Simulation and analytical performance studies of generic atm switch fabrics.

As technology improves exciting new services such as video phone become possible and economically viable but their deployment is hampered by the inability of the present networks to carry them. The long term vision is to have a single network able to carry all present and future services. Asynchronous Transfer Mode, ATM, is the versatile new packet -based switching and multiplexing technique proposed for the single network. Interest in ATM is currently high as both industrial and academic institutions strive to understand more about the technique. Using both simulation and analysis, this research has investigated how the performance of ATM switches is affected by architectural variations in the switch fabric design and how the stochastic nature of ATM affects the timing of constant bit rate services. As a result the research has contributed new ATM switch performance data, a general purpose ATM switch simulator and analytic models that further research may utilise and has uncovered a significant timing problem of the ATM technique. The thesis will also be of interest and assistance to anyone planning on using simulation as a research tool to model an ATM switch

On the role of feedback in network coding

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 143-149).Network coding has emerged as a new approach to operating communication networks, with a promise of improved efficiency in the form of higher throughput, especially in lossy conditions. In order to realize this promise in practice, the interfacing of network coding with existing network protocols must be understood well. Most current protocols make use of feedback in the form of acknowledgments (ACKs) for reliability, rate control and/or delay control. In this work, we propose a way to incorporate network coding within such a feedback-based framework, and study the various benefits of using feedback in a network coded system. More specifically, we propose a mechanism that provides a clean interface between network coding and TCP with only minor changes to the protocol stack, thereby allowing incremental deployment. In our scheme, the source transmits random linear combinations of packets currently in the TCP congestion window. At the heart of our scheme is a new interpretation of ACKs - the receiver acknowledges every degree of freedom (i.e., a linear combination that reveals one unit of new information) even if it does not reveal an original packet immediately. Such ACKs enable a TCP-compatible sliding-window implementation of network coding. Thus, with feedback, network coding can be performed in a completely online manner, without the need for batches or generations. Our scheme has the nice feature that packet losses on the link can be essentially masked from the congestion control algorithm by adding enough redundancy in the encoding process.(cont.) This results in a novel and effective approach for congestion control over networks involving lossy links such as wireless links. Our scheme also allows intermediate nodes to perform re-encoding of the data packets. This in turn leads to a natural way of running TCP flows over networks that use multipath opportunistic routing along with network coding. We use the new type of ACKs to develop queue management algorithms for coded networks, which allow the queue size at nodes to track the true backlog in information with respect to the destination. We also propose feedback-based adaptive coding techniques that are aimed at reducing the decoding delay at the receivers. Different notions of decoding delay are considered, including an order-sensitive notion which assumes that packets are useful only when delivered in order. We study the asymptotic behavior of the expected queue size and delay, in the limit of heavy traffic.by Jay Kumar Sundararajan.Ph.D

Ion Mobility-Mass Spectrometry and Collision Induced Unfolding of Multi-Protein Ligand Complexes.

Mass spectrometry (MS) serves as an indispensable technology for modern pharmaceutical drug discovery and development processes, where it is used to assess ligand binding to target proteins and to search for biomarkers that can be used to gauge disease progression and drug action. However, MS is rarely treated as a screening technology for the structural consequences of drug binding. Instead, more time-consuming technologies capable of projecting atomic models of protein-drug interactions are utilized. In this thesis, ion mobility-mass spectrometry (IM-MS) methods are developed in order to fill these technology gaps. Principle among these is collision induced unfolding (CIU), which leverages the ability of IM to separate ions according to their size and charge, in order to fingerprint gas-phase unfolding pathways for non-covalent protein complexes. Following a comprehensive introductory chapter, we demonstrate the consequences of sugar binding on the CIU of Concanavalin A (Con A) in Chapter 2. Our CIU assay reveals cooperative stabilization upon small molecule binding, and such effect cannot be easily detected by solution phase assays, or by MS alone. In Chapter 3, the underlying mechanism of multi-protein unfolding is systematically investigated by IM-MS and molecular modeling approaches. Our results show a strong positive correlation between monomeric Coulombic unfolding and the tetrameric CIU process. This provides strong evidence that multi-protein unfolding events are initiated primarily by charge migration from the complex to a single monomer. In Chapter 4, the interactions between human histone deacetylase 8 (HDAC8) and poly-r(C)-binding protein 1 (PCBP1) are investigated by IM-MS. Our data suggest that these proteins interact with each other in a specific manner, a fact revealed by our optimized ESI-MS workflow for quantifying binding affinity (KD) for weakly-associated hetero-protein complexes. In Chapter 5, the translocator protein (TSPO) dimer from Rhodobacter sphaeroides, as well as its disease-associated variant forms, is analyzed by IM-MS and CIU assays. By utilizing a combination of CIU and collision induced dissociation (CID) stability data, an unknown endogenous ligand bound to TSPO is detected and identified.PHDChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116693/1/shuainiu_1.pd

