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NER: Investigation and Characterization of Adsorption of Self Assembling Amyloid Beta Protein Aggregates on Gold Nanoparticles Embedded in a Sol-Gel Thin Film

$75,000FY2005ENGNSF

Suny College At Geneseo, Geneseo NY

Investigators

Abstract

We propose to investigate the application of gold nanoparticles as an effective marker for nuclei formation of amyloid b-peptides (Ab), which is a hallmark of Alzheimer's disease. The goal of this project is to establish a diagnostic method to relate the size of nanoparticles with the size of the assembled Ab arising from the aggregation process. The objectives are 1) to compile a spectroscopic characterization of gold nanoparticles when they coexist with Ab, 2) to find an indication of adsorption or self-assembly of Ab aggregates in a silica sol-gel matrix in thin film form. As aggregation of the protein takes place, light scattering will be strongly enhanced. Thus, we will adopt a surface reflectance diffuse spectroscopy technique, which is well suited for measuring the absorption spectroscopic information of the scattering surface area. The spectroscopic information will be correlated with the absorption information of gold nanoparticle complexes alone, and the spectral shift used for an estimation of the aggregation size. As a broader impact of the proposed study, the present study may result in a correlation scheme for protein conformation adsorbed on gold nanoparticles, which could be used to establish a standard diagnostic methodology for a protein aggregation. Through this research project, three undergraduate students will have an opportunity to be engaged in an application of nanopartcile science and they have an opportunity to use highly specialized instruments, such as an Atomic Force Microscope at the Center for Advanced Technology in Nanomaterials and Nanoelectronics, State University of New York at Albany.

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NER: Investigation and Characterization of Adsorption of Self Assembling Amyloid Beta Protein Aggregates on Gold Nanoparticles Embedded in a Sol-Gel Thin Film · GrantIndex