Development of a stochastic simulator for biological systems based on Calculus of Looping Sequences.

Molecular Biology produces a huge amount of data concerning the behavior of the single constituents of living organisms. Nevertheless, this reductionism view is not sucient to gain a deep comprehension of how such components interact together at the system level, generating the set of complex behavior we observe in nature. This is the main motivation of the rising of one of the most interesting and recent applications of computer science: Computational Systems Biology, a new science integrating experimental activity and mathematical modeling in order to study the organization principles and the dynamic behavior of biological systems. Among the formalisms that either have been applied to or have been inspired by biological systems there are automata based models, rewrite systems, and process calculi. Here we consider a formalism based on term rewriting called Calculus of Looping Sequences (CLS) aimed to model chemical and biological systems. In order to quantitatively simulate biological systems a stochastic extension of CLS has been developed; it allows to express rule schemata with the simplicity of notation of term rewriting and has some semantic means which are common in process calculi. In this thesis we carry out the study of the implementation of a stochastic simulator for the CLS formalism. We propose an extension of Gillespie's stochastic simulation algorithm that handles rule schemata with rate functions, and we present an efficient bottom-up, pre-processing based, CLS pattern matching algorithm. A simulator implementing the ideas introduced in this thesis, has been developed in F#, a multi-paradigm programming language for .NET framework modeled on OCaml. Although F# is a research project, still under continuous development, it has a product quality performance. It merges seamlessly the object oriented, the functional and the imperative programming paradigms, allowing to exploit the performance, the portability and the tools of .NET framework

Different media and supplements modulate the clonogenic and expansion properties of rabbit bone marrow mesenchymal stem cells

<p>Abstract</p> <p>Background -</p> <p>Rabbits provide an excellent model for many animal and human diseases, such as cardiovascular diseases, for the development of new vaccines in wound healing management and in the field of tissue engineering of tendon, cartilage, bone and skin.</p> <p>The study presented herein aims to investigate the biological properties of bone marrow rabbit MSCs cultured in different conditions, in order to provide a basis for their clinical applications in veterinary medicine.</p> <p>Findings -</p> <p>MSCs were isolated from 5 New Zealand rabbits. Fold increase, CFU number, doubling time, differentiation ability and immunophenotype were analyzed.</p> <p>With the plating density of 10 cells/cm²the fold increase was significantly lower with DMEM-20%FCS and MSCs growth was significantly higher with αMEM-hEGF. The highest clonogenic ability was found at 100 cell/cm²with MSCBM and at 10 cell/cm²with M199. Both at 10 and 100 cells/cm², in αMEM medium, the highest CFU increase was obtained by adding bFGF. Supplementing culture media with 10%FCS-10%HS determined a significant increase of CFU.</p> <p>Conclusion -</p> <p>Our data suggest that different progenitor cells with differential sensitivity to media, sera and growth factors exist and the choice of culture conditions has to be carefully considered for MSC management.</p

Abstract probabilistic semantics for the analysis of biological systems models

This Thesis concerns the development of probabilistic semantics tailored to model the dynamic behavior of biological systems in order to formally analyze them. More specifically, it attempts to overcome problems, related to uncertainty and to the state space explosion, inherent to models describing biological systems. Recently, many formalisms originated from Computer Science have been successfully applied to describe biological systems. Many of these formalisms include probabilistic aspects, and techniques like stochastic simulation and probabilistic model checking have been proposed to study biological systems properties. However, the practical application of formal analysis tools in this context is still limited. The size of state space associated with models is often prohibitively large. Moreover, the knowledge of biological processes is often incomplete, resulting in models with uncertain parameters. For these reasons the application of available Computer Science tools is often difficult. In addition, usual tools deal with models in which concurrency is described by interleaving semantics. However, interleaving is not suitable for modelling certain classes of biological systems. To overcome these problems, in this Thesis, we propose to apply abstraction techniques to probabilistic semantics of biological systems models. The application of such techniques presents several advantages. On one hand, these techniques can help in reducing the state space associated to models. On the other hand, they can help in handling models with uncertainty. About the management of uncertainty in models, we consider the uncertainty in stochastic parameters. Often, having incomplete knowledge of the kinetics of a system, we are not able to choose among models differing only for parameters. Hence, we define a framework to study models with parameters expressed as intervals, obtaining results that hold for all models with parameters included in the specified intervals. In more detail, probabilistic model checking can be performed on biochemical reactions systems models when kinetic rates, expressing the propensity of the interaction events, are not expressed precisely as point values, but as intervals. We define an effective method to derive an abstract semantics for such models and to obtain conservative bounds on probability of reachability properties. The abstract semantics, given in terms of Interval Markov Chain (IMC), is derived from a Labeled Transition System (LTS) semantics. It is proven to be correct, by means of abstract interpretation techniques, with respect to the Discrete Time Markov Chain (DTMC) semantics, usually associated with these systems. As example of application, we study how the behavior of a model of tumor cell growth changes when different intervals of kinetic rates are used. Subsequently, we face the problems related to the use of interleaving semantics and to the size of state space size of models. In particular, we define the probabilistic semantics for systems evolving in a maximally parallel way: in each step of the system evolution, as many interactions happen synchronously. Using the proposed semantics we are able to reproduce in vivo experiments outcomes on a model of C. elegans vulval development. Moreover, we develop an abstraction framework for the proposed maximally parallel probabilistic semantics. The framework is based on a form of predicate abstraction computing an abstract semantics in terms of IMC. Since the abstraction is parametric on a set of predicates, the abstract probabilistic model can be refined until a right compromise between dimension and precision is reached. We prove that conservative bounds on probabilities of reachability properties of systems evolving in a maximally parallel way can be computed on the abstract semantics. We show the efficacy of the approach, in terms of state and transition number reduction, by analysis probabilistic reachability on a simple model of seasonal animal reproduction

