A Kappa model for hepatic stellate cells activation by TGFB1

International audienc

A Kappa model for hepatic stellate cells activation by TGFB1

International audienc

A Kappa model for hepatic stellate cells activation by TGFB1

International audienceAll chronic hepatitis are associated with the development of fibrosis, which results in abnormal deposition of the extracellular matrix (ECM) leading to severe liver dysfunction. Fibrosis final stage, called cirrhosis, is the main risk of development of hepatocellular carcinoma (HCC). At the cellular level, hepatic stellate cells (HSCs) are major actors of fibrosis and tumor progression. Upon liver injury, HSCs are activated to repair tissue and are subsequently eliminated through three mechanisms: apoptosis, senescence and reversion, leading to a return to healthy status [5]. However,when the injury persists, HSCs remain activated with a myobroblastic phenotype, and extracellular matrix accumulates, leading to fibrosis, cirrhosis and cancer. Understanding the dynamics of HSC activation and their regulation by TGFB1 is essential to identify markers and therapeutic targets that may favor the resolution of fibrosis at the expense of its progression. For this purpose, we are developing a modelling approach using the Kappa language. Kappa is a rule-based language used for the rewriting of site graphs [1, 2, 4, 3] aiming at describing networks of interactions between occurrences of components, using a syntax inspired by chemistry. In this model, the components are occurrences of HSC in different states, and occurrences of the TGFB1 protein. Our preliminary results suggest a high plasticity of the HSC response to TGFB1 stimulation. Future work will focus on the integration of the ECM component networks that regulate TGFB1 availability.References:[1] O. Andrei and H. Kirchner. A rewriting calculus for multigraphs with ports. Electr. NotesTheor. Comput. Sci., 219:67–82, 2008.[2] V. Danos and C. Laneve. Formal molecular biology. Theoretical Computer Science,325(1):69 – 110, 2004. Computational Systems Biology.[3] A. Ehrlich, D. Duche, G. Ouedraogo, and Y. Nahmias. Challenges and opportunitiesin the design of liver-on-chip microdevices. Annual Review of Biomedical Engineering,21(1):219–239, 2019. PMID: 31167098.[4] J. R. Faeder, M. L. Blinov, B. Goldstein, and W. S. Hlavacek. Rule-based modeling ofbiochemical networks. Complexity, 10(4):22–41, 2005.[5] T. Kisseleva and D. Brenner. Molecular and cellular mechanisms of liver fibrosis and itsregression. Nature Reviews Gastroenterology & Hepatology, pages 1–16, 2020

Lumpability Abstractions of Rule-based Systems

The induction of a signaling pathway is characterized by transient complex formation and mutual posttranslational modification of proteins. To faithfully capture this combinatorial process in a mathematical model is an important challenge in systems biology. Exploiting the limited context on which most binding and modification events are conditioned, attempts have been made to reduce the combinatorial complexity by quotienting the reachable set of molecular species, into species aggregates while preserving the deterministic semantics of the thermodynamic limit. Recently we proposed a quotienting that also preserves the stochastic semantics and that is complete in the sense that the semantics of individual species can be recovered from the aggregate semantics. In this paper we prove that this quotienting yields a sufficient condition for weak lumpability and that it gives rise to a backward Markov bisimulation between the original and aggregated transition system. We illustrate the framework on a case study of the EGF/insulin receptor crosstalk.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

Taking Static Analysis to the Next Level: Proving the Absence of Run-Time Errors and Data Races with Astrée

International audienceWe present an extension of Astrée to concurrent C software. Astrée is a sound static analyzer for run-time errors previously limited to sequential C software. Our extension employs a scalable abstraction which covers all possible thread interleavings, and soundly reports all run-time errors and data races: when the analyzer does not report any alarm, the program is proven free from those classes of errors. We show how this extension is able to support a variety of operating systems (such as POSIX threads, ARINC 653, OSEK/AUTOSAR) and report on experimental results obtained on concurrent software from different domains, including large industrial software

Occurrence Counting Analysis for the pi-Calculus

We propose an abstract interpretation-based analysis for automatically proving non-trivial properties of mobile systems of processes. We focus on properties relying on the number of occurrences of processes during computation sequences, such as mutual exclusion and non-exhaustion of resources. We design a non-standard semantics for the pi-calculus in order to explicitly trace the origin of channels and to solve efficiently problems set by alpha-conversion and nondeterministic choices. We abstract this semantics into an approximate one. The use of a relational domain for counting the occurrences of processes allows us to prove quickly and efficiently properties such as mutual exclusion and non-exhaustion of resources. At last, dynamic partitioning allows us to detect some congurations by which no innite computation sequences can pass

A Semantics of Core Erlang with Handling of Signals

International audienceWe introduce a small step semantics for a subset of Core Erlang modeling its monitoring and signal systems. The goal of our semantics is to enable the construction of causal explanations for property violations, which will be the object of future work. As a first axis of reflection, we chose to study the impact of the order of messages on a faulty behavior. We present our semantics and discuss some of our design choices. This work is a part of a broader project on causal debugging of concurrent programs in Erlang

