Quantitative measurement and modeling of the DNA damage signaling network : DNA double-strand breaks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2009."September 2009." Cataloged from PDF version of thesis.Includes bibliographical references (p. 218-229).DNA double-strand breaks (DSB) are one of the major mediators of chemotherapy-induced cytotoxicity in tumors. Cells that experience DNA damage can initiate a DNA damage-mediated cell-cycle arrest, attempt to repair the damage and, if successful, resume the cell-cycle (arrest/repair/resume). Cells can also initiate an active cell-death program known as apoptosis. However, it is not known what "formula" a cell uses to integrate protein signaling molecule activities to determine which of these paths it will take, or what protein signaling-molecules are essential to the execution of that decision. A better understanding of how these cellular decisions are made and mediated on a molecular level is essential to the improvement of existing combination and targeted chemotherapies, and to the development of novel targeted and personalized therapies. Our goal has been to gain an understanding of how cells responding to DSB integrate protein signaling-molecule activities across distinct signaling networks to make and execute binary cell-fate decisions, under conditions relevant to tumor physiology and treatment. We created a quantitative signal-response dataset, measuring signals that widely sample the response of signaling networks activated by the induction of DSB, and the associated cellular phenotypic responses, that together reflect the dynamic cellular responses that follow the induction of DSB. We made use of mathematical modeling approaches to systematically discover signal-response relationships within the DSB-responsive protein signaling network. The structure and content of the signal-response dataset is described, and the use of mathematical modeling approaches to analyze the dataset and discover specific signal-response relationships is illustrated. As a specific example, we selected a particularly strong set of identified signal-response correlations between ERK1/2 activity and S phase cell-cycle phenotype, identified in the mathematical data analysis, to posit a causal relationship between ERK1/2 and S phase cell cycle phenotype. We translated this posited causal relationship into an experimental hypothesis and experimentally test this hypothesis. We describe the validation of an experimental hypothesis based upon model-derived signal response relationships, and demonstrate a dual role for ERK1/2 in mediating cell-cycle arrest and apoptosis following DNA damage. Directions for the extension of the signal-response dataset and mathematical modeling approaches are outlined.by Andrea R. Tentner.Ph.D

Highway traffic simulation on multi-processor computers

A computer model has been developed to simulate highway traffic for various degrees of automation with a high level of fidelity in regard to driver control and vehicle characteristics. The model simulates vehicle maneuvering in a multi-lane highway traffic system and allows for the use of Intelligent Transportation System (ITS) technologies such as an Automated Intelligent Cruise Control (AICC). The structure of the computer model facilitates the use of parallel computers for the highway traffic simulation, since domain decomposition techniques can be applied in a straight forward fashion. In this model, the highway system (i.e. a network of road links) is divided into multiple regions; each region is controlled by a separate link manager residing on an individual processor. A graphical user interface augments the computer model kv allowing for real-time interactive simulation control and interaction with each individual vehicle and road side infrastructure element on each link. Average speed and traffic volume data is collected at user-specified loop detector locations. Further, as a measure of safety the so- called Time To Collision (TTC) parameter is being recorded

