation and Identification

This report demonstrates a UV-embossed polymeric chip for protein separation and identification by Capillary Isoelectric Focusing (CIEF) and Matrix Assisted Laser Desportion/Ionization Mass Spectrometry (MALDI-MS). The polymeric chip has been fabricated by UV-embossing technique with high throughput; the issues in the fabrication have been addressed. In order to achieve high sensitivity of mass detection, five different types of UV curable polymer have been used as sample support to perform protein ionization in Mass Spectrometry (MS); the best results is compared to PMMA, which was the commonly used plastic chip for biomolecular separation. Experimental results show that signal from polyester is 12 times better than that of PMMA in terms of detection sensitivity. Finally, polyester chip is utilized to carry out CIEF to separate proteins, followed by MS identification.

Retargeting of pre-set regions on chromosome for high gene expression in mammalian cells

We have developed a system to hunt and reuse special gene integration sites that allow for high and stable gene expression. A vector, named pRGFP8, was constructed. The plasmid pRGFP8 contains a reporter gene, gfp2 and two extraneous DNA fragments. The gene gfp2 makes it possible to screen the high expression regions on the chromosome. The extraneous DNA fragments can help to create the unique loci on the chromosome and increase the gene targeting frequency by increasing the homology. After transfection into Chinese hamster ovary cells (CHO) cells, the linearized pRGFP8 can integrate into the chromosome of the host cells and form the unique sites. With FACS, 90 millions transfected cells were sorted and the cells with strongest GFP expression were isolated, and then 8 stable high expression GFP CHO cell lines were selected as candidates for the new host cell. Taking the unique site created by pRGFP8 on the chromosome in the new host cells as a targeting locus, the gfp2 gene was replaced with the gene of interest, human ifngamma, by transfecting the targeting plasmid pRIH-IFN. Then using FACS, the cells with the dimmest GFP fluorescence were selected. These cells showed they had strong abilities to produce the protein of interest, IFN-gamma. During the gene targeting experiment, we found there is positive correlation between the fluorescence density of the GFP CHO host cells and the specific production rate of IFN-gamma. This result shows that the strategy in our expression system is correct: the production of the interesting protein increases with the increase fluorescence of the GFP host cells. This system, the new host cell lines and the targeting vector, can be utilized for highly expressing the gene of interest. More importantly, by using FACS, we can fully screen all the transfected cells, which can reduce the chances of losing the best cells.

Gait Analysis for Classification

This thesis describes a representation of gait appearance for the purpose of person identification and classification. This gait representation is based on simple localized image features such as moments extracted from orthogonal view video silhouettes of human walking motion. A suite of time-integration methods, spanning a range of coarseness of time aggregation and modeling of feature distributions, are applied to these image features to create a suite of gait sequence representations. Despite their simplicity, the resulting feature vectors contain enough information to perform well on human identification and gender classification tasks. We demonstrate the accuracy of recognition on gait video sequences collected over different days and times and under varying lighting environments. Each of the integration methods are investigated for their advantages and disadvantages. An improved gait representation is built based on our experiences with the initial set of gait representations. In addition, we show gender classification results using our gait appearance features, the effect of our heuristic feature selection method, and the significance of individual features.