A Kappa model for hepatic stellate cells activation by TGFB1

International audienc

A Kappa model for hepatic stellate cells activation by TGFB1

International audienceAll chronic hepatitis are associated with the development of fibrosis, which results in abnormal deposition of the extracellular matrix (ECM) leading to severe liver dysfunction. Fibrosis final stage, called cirrhosis, is the main risk of development of hepatocellular carcinoma (HCC). At the cellular level, hepatic stellate cells (HSCs) are major actors of fibrosis and tumor progression. Upon liver injury, HSCs are activated to repair tissue and are subsequently eliminated through three mechanisms: apoptosis, senescence and reversion, leading to a return to healthy status [5]. However,when the injury persists, HSCs remain activated with a myobroblastic phenotype, and extracellular matrix accumulates, leading to fibrosis, cirrhosis and cancer. Understanding the dynamics of HSC activation and their regulation by TGFB1 is essential to identify markers and therapeutic targets that may favor the resolution of fibrosis at the expense of its progression. For this purpose, we are developing a modelling approach using the Kappa language. Kappa is a rule-based language used for the rewriting of site graphs [1, 2, 4, 3] aiming at describing networks of interactions between occurrences of components, using a syntax inspired by chemistry. In this model, the components are occurrences of HSC in different states, and occurrences of the TGFB1 protein. Our preliminary results suggest a high plasticity of the HSC response to TGFB1 stimulation. Future work will focus on the integration of the ECM component networks that regulate TGFB1 availability.References:[1] O. Andrei and H. Kirchner. A rewriting calculus for multigraphs with ports. Electr. NotesTheor. Comput. Sci., 219:67–82, 2008.[2] V. Danos and C. Laneve. Formal molecular biology. Theoretical Computer Science,325(1):69 – 110, 2004. Computational Systems Biology.[3] A. Ehrlich, D. Duche, G. Ouedraogo, and Y. Nahmias. Challenges and opportunitiesin the design of liver-on-chip microdevices. Annual Review of Biomedical Engineering,21(1):219–239, 2019. PMID: 31167098.[4] J. R. Faeder, M. L. Blinov, B. Goldstein, and W. S. Hlavacek. Rule-based modeling ofbiochemical networks. Complexity, 10(4):22–41, 2005.[5] T. Kisseleva and D. Brenner. Molecular and cellular mechanisms of liver fibrosis and itsregression. Nature Reviews Gastroenterology & Hepatology, pages 1–16, 2020

A Kappa model for hepatic stellate cells activation by TGFB1

International audienceAll chronic hepatitis are associated with the development of fibrosis, which results in abnormal deposition of the extracellular matrix (ECM) leading to severe liver dysfunction. Fibrosis final stage, called cirrhosis, is the main risk of development of hepatocellular carcinoma (HCC). At the cellular level, hepatic stellate cells (HSCs) are major actors of fibrosis and tumor progression. Upon liver injury, HSCs are activated to repair tissue and are subsequently eliminated through three mechanisms: apoptosis, senescence and reversion, leading to a return to healthy status [5]. However,when the injury persists, HSCs remain activated with a myobroblastic phenotype, and extracellular matrix accumulates, leading to fibrosis, cirrhosis and cancer. Understanding the dynamics of HSC activation and their regulation by TGFB1 is essential to identify markers and therapeutic targets that may favor the resolution of fibrosis at the expense of its progression. For this purpose, we are developing a modelling approach using the Kappa language. Kappa is a rule-based language used for the rewriting of site graphs [1, 2, 4, 3] aiming at describing networks of interactions between occurrences of components, using a syntax inspired by chemistry. In this model, the components are occurrences of HSC in different states, and occurrences of the TGFB1 protein. Our preliminary results suggest a high plasticity of the HSC response to TGFB1 stimulation. Future work will focus on the integration of the ECM component networks that regulate TGFB1 availability.References:[1] O. Andrei and H. Kirchner. A rewriting calculus for multigraphs with ports. Electr. NotesTheor. Comput. Sci., 219:67–82, 2008.[2] V. Danos and C. Laneve. Formal molecular biology. Theoretical Computer Science,325(1):69 – 110, 2004. Computational Systems Biology.[3] A. Ehrlich, D. Duche, G. Ouedraogo, and Y. Nahmias. Challenges and opportunitiesin the design of liver-on-chip microdevices. Annual Review of Biomedical Engineering,21(1):219–239, 2019. PMID: 31167098.[4] J. R. Faeder, M. L. Blinov, B. Goldstein, and W. S. Hlavacek. Rule-based modeling ofbiochemical networks. Complexity, 10(4):22–41, 2005.[5] T. Kisseleva and D. Brenner. Molecular and cellular mechanisms of liver fibrosis and itsregression. Nature Reviews Gastroenterology & Hepatology, pages 1–16, 2020