| 1. |
- Gad, Helge, et al.
(författare)
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MTH1 inhibition eradicates cancer by preventing sanitation of the dNTP pool
- 2014
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Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 508:7495, s. 215-221
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Tidskriftsartikel (refereegranskat)abstract
- Cancers have dysfunctional redox regulation resulting in reactive oxygen species production, damaging both DNA and free dNTPs. The MTH1 protein sanitizes oxidized dNTP pools to prevent incorporation of damaged bases during DNA replication. Although MTH1 is non-essential in normal cells, we show that cancer cells require MTH1 activity to avoid incorporation of oxidized dNTPs, resulting in DNA damage and cell death. We validate MTH1 as an anticancer target in vivo and describe small molecules TH287 and TH588 as first-in-class nudix hydrolase family inhibitors that potently and selectively engage and inhibit the MTH1 protein in cells. Protein co-crystal structures demonstrate that the inhibitors bindin the active site of MTH1. The inhibitors cause incorporation of oxidized dNTPs in cancer cells, leading to DNA damage, cytotoxicity and therapeutic responses in patient-derived mouse xenografts. This study exemplifies the non-oncogene addiction concept for anticancer treatment and validates MTH1 as being cancer phenotypic lethal.
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| 2. |
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| 3. |
- Asplund, Fredrik, 1977-
(författare)
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Tool Integration and Safety : A Foundation for Analysing the Impact of Tool Integrationon Non-functional Properties
- 2012
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The increasing complexity of embedded systems development is becoming difficult to handle with development environments based on disjoint engineering tools. Support for interactions between various engineering tools, especially through automated means, has therefore received an increased amount of attention during the last few years. The subsequent increase in the amount of tool integration is leading to an increased impact of tool integration on non-functional properties of development efforts, development environments and end products. At the same time there is a lack of methods and tools for analysing the relationship between these properties and tool integration. To establish a foundation for analysing this generic relationship, the specific relationship between tool integration and the safety of end products is analysed in this thesis.A survey was conducted to analyze the State of the Art of tool integration as related to safety. This survey specifically identified the lack of an efficient handling of tool integration by modern safety standards as an important concern. In relation to this survey, three theories were identified as of specific importance. These are the school of thought known as Systems Thinking, the Systems-Theoretic Accident Model and Processes (STAMP) causality model and the System-Theoretic Process Analysis (STPA) hazard analysis technique.Building on these theories, this thesis provides original contributions intended to (1) describe concepts and models related to tool integration and safety (the first and second contribution), (2) link tool integration to safety in a way that reduces complexity during analysis (the third contribution) and (3) propose how to interpret and make use of the implications of the presented theories and the first three contributions (the fourth and fifth contribution).• The first contribution is a new conceptual model of a development effort that emphasizes tool integration.• The second contribution is a new reference model for tool integration in highly heterogeneous environments.• The third contribution consists of nine safety-related tool chain properties, i.e. properties of tool chains that could mitigate at least part of the risks introduced by tool integration.• The fourth contribution is a proposition on how to identify safety implications due to a high level of automation of tool integration.• The fifth contribution is a proposition for a new software tool qualification process.
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| 4. |
- Axelsson, Karin, 1968-, et al.
(författare)
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Analyzing best practice and critical success factors in a health information system case : Are there any shortcuts to successful IT implementation?
- 2011
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Ingår i: Proceedings of the 19th European Conference on Information Systems - ECIS 2011. - : European Conference on Information Systems (ECIS) and Association for Information Systems AIS Electronic Library (AISeL). - 9789526035741 ; , s. 2157-2168
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This paper discusses critical success factors (CSF) and best practice in relation to IT implementation in the health sector. We have studied a University Hospital’s implementation of a health information system (HIS) and particularly one clinic which implementation process was described as very successful compared to other units at this hospital. The purpose of the paper is to gain further understanding of if and how well CSFs and best practice solutions can explain this successful case. We do this in order to explore if CSFs and best practice offer any shortcuts to successful IT implementation. By understanding the reasons behind this case’s success we can identify if CSFs and best practice potentially can explain the success, or if there are other explanations in this case. Based on our findings we discuss and question the sometimes overestimated belief in CSFs and best practice as shortcuts to success performance. An important contribution from this study is that situational and contextual factors are very critical to understand and acknowledge during HIS implementations.
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| 5. |
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| 6. |
- Axelsson, Patrik, 1985-, et al.
(författare)
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Discrete-time Solutions to the Continuous-time Differential Lyapunov Equation With Applications to Kalman Filtering
- 2012
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Prediction and filtering of continuous-time stochastic processes require a solver of a continuous-time differential Lyapunov equation (CDLE). Even though this can be recast into an ordinary differential equation (ODE), where standard solvers can be applied, the dominating approach in Kalman filter applications is to discretize the system and then apply the discrete-time difference Lyapunov equation (DDLE). To avoid problems with stability and poor accuracy, oversampling is often used. This contribution analyzes over-sampling strategies, and proposes a low-complexity analytical solution that does not involve oversampling. The results are illustrated on Kalman filtering problems in both linear and nonlinear systems.
