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See detailHuman telomerase reverse transcriptase depletion potentiates the growth- T inhibitory activity of imatinib in chronic myeloid leukemia stem cells
Grandjenettea, Cindy; Schnekenburger, Michael; Gaigneaux, Anthoula UL et al

in Cancer Letters (2020)

Although tyrosine kinase inhibitors (TKIs) revolutionized the management of chronic myeloid leukemia (CML), resistance against TKIs and leukemia stem cell (LSC) persistence remain a clinical concern ... [more ▼]

Although tyrosine kinase inhibitors (TKIs) revolutionized the management of chronic myeloid leukemia (CML), resistance against TKIs and leukemia stem cell (LSC) persistence remain a clinical concern. Therefore, new therapeutic strategies combining conventional and novel therapies are urgently needed. Since telomerase is involved in oncogenesis and tumor progression but is silent in most human normal somatic cells, it may be an interesting target for CML therapy by selectively targeting cancer cells while minimizing effects on normal cells. Here, we report that hTERT expression is associated with CML disease progression. We also provide evidence that hTERT-deficient K-562 cells do not display telomere shortening and that telomere length is maintained through the ALT pathway. Furthermore, we show that hTERT depletion exerts a growth-inhibitory effect in K- 562 cells and potentiates imatinib through alteration of cell cycle progression leading to a senescence-like phenotype. Finally, we demonstrate that hTERT depletion potentiates the imatinib-induced reduction of the ALDH+-LSC population. Altogether, our results suggest that the combination of telomerase and TKI should be considered as an attractive strategy to treat CML patients to eradicate cancer cells and prevent relapse by tar- geting LSCs. [less ▲]

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See detailThe low-dimensional algebraic cohomology of the Witt and the Virasoro algebra with values in natural modules
Ecker, Jill Marie-Anne UL; Schlichenmaier, Martin UL

in Banach Center Publications (2020)

The main aim of this contribution is to compute the low-dimensional algebraic cohomology of the Witt and the Virasoro algebra with values in the adjoint and the trivial module. The last section includes ... [more ▼]

The main aim of this contribution is to compute the low-dimensional algebraic cohomology of the Witt and the Virasoro algebra with values in the adjoint and the trivial module. The last section includes results for the general tensor densities modules, presented without proof. One of our main results is that the third algebraic cohomology of the Witt algebra with values in the adjoint module vanishes, while it is one-dimensional for the Virasoro algebra. The first and the second algebraic cohomology of the Witt and the Virasoro algebra with values in tensor densities modules vanish for almost all modules. In the case they do not vanish, we give explicit expressions for the generating cocycles. In our work, we consider algebraic cohomology and not only the sub-complex of continuous cohomology, meaning we do not put any continuity constraints on the cochains. Consequently, our results are independent of any choice of an underlying topology, and valid for any concrete realizations of the considered Lie algebras. [less ▲]

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See detailA Statistical View on Calcium Oscillations.
Powell, Jake; Falcke, Martin; Skupin, Alexander UL et al

in Advances in experimental medicine and biology (2020), 1131

Transient rises and falls of the intracellular calcium concentration have been observed in numerous cell types and under a plethora of conditions. There is now a growing body of evidence that these whole ... [more ▼]

Transient rises and falls of the intracellular calcium concentration have been observed in numerous cell types and under a plethora of conditions. There is now a growing body of evidence that these whole-cell calcium oscillations are stochastic, which poses a significant challenge for modelling. In this review, we take a closer look at recently developed statistical approaches to calcium oscillations. These models describe the timing of whole-cell calcium spikes, yet their parametrisations reflect subcellular processes. We show how non-stationary calcium spike sequences, which e.g. occur during slow depletion of intracellular calcium stores or in the presence of time-dependent stimulation, can be analysed with the help of so-called intensity functions. By utilising Bayesian concepts, we demonstrate how values of key parameters of the statistical model can be inferred from single cell calcium spike sequences and illustrate what information whole-cell statistical models can provide about the subcellular mechanistic processes that drive calcium oscillations. In particular, we find that the interspike interval distribution of HEK293 cells under constant stimulation is captured by a Gamma distribution. [less ▲]

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See detailDe 15-puzzel
Perucca, Antonella UL

Article for general public (2020)

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See detailDe zeven bruggen van Koningsbergen
Perucca, Antonella UL

Article for general public (2020)

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See detailAssociate Editor, Journal of International Financial Markets, Institutions and Money
Wolff, Christian UL

Diverse speeches and writings (2020)

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See detailAssociate Editor, Pacific Basin Finance Journal
Wolff, Christian UL

Diverse speeches and writings (2020)

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See detailKummer theory for number fields
Perucca, Antonella UL; Sgobba, Pietro UL; Tronto, Sebastiano UL

in Proceedings of the Roman Number Theory Association (2020)

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See detailLearning to lose control: A process-based account of behavioral addiction.
Perales, Jose C.; King, Daniel L.; Navas, Juan F. et al

in Neuroscience and biobehavioral reviews (2020), 108

Learning psycho(bio)logy has developed a solid corpus of evidence and theory regarding behavior control modes. The present article briefly reviews that literature and its influence on recent models in ... [more ▼]

