The theme of this thesis is to analyse the performance of a conventional mesh topology in a multipath fading environment and compare it with a newly proposed multiple cell based mesh topology. The communication performance in general is measured by the overall through-put, packets delivery reliability, average message delivery delay and power-consumption. In this thesis, for simplicity of the calculation the network performance is indirectly measured in-terms of the number of additional routes originally required to connect an isolated or disconnected device, percentage of the devices which have reliable and unreliable route from or to the back bone routers, number of hops from back-bone routers to the nodes and redundant routes which includes the routes inside the particular cell or outside to the other cell. In this simulation 240 nodes has been used within the area of 120 x 60 m2 which is just in accordance with an average size of industry. Network simulation is broken down into five different scenarios with respect to different number of field devices or nodes and back bone routers along with the presence of obstacles in the area and then analysed respectively. Entire simulation and analytical work have been done on MATLAB. Major applications of multiple cell based mesh topology can be used within industrial process automation, such as pulp and paper, steel, oil and gas, etc.

¡@¡@A single chip of variable length FFT processor is presented in this thesis. This processor can be applied for the applications with 128/256/512/1024/2048-point FFT. This processor is based on SDF (single path delay feedback) pipeline architecture with radix-2^3 computation element. The number of bits for input data and twiddle factors is carefully selected by system simulation to meet the requirements of OFDM system. In addition, we propose a feedback twiddle factor generator to instead the lookup table for twiddle factors to reduce the storage size of memory. The FFT processor is carried out by CMOS 0.35£gm 2P4M process with core area 3.381x3.3625 mm^2. In the gate level simulation, the output data rate of this FFT processor is above 22.72MHz, so the processor can meet the requirement of IEEE 802.16e standard.

CD4+CD25+Foxp3+ T regulatory (Treg) cells are critical in maintaining self tolerance and promoting the acceptance of allogeneic tissue/organ grafts. To be widely applied in clinical settings, there needs to be a readily available source of Treg cells, a requirement that is better met if non-histocompatible donor cells could be utilized in adoptive therapy. Therefore, to investigate the therapeutic potential of fully allogeneic Treg cells to control autoimmune disease or allograft rejection, we utilized IL-2R beta-deficient mice that exhibit rapid lethal autoimmunity due to low production of an ineffective population of Treg cells. We show that adoptive transfer of MHC-mismatched Treg cells into IL-2R beta-/- mice resulted in life-long engraftment of the donor cells, which exhibited skewed reactivity toward host alloantigens, and prevented autoimmunity. When such animals received skin grafts, they exhibited tolerance to those grafts that expressed MHC molecules from which the donor Treg cells were derived. Collectively, these data provide proof-of-principle that effective engraftment by allogeneic Treg cells controls autoimmunity and leads to favorable conditions for long-term acceptance of allografts. Current data indicates that CD4+CD25+Foxp3+ Treg cells exhibit a broad TCR repertoire. However, the relationship between this diversity and capacity to control a similarly diverse population of potentially autoreactive T cells remains to be defined. To investigate this issue, we assessed the TCR repertoire of chimeric donor Treg cells in IL-2R beta-/- mice that were adoptively treated with a diverse polyclonal Treg inoculums. We demonstrate that autoimmune disease was fully prevented by engrafted donor Treg cells in spite of a TCR repertoire that is less diverse than the input cells. However, in settings where the input TCR repertoire is limited by utilizing donor Treg cells that express a single TCR beta chain, control of disease was hampered, correlating with a limited TCR alpha repertoire within the engrafting donor Treg cells. Collectively, these findings suggest that for adoptive therapy, a diverse TCR repertoire of input Treg cell inoculums is an essential requirement for effective control of polyclonal autoreactive T cells but perturbations in the repertoire that results in significant limitation to this diversity may compromise Treg cell efficacy at fully keeping autoaggressive cells in check.