Technological developments in mass spectrometry towards molecular structural elucidation of macromolecular assemblies

Retrieving higher-order structural features of macromolecular assemblies (MMAs), such as protein complexes and viruses, is of great interest. These characteristics are crucial for understanding the functions and interactions of MMAs with other molecular species or receptors. While various techniques such as cryogenic-electron microscopy, nuclear magnetic resonance, and x-ray crystallography are capable of providing high-resolution structures of MMAs, they come with some limitations. This thesis primarily focuses on the technological developments in mass spectrometry (MS) in retrieving molecular features of MMAs at different levels of their organization. For that, aspects of soft-ionizing techniques (nano-electrospray ionization and matrix-assisted laser desorption/ionization), axial/orthogonal reflectron time-of-flight and high-resolution Orbitrap MS, top-down proteomics (ultraviolet photodissociation and higher-energy collisional dissociation), and mass-to-charge ratio/time-resolved imaging using pixelated Timepix and Timepix3 application-specific integrated circuit based detection assemblies were brought together

Phosphoproteomics and proteomic phenotyping to assess signal transduction in cancer cells

This thesis applies quantitative mass spectrometry to research topics in relation to cancer. Proteome-wide quantification at the protein expression level and phosphorylation level were achieved. The technologies developed and used here cover the latest improvements in instrumentation in mass spectrometry, strategies in phosphopeptide enrichment in large scale, algorithms in data analysis and their streamlined implementation, and data mining in downstream bioinformatics. For each of the projects described in this thesis, proteome mapping routinely resulted in identification and quantitation of around 4,000 proteins and phosphoproteome mapping often lead to quantitation of more than 5,000 phosphorylation sites. This ‘systems-wide’ quantitation of the proteome and phosphoproteome is a completely novel development, which has not been used in cancer related topics before. Three major biology topics are studied in this thesis. In the first project, the phosphoproteome of a mouse liver cancer cell line Hepa1-6 was analyzed in-depth, by using phosphatase inhibitors (calyculin A, deltamethrin, and Na-pervanadate) to boost phosphorylation. The characterization of the phosphoproteome revealed a broad spectrum of cellular compartmentalization and biological functions. Quantitation of phosphatase inhibitor treatment using the Stable Isotope Labeling by Amino Acids in Cell culture (SILAC) method revealed the quantitative effects of these inhibitor compounds on the whole phosphoproteome. To our surprise, these three broadband phosphatase inhibitors displayed very different efficiency, with tyrosine phosphorylation significantly boosted but serine/threonine phosphorylation much less affected. Additionally, a method to estimate an upper bound of the stoichiometry of phosphorylation was introduced by comparing phosphorylation in three SILAC conditions: non-treated cells, stimulated cells (e.g. with insulin), and only phosphatase inhibitor treated cells. The methods developed here can be used directly in development of drugs directed against kinases and phosphatases, key regulators in cancer and other diseases. The second project continues with the application of phosphoproteomics techniques. Kinase inhibitors influence cellular signal transduction processes and therefore are of great potential in rescuing aberrant cellular signaling in tumors. In fact they constitute a significant portion of drug developing programs in pharmaceutical industry. With the aim of quantifying the effect of kinase inhibitors over the entire signaling network, the second project first set out to study two very commonly used kinase inhibitor compounds for MAPKs: U0126 and SB202190. Their effect on epidermal growth factor (EGF) signal transduction was quantified and compared using the HeLa cell system. The study confirmed that the MAPK cascades are the predominant signaling branches for propagating the EGF signaling at early time points of stimulation. These large scale examinations also suggest that U0126 and SB202190 are quite specific inhibitors for MAPKs as the majority of regulated phosphopeptides appears to belong to the MAPK pathways. In the second part of the project, the effect on phosphoproteome changes of the chemical compound dasatinib, which was demonstrated to effectively inhibit the constitutively activated fusion protein BCR-ABL and was recently approved for chronic myelogenous leukemia (CML) therapy, was quantified in the human CML cell line K562. Bioinformatic analysis revealed that the most influenced signal transduction branch was the Erk1/2 cascade. Overall more than 500 phosphorylation sites were found to be regulated by dasatinib, the vast majority not described in the literature yet. The third project compared the proteomes of mouse hepatoma cell line Hepa1-6 with the non-transformed mouse primary hepatocytes. This was performed by combining the SILAC heavy labeled form of Hepa1-6 with the primary hepatocytes. To characterize the features of these two proteomes, quantitation information (i.e. protein ratios between the two cell types) was used to divide all proteins into five quantiles. Each quantile was clustered according to the Gene Ontology and KEGG pathway databases to assess their enriched functional groups and signaling pathways. To integrate this information at a higher level, hierarchical clustering based on the p-value from the first Gene Ontology and KEGG clustering was performed. Using this improved bioinformatic algorithm for data mining, the proteomic phenotypes of the primary cells and transformed cells are immediately apparent. Primary hepatocytes are enriched in mitochondrial functions such as metabolic regulation and detoxification, as well as liver functions with tissue context such as secretion of plasma and low-density lipoprotein (LDL). In contrast, the transformed cancer cell line Hepa1-6 is enriched in cell cycle and growth functions. Interestingly, several aspects of the molecular basis of the “Warburg effect” described in many cancer cells became apparent in Hepa1-6, such as increased expression of glycolysis markers and decreased expression of markers for tricarboxylic acid (TCA) cycle. Studies in this thesis only provide examples of the application of mass spectrometry-based quantitative proteomics and phosphoproteomics in cancer research. The connection to clinical research, especially the assessment of drug effects on a proteome wide scale, is a specific feature of this thesis. Although this development is only in its infancy, it reflects a trend in the quantitative mass spectrometry field. We believe that more and more clinical related topics can and will be studied by these powerful methods