Preserving landmark legacy software with the Software Heritage Acquisition Process

International audienceThe source code of landmark software developed since the beginning of the computer era is a precious part of our cultural heritage, and needs to be properly rescued, curated, archived and made available to present and future generations. In this article, we present the Software Heritage Acquisition Process, that has been designed to provide detailed guidelines on how to perform this important task, preserving important historical information. This process has been validated extensively on several important pieces of software source code of historical relevance in the University of Pisa, in collaboration with UNESCO, and is open to all for adoption and improvement

Probabilistic Model Checking of Biological Systems with Uncertain Kinetic Rates

Abstract. We present an abstraction of the probabilistic semantics of Multiset Rewriting to formally express systems of reactions with uncertain kinetic rates. This allows biological systems modelling when the exact rates are not known, but are supposed to lie in some intervals. On these (abstract) models we perform probabilistic model checking obtaining lower and upper bounds for the probabilities of reaching states satisfying given properties. These bounds are under- and overapproximations, respectively, of the probabilities one would obtain by verifying the models with exact kinetic rates belonging to the intervals

Molecular and physiological responses to salt stress in salinity-sensitive and tolerant Hibiscus rosa-sinensis cultivars

Abstract Ornamental plants are used to decorate urban and peri-urban areas, and during their cultivation or utilisation, they can be exposed to abiotic stress. Salinity is an abiotic stress factor that limits plant growth and reduces the ornamental value of sensitive species. In this study, transcriptomic analysis was conducted to identify genes associated with tolerance or sensitivity to salinity in two hibiscus (Hibiscus rosa-sinensis L.) cultivars, ‘Porto’ and ‘Sunny wind’. The physiological and biochemical parameters of plants exposed to 50, 100, or 200 mM NaCl and water (control) were monitored. Salinity treatments were applied for six weeks. After four weeks, differences between cultivars were clearly evident and ‘Porto’ was more tolerant than ‘Sunny wind’. The tolerant cultivar showed lower electrolyte leakage and ABA concentrations, and higher proline content in the leaves. Accumulation of Na in different organs was lower in the flower organs of ‘Porto’. At the molecular level, several differential expressed genes were observed between the cultivars and flower organs. Among the highly expressed DEGs, coat protein, alcohol dehydrogenase, and AP2/EREBP transcription factor ERF-1. Among the downregulated genes, GH3 and NCED were the most interesting. The differential expression of these genes may explain the salt stress tolerance of ‘Porto’. Graphical Abstrac

Software Stories for landmark legacy code

Software Heritage in collaboration with the sciencestories.io team and the University of Pisa are introducing a new way to showcase software, that can be accessible to a wide range of software enthusiasts without any technical background, Software Stories. The project is supported by UNESCO as part of the shared mission to collect, preserve and share source code as precious asset of humankind [1]. The Software Stories interface is designed to highlight materials about a software title in a visual manner, similar to a digital software museum. The engine provides a semi-automatic tool for curators to create the presentation layer of the Software Heritage Acquisition Process (SWHAP) [2] allowing curators to generate a multimedia overview of a landmark legacy software title.For the prototype, the University of Pisa has provided three software titles that were curated in 2019 during the creation of the SWHAP. Thesesoftware titles were collected and curated in GitHub and then archived in Software Heritage. For the presentation layer the collected materialsand metadata were deposited in Wikidata and Wikimedia Commons. You can visit https://stories.softwareheritage.org to check the Pisa collection and watch the demonstration video online on https://youtu.be/s6uVdRDh5Xk.[1] Expert Group Report. Paris call: Software source code as heriitage for sustainable development. Available from https://unesdoc.un-esco.org/ark:/48223/pf0000366715, 2019.[2] Laura Bussi, Roberto Di Cosmo, Carlo Montangero, and Guido Scatena. The software heritage acquisition process. Technical Report CI-2019/WS/8, UNESCO, Università di Pisa, Inria, 2019. https://unesdoc.unesco.org/ark:/48223/pf000037101

Survive or die? A molecular insight into salt-dependant signaling network

The response of plants to salt stress involves dynamic changes in growth and signaling leading to successful adaptation or death. To elucidate how these opposed events are coordinated we identified a salt-tolerant (obesifruticosa) and a salt-sensitive (aestiva) Antirrhinum majus mutants using shoots as sensitive indicator of stress magnitude. A series of physiological tests were performed that compared the response after 6 h and 3 days of these contrasting mutants grown in agar under a single (200 mM) NaCl concentration, including shoot area, root length, relative water content, plant height, and overall biomass accumulation. Additional measurements of ABA content, chlorophyll degradation, ethylene production, net photosynthesis rates and Na+, K+, Ca2+, and Mg2+ content were also reported. RNA-seq analysis was performed on the two mutants after 6 h and 3 days under 200 mM NaCl. A total of 9199 transcripts were found to be differentially expressed in response to NaCl treatment in the two mutants. A large collection of known genes, including MAPKs, CDKs, CDPKs, CIPKs, various transcription factors, various ion transport proteins, and various genes involved in ABA and ethylene signaling pathways were described in detail that displayed differential expression profiles. Overall these data provided evidences of a putative osmotic tolerance sensing and signaling mechanism through a better integration and transduction of environmental cues into growth programs. The reprogramming of calcium-signaling components, generates specific stress signatures affecting differentially the salinity tolerance traits, such as tissue tolerance and anion exclusion. Interestingly, the hormones ABA and ethylene may action as a positive regulators of salt acclimation by the modulation of their signal transduction pathway