Investigating modularity in the analysis of process algebra models of biochemical systems

Compositionality is a key feature of process algebras which is often cited as one of their advantages as a modelling technique. It is certainly true that in biochemical systems, as in many other systems, model construction is made easier in a formalism which allows the problem to be tackled compositionally. In this paper we consider the extent to which the compositional structure which is inherent in process algebra models of biochemical systems can be exploited during model solution. In essence this means using the compositional structure to guide decomposed solution and analysis. Unfortunately the dynamic behaviour of biochemical systems exhibits strong interdependencies between the components of the model making decomposed solution a difficult task. Nevertheless we believe that if such decomposition based on process algebras could be established it would demonstrate substantial benefits for systems biology modelling. In this paper we present our preliminary investigations based on a case study of the pheromone pathway in yeast, modelling in the stochastic process algebra Bio-PEPA

Process Calculi Abstractions for Biology

Several approaches have been proposed to model biological systems by means of the formal techniques and tools available in computer science. To mention just a few of them, some representations are inspired by Petri Nets theory, and some other by stochastic processes. A most recent approach consists in interpreting the living entities as terms of process calculi where the behavior of the represented systems can be inferred by applying syntax-driven rules. A comprehensive picture of the state of the art of the process calculi approach to biological modeling is still missing. This paper goes in the direction of providing such a picture by presenting a comparative survey of the process calculi that have been used and proposed to describe the behavior of living entities. This is the preliminary version of a paper that was published in Algorithmic Bioprocesses. The original publication is available at http://www.springer.com/computer/foundations/book/978-3-540-88868-

Design and Development of Software Tools for Bio-PEPA

This paper surveys the design of software tools for the Bio-PEPA process algebra. Bio-PEPA is a high-level language for modelling biological systems such as metabolic pathways and other biochemical reaction networks. Through providing tools for this modelling language we hope to allow easier use of a range of simulators and model-checkers thereby freeing the modeller from the responsibility of developing a custom simulator for the problem of interest. Further, by providing mappings to a range of different analysis tools the Bio-PEPA language allows modellers to compare analysis results which have been computed using independent numerical analysers, which enhances the reliability and robustness of the results computed.

SiSeRHMap v1.0: A simulator for mapped seismic response using a hybrid model

SiSeRHMap is a computerized methodology capable of drawing up prediction maps of seismic response. It was realized on the basis of a hybrid model which combines different approaches and models in a new and non-conventional way. These approaches 5 and models are organized in a code-architecture composed of five interdependent modules. A GIS (Geographic Information System) Cubic Model (GCM), which is a layered computational structure based on the concept of lithodynamic units and zones, aims at reproducing a parameterized layered subsoil model. A metamodeling process confers a hybrid nature to the methodology. In this process, the one-dimensional linear 10 equivalent analysis produces acceleration response spectra of shear wave velocitythickness profiles, defined as trainers, which are randomly selected in each zone. Subsequently, a numerical adaptive simulation model (Spectra) is optimized on the above trainer acceleration response spectra by means of a dedicated Evolutionary Algorithm (EA) and the Levenberg–Marquardt Algorithm (LMA) as the final optimizer. In the fi15 nal step, the GCM Maps Executor module produces a serial map-set of a stratigraphic seismic response at different periods, grid-solving the calibrated Spectra model. In addition, the spectra topographic amplification is also computed by means of a numerical prediction model. This latter is built to match the results of the numerical simulations related to isolate reliefs using GIS topographic attributes. In this way, different sets 20 of seismic response maps are developed, on which, also maps of seismic design response spectra are defined by means of an enveloping technique

