Fundamental issues in systems biology.

types: Journal Article; Research Support, Non-U.S. Gov'tIn the context of scientists' reflections on genomics, we examine some fundamental issues in the emerging postgenomic discipline of systems biology. Systems biology is best understood as consisting of two streams. One, which we shall call 'pragmatic systems biology', emphasises large-scale molecular interactions; the other, which we shall refer to as 'systems-theoretic biology', emphasises system principles. Both are committed to mathematical modelling, and both lack a clear account of what biological systems are. We discuss the underlying issues in identifying systems and how causality operates at different levels of organisation. We suggest that resolving such basic problems is a key task for successful systems biology, and that philosophers could contribute to its realisation. We conclude with an argument for more sociologically informed collaboration between scientists and philosophers.Funding received from the Economic and Social Research Council (ESRC), UK, and Overseas Conference Funding from the British Academy

Static platelet adhesion, flow cytometry and serum TXB2 levels for monitoring platelet inhibiting treatment with ASA and clopidogrel in coronary artery disease: a randomised cross-over study

<p>Abstract</p> <p>Background</p> <p>Despite the use of anti-platelet agents such as acetylsalicylic acid (ASA) and clopidogrel in coronary heart disease, some patients continue to suffer from atherothrombosis. This has stimulated development of platelet function assays to monitor treatment effects. However, it is still not recommended to change treatment based on results from platelet function assays. This study aimed to evaluate the capacity of a static platelet adhesion assay to detect platelet inhibiting effects of ASA and clopidogrel. The adhesion assay measures several aspects of platelet adhesion simultaneously, which increases the probability of finding conditions sensitive for anti-platelet treatment.</p> <p>Methods</p> <p>With a randomised cross-over design we evaluated the anti-platelet effects of ASA combined with clopidogrel as well as monotherapy with either drug alone in 29 patients with a recent acute coronary syndrome. Also, 29 matched healthy controls were included to evaluate intra-individual variability over time. Platelet function was measured by flow cytometry, serum thromboxane B₂(TXB₂)-levels and by static platelet adhesion to different protein surfaces. The results were subjected to Principal Component Analysis followed by ANOVA, t-tests and linear regression analysis.</p> <p>Results</p> <p>The majority of platelet adhesion measures were reproducible in controls over time denoting that the assay can monitor platelet activity. Adenosine 5'-diphosphate (ADP)-induced platelet adhesion decreased significantly upon treatment with clopidogrel compared to ASA. Flow cytometric measurements showed the same pattern (r²= 0.49). In opposite, TXB₂-levels decreased with ASA compared to clopidogrel. Serum TXB₂and ADP-induced platelet activation could both be regarded as direct measures of the pharmacodynamic effects of ASA and clopidogrel respectively. Indirect pharmacodynamic measures such as adhesion to albumin induced by various soluble activators as well as SFLLRN-induced activation measured by flow cytometry were lower for clopidogrel compared to ASA. Furthermore, adhesion to collagen was lower for ASA and clopidogrel combined compared with either drug alone.</p> <p>Conclusion</p> <p>The indirect pharmacodynamic measures of the effects of ASA and clopidogrel might be used together with ADP-induced activation and serum TXB₂for evaluation of anti-platelet treatment. This should be further evaluated in future clinical studies where screening opportunities with the adhesion assay will be optimised towards increased sensitivity to anti-platelet treatment.</p

Aerodynamic Loss and Mixing Over a Cavity Flame Holder Located Downstream of Pylon-Aided Fuel Injection

Cavity-based fuel injection and flame holding found in hydrocarbon-fueled scramjet applications are of interest. The Air Force Research Lab (AFRL) and the Air Force Institute of Technology (AFIT) at Wright-Patterson Air Force Base in Ohio are investigating the enhancement of fuel-air mixing with small pylons that project into the supersonic flow upstream of a flame holder cavity. This follows previous qualitative (Mie scattering and NO-PLIF visualizations) results which suggested that injection behind pylons, may improve fuel-air mixing. Three pylons geometries (medium, tall, and wide) shaped as thin triangular wedges with a 30o inclination angle were tested and compared to baseline transverse injection without pylons at two injection pressures. The AFRL provided facility, was a supersonic (Mach 2) continuous flow wind tunnel with existing cavity and pylon setup. The goal was to measure mixing efficiency and shock loss of each pylon setup for comparison to the baseline condition of transverse injection without pylons. Non-reacting flow was measured using conventional probing and spontaneous Raman spectroscopy to obtain pitot pressure, total temperature, cone-static pressure and species concentration over the cavity downstream of the injection. Results demonstrated that pylons increase fuel penetration, while not adding significantly to shock losses or overall mixing compared to baseline

Improving Symbolic System-Level Synthesis by Solver Coordination and Domain-Specific Heuristics

