Targeting ATM pathway for therapeutic intervention in cancer

The Ataxia Telangiectasia Mutated gene encodes the ATM protein, a key element in the DNA damage response (DDR) signalling pathway responsible for maintaining genomic integrity within the cell. The ATM protein belongs to a family of large protein kinases containing the phosphatidylinositol-3 catalytic domain, including ATM, ATR and PI3K. ATM provides the crucial link between DNA damage, cell cycle progression and cell death by first sensing double stranded DNA breaks and subsequently phosphorylating and activating other downstream proteins functioning in DNA damage repair, cell cycle arrest and apoptotic pathways,. Mammalian cells are constantly challenged by genotoxic agents from a variety of sources and therefore require a robust sensing and repair mechanism to maintain DNA integrity or activate alternative cell fate pathways. This review covers the role of ATM in DDR signalling and describes the interaction of the ATM kinase with other proteins in order to fulfil its various functions. Special emphasis is given to how the growing knowledge of the DDR can help identify drug targets for cancer therapy, thus providing a rationale for exploiting the ATM pathway in anticancer drug development. Moreover, we discuss how a network modelling approach can be used to identify and characterise ATM inhibitors and predict their therapeutic potential

MICRODENSITOMETRIC STUDIES ON NUCLEI OF TISSUE CULTURES FROM HUMAN EMBRYONAL KIDNEY, INFECTED WITH VIRUSES OF THE ECHO AND ADENO GROUPS

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Electrical activation and electron spin coherence of ultra low dose antimony implants in silicon

We implanted ultra low doses (2x10^11 cm-2) of 121Sb ions into isotopically enriched 28Si and find high degrees of electrical activation and low levels of dopant diffusion after rapid thermal annealing. Pulsed Electron Spin Resonance shows that spin echo decay is sensitive to the dopant depths, and the interface quality. At 5.2 K, a spin decoherence time, T2, of 0.3 ms is found for profiles peaking 50 nm below a Si/SiO2 interface, increasing to 0.75 ms when the surface is passivated with hydrogen. These measurements provide benchmark data for the development of devices in which quantum information is encoded in donor electron spins

Quantitative Regular Expressions for Arrhythmia Detection Algorithms

Motivated by the problem of verifying the correctness of arrhythmia-detection algorithms, we present a formalization of these algorithms in the language of Quantitative Regular Expressions. QREs are a flexible formal language for specifying complex numerical queries over data streams, with provable runtime and memory consumption guarantees. The medical-device algorithms of interest include peak detection (where a peak in a cardiac signal indicates a heartbeat) and various discriminators, each of which uses a feature of the cardiac signal to distinguish fatal from non-fatal arrhythmias. Expressing these algorithms' desired output in current temporal logics, and implementing them via monitor synthesis, is cumbersome, error-prone, computationally expensive, and sometimes infeasible. In contrast, we show that a range of peak detectors (in both the time and wavelet domains) and various discriminators at the heart of today's arrhythmia-detection devices are easily expressible in QREs. The fact that one formalism (QREs) is used to describe the desired end-to-end operation of an arrhythmia detector opens the way to formal analysis and rigorous testing of these detectors' correctness and performance. Such analysis could alleviate the regulatory burden on device developers when modifying their algorithms. The performance of the peak-detection QREs is demonstrated by running them on real patient data, on which they yield results on par with those provided by a cardiologist.Comment: CMSB 2017: 15th Conference on Computational Methods for Systems Biolog

Early sexual dimorphism in the developing gut microbiome of northern elephant seals

