Placement and routing for cross-referencing digital microfluidic biochips.

Xiao, Zigang."October 2010."Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (leaves 62-66).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.viChapter 1 --- Introduction --- p.1Chapter 1.1 --- Microfluidic Technology --- p.2Chapter 1.1.1 --- Continuous Flow Microfluidic System --- p.2Chapter 1.1.2 --- Digital Microfluidic System --- p.2Chapter 1.2 --- Pin-Constrained Biochips --- p.4Chapter 1.2.1 --- Droplet-Trace-Based Array Partitioning Method --- p.5Chapter 1.2.2 --- Broadcast-addressing Method --- p.5Chapter 1.2.3 --- Cross-Referencing Method --- p.6Chapter 1.2.3.1 --- Electrode Interference in Cross-Referencing Biochips --- p.7Chapter 1.3 --- Computer-Aided Design Techniques for Biochip --- p.8Chapter 1.4 --- Placement Problem in Biochips --- p.8Chapter 1.5 --- Droplet Routing Problem in Cross-Referencing Biochips --- p.11Chapter 1.6 --- Our Contributions --- p.14Chapter 1.7 --- Thesis Organization --- p.15Chapter 2 --- Literature Review --- p.16Chapter 2.1 --- Introduction --- p.16Chapter 2.2 --- Previous Works on Placement --- p.17Chapter 2.2.1 --- Basic Simulated Annealing --- p.17Chapter 2.2.2 --- Unified Synthesis Approach --- p.18Chapter 2.2.3 --- Droplet-Routing-Aware Unified Synthesis Approach --- p.19Chapter 2.2.4 --- Simulated Annealing Using T-tree Representation --- p.20Chapter 2.3 --- Previous Works on Routing --- p.21Chapter 2.3.1 --- Direct-Addressing Droplet Routing --- p.22Chapter 2.3.1.1 --- A* Search Method --- p.22Chapter 2.3.1.2 --- Open Shortest Path First Method --- p.23Chapter 2.3.1.3 --- A Two Phase Algorithm --- p.24Chapter 2.3.1.4 --- Network-Flow Based Method --- p.25Chapter 2.3.1.5 --- Bypassibility and Concession Method --- p.26Chapter 2.3.2 --- Cross-Referencing Droplet Routing --- p.28Chapter 2.3.2.1 --- Graph Coloring Method --- p.28Chapter 2.3.2.2 --- Clique Partitioning Method --- p.30Chapter 2.3.2.3 --- Progressive-ILP Method --- p.31Chapter 2.4 --- Conclusion --- p.32Chapter 3 --- CrossRouter for Cross-Referencing Biochip --- p.33Chapter 3.1 --- Introduction --- p.33Chapter 3.2 --- Problem Formulation --- p.34Chapter 3.3 --- Overview of Our Method --- p.35Chapter 3.4 --- Net Order Computation --- p.35Chapter 3.5 --- Propagation Stage --- p.36Chapter 3.5.1 --- Fluidic Constraint Check --- p.38Chapter 3.5.2 --- Electrode Constraint Check --- p.38Chapter 3.5.3 --- Handling 3-pin net --- p.44Chapter 3.5.4 --- Waste Reservoir --- p.45Chapter 3.6 --- Backtracking Stage --- p.45Chapter 3.7 --- Rip-up and Re-route Nets --- p.45Chapter 3.8 --- Experimental Results --- p.46Chapter 3.9 --- Conclusion --- p.47Chapter 4 --- Placement in Cross-Referencing Biochip --- p.49Chapter 4.1 --- Introduction --- p.49Chapter 4.2 --- Problem Formulation --- p.50Chapter 4.3 --- Overview of the method --- p.50Chapter 4.4 --- Dispenser and Reservoir Location Generation --- p.51Chapter 4.5 --- Solving Placement Problem Using ILP --- p.51Chapter 4.5.1 --- Constraints --- p.53Chapter 4.5.1.1 --- Validity of modules --- p.53Chapter 4.5.1.2 --- Non-overlapping and separation of Modules --- p.53Chapter 4.5.1.3 --- Droplet-Routing length constraint --- p.54Chapter 4.5.1.4 --- Optical detector resource constraint --- p.55Chapter 4.5.2 --- Objective --- p.55Chapter 4.5.3 --- Problem Partition --- p.56Chapter 4.6 --- Pin Assignment --- p.56Chapter 4.7 --- Experimental Results --- p.57Chapter 4.8 --- Conclusion --- p.59Chapter 5 --- Conclusion --- p.60Bibliography --- p.6