Deciding binding, routing, and scheduling within system synthesis for hard real-time systems can be a challenging task. Symbolic methods leveraging results from the area of satisfiability modulo theories (SMT) solving have shown to be scalable methods for this by splitting the work between a logic solver for routing and binding, and a background theory solver performing schedulability analysis. For these methods, in order to prune the search space of infeasible implementations efficiently, a feedback by the background theory is required. It can be observed that previous approaches might fail here as feedback cannot be derived within a reasonable amount of time. We propose a coordinated synthesis approach that overcomes this issue. Here, we leverage an answer set solver as logic solver that is enhanced with a scheduling-aware binding and routing refinement. Based on the answer set solver&rsquo;s decisions for binding and routing, a background theory solver then computes time-triggered schedules to resolve resource access conflicts. If no feasible schedule exists, a feedback to the answer set solver can be derived within reasonable time. Our experiments synthesizing massively parallel hardware architectures show that our approach increases the applicability of symbolic synthesis considerably. While more than half of the investigated instances in our experiments cannot be solved in the non-coordinated approach already at small 2-dimensional 3&times;3 tiled mesh hardware architectures with 60% average computational utilization per tile, the coordinated synthesis approach scales up to 5&times;5 architectures with average utilization of 70% per tile (2.8&times; the hardware architecture size than before). Furthermore, we increase the scalability and the robustness of our approach by encoding our domain-knowledge within domain-specific heuristics in our designated answer set solver. Within our experiments, we observe that the domain-specific heuristics enable us to scale up to 6&times;6 architectures with 70% average utilization per tile

Accelerating Design Space Exploration

The size of search spaces in embedded system design is one of the most critical problems during design space exploration. Pareto-Front Arithmetics (PFA) has shown to be useful to overcome this problem by decomposing a hierarchical search space and just exploring each part of the system separately. Later, the exploration results are combined at higher levels of the hierarchy. In order to decrease the exploration time, this combination is performed in the objective space only. In general, this will lead to suboptimal and infeasible results. In this paper, we present new results regarding the trade-off between the quality of the results and the exploration time

Accelerating Design Space Exploration Using Pareto-Front Arithmetics

In this paper, we propose an approach for the synthesis of heterogeneous (embedded) systems, while exploiting a hierarchical problem structure. Particular to our approach is that we explore the set of so-called Pareto-optimal solutions, i.e., optimizing multiple objectives simultaneously. Since system complexity grows steadily leading to giant search spaces which demand for new strategies in design space exploration, we propose Pareto-Front Arithmetics (PFA) using results of subsystems to construct implementations of the top-level system. This way, we are able to reduce the exploration time dramatically. An example of an MPEG4 coder is used to show the benefit of this approach in reallife applications

Towards a unified execution model for transactions in TLM

Even though Transaction Level Modeling(TLM) with SystemC is widely being used and despite the existence of several formal models for TLM, there is no generally accepted definition of what a transaction is and how exactly to define Transaction Level Modeling. The key contribution of this paper is the analysis of TLM characteristics and a definition of transactions resulting in better analyzability of TLMs. For this purpose, transactions are restricted to the ACID properties (atomicity, consistency, isolation, and durability) known from database systems. Based on these results, a finite state machine model well suited for formal analysis will be proposed along with an implementation of the basic concepts in SystemC

Improving Symbolic System-Level Synthesis by Solver Coordination and Domain-Specific Heuristics

Deciding binding, routing, and scheduling within system synthesis for hard real-time systems can be a challenging task. Symbolic methods leveraging results from the area of satisfiability modulo theories (SMT) solving have shown to be scalable methods for this by splitting the work between a logic solver for routing and binding, and a background theory solver performing schedulability analysis. For these methods, in order to prune the search space of infeasible implementations efficiently, a feedback by the background theory is required. It can be observed that previous approaches might fail here as feedback cannot be derived within a reasonable amount of time. We propose a coordinated synthesis approach that overcomes this issue. Here, we leverage an answer set solver as logic solver that is enhanced with a scheduling-aware binding and routing refinement. Based on the answer set solver’s decisions for binding and routing, a background theory solver then computes time-triggered schedules to resolve resource access conflicts. If no feasible schedule exists, a feedback to the answer set solver can be derived within reasonable time. Our experiments synthesizing massively parallel hardware architectures show that our approach increases the applicability of symbolic synthesis considerably. While more than half of the investigated instances in our experiments cannot be solved in the non-coordinated approach already at small 2-dimensional 3×3 tiled mesh hardware architectures with 60% average computational utilization per tile, the coordinated synthesis approach scales up to 5×5 architectures with average utilization of 70% per tile (2.8× the hardware architecture size than before). Furthermore, we increase the scalability and the robustness of our approach by encoding our domain-knowledge within domain-specific heuristics in our designated answer set solver. Within our experiments, we observe that the domain-specific heuristics enable us to scale up to 6×6 architectures with 70% average utilization per tile

Exact Design Space Exploration Based on Consistent Approximations

The aim of design space exploration (DSE) is to identify implementations with optimal quality characteristics which simultaneously satisfy all imposed design constraints. Hence, besides searching for new solutions, a quality evaluation has to be performed for each design point. This process is typically very expensive and takes a majority of the exploration time. As nearly all the explored design points are sub-optimal, most of them get discarded after evaluation. However, evaluating a solution takes virtually the same amount of time for both good and bad ones. That way, a huge amount of computing power is literally wasted. In this paper, we propose a solution to the aforementioned problem by integrating efficient approximations in the background of a DSE engine in order to allow an initial evaluation of each solution. Only if the approximated quality indicates a promising candidate, the time-consuming exact evaluation is executed. The novelty of our approach is that (1) although the evaluation process is accelerated by using approximations, we do not forfeit the quality of the acquired solutions and (2) the integration in a background theory allows sophisticated reasoning techniques to prune the search space with the help of the approximation results. We have conducted an experimental evaluation of our approach by investigating the dependency of the accuracy of used approximations on the performance gain. Based on 120 electronic system level problem instances, we show that our approach is able to increase the overall exploration coverage by up to six times compared to a conservative DSE whenever accurate approximation functions are available