Learning psycho(bio)logy has developed a solid corpus of evidence and theory regarding behavior control modes. The present article briefly reviews that literature and its influence on recent models in which the transition from goal-directed to compulsive behavior is identified as the main process underlying substance use disorders. This literature is also relevant to non-substance addictive disorders, and serves as basis to propose a restricted definition of behavioral addiction relying on the presence of behavior-specific compulsivity. Complementarily, we consider whether some activities can become disordered while remaining mostly goal-driven. Based on reinforcement learning models, relative outcome utility computation is proposed as an alternative mechanism through which dysfunctional behaviors (even not qualifying as addictive) can override adaptive ones, causing functional impairment. Beyond issues of conceptual delimitation, recommendations are made regarding the importance of identifying individual etiological pathways to dysregulated behavior, the necessity of accurately profiling at-risk individuals, and the potential hazards of symptom-based diagnosis. In our view, the validity of these recommendations does not depend on the position one takes in the nosological debate. [less ▲]

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See detailMachine learning in nanoscience: big data at small scales
Brown, Keith A.; Brittman, Sarah; Maccaferri, Nicolò UL et al

in Nano Letters (2020), 20(1), 2-10

Recent advances in machine learning (ML) offer new tools to extract new insights from large data sets and to acquire small data sets more effectively. Researchers in nanoscience are experimenting with ... [more ▼]

Recent advances in machine learning (ML) offer new tools to extract new insights from large data sets and to acquire small data sets more effectively. Researchers in nanoscience are experimenting with these tools to tackle challenges in many fields. In addition to ML’s advancement of nanoscience, nanoscience provides the foundation for neuromorphic computing hardware to expand the implementation of ML algorithms. In this mini-review, which is not able to be comprehensive, we highlight some recent efforts to connect the ML and nanoscience communities focusing on three types of interaction: (1) using ML to analyze and extract new information from large nanoscience data sets, (2) applying ML to accelerate materials discovery, including the use of active learning to guide experimental design, and (3) the nanoscience of memristive devices to realize hardware tailored for ML. We conclude with a discussion of challenges and opportunities for future interactions between nanoscience and ML researchers. [less ▲]

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See detailMember, Management Board, European Banking Center Network
Wolff, Christian UL

Diverse speeches and writings (2020)

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See detailClarifying the Role of Negative Emotions in the Origin and Control of Impulsive Actions.
Eben, Charlotte; Billieux, Joël UL; Verbruggen, Frederick

in Psychologica Belgica (2020), 60(1), 1-17

This critical review elaborates on the origin of impulsive actions and how these can be controlled. We focus in particular on the role of negative events. First, we outline how impulsive actions often ... [more ▼]

This critical review elaborates on the origin of impulsive actions and how these can be controlled. We focus in particular on the role of negative events. First, we outline how impulsive actions often originate from negative events that are (emotionally) appraised. A discrepancy between this current state and a desired goal state leads to action tendencies. The urgency of the resulting action depends on the importance of the goal and the size of the discrepancy. Second, we discuss how such impulsive actions can be regulated or controlled e.g. by biasing competition between different options, or by completely suppressing all motor output. Importantly, such control mechanisms might also depend on emotional factors. To reconcile these findings, we present a coherent theoretical framework, taking into account various cognitive, affective, and motivational mechanisms as well as contextual factors that play a crucial role in the origin and control of impulsive actions. [less ▲]

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See detailModeling and Implementation of 5G Edge Caching over Satellite
Vu, Thang Xuan UL; Poirier, Yannick; Chatzinotas, Symeon UL et al

in International Journal of Satellite Communications and Networking (2020)

The fifth generation (5G) wireless networks have to deal with the high data rate and stringent latency requirements due to the massive invasion of connected devices and data-hungry applications. Edge ... [more ▼]

The fifth generation (5G) wireless networks have to deal with the high data rate and stringent latency requirements due to the massive invasion of connected devices and data-hungry applications. Edge caching is a promising technique to overcome these challenges by prefetching the content closer to the end users at the edge node’s local storage. In this paper, we analyze the performance of edge caching 5G networks with the aid of satellite communication systems. Firstly, we investigate the satellite-aided edge caching systems in two promising use cases: a) in dense urban areas, and b) in sparsely populated regions, e.g., rural areas. Secondly, we study the effectiveness of satellite systems via the proposed satellite-aided caching algorithm, which can be used in three configurations: i) mono-beam satellite, ii) multi-beam satellite, and iii) hybrid mode. Thirdly, the proposed caching algorithm is evaluated by using both empirical Zipf-distribution data and the more realistic Movielens dataset. Last but not least, the proposed caching scheme is implemented and tested by our developed demonstrators which allow real-time analysis of the cache hit ratio and cost analysis. [less ▲]

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See detailUnderstanding the Evolution of Android App Vulnerabilities
Gao, Jun UL; li, li; Bissyande, Tegawendé François D Assise UL et al

in IEEE Transactions on Reliability (2020)