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| 7. |
- Axelsson, Patrik, 1985-, et al.
(författare)
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Extended Kalman Filter Applied to Industrial Manipulators
- 2010
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Ingår i: Proceedings of Reglermöte 2010.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This paper summarizes previous work on tool position estimation on industrial manipulators, and emphasize the problems that must be taken care of in order to get a satisfied result. The acceleration of the robot tool, measured by an accelerometer, together with measurements of motor angles are used. The states are estimated with an extended Kalman filter. A method for tuning the covariance matrices for the noise, used in the observer, is suggested. The work has been focused on a robot with two degrees of freedom.
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| 8. |
- Axelsson, Patrik, 1985-, et al.
(författare)
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ML Estimation of Process Noise Variance in Dynamic Systems
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The performance of a non-linear filter hinges in the end on the accuracy of the assumed non-linear model of the process. In particular, the process noise covariance $Q$ is hard to get by physical modeling and dedicated system identification experiments. We propose a variant of the expectation maximization (EM) algorithm which iteratively estimates the unobserved state sequence and $Q$ based on the observations of the process. The extended Kalman smoother (EKS) is the instrument to find the unobserved state sequence. Our contribution fills a gap in literature, where previously only the linear Kalman smoother and particle smoother have been applied. The algorithm will be important for future industrial robots with more flexible structures, where the particle smoother cannot be applied due to the high state dimension. The proposed method is compared to two alternative methods on a simulated robot.
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| 9. |
- Axelsson, Patrik, 1985-, et al.
(författare)
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ML Estimation of Process Noise Variance in Dynamic Systems
- 2011
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Ingår i: Proceedings of the 18th IFAC World Congress. - 9783902661937 ; , s. 5609-5614
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Konferensbidrag (refereegranskat)abstract
- The performance of a non-linear filter hinges in the end on the accuracy of the assumed non-linear model of the process. In particular, the process noise covariance Q is hard to get by physical modeling and dedicated system identification experiments. We propose a variant of the expectation maximization (EM) algorithm which iteratively estimates the unobserved state sequence and Q based on the observations of the process. The extended Kalman smoother (EKS) is the instrument to find the unobserved state sequence. Our contribution fills a gap in literature, where previously only the linear Kalman smoother and particle smoother have been applied. The algorithm will be important for future industrial robots with more flexible structures, where the particle smoother cannot be applied due to the high state dimension. The proposed method is compared to two alternative methods on a simulated robot.
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| 10. |
- Axelsson, Patrik, 1985-
(författare)
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On Sensor Fusion Applied to Industrial Manipulators
- 2011
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- One of the main tasks for an industrial robot is to move the end-effector in a predefined path with a specified velocity and acceleration. Different applications have different requirements of the performance. For some applications it is essential that the tracking error is extremely low, whereas other applications require a time optimal tracking. Independent of the application, the controller is a crucial part of the robot system. The most common controller configuration uses only measurements of the motor angular positions and velocities, instead of the position and velocity of the end-effector.The development of new cost optimised robots have introduced unwanted flexibilities in the joints and the links. It is no longer possible to get the desired performance and robustness by only measuring the motor angular positions. This thesis investigates if it is possible to estimate the end-effector position when an accelerometer is mounted at the end-effector. The main focus is to investigate Bayesian estimation methods for state estimation, here represented by the extended Kalman filter (EKF) and the particle filter (PF).A simulation study is performed on a two degrees of freedom industrial robot model using an EKF. The study emphasises three important problems to take care of in order to get a good performance. The first one is related to model errors which in general requires better identification methods. The second problem is about tuning of the EKF, i.e., the choice of covariance matrices for the measurement and process noise. It is desirable to have an automatic tuning procedure which minimises the estimation error and is robust to initial conditions of the tuned parameters. A variant of the expectation maximisation (EM) algorithm is proposed for estimation of the process noise covariance matrix Q. The EM algorithm iteratively estimates the unobserved state sequence and the matrix Q based on the observations of the process, where the extended Kalman smoother (EKS) is the instrument to find the unobserved state sequence.The third problem considers the orientation and position of the accelerometer mounted to the end-effector. A novel method to find the orientation and position of the triaxial accelerometer is proposed and evaluated on experimental data. The method consists of two consecutive steps, where the first is to estimate the orientation of the sensor from static experiments. In the second step the sensor position relative to the robot base is identified using sensor readings when the sensor moves in a circular path and where the sensor orientation is kept constant in a path fixed coordinate system.Finally, experimental evaluations are performed on an ABB IRB4600 robot. Different observers using the EKF, EKS and PF with different estimation models are proposed. The estimated paths are compared to the true path measured by a laser tracking system. There is no significant difference in performance between the six observers. Instead, execution time, model complexities and implementation issues have to be considered when choosing the method.
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