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221 results on '"Motta, Santo"'

53. The CRF-method for semiconductors' intravalley collision kernels: II – The 3D case

Author

Barone, C and Motta, Santo

Subjects
Semiconductors, Kinetic equations, lcsh:Mathematics, lcsh:QA1-939
Abstract

If the collisions are redefined as a flux a kinetic conservation law can be written in divergence form. This can be handled numerically, in the framework of Finite Particle Approximation, using the CRF-method. In this paper we use the CRF-method for semiconductors' intravalley collision kernels. We extend the results obtained in a previous paper to the case of a 3D momentum space.

Published
1993

59. GRID-BASED CANCER GROWTH SIMULATIONS

Author

Alemani, D, Pappalardo, Francesco, Pennisi, MARZIO ALFIO, Mastriani, E, and Motta, Santo

Subjects
HYBRID MODELS, GRID, CANCER
Published
2009

73. iAtheroSim

Author

Pappalardo, Francesco, primary, Pennisi, Marzio, additional, Chiacchio, Ferdinando, additional, Musumeci, Salvatore, additional, and Motta, Santo, additional

Published
2013
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78. Immune System Network and Cancer Vaccine

Author

Bianca, Carlo, primary, Pennisi, Marzio, additional, Motta, Santo, additional, Ragusa, Maria Alessandra, additional, Simos, Theodore E., additional, Psihoyios, George, additional, Tsitouras, Ch., additional, and Anastassi, Zacharias, additional

Published
2011
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80. In silico Modeling and In vivo Efficacy of Cancer-Preventive Vaccinations

Author

Palladini, Arianna, primary, Nicoletti, Giordano, additional, Pappalardo, Francesco, additional, Murgo, Annalisa, additional, Grosso, Valentina, additional, Stivani, Valeria, additional, Ianzano, Marianna L., additional, Antognoli, Agnese, additional, Croci, Stefania, additional, Landuzzi, Lorena, additional, De Giovanni, Carla, additional, Nanni, Patrizia, additional, Motta, Santo, additional, and Lollini, Pier-Luigi, additional

Published
2010
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90. Computational modeling of the expansion of human cord blood CD1331+hematopoietic stem/progenitor cells with different cytokine combinations.

Author

Gullo, Francesca, van der Garde, Mark, Russo, Giulia, Pennisi, Marzio, Motta, Santo, Pappalardo, Francesco, and Watt, Suzanne

Subjects
CYTOLOGY, HEMATOPOIETIC stem cell transplantation, STEM cell culture, CORD blood, CYTOKINES, PROGENITOR cells, CELLULAR signal transduction
Abstract

Motivation: Many important problems in cell biology require dense non-linear interactions between functional modules to be considered. The importance of computer simulation in understanding cellular processes is now widely accepted, and a variety of simulation algorithms useful for studying certain subsystems have been designed. Expansion of hematopoietic stem and progenitor cells (HSC/HPC) in ex vivo culture with cytokines and small molecules is a method to increase the restricted numbers of stem cells found in umbilical cord blood (CB), while also enhancing the content of early engrafting neutrophil and platelet precursors. The efficacy of the expanded product depends on the composition of the cocktail of cytokines and small molecules used for culture. Testing the influence of a cytokine or small molecule on the expansion of HSC/HPC is a laborious and expensive process. We therefore developed a computational model based on cellular signaling interactions that predict the influence of a cytokine on the survival, duplication and differentiation of the CD133+ HSC/HPC subset from human umbilical CB. Results: We have used results from in vitro expansion cultures with different combinations of one or more cytokines to develop an ordinary differential equation model that includes the effect of cytokines on survival, duplication and differentiation of the CD133+ HSC/HPC. Comparing the results of in vitro and in silico experiments, we show that the model can predict the effect of a cytokine on the fold expansion and differentiation of CB CD133+ HSC/HPC after 8-day culture on a 3D scaffold. [ABSTRACT FROM AUTHOR]

Published
2015
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93. Immune System Network and Cancer Vaccine.

Author

Bianca, Carlo, Pennisi, Marzio, Motta, Santo, and Ragusa, Maria Alessandra

Subjects
IMMUNE system, CANCER vaccines, MATHEMATICAL models, CANCER treatment, DRUG administration
Abstract

This paper deals with the mathematical modelling of the immune system response to cancer disease, and specifically with the treatment of the mammary carcinoma in presence of an immunoprevenction vaccine. The innate action of the immune system network, the external stimulus represented by repeated vaccine administrations and the competition with cancer are described by an ordinary differential equations-based model. The mathematical model is able to depict preclinical experiments on transgenic mice. The results are of great interest both in the applied and theoretical sciences. [ABSTRACT FROM AUTHOR]

Published
2011
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94. Modelling Vaccine Protocols.

Author

Alt, Wolfgang, Adler, Fred, Chaplain, Mark, Deutsch, Andreas, Dress, Andreas, Krakauer, David, Tranquillo, Robert T., Hosking, Roger J., Venturino, Ezio, Motta, Santo, Lollini, Pier-Luigi, and Pappalardo, Francesco

Abstract

Living organisms are natural complex systems where mathematical modelling may play a crucial role, since a model can be built with imperfect knowledge of some related phenomenon and model parameters (initial data, entities, relations between entities) can be adjusted to fit modelling results to experimental measurements. The model can then be used to understand the general behaviour of the phenomenon in different situations, to perform model experiments or simulations, to understand the role of single constituents and relations, to plan new experiments, or to test theoretical assumptions and suggest theory modifications. Modelling can therefore stimulate scientific creativity and produce better theoretical descriptions of the reality. We describe here our efforts to devise models of the immune system, and in particular the competition between immune defences and tumor cells. An agent-based model of the effects of a vaccine designed to prevent mammary carcinoma incidence in transgenic mice was developed. This model faithfully summarises not only the outcome of vaccination experiments, but also the dynamics of immune responses elicited by the vaccine. A genetic algorithm was used to drive the model and predict optimised vaccination schedules, which are currently being tested in vivo. The implications of biologic diversity on model development and perspectives to develop natural-scale models of the immune system are also discussed. [ABSTRACT FROM AUTHOR]

Published
2008
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95. Towards a Personalized Schedule with Triplex Vaccine.

Author

Carbonell, Jaime G., Siekmann, Jörg, Masulli, Francesco, Mitra, Sushmita, Pasi, Gabriella, Pappalardo, Francesco, Motta, Santo, Lollini, Pier Luigi, Mastriani, Emilio, and Pennisi, Marzio

Abstract

The immune system is a large and complex system still incompletely understood. The synergy of biological knowledge included in data bases, mathematical and computational models and bioinformatics tools can help in gain a deeper understanding. In this paper, we try to understand how one can characterize a mouse in order to find the better vaccination protocol against mammary carcinoma for that individual. This study will be expanded in the framework of ImmunoGrid EC project. [ABSTRACT FROM AUTHOR]

Published
2007
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96. Searching of Optimal Vaccination Schedules.

Author

Pennisi, Marzio Alfio, Pappalardo, Francesco, Zhang, Ping, and Motta, Santo

Subjects
GENETIC algorithms, CANCER prevention, IMMUNE response, THERAPEUTICS
Abstract

The article discusses the study which applied genetic algorithms (GAs) to approach the problem of looking for best schedules in the immunoprevention of cancer. It says that the researchers used a model of the immune response to compute the fitness function. The study showed the implication of interdisciplinary cooperation in approaches in the field of biology.

Published
2009
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