Michael Franklin - US grants

biomedical equipment resource; biomedical equipment purchase;

Substituted imidazole compounds include agents which have therapeutically useful, H2 antagonist, anticonvulsant, antiinflammatory and sedative-hypnotic properties. N-substituted imidazoles are best known for their antimycotic activity. N- substituted imidazoles, although mostly investigated for drug interactions resulting from their inhibitory properties have recently become known as powerful inducers of hepatic oxidative drug metabolism. An investigation of the conditions and characteristics necessary for induction and their relationship to inhibitory properties, and the relevance of both processes to drug interactions and drug toxicity is the major thrust of this proposal. The dose, route and duration of N-substituted imidazole administration necessary for the induction, especially the "dose dependent isozyme induction" and "high magnitude" induction characteristics of Phase I cytochrome P-450 oxidations as well as changes in Phase II glutathione, sulfate and glucuronic acid conjugations in male rats will be determined. Hepatic concentrations of the N-substituted imidazoles will be monitored. New N-substituted imidazoles will be synthesized to augment those commercially available in attempts to delineate the characteristics of the molecule necessary for the various induction characteristics. The cytochrome P-450 isozymes and classes of UDP-glucuronosyl-transferases induced will be compared with those present after administration of classical inducing agents. New isozymes or novel induction profiles of known isozymes of cytochrome P-450 will be sought using characteristic monooxygenase activities and SDS polyacrylamide gel electrophoresis of microsomal fractions anion exchange HPLC fractionation, (also coupled with SDS-polyacrylamide gel electrophoresis) and reconstitution of enzymatic activity. The relationship between the cytochrome P-450 isozyme(s) which are inhibited and isozymes which are induced by N-substituted imidazoles will be investigated. The effect of inhibition and induction of Phase I oxidation and any changes in Phase II conjugations on the pharmacological effect and hepatotoxicity of model compounds will be investigated. The overall findings will provide greater accuracy to the prediction of drug-drug interactions likely to arise from the therapeutic use of N- substituted imidazoles.

The needs of many application domains are not met by current database system technology. Relational database systems (RDBMSs) excel at providing high-level, associative (i.e., query-based) access to large sets of flat records. Object-oriented database systems (OODBMSs) on the other hand, provide more powerful data modelling capabilities, but primarily support navigation-based access to the data. The goal of this research is to develop flexible workstation/server database systems which can dynamically adapt to the requirements of a wide range of applications, allowing those applications to exploit database capabilities and benefit from the continuing rapid gains in workstation and local area network price/performance. Such database systems will be able to adaptively choose between query-oriented and navigation-oriented strategies based on both compile-time and runtime considerations. The approach taken will be to extend the techniques that have been recently developed for navigation-oriented OODBMSs to co-exist with techniques from the more traditional query-oriented (relational) approach. To achieve this end, however, will require significant work in performance modeling and analysis, the development of new data management algorithms and new query optimization techniques, and the resolution of numerous database systems architecture issues. The results of this project will include analyses of the tradeoffs between data-shipping and query-shipping, algorithms for cache maintenance, query optimization, and memory management, and detailed performance analyses based on simulation and implementation of these new techniques.

Many emerging networked applications have the property that communication among nodes is asymmetric. Typically, servers can and/or must send much more data to clients than clients send back to the servers. Examples include wireless networks with mobile clients, cable and direct satellite broadcast TV systems, information dispersal and information retrieval applications. Broadcast Disks technique exploits the characteristics of such environments, by treating a broadcast stream of data that are repeatedly and cyclicly transmitted as a storage device. The essence of this approach is to superimpose multiple broadcast programs (or `disks`) spinning at different speeds on a single broadcast channel; in effect, creating an arbitrarily fine-grained memory hierarchy. The technique also integrates the use of client storage resources for caching and prefetching data that is delivered over the broadcast. The Broadcast Disks approach provides improved performance for non-uniformly accessed data and increased availability of important data. The challenges being addressed in this project include: broadcast program generation, caching and prefetching strategies, and adapting to volatile data, changing client needs, and communication errors. The results of this research will be techniques, analyses, and prototype implementations of this novel approach, which has the potential to significantly improve the performance and availability of future distributed computing systems. The education portion of this project aims to develop new courses, software tools and laboratories that will provide students at all levels with more direct, hands-on experience in building database systems and applications.