付記する学位プログラム名: 充実した健康長寿社会を築く総合医療開発リーダー育成プログラム / 京都大学 / 新制・課程博士 / 博士(医科学) / 甲第23116号 / 医科博第127号 / 新制||医科||8(附属図書館) / 京都大学大学院医学研究科医科学専攻 / (主査)教授 藤田 恭之, 教授 渡邊 直樹, 教授 岩田 想 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

As the problem of resistance increases in the current health care system, new solutions to this problem are not emerging at a similar rate. The ability to discover novel antibiotics, and modify existing antibiotics, is competing with highly evolving resistance profiles. An alternate solution to this problem may be to search for inhibitors of these resistance mechanisms and pairing them with current antibiotics. Proof of this hypothesis lies in the great success of P-lactamase inhibitors already in the clinic. Inhibitors may be created using synthetic methods, however searching for inhibitors found in the natural environment may lead to a greater success. For example, bacteria in their natural setting must cope with constant exposure to antibiotics secreted by both themselves and by other species. As well, bacteria must be able to handle encounters with other species that are resistant to their own defense mechanisms. With this in consideration, it is possible that these bacteria have already established an ability to challenge resistance encountered in their own environment, such as through the secretion of compounds that inhibit these mechanisms. Screening of such inhibitors can be done against purified resistance elements or via cell-based screens with resistant bacteria. The focus of this research was to develop expression systems which contain inducible antibiotic resistance genes to be used for whole-cell screening for inhibitors of antibiotic resistance. The expression systems studied were pSWEET, for use in the Gram positive bacterium Bacillus subtilis, and pETcoco, for use in the Gram negative bacterium Escherichia coli. It was found that the pSWEET expression system integrated into the B. subtilis chromosome at unspecified locations and was not an ideal system for the proposed screen. pET coco holds promise as a suitable expression system but at this point in time it requires further examination to ensure plasmid stability and reproducibility of results. Therefore further examination of these two systems is needed if they are to be used in a screen for inhibitors, and a search for substitute systems must be undertaken. / Thesis / Master of Science (MSc)

The detection of small molecules in complex sample matrices such as environmental (surface and ground water, sediment, etc.) and biological (blood, serum, plasma, etc.) samples is of paramount importance for monitoring the distribution of environmental pollutants and their patterns of exposure within the population as well as diagnosing and managing diseases. Biosensors have demonstrated a singular ability to sensitively and selectively detect analytes in complex samples without the need for extensive sample preparation and pretreatment. Nature has demonstrated myriad examples of exquisite selectivity in spite of complexity and we seek to take advantage of that attribute in the development of novel biosensing systems. In the work presented here, we have developed both cell- and proteinbased biosensing systems for the detection of hydroxylated polychlorinated biphenyls (OH-PCBs) and protein-based sensing systems for the detection of glucose. In the development of a whole-cell sensing system, the regulatory protein, HbpR, and its associated promoter was used to modulate the expression of luciferase. Additionally, the effector binding domain of HbpR, HbpR-A, was isolated and modified with a solvatochromic fluorophore resulting in a proteinbased sensing system. For the detection of glucose, two different glucose binding proteins were engineered in an effort to tailor their characteristics, such as binding affinity and thermal stability, to develop a rugged, sensitive proteinbased sensing system. We envision that these biosensing systems will find applications in the areas of environmental pollutant monitoring and the management and treatment of diseases such as diabetes.

Worldwide, 3.575 million people die each year from water-related diseases. The water and sanitation crisis claims more lives than any warfare and is predicted to be one of the biggest global challenges of this century. The rapid, accurate detection of viral pathogens from environmental samples is an ongoing and pertinent challenge in biological engineering. Currently employed methods are lacking in either efficiency or specificity. Here we explore a novel method for virus detection and concurrently use this method to learn more about the very early stages of the virus infection process. The method combines Fourier transform infrared (FTIR) spectroscopy, a method of visualizing molecules based on changes in vibration of particles, and mammalian cells as the biosensor. This method is used to detect and investigate viruses from the family picornaviridae, chosen due to their public health burden and their widespread presence in environmental samples, especially water sources. This family includes the Polioviruses, echoviruses and Coxsackieviruses, among others, many of which are human pathogens.The research outlined in this dissertation is aimed at developing and implementing a new cell-based biosensor that combines the advantages of FTIR spectroscopy with the ability of buffalo green monkey kidney (BGMK) cells to sense diverse stimuli, including infective enteroviruses. The goal of developing this biosensor is outlined in the first paper. The second paper focuses on the application of advanced statistical methods to analyze the spectra to discriminate different viral infections in BGMK cells. Finally, we designed a non-reactive metal biochamber to use with attenuated total reflectance-FTIR. This allowed near-continuous acquisition of real-time spectral data for the study of biochemical changes in mammalian cells caused by poliovirus (PV1) infection. This system is capable of tracking changes in cell biochemistry in minute intervals for many hours at a time.This work demonstrates the feasibility of FTIR spectroscopy in combination with the broad sensitivity of mammalian cells for potential use in the detection of infective viruses from environmental samples. We envision this method being extended to high throughput, automated systems to screen for viruses or other toxins in drinking water systems and medical applications.