Aspirin-dependent effects on purinergic P2Y1 receptor express

Chronic treatment with aspirin in healthy volunteers (HVs) is associated with recovery of adenosine diphosphate (ADP)-induced platelet activation. The purinergic P2Y1 receptor exerts its effects via a Gq-protein, which is the same biochemical pathway activated by thromboxane-A2 receptor. We hypothesized that recovery of ADP-induced platelet activation could be attributed to increased P2Y1 expression induced by chronic aspirin exposure. We performed a multi-phase investigation which embraced both in vitro and in vivo experiments conducted in (1) human megakaryoblastic DAMI cells, (2) human megakaryocytic progenitor cell cultures, (3) platelets obtained from HVs treated with aspirin and (4) platelets obtained from aspirin-treated patients. DAMI cells treated with aspirin or WY14643 (PPARα agonist) had a significant up-regulation of P2Y1 mRNA, which was shown to be a PPARα-dependent process. In human megakaryocytic progenitors, in the presence of aspirin or WY14643, P2Y1 mRNA expression was higher than in mock culture. P2Y1 expression increased in platelets obtained from HVs treated with aspirin for 8 weeks. Platelets obtained from patients who were on aspirin for more than 2 months had increased P2Y1 expression and ADP-induced aggregation compared with patients on aspirin treatment for less than a month. Overall, our results suggest that aspirin induces genomic changes in megakaryocytes leading to P2Y1 up-regulation and that PPARα is the nuclear receptor involved in this regulation. Since P2Y1 is coupled to the same Gq-protein of thromboxane-A2 receptor, platelet adaptation in response to pharmacological inhibition seems not to be receptor specific, but may involve other receptors with the same biochemical pathway

Segmentation of lung fields in digital chest radiographs by artificial neural networks

Lung field segmentation is a basic step for virtually any quantitative procedure. In this view, due to the imaging process and the complexity of the imaged district, an efficient use of prior anatomical knowledge is crucial. In this report we describe a new approach to lung field segmentation which is based on fuzzy boundary modeling and a neural network architecture including supervised multilayer networks and topology preserving maps

Modelling the effect of SMP production and external carbon addition on S-driven autotrophic denitrification

The aim of this study was to develop a mathematical model to assess the effect of soluble microbial products production and external carbon source addition on the performance of a sulfur-driven autotrophic denitrification (SdAD) process. During SdAD, the growth of autotrophic biomass (AUT) was accompanied by the proliferation of heterotrophic biomass mainly consisting of heterotrophic denitrifiers (HD) and sulfate-reducing bacteria (SRB), which are able to grow on both the SMP derived from the microbial activities and on an external carbon source. The process was supposed to occur in a sequencing batch reactor to investigate the effects of the COD injection on both heterotrophic species and to enhance the production and consumption of SMP. The mathematical model was built on mass balance considerations and consists of a system of nonlinear impulsive differential equations, which have been solved numerically. Different simulation scenarios have been investigated by varying the main operational parameters: cycle duration, day of COD injection and quantity of COD injected. For cycle durations of more than 15 days and a COD injection after the half-cycle duration, SdAD represents the prevailing process and the SRB represent the main heterotrophic family. For shorter cycle duration and COD injections earlier than the middle of the cycle, the same performance can be achieved increasing the quantity of COD added, which results in an increased activity of HD. In all the performed simulation even in the case of COD addition, AUT remain the prevailing microbial family in the reactor

Sudden onset acute liver failure in a patient with clinically occult small cell lung carcinoma: autopsy report and review of the medical literature

Liver metastases are commonly found in advanced cancer patients; however, acute liver failure secondary to diffuse liver infiltration is rare. Small cell lung carcinoma accounts for 15% of lung carcinomas. We describe the ninth case of small cell lung carcinoma massively metastatic to the liver, reported in the scientific literature, with sudden clinical onset and death after a few days. An autopsy was performed to understand the cause of death

Rhabdomyosarcoma mimicking lymphangioma: report of three cases

oai:eyereports.org:article/37We report three cases of proptosis, in children aged 6, 10 and 12, whereby in all cases the first clinical, radiologic and ultrasonographic diagnosis was lymphangioma, while the final anatomopathological diagnosis was rhabdomyosarcoma. In presence of a rapidly worsening exophthalmos or eyelid swelling in a child, an early correct diagnosis is very important. Imaging techniques play a very important role in the diagnosis, but are often inconclusive and an excisional biopsy (if feasible) must always be considere