Acetylcholinesterase expression in muscle is specifically controlled by a promoter-selective enhancesome in the first intron

Mammalian acetylcholinesterase (AChE) gene expression is exquisitely regulated in target tissues and cells during differentiation. An intron located between the first and second exons governs a similar to 100-fold increase in AChE expression during myoblast to myotube differentiation in C2C12 cells. Regulation is confined to 255 bp of evolutionarily conserved sequence containing functional transcription factor consensus motifs that indirectly interact with the endogenous promoter. To examine control in vivo, this region was deleted by homologous recombination. The knock-out mouse is virtually devoid of AChE activity and its encoding mRNA in skeletal muscle, yet activities in brain and spinal cord innervating skeletal muscle are unaltered. The transcription factors MyoD and myocyte enhancer factor-2 appear to be responsible for muscle regulation. Selective control of AChE expression by this region is also found in hematopoietic lineages. Expression patterns in muscle and CNS neurons establish that virtually all AChE activity at the mammalian neuromuscular junction arises from skeletal muscle rather than from biosynthesis in the motoneuron cell body and axoplasmic transport

DiVinE-CUDA - A Tool for GPU Accelerated LTL Model Checking

In this paper we present a tool that performs CUDA accelerated LTL Model Checking. The tool exploits parallel algorithm MAP adjusted to the NVIDIA CUDA architecture in order to efficiently detect the presence of accepting cycles in a directed graph. Accepting cycle detection is the core algorithmic procedure in automata-based LTL Model Checking. We demonstrate that the tool outperforms non-accelerated version of the algorithm and we discuss where the limits of the tool are and what we intend to do in the future to avoid them

Sediment Transport of Fine Sand to Fine Gravel on Transverse Bed Slopes in Rotating Annular Flume Experiments

Large‐scale morphology, in particular meander bend depth, bar dimensions, and bifurcation dynamics, are greatly affected by the deflection of sediment transport on transverse bed slopes due to gravity and by secondary flows. Overestimating the transverse bed slope effect in morphodynamic models leads to flattening of the morphology, while underestimating leads to unrealistically steep bars and banks and a higher braiding index downstream. However, existing transverse bed slope predictors are based on a small set of experiments with a minor range of flow conditions and sediment sizes, and in practice models are calibrated on measured morphology. The objective of this research is to experimentally quantify the transverse bed slope effect for a large range of near‐bed flow conditions with varying secondary flow intensity, sediment sizes (0.17–4 mm), sediment transport mode, and bed state to test existing predictors. We conducted over 200 experiments in a rotating annular flume with counterrotating floor, which allows control of the secondary flow intensity separate from the streamwise flow velocity. Flow velocity vectors were determined with a calibrated analytical model accounting for rough bed conditions. We isolated separate effects of all important parameters on the transverse slope. Resulting equilibrium transverse slopes show a clear trend with varying sediment mobilities and secondary flow intensities that deviate from known predictors depending on Shields number, and strongly depend on bed state and sediment transport mode. Fitted functions are provided for application in morphodynamic modelin

Parallelizing Deadlock Resolution in Symbolic Synthesis of Distributed Programs

Previous work has shown that there are two major complexity barriers in the synthesis of fault-tolerant distributed programs: (1) generation of fault-span, the set of states reachable in the presence of faults, and (2) resolving deadlock states, from where the program has no outgoing transitions. Of these, the former closely resembles with model checking and, hence, techniques for efficient verification are directly applicable to it. Hence, we focus on expediting the latter with the use of multi-core technology. We present two approaches for parallelization by considering different design choices. The first approach is based on the computation of equivalence classes of program transitions (called group computation) that are needed due to the issue of distribution (i.e., inability of processes to atomically read and write all program variables). We show that in most cases the speedup of this approach is close to the ideal speedup and in some cases it is superlinear. The second approach uses traditional technique of partitioning deadlock states among multiple threads. However, our experiments show that the speedup for this approach is small. Consequently, our analysis demonstrates that a simple approach of parallelizing the group computation is likely to be the effective method for using multi-core computing in the context of deadlock resolution

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23 февраля 2011 года исполнилось 75 лет со дня рождения главного инженера Днепродзержинской ГЭС — Кучерявого Владислава Семеновича.15 июня 2011 г. исполняется 70 лет ученому — гидроэнергетику, доктору технических наук, начальнику отдела расчетного обоснования ПАО "Укргидропроект", профессору, заведующему кафедрой гидротехнического строительства Харьковского государственного технического университета строительства и архитектуры Александру Исааковичу Вайнбергу

The druggable antimalarial target PfDXR : overproduction strategies and kinetic characterization