The Phage Toolbox: Automating Phage Discovery Using Novel Software, Devices, and High-Throughput Methodology

With reports of antibiotic resistance on the rise, the need for alternative therapeutic options is of high importance. Bacteriophage (or phage) therapy is a valuable alternative strategy that holds high promise for treating bacterial infections not responsive to traditional antibiotics. Furthermore, the ability to automate phage therapy research would push the field forward by speeding the time for development, discovery, and reproducible outcomes. This dissertation provides solutions to these challenges by delivering a range of software and device-related tools to streamline and automate phage research. Together, these tools converge to create a &ldquo;phage toolbox&rdquo;, where each tool can be used independently or collectively, paving the way for more automated solutions in phage discovery. The tools presented in this dissertation include (1) PhageBox, (2) PhageFilter, (3) PhageScanner, and (4) DebruijnExtend. PhageBox is an open-source digital microfluidics extension that offers magnetic and temperature control. Furthermore, the proof-of-concept applications show specialized utility towards bacteriophages. PhageFilter is an ultralow memory software tool that introduces a Genome Sequence Bloom Tree (gSBT) to assign short or long-read sequencing data to genomes, enabling accurate DNA filtering, binning, and abundance estimation. Potentially using these filtered sequences, PhageScanner is a machine learning pipeline and software tool that predicts phage virion proteins (PVPs) from metagenomic sequencing data. This extends upon preceding work in this area by using both oligonucleotide and protein sequence information. Lastly, DebruijnExtend presents a tool and algorithm for predicting the secondary structure of proteins from the primary sequence, which can assist with feature extraction and determining subtle differences in the secondary structures of phage structural proteins. The collection of tools presented here offers a comprehensive toolbox for automating phage research from a multidisciplinary perspective, including microfluidics, wet lab biology, and bioinformatics. As we witness the rise of the Internet of Things, Artificial Intelligence, and Synthetic Biology, we are beginning to realize the potential for making significant advances in biology through a multidisciplinary approach. These tools contribute to this paradigm shift by introducing opensource projects that leverage concepts from each of these areas. We envision a future where a consortium of companies and researchers will concentrate on developing bioinformatics software and open-source devices to automate phage biology.</p

Optimisation of microfluidic experiments for model calibration of a synthetic promoter in S. cerevisiae