The gut microbiome is an integral part of a species’ ecology, but we know little about how host characteristics impact its development in wild populations. Here, we explored the role of such intrinsic factors in shaping the gut microbiome of northern elephant seals during a critical developmental window of six weeks after weaning, when the pups stay ashore without feeding. We found substantial sex-differences in the early-life gut microbiome, even though males and females could not yet be distinguished morphologically. Sex and age both explained around 15% of the variation in gut microbial beta diversity, while microbial communities sampled from the same individual showed high levels of similarity across time, explaining another 40% of the variation. Only a small proportion of the variation in beta diversity was explained by health status, assessed by full blood counts, but clinically healthy individuals had a greater microbial alpha diversity than their clinically abnormal peers. Across the post-weaning period, the northern elephant seal gut microbiome was highly dynamic. We found evidence for several colonisation and extinction events as well as a decline in Bacteroides and an increase in Prevotella, a pattern that has previously been associated with the transition from nursing to solid food. Lastly, we show that genetic relatedness was correlated with gut microbiome similarity in males but not females, again reflecting early sex-differences. Our study represents a naturally diet-controlled and longitudinal investigation of how intrinsic factors shape the early gut microbiome in a species with extreme sex differences in morphology and life history

Counterexample-Guided Polynomial Loop Invariant Generation by Lagrange Interpolation

We apply multivariate Lagrange interpolation to synthesize polynomial quantitative loop invariants for probabilistic programs. We reduce the computation of an quantitative loop invariant to solving constraints over program variables and unknown coefficients. Lagrange interpolation allows us to find constraints with less unknown coefficients. Counterexample-guided refinement furthermore generates linear constraints that pinpoint the desired quantitative invariants. We evaluate our technique by several case studies with polynomial quantitative loop invariants in the experiments

PrIC3: Property Directed Reachability for MDPs

IC3 has been a leap forward in symbolic model checking. This paper proposes PrIC3 (pronounced pricy-three), a conservative extension of IC3 to symbolic model checking of MDPs. Our main focus is to develop the theory underlying PrIC3. Alongside, we present a first implementation of PrIC3 including the key ingredients from IC3 such as generalization, repushing, and propagation

Non-polynomial Worst-Case Analysis of Recursive Programs

We study the problem of developing efficient approaches for proving worst-case bounds of non-deterministic recursive programs. Ranking functions are sound and complete for proving termination and worst-case bounds of nonrecursive programs. First, we apply ranking functions to recursion, resulting in measure functions. We show that measure functions provide a sound and complete approach to prove worst-case bounds of non-deterministic recursive programs. Our second contribution is the synthesis of measure functions in nonpolynomial forms. We show that non-polynomial measure functions with logarithm and exponentiation can be synthesized through abstraction of logarithmic or exponentiation terms, Farkas' Lemma, and Handelman's Theorem using linear programming. While previous methods obtain worst-case polynomial bounds, our approach can synthesize bounds of the form $\mathcal{O}(n\log n)$ as well as $\mathcal{O}(n^r)$ where $r$ is not an integer. We present experimental results to demonstrate that our approach can obtain efficiently worst-case bounds of classical recursive algorithms such as (i) Merge-Sort, the divide-and-conquer algorithm for the Closest-Pair problem, where we obtain $\mathcal{O}(n \log n)$ worst-case bound, and (ii) Karatsuba's algorithm for polynomial multiplication and Strassen's algorithm for matrix multiplication, where we obtain $\mathcal{O}(n^r)$ bound such that $r$ is not an integer and close to the best-known bounds for the respective algorithms.Comment: 54 Pages, Full Version to CAV 201

The complex TIE between macrophages and angiogenesis

Macrophages are primarily known as phagocytic immune cells, but they also play a role in diverse processes, such as morphogenesis, homeostasis and regeneration. In this review, we discuss the influence of macrophages on angiogenesis, the process of new blood vessel formation from the pre-existing vasculature. Macrophages play crucial roles at each step of the angiogenic cascade, starting from new blood vessel sprouting to the remodelling of the vascular plexus and vessel maturation. Macrophages form promising targets for both pro- and anti-angiogenic treatments. However, to target macrophages, we will first need to understand the mechanisms that control the functional plasticity of macrophages during each of the steps of the angiogenic cascade. Here, we review recent insights in this topic. Special attention will be given to the TIE2-expressing macrophage (TEM), which is a subtype of highly angiogenic macrophages that is able to influence angiogenesis via the angiopoietin-TIE pathway