This research addresses the problem of adding data management facilities to inherently autonomous, distributed information sources such as those that occur in the web. Here, by data management, is meant the allocation and structuring of resources to provide more responsive access to data for applications. In this kind of environment, data management must be superimposed through an independently controlled service that exists between the data sources and the applications. This is facilitated through the introduction of architecture based on data centers, a collection of machines that prestage and distribute data for its clients. Client applications submit profiles describing their overall data needs, and the data center gathers data and organizes it on behalf of their clients in order to provide efficient data access. This research explores systems issues and techniques for the design and operation of data centers. This includes the management of large numbers of profiles, heuristics for balancing the needs of large numbers of users against the available resources of the data center, and the efficient processing of future client data needs against the data that is managed by the data center.

A grant has been awarded to Montana State University under the direction of Dr. Timothy Ford. The grant will provide MSU with instrumentation for laser microdissection of biological samples and for genomic analysis of the isolated cells. Individual cells often live within larger cell populations. This is true both for multicellular organisms and for single-cell organisms. In multicellular organisms, cells develop into various cell types. This differentiation is due to the programmed induction or repression of genes during the developmental process. Single-cell organisms, including bacteria, often live in microbial communities, where individual cells experience gradients of nutrients or toxic waste product. These gradients affect the genetic responses of bacteria, and ultimately impact the global cycling of nutrients. In the past, biological characterizations of cellular activities often had to be performed on large cell populations, following sample homogenization. However, since not all cells within a population behave similarly, the results only represent average activities, and do not address the activities of individual cells within the population, which may vary at spatially localized sites. To begin characterizing the activities of individual cells within populations, instrumentation will be acquired to isolate and characterize cells from surrounding tissues or cellular communities. The laser capture microdissection microscope allows the excision of biological samples on the scale of an individual cell without damage to the cell or to the surrounding population. The DNA microarray instrumentation, allows the study of gene expression patterns of these isolated cells. Therefore, the combination of these two instruments will allow investigators at MSU to gain a better understanding of gene expression processes that occur on spatially localized populations of cells, without the need for sample homogenization. These studies will enhance the understanding of how cells differentiate into multicellular organisms, and how single-cell organisms respond to and impact the surrounding environment.

This grant proposal represented the collective efforts of ten researchers at Montana State University, and the grant will have a positive impact on their research programs. In particular, the instrumentation provided here will be used for two main research endeavors that include: (I) the study of the physiology and ecology of microorganisms, and (II) the study of developmental biology and neurobiology. In the microbial ecology studies, the instruments will be used for research projects including (i) characterization of gene expression patterns in bacterial communities, known as biofilms, (ii) characterization of gene expression in response to toxic metals, and in the geochemical cycling of metals, and (iii) characterization of microbial ecotypes in hot-spring microbial mat communities. In the developmental biology studies, investigators will focus on experiments including (i) processes involved in the development of the central nervous system, and (ii) gene expression during the repair of damaged nerve cells. In addition to the benefit to research at MSU, this instrumentation will enhance undergraduate, graduate and minority educational programs. In the scientific disciplines, MSU has a hands-on undergraduate educational program. Most junior and senior undergraduate students in the science departments perform independent research projects that contribute to their undergraduate thesis work. By enhancing the infrastructure at MSU, this grant will provide these students with the opportunity to use state of the art instrumentation, that will become an integral component for their future careers in the biological sciences. Graduate students will also be able to enhance their Ph.D. thesis studies through the use of this instrumentation.

This grant will provide outreach to the community primarily through the Montana BRIN program, designed to attract Native American students from Montana's tribal colleges to scientific disciplines. BRIN concentrates on mentoring tribal college faculty and students on the MSU campus, and includes summer undergraduate research programs for these students and faculty. The grant provided here will allow these students to become familiar with state-of-the-art instrumentation used in modern academic and industrial laboratories. This grant will also have a broad impact of scientific importance. Recent advances in DNA sequencing technology have provided a tremendous amount of genome sequence information of organisms from all domains of life. Presently, one of the main goals in the biological sciences, is to begin characterizing the activities of these genes, many of which have not yet been assigned a specific function. By characterizing gene expression events that occur in situ or in vivo, it will now be possible to develop new hypotheses on the role of these genes, and how these genes enable an organism (or cell) to thrive in its particular ecological niche.