Technology, nowadays, has given us huge computational potential, but computer sciences have major problems tapping into this pool of resources. One of the main issues is how to program and design distributed systems. Biology has solved this issue about half a billion years ago, during the Cambrian explosion: the evolution of multicellularity. The evolution of multicellularity allowed cells to differentiate and so divide different tasks to different groups of cells; this combined with evolution gives us a very good example of how massively parallel distributed computational system can function and be “programmed”. However, the evolution of multicellularity is not very well understood, and most traditional methodologies used in evolutionary theory are not apt to address and model the whole transition to multicellularity. In this thesis I develop and argue for new computational artificial life methodologies for the study of the evolution of multicellularity that are able to address the whole transition, give new insights, and complement existing methods. I argue that these methodologies should have three main characteristics: accessible across scientific disciplines, have potentiality for complex behaviour, and be easy to analyse. To design models, which possess those characteristics, I developed a model of genetic regulatory networks (GRNs) that control artificial cells, which I have used in multiple evolutionary experiments. The first experiment was designed to present some of the engineering problems of evolving multicelled systems (applied to graph-colouring), and to perfect my artificial cell model. The two subsequent experiments demonstrate the characteristics listed above: one model based on a genetic algorithm with an explicit two-level fitness function to evolve multicelled cooperative patterning, and one with freely evolving artificial cells that have evolved some multicelled cooperation as evidenced by novel measures, and has the potential to evolve multicellularity. These experiments show how artificial life models of evolution can discover and investigate new hypotheses and behaviours that traditional methods cannot.

Rapid prototyping tools exist in many fields of science and engineering, but are rare in biology especially not general tools that can handle the diversity and complexity of the many spatial and temporal scales in nature. In this thesis a general use, cell-based, middle-out biology emulation programming framework (outlining a programming paradigm) is presented, that enables biologists to emulate and use virtual biological systems of previously unimaginable complexity and potentially get results accurate enough to be used in research and ultimately, in clinical practice, such as diagnosis or operations. With this technology, virtual organisms can be created that are viable, fit and can be optimised for any task that arises. The tool, realised with a programming framework created for the C++ language is detailed and demonstrated through several examples of increasing complexity, namely several example organisms and a cancer emulation, showing both viable virtual organisms and usable experimental results.

The behaviour of individual cells must be carefully coordinated across a tissue to achieve correct function. In particular, proliferation and differentiation decisions must be precisely regulated throughout development, tissue maintenance, and repair. A better understanding of how these processes are controlled would have implications for human health; cancer is, after all, dysregulated proliferation, while regenerative medicine relies on being able to influence cell decisions accurately. To investigate such fundamental biological processes, it is common practice to use an experimentally tractable model organism. Here, we focus on the germ line of the nematode worm C. elegans, which provides opportunities to study organogenesis, tissue maintenance, and ageing effects. Despite the advantages of this organism as a biological model, certain questions about germ cell behaviour and coordination remain challenging to address in the lab. There is therefore a need for computational models of the germ line to complement experimental approaches. In this thesis, we develop a new in silico model of the C. elegans germ line. Novel aspects include working in three dimensions, covering the late larval period, and integrating a logical model of germ cell behaviour into a wider cell mechanics simulation. Our model produces a reasonable fit to wild-type germline behaviour, and provides the first cell tracking and labelling predictions for the larval period. It also suggests two new biological hypotheses: 1) that “stretching” growth plays a significant role in gonadogenesis, and 2) that a feedback mechanism acts on the germ cell cycle to prevent overproliferation. Having introduced the full model, we address some technical questions arising from our work, namely: what is the effect of applying a more physically realistic force law?; and can simulation performance be improved by changing the numerical scheme? Finally, we use in silico modelling to compare a number of hypothesised germ line maintenance mechanisms. There, our results support a model with functionally equivalent germ cells undergoing at most infrequent, transient cell cycle arrests.