Paola Cerrai

Delay-induced oscillatory dynamics of tumour-immune system interaction

The aim of this work on tumour-immune system (T-IS) interaction is to assess the effect of delays concerning the stimulation of the immune system by tumour cells, as well as the interplay between antitumour immunotherapies and delays. After defining a new family of super-macroscopic models for the T-IS interaction, we introduce a constant delay in the proliferation of immune effectors. We then investigate, both analytically and by means of simulations, the stability of equilibria and the onset of sustained oscillations through Hopf bifurcations. Both constant and exponentially distributed lags are considered. In particular, in the case of periodically varying immunotherapies we show that nonlinear resonances and chaos may arise, although for parameters slightly outside the range of biological realism.

Information and dynamical systems: a concrete measurement on sporadic dynamics

Abstract We present a method for the study of dynamical systems based on the notion of quantity of information. Measuring the quantity of information of a string by using data compression algorithms, it is possible to give a notion of orbit complexity of dynamical systems. In compact ergodic dynamical systems, entropy is almost everywhere equal to orbit complexity. We have introduced a new compression algorithm called CASToRe which allows a direct estimation of the information content of the orbits in the 0-entropy case. The method is applied to a sporadic dynamical system (Manneville map).

A bi-parametric model for the tumour angiogenesis and antiangiogenesis therapy

In this work we study a family of phenomenological super-macroscopic models describing the tumour angiogenesis and antiangiogenesis therapy, introduced by Folkman and coworkers [P. Hahnfeldt, D. Panigrahy, J. Folkman, L. Hlatky, Tumour development under angiogenic signaling: A dynamical theory of tumour growth, treatment response, and postvascular dormancy, Cancer Res. 59 (1999) 4770-4775], and depending on two positive parameters @a@?[0,1] and @c@?[0,5/3]. Here we extend the model by considering not only vessel-disrupting antiangiogenic therapies, but also drugs purely inhibiting the proliferation of endothelial cells, as well as drugs exerting both these actions. By means of cooperativity theory, we show that in order for the family to describe the biological phenomena under study one has to add a further constraint on the two parameters: @c@?@a. We find conditions for the therapy-induced tumour eradication, and for the local and global stability of the equilibria in the case of low-level therapy or in the absence of it. We also consider the case @c>@a. Finally, in the concluding remarks, we stress some limitations of our super-macroscopic approach, and outline some steps of improvement that might lead to more comprehensive detailed multiscale modelling of tumour angiogenesis.

Six novel MEN1 gene mutations in sporadic parathyroid tumors

We report nine mutations of the multiple endocrine neoplasia type 1 (MEN1) gene in sporadic parathyroid adenomas. Six of them have not previously been described: E60X, P32R, 261delA, 934+2T→G, S443P, and 1593insC. The tissue samples were initially submitted to LOH analysis at 11q13 followed by SSCP screening of LOH‐positive samples. Mutations were identified by direct sequencing and subcloning. Three (E60X, P32R, and 261delA) were in exon 2, one (934+2bp) in the splice junction of exon 5, one (S443P) in exon 9, and one (1593insC) in exon 10. The 3 mutations in exon 2 were associated with loss and/or creation of a restriction site. The corresponding germline sequence of the MEN1 gene was normal. Most mutations would likely result in a nonfunctional menin protein, and therefore in the loss of a tumor suppressor protein.