Making Sense at Scale with Algorithms, Machines, and People
University of California, Berkeley

The world is increasingly awash in data. As more and more human activities move on line, and as a growing array of connected devices become integral part of daily life, the amount and diversity of data being generated continues to explode. According to one estimate, more than a Zettabyte (one billion terabytes) of new information was created in 2010 alone, with the rate of new information increasing by roughly 60% annually. This data takes many forms: free-form tweets, text messages, blogs and documents; structured streams produced by computers, sensors and scientific instruments; and media such as images and video.
Buried in this flood of data are the keys to solving huge societal problems, for improving productivity and efficiency, for creating new economic opportunities, and for unlocking new discoveries in medicine, science and the humanities. However, raw data alone is not sufficient; we can only make sense of our world by turning this data into knowledge and insight. This challenge, known as the Big Data problem, cannot be solved by the straightforward application of current data analytics technology due to the sheer volume and diversity of information. Rather, to solve it requires throwing away old preconceptions about data management and breaking down many of the traditional boundaries in and around Computer Science and related disciplines.

The Algorithms, Machines, and People (AMP) expedition at the University of California, Berkeley is addressing this challenge head-on. AMP is a collaboration of researchers with a wide range of data-related expertise, committed to working together to create a new data analytics paradigm. AMP will produce fundamental innovations in and a deep integration of three very different types of computational resources:
1. Algorithms: new machine-learning and analysis methods that can operate at large scale and can give flexible tradeoffs between timeliness, accuracy, and cost.
2. Machines: systems infrastructure that allows programmers to easily harness the power of scalable cloud and cluster computing for making sense of data.
3. People: crowdsourcing human activity and intelligence to create hybrid human/computer solutions to problems not solvable by today's automated data analysis technologies alone.

AMP research will be guided and evaluated through close collaboration with domain experts in key societal applications including: cancer genomics and personalized medicine, large-scale sensing for traffic prediction and environmental monitoring, urban planning, and network security. Advances pioneered by the project will be made widely available through the development of the Berkeley Data Analysis System (BDAS), an open source software platform that seamlessly blends Algorithm, Machine and People resources to solve big data problems.

For more information visit http://amplab.cs.berkeley.edu

The Big Data Innovation Hub for the Western United States will join stakeholders from academia, industry, non-profit institutions and the community who share common challenges and innovative approaches related to the acquisition, storage, analysis and integration of large or "messy" data, commonly referred to as Big Data. The West's Innovation Hub (Hub) will serve 13 states with Montana, Colorado and New Mexico marking the eastern boundary. This project will develop the organizational and governance structures for the Hub, and initiate efforts toward defining spoke activities for subsequent phases of the data innovation hubs program.

The initial themes include Big Data technology, data-enabled scientific discovery and learning, managing natural resources and hazards, metro data science, and precision medicine. Partnerships fostered through the Hub will enable the use of Big Data to assess risks related to regional and long-term decisions. The Hub's structure will enable impact in later phases of the Hubs program that may include data-driven models for managing natural resources to tools for integrating self-collected patient data for more precise care options. Through coordination activities that inspire the action of its members, the Hub has the potential to facilitate the improved flow of commercial technologies in ways that maximize competitiveness for member organizations, such as universities, and vice versa: the Hub has the potential to expand the impact of its members' technologies through greater adoption or via start-ups. The Hub will be impactful by facilitating cross-discipline approaches to Big Data innovation and problem solving, influencing the next generation of thought leaders and data scientists. The partnerships enabled by the Hub will lead to professional certificate programs and student internships, creating a pipeline of graduates from partner institutions to impact corporations, public and governmental agencies, national labs, resource-planning agencies, and regulatory commissions.

Project URL: BDHub.SDSC.edu