Cell decision processes in response to DNA DSB

Thesis (S.M.)--Massachusetts Institute of Technology, Biological Engineering Division, June 2006."February 2006."Includes bibliographical references (leaves 56-59).Following exposure to DNA damage, cells initiate a stress response involving multiple protein kinase signaling cascades. The DNA damage response results in one of several possible cell-fate decisions, or cellular responses: induction of cell-cycle arrest, initiation of DNA repair, activation of transcriptional programs, and either apoptosis, necrosis or cell senescence. The mechanisms by which cells make these decisions, and how cell fate depends upon variables such as DNA damage type and dose, and other environmental factors, is unknown. The process by which cells select among alternate fates following such stimuli, or "cues" is likely to involve a dynamic, multi-variate integration of signals from each of the kinase signaling components. A major goal of signal transduction research is to understand how information flows through signal transduction pathways downstream of a given cue, such as DNA damage, and how signals are integrated, in order to mediate cellular responses. Mathematical modeling approaches are necessary to advance our understanding of these processes.(cont.) Indeed, statistical mining and modeling of large datasets, consisting of quantitative, dynamic signaling and response measurements, is capable of yielding models that identify key signaling components in a given cue-response relationship, as well as models that are highly predictive of cellular response following novel cues that perturb the same network. We have validated a novel assay system that allows for the high throughput collection of quantitative and dynamic signaling data for 7 protein kinases or phospho-proteins known to be "hubs" in the DNA damage response and/or general stress response networks, including ATM, Chk2, H2AX, JNK, p38, ERK and p53. This novel high-throughput In-cell Western assay is based on immuno-fluorescent staining and detection of target proteins in a "whole cell" environment, performed and visualized in a 96-well plate format. This assay allows for the detection and measurement of up to 7 target proteins in triplicate, over up to 3 treatment regimes, or up to 21 signals for a single treatment, simultaneously. Pre-processing steps, and steps involved in the protocol itself are significantly fewer (and require smaller amount of most reagents and biological material),(cont.) as compared to traditional signal measurement methods, such as quantitative Western analysis and kinase assays. We have used this novel high-throughput In-cell Western assay to investigate the DNA damage response after the specific induction of DNA double strand breaks (DSB). We have measured the dynamics of seven "hub" proteins modified with activating phosphorylations (as a surrogate measure of protein activity) that span major branches of the DNA damage, stress, and death signaling networks, following the specific induction of DNA double strand breaks. Signaling proteins measured include ATM, Chk2, H2AX, JNK, p38, ERK and p53. In parallel with these signaling measurements, we have quantitatively measured corresponding phenotypic responses, such as cell cycle profile and apoptosis. In future work, we will use a Partial Least Squares (PLS) regression analysis approach to construct a statistical model using this data, which is predictive of the cellular responses included in our measurements, following perturbation of this branch of the DNA damage response network. This analysis should reveal key signaling components involved in the decision-making process (possible molecular targets for the improvement of cancer therapy regimens that rely upon the induction of DSB, e.g. the topoisomerase inhibitor, cisplatin), and provide a basis for constructing new, and improving existing, physics-chemical models of this branch of the DNA damage response network.by Andrea R. Tentner.S.M

Severe accident approach - final report. Evaluation of design measures for severe accident prevention and consequence mitigation.

An important goal of the US DOE reactor development program is to conceptualize advanced safety design features for a demonstration Sodium Fast Reactor (SFR). The treatment of severe accidents is one of the key safety issues in the design approach for advanced SFR systems. It is necessary to develop an in-depth understanding of the risk of severe accidents for the SFR so that appropriate risk management measures can be implemented early in the design process. This report presents the results of a review of the SFR features and phenomena that directly influence the sequence of events during a postulated severe accident. The report identifies the safety features used or proposed for various SFR designs in the US and worldwide for the prevention and/or mitigation of Core Disruptive Accidents (CDA). The report provides an overview of the current SFR safety approaches and the role of severe accidents. Mutual understanding of these design features and safety approaches is necessary for future collaborations between the US and its international partners as part of the GEN IV program. The report also reviews the basis for an integrated safety approach to severe accidents for the SFR that reflects the safety design knowledge gained in the US during the Advanced Liquid Metal Reactor (ALMR) and Integral Fast Reactor (IFR) programs. This approach relies on inherent reactor and plant safety performance characteristics to provide additional safety margins. The goal of this approach is to prevent development of severe accident conditions, even in the event of initiators with safety system failures previously recognized to lead directly to reactor damage

Simulations of highway traffic with various degrees of automation

A traffic simulator to study highway traffic under various degrees of automation is being developed at Argonne National Laboratory (ANL). The key components of this simulator include a global and a local Expert Drive Mode, a human factor study and a graphical user interface. Further, an Autonomous Intelligent Cruise Control (AICC) which is based on a neural network controller is described and results for a typical driving scenario are given