This thesis explores, implements, and examines the methods to improve the efficiency of model calibration experiments for synthetic biological circuits in three aspects: experimental technique, optimal experimental design (OED), and automatic experiment abnormality screening (AEAS). Moreover, to obtain a specific benchmark that provides clear-cut evidence of the utility, an integrated synthetic orthogonal promoter in yeast (S. cerevisiae) and a corresponded model is selected as the experiment object. This work first focuses on the “wet-lab” part of the experiment. It verifies the theoretical benefit of adopting microfluidic technique by carrying out a series of in-vivo experiments on a developed automatic microfluidic experimental platform. Statistical analysis shows that compared to the models calibrated with flow-cytometry data (a representative traditional experimental technique), the models based on microfluidic data of the same experiment time give significantly more accurate behaviour predictions of never-encountered stimuli patterns. In other words, compare to flow-cytometry experiments, microfluidics can obtain models of the required prediction accuracy within less experiment time. The next aspect is to optimise the “dry-lab” part, i.e., the design of experiments and data processing. Previous works have proven that the informativeness of experiments can be improved by optimising the input design (OID). However, the amount of work and the time cost of the current OID approach rise dramatically with large and complex synthetic networks and mathematical models. To address this problem, this thesis introduces the parameter clustering analysis and visualisation (PCAV) to speed up the OID by narrowing down the parameters of interest. For the first time, this thesis proposes a parameter clustering algorithm based on the Fisher information matrix (FIMPC). Practices with in-silico experiments on the benchmarking promoter show that PCAV reduces the complexity of OID and provides a new way to explore the connections between parameters. Moreover, the analysis shows that experiments with FIMPC-based OID lead to significantly more accurate parameter estimations than the current OID approach. Automatic abnormality screening is the third aspect. For microfluidic experiments, the current identification of invalid microfluidic experiments is carried out by visual checks of the microscope images by experts after the experiments. To improve the automation level and robustness of this quality control process, this work develops an automatic experiment abnormality screening (AEAS) system supported by convolutional neural networks (CNNs). The system learns the features of six abnormal experiment conditions from images taken in actual microfluidic experiments and achieves identification within seconds in the application. The training and validation of six representative CNNs of different network depths and design strategies show that some shallow CNNs can already diagnose abnormal conditions with the desired accuracy. Moreover, to improve the training convergence of deep CNNs with small data sets, this thesis proposes a levelled-training method and improves the chance of convergence from 30% to 90%. With a benchmark of a synthetic promoter model in yeast, this thesis optimises model calibration experiments in three aspects to achieve a more efficient procedure: experimental technique, optimal experimental design (OED), and automatic experiment abnormality screening (AEAS). In this study, the efficiency of model calibration experiments for the benchmarking model can be improved by: adopting microfluidics technology, applying CAVP parameter analysis and FIMPC-based OID, and setting up an AEAS system supported by CNN. These contributions have the potential to be exploited for designing more efficient in-vivo experiments for model calibration in similar studies

Engineering and technology applications of control co-design: a survey

Control-inspired design, as the name suggests, involves drawing inspiration from control theory to design other engineering systems. Engineers may use the principles of feedback control to design systems that can adapt and self-correct in response to changing conditions. This technique is known as Control Co-design (CCD), and it focuses on the redesign of dynamics and subsystem interactions. CCD offers several benefits, such as improved performance, reduced design time and cost, and increased reliability, and has been applied to a variety of areas. In this paper, we present a review of 197 articles related to CCD and highlight the main topics of its applications, such as renewable energy, vehicular and aircraft control systems and communication systems in control. We delimit the applications of CCD in the field of engineering, providing an introductory understanding of this topic and presenting the main works developed in this field in recent years, as well as discussing the tendencies and benefits of CCD. The paper offers an in-depth conceptualisation of CCD. A theoretical example is provided to illustrate CCD’s application in a Hybrid Wind-Wave Platform (HWWP), detailing the interaction between aerodynamic and hydrodynamic design domains and their control challenges, along with discussions on simultaneous and nested CCD formulations