The Android ecosystem today is a growing universe of a few billion devices, hundreds of millions of users and millions of applications targeting a wide range of activities where sensitive information is ... [more ▼]

The Android ecosystem today is a growing universe of a few billion devices, hundreds of millions of users and millions of applications targeting a wide range of activities where sensitive information is collected and processed. Security of communication and privacy of data are thus of utmost importance in application development. Yet, regularly, there are reports of successful attacks targeting Android users. While some of those attacks exploit vulnerabilities in the Android OS, others directly concern application-level code written by a large pool of developers with varying experience. Recently, a number of studies have investigated this phenomenon, focusing however only on a specific vulnerability type appearing in apps, and based on only a snapshot of the situation at a given time. Thus, the community is still lacking comprehensive studies exploring how vulnerabilities have evolved over time, and how they evolve in a single app across developer updates. Our work fills this gap by leveraging a data stream of 5 million app packages to re-construct versioned lineages of Android apps and finally obtained 28;564 app lineages (i.e., successive releases of the same Android apps) with more than 10 app versions each, corresponding to a total of 465;037 apks. Based on these app lineages, we apply state-of- the-art vulnerability-finding tools and investigate systematically the reports produced by each tool. In particular, we study which types of vulnerabilities are found, how they are introduced in the app code, where they are located, and whether they foreshadow malware. We provide insights based on the quantitative data as reported by the tools, but we further discuss the potential false positives. Our findings and study artifacts constitute a tangible knowledge to the community. It could be leveraged by developers to focus verification tasks, and by researchers to drive vulnerability discovery and repair research efforts. [less ▲]

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See detailApproximation-Refinement Testing of Compute-Intensive Cyber-Physical Models: An Approach Based on System Identification
Menghi, Claudio UL; Nejati, Shiva UL; Briand, Lionel UL et al

in Proceedings of the 42st International Conference on Software Engineering (2020)

Black-box testing has been extensively applied to test models of Cyber-Physical systems (CPS) since these models are not often amenable to static and symbolic testing and verification. Black-box testing ... [more ▼]

Black-box testing has been extensively applied to test models of Cyber-Physical systems (CPS) since these models are not often amenable to static and symbolic testing and verification. Black-box testing, however, requires to execute the model under test for a large number of candidate test inputs. This poses a challenge for a large and practically-important category of CPS models, known as compute-intensive CPS (CI-CPS) models, where a single simulation may take hours to complete. We propose a novel approach, namely ARIsTEO, to enable effective and efficient testing of CI-CPS models. Our approach embeds black-box testing into an iterative approximation-refinement loop. At the start, some sampled inputs and outputs of the CI-CPS model under test are used to generate a surrogate model that is faster to execute and can be subjected to black-box testing. Any failure-revealing test identified for the surrogate model is checked on the original model. If spurious, the test results are used to refine the surrogate model to be tested again. Otherwise, the test reveals a valid failure. We evaluated ARIsTEO by comparing it with S-Taliro, an open-source and industry-strength tool for testing CPS models. Our results, obtained based on five publicly-available CPS models, show that, on average, ARIsTEO is able to find 24% more requirements violations than S-Taliro and is 31% faster than S-Taliro in finding those violations. We further assessed the effectiveness and efficiency of ARIsTEO on a large industrial case study from the satellite domain. In contrast to S-Taliro, ARIsTEO successfully tested two different versions of this model and could identify three requirements violations, requiring four hours, on average, for each violation. [less ▲]

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See detailAttribute evaluation on attack trees with incomplete information
Buldas, Ahto; Gadyatskaya, Olga UL; Lenin, Aleksandr et al

in Computers and Security (2020), 88(101630),

Attack trees are considered a useful tool for security modelling because they support qualitative as well as quantitative analysis. The quantitative approach is based on values associated to each node in ... [more ▼]

Attack trees are considered a useful tool for security modelling because they support qualitative as well as quantitative analysis. The quantitative approach is based on values associated to each node in the tree, expressing, for instance, the minimal cost or probability of an attack. Current quantitative methods for attack trees allow the analyst to, based on an initial assignment of values to the leaf nodes, derive the values of the higher nodes in the tree. In practice, however, it shows to be very difficult to obtain reliable values for all leaf nodes. The main reasons are that data is only available for some of the nodes, that data is available for intermediate nodes rather than for the leaf nodes, or even that the available data is inconsistent. We address these problems by developing a generalisation of the standard bottom-up calculation method in three ways. First, we allow initial attributions of non-leaf nodes. Second, we admit additional relations between attack steps beyond those provided by the underlying attack tree semantics. Third, we support the calculation of an approximative solution in case of inconsistencies. We illustrate our method, which is based on constraint programming, by a comprehensive case study. [less ▲]

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See detailNouvelles perspectives sur les maternités. Regards croisés des Sciences et de la littérature
Barthelmebs, Hélène UL; Raguin, Marjolaine

Book published by Peter Lang (2020)

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See detailNormal approximation for functions of hidden Markov models
Kerchev, George UL

E-print/Working paper (2020)

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