Laboratory Directed Research and Development Program FY 2004 Annual Report

The Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD) Program reports its status to the U.S. Department of Energy (DOE) in March of each year. The program operates under the authority of DOE Order 413.2A, 'Laboratory Directed Research and Development' (January 8, 2001), which establishes DOE's requirements for the program while providing the Laboratory Director broad flexibility for program implementation. LDRD funds are obtained through a charge to all Laboratory programs. This report describes all ORNL LDRD research activities supported during FY 2004 and includes final reports for completed projects and shorter progress reports for projects that were active, but not completed, during this period. The FY 2004 ORNL LDRD Self-Assessment (ORNL/PPA-2005/2) provides financial data about the FY 2004 projects and an internal evaluation of the program's management process. ORNL is a DOE multiprogram science, technology, and energy laboratory with distinctive capabilities in materials science and engineering, neutron science and technology, energy production and end-use technologies, biological and environmental science, and scientific computing. With these capabilities ORNL conducts basic and applied research and development (R&D) to support DOE's overarching national security mission, which encompasses science, energy resources, environmental quality, and national nuclear security. As a national resource, the Laboratory also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Work For Others (WFO) program. Information about the Laboratory and its programs is available on the Internet at <http://www.ornl.gov/>. LDRD is a relatively small but vital DOE program that allows ORNL, as well as other multiprogram DOE laboratories, to select a limited number of R&D projects for the purpose of: (1) maintaining the scientific and technical vitality of the Laboratory; (2) enhancing the Laboratory's ability to address future DOE missions; (3) fostering creativity and stimulating exploration of forefront science and technology; (4) serving as a proving ground for new research; and (5) supporting high-risk, potentially high-value R&D. Through LDRD the Laboratory is able to improve its distinctive capabilities and enhance its ability to conduct cutting-edge R&D for its DOE and WFO sponsors. To meet the LDRD objectives and fulfill the particular needs of the Laboratory, ORNL has established a program with two components: the Director's R&D Fund and the Seed Money Fund. As outlined in Table 1, these two funds are complementary. The Director's R&D Fund develops new capabilities in support of the Laboratory initiatives, while the Seed Money Fund is open to all innovative ideas that have the potential for enhancing the Laboratory's core scientific and technical competencies. Provision for multiple routes of access to ORNL LDRD funds maximizes the likelihood that novel and seminal ideas with scientific and technological merit will be recognized and supported