The automation of protein crystal presentation for x ray diffraction experiments using standing acoustic waves in a microfluidic chip environment

As the pressure continues to grow on Diamond and the world's synchrotrons for higher throughput of diffraction experiments, new and novel techniques are required for presenting micron dimension crystals to the X ray beam. Currently this task is both labour intensive and primarily a serial process. Diffraction measurements typically take milliseconds but sample preparation and presentation can reduce throughput down to 4 measurements an hour. With beamline waiting times as long as two years it is of key importance for researchers to capitalize on available beam time, generating as much data as possible. Other approaches detailed in the literature [1] [2] [3] are very much skewed towards automating, with robotics, the actions of a human protocols. The work detailed here is the development and discussion of a bottom up approach relying on SSAW self assembly, including material selection, microfluidic integration and tuning of the acoustic cavity to order the protein crystals.

The automation of protein crystal presentation for X ray diffraction experiments using standing acoustic waves in a microfluidic chip environment

As the pressure continues to grow on Diamond and the world's synchrotrons for higher throughput of diffraction experiments, new and novel techniques are required for presenting micron dimension crystals to the X ray beam. Currently this task is both labour intensive and primarily a serial process. Diffraction measurements typically take milliseconds but sample preparation and presentation can reduce throughput down to 4 measurements an hour. With beamline waiting times as long as two years it is of key importance for researchers to capitalize on available beam time, generating as much data as possible. Other approaches detailed in the literature [1] [2] [3] are very much skewed towards automating, with robotics, the actions of a human protocols. The work detailed here is the development and discussion of a bottom up approach relying on SSAW self assembly, including material selection, microfluidic integration and tuning of the acoustic cavity to order the protein crystals.

Development and reliability of a direct access sensor using flip chip on flex technology with anisotropic conductive adhesive

Technological developments in biomedical microsystems are opening up new opportunities to improve healthcare procedures. Swallowable diagnostic sensing capsules are an example of these. In none of the diagnostic sensing capsules, is the sensor’s first level packaging achieved via Flip Chip Over Hole (FCOH) method using Anisotropic Conductive Adhesive (ACA). In a capsule application with direct access sensor (DAS), ACA not only provides the electrical interconnection but simultaneously seals the interconnect area and the underlying electronics. The development showed that the ACA FCOH was a viable option for the DAS interconnection. Adequate adhesive formed a strong joint that withstood a shear stress of 120N/mm2 and a compressive stress of 6N required to secure the final sensor assembly in place before encapsulation. Electrical characterization of the ACA joint in a fluid environment showed that the ACA was saturated with moisture and that the ions in the solution actively contributed to the leakage current, characterized by the varying rate of change of conductance. Long term hygrothermal aging of the ACA joint showed that a thermal strain of 0.004 and a hygroscopic strain of 0.0052 were present and resulted in a fatigue like process. In-vitro tests showed that high temperature and acidity had a deleterious effect of the ACA and its joint. It also showed that the ACA contact joints positioned at around or over 1mm would survive the gastrointestinal (GI) fluids and would be able to provide a reliable contact during the entire 72hr of the GI transit time. A final capsule demonstrator was achieved by successfully integrating the DAS, the battery and the final foldable circuitry into a glycerine capsule. Final capsule soak tests suggested that the silicone encapsulated system could survive the 72hr gut transition.

Mapping Protein-DNA Interactions Using ChIP-exo and Illumina-Based Sequencing

Chromatin immunoprecipitation (ChIP) provides a means of enriching DNA associated with transcription factors, histone modifications, and indeed any other proteins for which suitably characterized antibodies are available. Over the years, sequence detection has progressed from quantitative real-time PCR and Southern blotting to microarrays (ChIP-chip) and now high-throughput sequencing (ChIP-seq). This progression has vastly increased the sequence coverage and data volumes generated. This in turn has enabled informaticians to predict the identity of multi-protein complexes on DNA based on the overrepresentation of sequence motifs in DNA enriched by ChIP with a single antibody against a single protein. In the course of the development of high-throughput sequencing, little has changed in the ChIP methodology until recently. In the last three years, a number of modifications have been made to the ChIP protocol with the goal of enhancing the sensitivity of the method and further reducing the levels of nonspecific background sequences in ChIPped samples. In this chapter, we provide a brief commentary on these methodological changes and describe a detailed ChIP-exo method able to generate narrower peaks and greater peak coverage from ChIPped material.