SUITE an Innovative Bioreactor Platform for in vitro Experiments

In-vitro cell cultures are a fundamental step in preclinical drug testing and are of great interest to the pharmaceutical industry. The most common method for culturing cells is in cell culture incubators. These are large and cumbersome and all mechanical stimuli are absent. They are nevertheless used ubiquitously and their results quoted as "standards" of in-vitro protocols. Several alternative culture methods have been proposed, and many systems are currently available commercially. Indeed, systems and devices for maintaining cells and tissues in controlled physical conditions, or bioreactors, have become an important tool in many areas of research. This is not only due to the growing interest in tissue engineering but also because it is now being increasingly recognised that cells respond not only to their biochemical, but also to their physical environment, and both cues are necessary to create a biomimetic habitat. However most bioreactors for cell culture and tissue engineering are cumbersome and only provide a few cues such as flow or strain, allowing limited control and flexibility. Since drug testing involves a large number of tests on identical cell cultures, a single well culture is inadequate and costly both in time and money. The High Throughput Screening (HTS), is a methodology for scientific experimentation widely used in drug discovery, based on a brute-force approach to collect a large amount of experimental data in less time and using less animals. The parallel nature of HTS makes it possible to collect a large amount of data from a small number of experiments and in a very short time. HTS, however, suffers from a significant problem that may affect the relevance of tests: the environment discrepancy problem. Another problem related with the actual drug testing and tissue engineering experiments is the enormous number of animals that have to be scarified every year. The aim of this study was to develop a generic platform or SUITE (Supervising Unit for In-vitro TEsting) for cell, tissue and organ culture composed of two main components: a universal control unit and an array of bioreactor chambers. The platform provides a biomimetic habitat to cells and tissues since the environment in the chambers is controlled and regulated to provide biomechanical and biophysical stimuli similar to those found in-vivo. In this work I describe how a new concept of cell culture bioreactor was developed by integrating different technologies and research fields. The data extracted using this new cell culture approach is more predictive of the in vivo response with respect to the multi-well approach, particularly for drug related studies. The starting point was a thorough analysis of currently used in-vitro methods; their pros and cons were assessed to exploit their advantages and overcome or circumvent their disadvantages. As far as the culture chamber is concerned, the approach was to use the methods and materials commonly employed in microfluidic fabrication, but at scales compatible with classical culture systems such as petri-dishes and multiwells. This renders the bioreactors more amenable to use by biologists and enables the use of cell densities comparable with classic systems as well as the use of conventional assaying techniques. In most cases, the cell culture chambers are thus made out of PDMS (Polydimethylsiloxane), using soft-moulding with micro- or mini-machined masters, or what we call Soft Milli-molding. A system on a plate Multi Compartmental Modular Bioreactor (MCmB) was developed using this technology. The MCmB is a modular chamber for high throughput multi compartmental bioreactor experiments. It is designed to be used in a wide range of applications and with various cell types. A precise stimulus application is also very important to better understand the correlation between physical variables and pathologies allowing a more accurate study of the tissue physiology and pathologies. For this reason in these thesis three additional stimulation chambers for vascular and articular cartilage stimulation respectively were also designed and tested. The control system was developed to be user-friendly, flexible and expandable to include new stimuli and was based on modular components, including motors and sensors. Importantly a single software interface was designed to allow data acquisition and monitoring of several chambers in series or in parallel. Using SUITE, high throughput experiments can be performed in an in vivo-like simulated environment for a long time to simulate different physiological or pathological scenarios or for toxicity testing of cells, tissues or in-vitro organ models

Fabrication of Micro- and Nano-Fluidic Lab-On-A-Chip Devices Utilizing Proton Beam Writing Technique

Ph.DDOCTOR OF PHILOSOPH

Design of electronic systems for automotive sensor conditioning

This thesis deals with the development of sensor systems for automotive, mainly targeting the exploitation of the new generation of Micro Electro-Mechanical Sensors (MEMS), which achieve a dramatic reduction of area and power consumption but at the same time require more complexity in the sensor conditioning interface. Several issues concerning the development of automotive ASICs are presented, together with an overview of automotive electronics market and its main sensor applications. The state of the art for sensor interfaces design (the generic sensor interface concept), consists in sharing the same electronics among similar sensor applications, thus saving cost and time-to-market but also implementing a sub-optimal system with area and power overheads. A Platform Based Design methodology is proposed to overcome the limitations of generic sensor interfaces, by keeping the platform generality at the highest design layers and pursuing the maximum optimization and performances in the platform customization for a specific sensor. A complete design flow is presented (up to the ASIC implementation for gyro sensor conditioning), together with examples regarding IP development for reuse and low power optimization of third party designs. A further evolution of Platform Based Design has been achieved by means of implementation into silicon of the ISIF (Intelligent Sensor InterFace) platform. ISIF is a highly programmable mixed-signal chip which allows a substantial reduction of design space exploration time, as it can implement in a short time a wide class of sensor conditioning architectures. Thus it lets the designers evaluate directly on silicon the impact of different architectural choices, as well as perform feasibility studies, sensor evaluations and accurate estimation of the resulting dedicated ASIC performances. Several case studies regarding fast prototyping possibilities with ISIF are presented: a magneto-resistive position sensor, a biosensor (which produces pA currents in presence of surface chemical reactions) and two capacitive inertial sensors, a gyro and a low-g YZ accelerometer. The accelerometer interface has also been implemented in miniboards of about 3 cm2 (with ISIF and sensor dies bonded together) and a series of automatic trimming and characterization procedures have been developed in order to evaluate sensor and interface behaviour over the automotive temperature range, providing a valuable feedback for the implementation of a dedicated accelerometer interface