New challenges for cancer systems biomedicine

Part I Towards a Comprehensive Theory of Cancer Growth.- Combining Game Theory and Graph Theory to Model Interactions between Cells in the Tumor Microenvironment.- Growth as the Root of all Evil in Carcinomas: Synergy between pH Buffering and Anti-Angiogenesis prevents Emergence of Hallmarks of Cancer.- Phase Transitions in Cancer.- Part II Cancer Related Signalling Pathways.- Spatio-Temporal Modelling of Intracellular Signalling Pathways: Transcription Factors, Negative Feedback Systems and Oscillations.- Understanding Cell Fate Decisions by Identifying Crucial System Dynamics.- Modelling Biochemical Pathways with the Calculus of Looping Sequences.- Dynamic Simulations of Pathways Downstream of TGFss, Wnt and EGF-Family Growth Factors, in Colorectal Cancer, including Mutations and Treatments with Onco-Protein Inhibitors.- Part III Basic Mechanisms of Tumor Progression.- Some Results on the Population Behavior of Cancer Stem Cells.- Glucose Metabolism in Multicellular Spheroids, ATP Production and Effects of Acidity.- Cell-Cell Interactions in Solid Tumors - the Role of Cancer Stem Cells.- Hybrid Cellular Potts Model for Solid Tumor Growth.- Part IV Tumor-Immune System Interplay and Immunotherapy.- Computational Models as Novel Tools for Cancer Vaccines.- On the Dynamics of Tumor-Immune System Interactions and Combined Chemo- and Immunotherapy.- Modeling the Kinetics of the Immune Response.- Part V Computational Method for Improving Chemotherapy.- Optimizing Cancer Chemotherapy: from Mathematical Theories to Clinical Treatment.- A Systems Biomedicine Approach for Chronotherapeutics Optimization: Focus on the Anticancer Drug Irinotecan.- Modeling the Dynamics of HCV Infected Cells to Tailor Antiviral Therapy in Clinical Practice: Can This Approach Fit for Neoplastic Cells?.- Introducing Drug Transport Early in the Design of Hypoxia Selective Anticancer Agents Using a Mathematical Modelling Approach.- Top-Down Multiscale Simulation of Tumor Response to Treatment in the Context of In Silico Oncology. The Notion of Oncosimulator.- Challenges in the Integration of Flow Cytometry and Time-Lapse Live Cell Imaging Data Using a Cell Proliferation Model.

Six novel MEN1 gene mutations in sporadic parathyroid tumors Communicated by: Richard G.H. Cotton Online Citation: Human Mutation, Mutation in Brief #373 (2000) Online http://journals.wiley.com/1059-7794/pdf/mutation/373.pdf

We report nine mutations of the multiple endocrine neoplasia type 1 (MEN1) gene in sporadic parathyroid adenomas. Six of them have not previously been described: E60X, P32R, 261delA, 934+2T-->G, S443P, and 1593insC. The tissue samples were initially submitted to LOH analysis at 11q13 followed by SSCP screening of LOH-positive samples. Mutations were identified by direct sequencing and subcloning. Three (E60X, P32R, and 261delA) were in exon 2, one (934+2bp) in the splice junction of exon 5, one (S443P) in exon 9, and one (1593insC) in exon 10. The 3 mutations in exon 2 were associated with loss and/or creation of a restriction site. The corresponding germline sequence of the MEN1 gene was normal. Most mutations would likely result in a nonfunctional menin protein, and therefore in the loss of a tumor suppressor protein.

Special issue on Erice ‘MathCompEpi 2015’ Proceedings

The mathematical and computational modelling of the spread of infectious diseases is a research field in applied mathematics that in the same time was both able to give an impetum to various areas of the dynamical systems theory and mathematical analysis, and to give an important contribution to the biological and epidemiological understanding of the spread of these diseases. National as well as Inter-National health authorities adopt routinely in the practice methodologies and concept that were born in the field of Mathematical and Computational Epidemiology (MCE) for assisting public Health decisions and policies. A major example is provided by the huge advancement in modelling and prediction on pandemic threats, and related preparedness plans for disease containment/mitigation. This operative influence in biomedicine is unparalleled in any other fields of mathematical and computational biology, with the possible exception of intra-host virus dynamics, whose models partly derive from those of MCE.

Artificial life and speciation, a case study: heterochromatin and speciation in the Microtus savii Group (Rodentia-Arvicolinae).

Artificial life is a tool which is used for simulation of peculiar cases of evolutionary events. The main characteristic of artificial life is that with this technique it is possible to simulate for a high number of generations the evolution of a population of individuals. Each individual is characterised by a small number of parameters, but each individual has its own evolutive story. So far it is possible to simulate the evolution of a population of some thousands specimens, for a high number of generations. The realistic aspect of the simulation is that each specimen is taken individually. In our opinion this instrument is very useful to simulate the evolution of the hybrids barrier during speciation. For this reason it is applied to a peculiar case of speciation, that of the Savi pine vole (Microtus savii) whose experimental data were recently investigated.

Geophysiological Modeling: New Ideas on Modeling the Evolution of Ecosystems.

Living organisms evolve within ecological associations (from ecosystems to the biosphere) that are constituted by a biological component and a physico-chemical component. It is generally supposed that interactions such as competition and predation between the biological components of ecosystems are the main cause for the observed organization of ecosystems. We believe that in the search for a more comprehensive theory of evolution a much greater attention should be paid to the ways in which living organisms interact with the physico-chemical environment. To test our ideas, we develop a mathematical model to study the evolution of ecosystems, and we apply it to the study of hydrothermal vents. The model proposed is still a qualitative model. It tries to study, in a first approximation, the behaviours of the biological and chemical components. In the following we hope to develop and to improve it so to give a more realistic model.