Plasmodium falciparum 1–deoxy–D–xylulose–5–phosphate reductoisomerase (PfDXR) is a key enzyme in the synthesis of isoprenoids in the malaria parasite, using a pathway that is absent in the human host. This enzyme is receiving attention as it has been validated as a promising drug target. However, an impediment to the characterisation of this enzyme has been the inability to obtain sufficient quantities of the enzyme in a soluble and functional form. The expression of PfDXR from the codon harmonised coding region, under conditions of strongly controlled transcription and induction, resulted in a yield of 2 – 4 mg/L of enzyme, which is 8 to 10–fold higher than previously reported yields. The kinetic parameters Km, Vmax and kcat were determined for PfDXR using an NADPH–dependent assay. Residues K295 and K297, unique to species of Plasmodium and located in the catalytic hatch region; and residues V114 and N115, essential for NADPH binding, were mutated to resemble those found in E. coli DXR. Interestingly, these mutations decreased the substrate affinity of PfDXR to values resembling that of E. coli DXR. PfDXR-K295N, K297S and PfDXR-V114A, N115G demonstrated a decreased ability to turnover substrate by 4–fold and 2-fold respectively in comparison to PfDXR. This study indicates a difference in the role of the catalytic hatch in capturing substrate by species of Plasmodium. The results of this study could contribute to the development of inhibitors of PfDXR.National Research Foundation Grant awarded to AB (Thuthuka Programme) and a SAMI Grant awarded to GLB. LSS was awarded a post–doctoral bursary by the South African Malaria Initiative programme; JG was awarded a PhD bursary by SAMI and National Research Foundation and HJ was awarded an Honours bursary by Rhodes University.http://www.eurekaselect.com/628/journal/protein-amp-peptide-lettershb201

Polymerogenic neuroserpin causes mitochondrial alterations and activates NFκB but not the UPR in a neuronal model of neurodegeneration FENIB

The neurodegenerative condition FENIB (familiar encephalopathy with neuroserpin inclusion bodies) is caused by heterozygous expression of polymerogenic mutant neuroserpin (NS), with polymer deposition within the endoplasmic reticulum (ER) of neurons. We generated transgenic neural progenitor cells (NPCs) from mouse fetal cerebral cortex stably expressing either the control protein GFP or human wild type, polymerogenic G392E or truncated (delta) NS. This cellular model makes it possible to study the toxicity of polymerogenic NS in the appropriated cell type by in vitro differentiation to neurons. Our previous work showed that expression of G392E NS in differentiated NPCs induced an adaptive response through the upregulation of several genes involved in the defence against oxidative stress, and that pharmacological reduction of the antioxidant defences by drug treatments rendered G392E NS neurons more susceptible to apoptosis than control neurons. In this study, we assessed mitochondrial distribution and found a higher percentage of perinuclear localisation in G392E NS neurons, particularly in those containing polymers, a phenotype that was enhanced by glutathione chelation and rescued by antioxidant molecules. Mitochondrial membrane potential and contact sites between mitochondria and the ER were reduced in neurons expressing the G392E mutation. These alterations were associated with a pattern of ER stress that involved the ER overload response but not the unfolded protein response. Our results suggest that intracellular accumulation of NS polymers affects the interaction between the ER and mitochondria, causing mitochondrial alterations that contribute to the neuronal degeneration seen in FENIB patients

Parallel symbolic state-space exploration is difficult, but what is the alternative?

State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1) parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2) symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal

Efficient Parallel Statistical Model Checking of Biochemical Networks

We consider the problem of verifying stochastic models of biochemical networks against behavioral properties expressed in temporal logic terms. Exact probabilistic verification approaches such as, for example, CSL/PCTL model checking, are undermined by a huge computational demand which rule them out for most real case studies. Less demanding approaches, such as statistical model checking, estimate the likelihood that a property is satisfied by sampling executions out of the stochastic model. We propose a methodology for efficiently estimating the likelihood that a LTL property P holds of a stochastic model of a biochemical network. As with other statistical verification techniques, the methodology we propose uses a stochastic simulation algorithm for generating execution samples, however there are three key aspects that improve the efficiency: first, the sample generation is driven by on-the-fly verification of P which results in optimal overall simulation time. Second, the confidence interval estimation for the probability of P to hold is based on an efficient variant of the Wilson method which ensures a faster convergence. Third, the whole methodology is designed according to a parallel fashion and a prototype software tool has been implemented that performs the sampling/verification process in parallel over an HPC architecture

Triad3a induces the degradation of early necrosome to limit RipK1-dependent cytokine production and necroptosis.

Understanding the molecular signaling in programmed cell death is vital to a practical understanding of inflammation and immune cell function. Here we identify a previously unrecognized mechanism that functions to downregulate the necrosome, a central signaling complex involved in inflammation and necroptosis. We show that RipK1 associates with RipK3 in an early necrosome, independent of RipK3 phosphorylation and MLKL-induced necroptotic death. We find that formation of the early necrosome activates K48-ubiquitin-dependent proteasomal degradation of RipK1, Caspase-8, and other necrosomal proteins. Our results reveal that the E3-ubiquitin ligase Triad3a promotes this negative feedback loop independently of typical RipK1 ubiquitin editing enzymes, cIAPs, A20, or CYLD. Finally, we show that Triad3a-dependent necrosomal degradation limits necroptosis and production of inflammatory cytokines. These results reveal a new mechanism of shutting off necrosome signaling and may pave the way to new strategies for therapeutic manipulation of inflammatory responses