DNAコンピューティングシステムの設計支援 : DNAツールボックスとその拡張

学位の種別:課程博士University of Tokyo(東京大学

2022 URS Abstract Booklet

Complete Schedule of Events for the 24th Annual Undergraduate Research Symposium at Minnesota State University, Mankato

Geometric Algorithms and Data Structures for Simulating Diffusion Limited Reactions

Radiation therapy is one of the most effective means for treating cancers. An important calculation in radiation therapy is the estimation of dose distribution in the treated patient, which is key to determining the treatment outcome and potential side effects of the therapy. Biological dose — the level of biological damage (e.g., cell killing ratio, DNA damage, etc.) inflicted by the radiation is the best measure of treatment quality, but it is very difficult to calculate. Therefore, most clinics today use physical dose - the energy deposited by incident radiation per unit body mass - for planning radiation therapy, which can be calculated accurately using kinetic Monte Carlo simulations. Studies have found that physical dose correlates with biological dose, but exhibits a very complex relationship that is not yet well understood. Generally speaking, the calculation of biological dose involves four steps: (1) the calculation of physical dose distribution, (2) the generation of radiochemicals based on the physical dose distribution, (3) the simulation of interactions between radiochemicals and bio-matter in the body, and (4) the estimation of biological damage based on the distribution of radiochemicals. This dissertation focuses on the development of a more efficient and effective simulation algorithm to speed up step (3). The main contribution of this research is the development of an efficient and effective kinetic Monte Carlo (KMC) algorithm for simulating diffusion-limited chemical reactions in the context of radiation therapy. The central problem studied is - given n particles distributed among a small number of particle species, all allowed to diffuse and chemically react according to a small number of chemical reaction equations - predict the radiochemical yield over time. The algorithm presented makes use of a sparse grid structure, with one grid per species per radiochemical reactant used to group particles in a way that makes the nearest neighbor search efficient, where particles are stored only once, yet are represented in grids of all appropriate reaction radii. A kinetic data structure is used as the time stepping mechanism, which provides spatially local updates to the simulation at a frequency which captures all events - retaining accuracy. A serial and three parallel versions of the algorithm have been developed. The parallel versions implement the kinetic data structure using both a standard priority queue and a treap data structure in order to investigate the algorithms scalability. The treap provides a way for each thread of execution to do more work in a particular region of space. A comparison with a spatial discretization variant of the algorithm is also provided

Wright State University\u27s Symposium of Student Research, Scholarship & Creative Activities from Thursday, October 26, 2023

The student abstract booklet is a compilation of abstracts from students\u27 oral and poster presentations at Wright State University\u27s Symposium of Student Research, Scholarship & Creative Activities on October 26, 2023.https://corescholar.libraries.wright.edu/celebration_abstract_books/1001/thumbnail.jp

Circuits and Systems for Lateral Flow Immunoassay Biosensors at the Point-of-Care

Lateral Flow Immunoassays (LFIAs) are biosensors, which among others are used for the detection of infectious diseases. Due to their numerous advantages, they are particularly suitable for point of care testing, especially in developing countries where there is lack of medical healthcare centers and trained personnel. When the testing sample is positive, the LFIAs generate a color test line to indicate the presence of analyte. The intensity of the test line relates to the concentration of analyte. Even though the color test line can be visually observed for the accurate quantification of the results in LFIAs an external electronic reader is required. Existing readers are not fully optimized for point-of-care (POC) testing and therefore have significant limitations. This thesis presents the development of three readout systems that quantify the results of LFIAs. The first system was implemented as a proof of concept of the proposed method, which is based on the scanning approach without using any moving components or any extra optical accessories. Instead, the test line and the area around it, are scanned using an array of photodiodes (1 × 128). The small size of the pixels gives the system sufficient spatial resolution, to avoid errors due to positioning displacement of the strip. The system was tested with influenza A nucleoprotein and the results demonstrate its quantification capabilities. The second generation system is an optimized version of the proof of concept system. Optimization was performed in terms of matching the photodetectors wavelength with the maximum absorption wavelength of the gold nanoparticles presented in the tested LFIA. Ray trace simulations defined the optimum position of all the components in order to achieve uniform light distribution across the LFIA with the minimum number of light sources. An experimental model of the optical profile of the surface of LFIA was also generated for accurate simulations. Tests of the developed system with LFIAs showed its ability to quantify the results while having reduced power consumption and better limit of detection compared to the first system. Finally, a third generation system was realized which demonstrated the capability of having a miniaturized reader. The photodetector of the previous systems was replaced with a CMOS Image Sensor (CIS), specifically designed for this application. The pixel design was optimized for very low power consumption via biasing the transistors in subthreshold and by reusing the same amplifier for both photocurrent to voltage conversion and noise cancellation. With uniform light distribution at 525 nm and 76 frames/s the chip has 1.9 mVrms total output referred noise and a total power consumption of 21 μW. In tests with lateral flow immunoassay, this system detected concentrations of influenza A nucleoprotein from 0.5 ng/mL to 200 ng/mL

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here