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- Atienza-Párraga, Alba, et al.
(author)
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Epigenomic re-configuration of primary multiple myeloma underlies the synergistic effect of combined DNMT and EZH2 inhibition.
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Other publication (other academic/artistic)abstract
- Multiple myeloma (MM) is characterized by an overexpression of EZH2 and a subsequent increase in H3K27me3-mediated silencing. However, the genome-wide redistribution of this mark in context with other epigenetic tags remains largely unexplored. Here, we show that EZH2 physically interacts with DNMT1 and that combined inhibition leads to a reduced G2/M arrest and increased apoptosis in MM. In addition, we present a catalogue of the genomic regulatory regions in normal plasma cells (NPC) as defined by their individual combination of histone marks. We used ChIP-seq and ATAC-seq data to generate whole-genome NPC chromatin annotations which we further analysed using DNA methylation arrays and RNA-seq. Comparison between NPC and MM demonstrated that, despite the global hypomethylation, enhancers show a tendency towards a higher DNA methylation levels in MM, whereas Polycomb and heterochromatic sites, highly methylated in NPC, show intermediate levels of the mark. Across all examined regulatory regions, 5-azacytidine treatment strongly reduced DNA methylation in MM. Furthermore, we find an extensive re-structuration of the global histone patterns in MM. We noticed a widespread increase in H3K27me3 except at active TSSs/promoters and enhancers, where we found a selective gain of the mark, suggestive of a directed silencing. In contrast, poised TSSs lose H3K27me3 and gain the activation mark H3K27ac, reflecting potential activation. Taken together, we present a comprehensive map of the epigenomic changes in MM as compared to NPC and provide insights into the interplay between EZH2 and DNMT1 in MM.
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| 7. |
- Jin, Junchen, et al.
(author)
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A multi-objective agent-based approach for road traffic controls: application for adaptive traffic signal systems
- 2017
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Other publication (other academic/artistic)abstract
- Agent-based approaches have gained popularity in engineering applications, but its potential for advanced traffic controls has not been sufficiently explored. This paper presents a multi-agent framework that models traffic control instruments and their interactions with road traffic. A multi-objective Markov decision process is applied to model agent operations, allowing agents to form a decision in the context of multiple policy goals. The problem is reformulated by a constrained Markov decision process (CMDP) to enhance the computational efficiency. In the study, the policy goal with the highest priority becomes the optimization objective, but the other objectives are transferred as constraints for optimization. A reinforcement learning based approach is developed with different function approximation methods used to enhance the control algorithm. For implementation of multi-objective control, a threshold lexicographic ordering method is introduced and integrated with the learning algorithm. While the multi-objective intelligent control method could be potentially applied for different road traffic controls, this paper demonstrates a case study on traffic signal control in a road network in Stockholm. Intersections are modeled as agents that can make intelligent timing decisions according to the detected traffic states and update their knowledge from system feedback. The evaluation results show the benefits offered by the control approach especially when multiple policy requirements are introduced.
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- Jin, Junchen, et al.
(author)
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A non-parametric Bayesian framework for traffic-state estimation at signalized intersections
- 2017
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Other publication (other academic/artistic)abstract
- An accurate and practical traffic-state estimation (TSE) method for signalized intersections plays an important role for real-time operations to facilitate efficient traffic management. This paper presents a generalized modeling framework for estimating traffic states at signalized intersections. The framework is non-parametric and data-driven, without the requirement on explicit models of traffic. Additionally, in principle, any type of data source together with any type of signal controller can be incorporated with the proposed framework. The Bayesian filter (BF) approach is the core of the framework and introduces a recursive state estimation process. The required transition and measurement models of the BFs are trained using Gaussian process (GP) regression models with respect to a set of historical data. A Gaussian process model uses kernel functions to describe the proximity among data points, and the hyper-parameters adopted in the GP model are optimized according to the training data. In addition to the detailed derivation of the integration of BFs and GP regression models, an algorithm based on the extended Kalman filter is presented for real-time traffic estimation. The effectiveness of the proposed framework is demonstrated through several numerical experiments using data generated in microscopic traffic simulations. Both fixed-location data (i.e., loop detector) and mobile data (i.e., connected vehicle) are examined with the framework. As a result, the method performs well for the tested traffic conditions. In particular, the estimator provides a competitive estimation accuracy merely using the position information of a small portion of vehicles at the intersection. The approach is suitable for a short-term estimation requirement, which is normally a challenging task in traffic control and operations.
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- Jin, Junchen, et al.
(author)
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Heavy-duty vehicle platoons in real traffic: simulation modeling and analysis
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Other publication (other academic/artistic)abstract
- In freight transport systems, fuel consumption can be significantly reduced by means of heavy-duty vehicle (HDV) platooning on highways. An HDV platoon refers to a group of HDVs with small intermediate distances enabled by the HDVs being equipped by sensors and controllers. It is of importance for transport authorities and industries to explore the effects on overall traffic systems by introducing HDV platooning. Although previous studies have investigated the potential benefits of HDV platooning, the control performance and effects in real traffic have barely been explored. In the present study, a simulation platform has been developed to model and analyze the effects of HDV platoons in real traffic conditions. The simulation model is based on an open-source microscopic traffic simulator, SUMO, and calibrated using data collected by a motorway control system (MCS). The current model incorporates the vehicle dynamics of HDVs in the simulation, while an HDV in a platoon is controlled by a proportional-integral-derivative (PID) controller for its longitudinal behavior. Furthermore, the PID control parameters have been optimized for a driving cycle, according to predefined criteria, while taking vehicle dynamics and stability conditions into account. A case study has been carried out by adopting HDV platooning on a highway stretch in Sweden. The performance of the HDV platoons and effects on the other vehicles on the highway have been evaluated for different scenarios through multiple simulation runs. As a result, it is found that substantial fuel reductions have been achieved for HDVs if they form platoons in the evaluation cases. The analysis of the other vehicles shows only rather small effects when HDV platooning is implemented.
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