Argonne simulation framework for intelligent transportation systems

A simulation framework has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS). The simulator is designed to run on parallel computers and distributed (networked) computer systems; however, a version for a stand alone workstation is also available. The ITS simulator includes an Expert Driver Model (EDM) of instrumented ``smart`` vehicles with in-vehicle navigation units. The EDM is capable of performing optimal route planning and communicating with Traffic Management Centers (TMC). A dynamic road map data base is sued for optimum route planning, where the data is updated periodically to reflect any changes in road or weather conditions. The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide 2-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphical user interfaces that includes human-factors studies to support safety and operational research. Realistic modeling of variations of the posted driving speed are based on human factor studies that take into consideration weather, road conditions, driver`s personality and behavior and vehicle type. The simulator has been developed on a distributed system of networked UNIX computers, but is designed to run on ANL`s IBM SP-X parallel computer system for large scale problems. A novel feature of the developed simulator is that vehicles will be represented by autonomous computer processes, each with a behavior model which performs independent route selection and reacts to external traffic events much like real vehicles. Vehicle processes interact with each other and with ITS components by exchanging messages. With this approach, one will be able to take advantage of emerging massively parallel processor (MPP) systems

Combined experimental and computational analysis of DNA damage signaling reveals context-dependent roles for Erk in apoptosis and G1/S arrest after genotoxic stress

Data-driven modeling was used to analyze the complex signaling dynamics that connect DNA repair with cell survival, cell-cycle arrest, or apoptosis. This analysis revealed an unexpected role for Erk in G1/S arrest and apoptotic cell death following doxorubicin-induced DNA damage

Advances in thermal hydraulic and neutronic simulation for reactor analysis and safety

This paper describes several large-scale computational models developed at Argonne National Laboratory for the simulation and analysis of thermal-hydraulic and neutronic events in nuclear reactors and nuclear power plants. The impact of advanced parallel computing technologies on these computational models is emphasized

Accuracy of Eulerian–Eulerian, two-fluid CFD boiling models of subcooled boiling flows

Boiling flows are frequently found in industry and engineering due to the large amount of heat that can be transferred within such flows with minimum temperature differences. In the nuclear industry, boiling affects in different ways the operation of almost all water-cooled nuclear reactors. Recently, the use of computational fluid dynamic (CFD) approaches to predict boiling flows is increasing and, in the nuclear area, CFD is being developed to solve thermal hydraulic safety issues such as establishing the critical heat flux, which is perhaps the major threat to the integrity of nuclear fuel rods. In this paper, the accuracy of an Eulerian–Eulerian, two-fluid CFD model is evaluated over a large database of subcooled boiling flows, avoiding the rather popular case-by-case tuning of descriptive models to a limited number of experiments. The model includes a Reynolds stress turbulence model, the method of moments-based S-gamma population balance approach and a boiling model derived using the heat flux partitioning approach. The database covers a large range of conditions in subcooled boiling flows of water and refrigerants in vertical pipes and annular channels. Overall, a satisfactory predictive accuracy is achieved for some quantities of interest, such as the void fraction and the turbulence and liquid temperature fields, but results are less satisfactory in other areas, more specifically for the average bubble diameter and the mean velocity profiles close to the wall in annular channels. Agreement may be improved with advances in the treatment of large bubbles and bubble break-up and coalescence, as well as in improved modelling of the boiling region close to the wall, and more specifically the bubble departure diameter, the wall treatment and the contribution of bubbles to turbulence

SAS4A analysis of unprotected loss of flow accidents in a metal fuel reactor

This paper discusses the SAS4A code system which is used to analyze the core behavior under beyond-design-base transient conditions for various Advanced Liquid Metal Reactor (ALMR) designs. The results of these analyses provide help in assessing the outcomes of various accident sequences, and provide guidance for future experimental needs and mathematical model development. This paper describes the thermal-hydraulic and neutronic events that occur in a low void worth metal fuel core [2] during a very rapid unprotected Loss of Flow (LOF) accident, with a flow decay half time t[sub 1/2] = 0.3s. This LOF was selected because it leads to fuel pin failure and subsequent fuel relocation. The only mechanistic initiator that can lead to such a rapid LOF is, possibly, a severe earthquake. For slower LOFs pin failure and fuel relocation do not occur, as negative reactivity from other core feedback effects has enough time to counteract the positive reactivity introduced by the early sodium boiling