A parametric study of flip-chip reliability via computer simulation

Abstract not available

Large scale parallel simulations for the assembly of a flip-chip component to a printed circuit

Abstract not available

Dynamic Workload Parallelization and System Calibration on Single-Chip Cloud Computer

Many-core systems are emerging from the need of more computational power and power efficiency. However there are many issues which still revolve around the many-core systems. These systems need specialized software before they can be fully utilized and the hardware itself may differ from the conventional computational systems. To gain efficiency from many-core system, programs need to be parallelized. In many-core systems the cores are small and less powerful than cores used in traditional computing, so running a conventional program is not an efficient option. Also in Network-on-Chip based processors the network might get congested and the cores might work at different speeds. In this thesis is, a dynamic load balancing method is proposed and tested on Intel 48-core Single-Chip Cloud Computer by parallelizing a fault simulator. The maximum speedup is difficult to obtain due to severe bottlenecks in the system. In order to exploit all the available parallelism of the Single-Chip Cloud Computer, a runtime approach capable of dynamically balancing the load during the fault simulation process is used. The proposed dynamic fault simulation approach on the Single-Chip Cloud Computer shows up to 45X speedup compared to a serial fault simulation approach. Many-core systems can draw enormous amounts of power, and if this power is not controlled properly, the system might get damaged. One way to manage power is to set power budget for the system. But if this power is drawn by just few cores of the many, these few cores get extremely hot and might get damaged. Due to increase in power density multiple thermal sensors are deployed on the chip area to provide realtime temperature feedback for thermal management techniques. Thermal sensor accuracy is extremely prone to intra-die process variation and aging phenomena. These factors lead to a situation where thermal sensor values drift from the nominal values. This necessitates efficient calibration techniques to be applied before the sensor values are used. In addition, in modern many-core systems cores have support for dynamic voltage and frequency scaling. Thermal sensors located on cores are sensitive to the core's current voltage level, meaning that dedicated calibration is needed for each voltage level. In this thesis a general-purpose software-based auto-calibration approach is also proposed for thermal sensors to calibrate thermal sensors on different range of voltages.

A functional specification and validation model for networks on chip in the ACL2 logic

International audience

Optimisation tools for flip-chip design

Abstract not available

Portable “lab-on-chip” platform for bovine mastitis diagnosis in raw milk

Tese de Doutoramento em Ciências Veterinárias, Especialidade de Ciências Biológicas e Biomédicas

Structural determination and gynecological tumor diagnosis using antibody chip captured proteins

Purpose: To identify markers for gynecological tumor diagnosis using antibody chip capture. Methods: Marker proteins, including cancer antigen 153 (CA153), CA125, and carcinoembryonic antigen (CEA), were analyzed using antibody chip capture of serum samples. Fifteen agglutinin types that specifically recognized five common glycans (fucose, sialic acid, mannose, N - acetylgalactosamine, and N-acetylglucosamine) were used to detect marker protein glycan levels. The levels of CA153, CA125, and CEA from 49 healthy control samples, 31 breast cancer samples, 24 cervical cancer samples, and 19 ovarian cancer samples were used to measure the glycan levels of these marker proteins. Results: In breast cancer samples, CA153 and CA125 were down-regulated (p < 0.01), while differences in ovarian cancer samples were not statistically significant (p > 0.01). The total accuracy was 85.1 %, with 96.8 % accuracy for breast cancer, 75 % in cervical cancer, and 78.9 % in ovarian cancer. Cross-validation analyses showed that breast cancer had 93.5 % accuracy, cervical cancer was 66.7 %, and ovarian cancer was 68.4 %, leading to 78.4 % total accuracy (58/74). Conclusions: The results indicate that better clinical diagnosis of gynecological tumors can be obtained by monitoring changes in glycan levels of serum proteins and types of proteoglycan changes.

Citrus HLB x Potato "Zebra Chip" in Brazil: Attempting to transmit citrus Candidatus liberibacter spp (asiaticus and americanus) to potato plants.

2009

Industrial lab-on-a-chip: design, applications and scale-up for drug discovery and delivery

Microfluidics is an emerging and promising interdisciplinary technology which offers powerful platforms for precise production of novel functional materials (e.g., emulsion droplets, microcapsules, and nanoparticles as drug delivery vehicles- and drug molecules) as well as high-throughput analyses (e.g., bioassays, detection, and diagnostics). In particular, multiphase microfluidics is a rapidly growing technology and has beneficial applications in various fields including biomedicals, chemicals, and foods. In this review, we first describe the fundamentals and latest developments in multiphase microfluidics for producing biocompatible materials that are precisely controlled in size, shape, internal morphology and composition. We next describe some microfluidic applications that synthesize drug molecules, handle biological substances and biological units, and imitate biological organs. We also highlight and discuss design, applications and scale up of droplet- and flow-based microfluidic devices used for drug discovery and delivery.

Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities.