The recent tumor research has lead scientists to recognize the central role played by cancer stem cells in sustaining malignancy and chemo-resistance. A model of cancer presented by one of us describes the mechanisms that give rise to the different kinds of cancer stem-like cells and the role of these cells in cancer diseases. The model implies a shift in the conceptualization of the disease from reductionism to complexity theory. By exploiting the link between the agent-based simulation technique and the theory of complexity, the medical view is here translated into a corresponding computational model. Two main categories of agents characterize the model, 1) cancer stem-like cells and 2) stem cell differentiation stage factors. Cancer cells agents are then distinguished based on the differentiation stage associated with the malignancy. Differentiation factors interact with cancer cells and then, with varying degrees of fitness, induce differentiation or cause apoptosis. The model inputs are then fitted to experimental data and numerical simulations carried out. By performing virtual experiments on the model's choice variables a decision-maker (physician) can obtains insights on the progression of the disease and on the effects of a choice of administration frequency and or dose. The model also paves the way to future research, whose perspectives are discussed.

Description:The social sciences, especially economics, management, and organizational science, are experiencing a tremendous renewed interest for their epistemological and methodological statutes, as witnessed by the many books and specialized journals established during the last two decades. Relational Methodologies and Epistemology in Economics and Management Sciencesidenti es and presents the four main network-based methodologies including network analysis, Boolean network simulation modeling, arti cial neural network simulation modeling, and agentbased simulation modeling in addition to their conceptual-epistemological implications and concrete applications within the social and natural sciences.

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According to modern international economics, and especially evolutionary economic geography, a country industry characteristics influence the structure of its international trade. Following this view, this chapter moves from the following basic research issue: if two sectors are very different according to market, economic and technological aspects, should we expect that its corresponding international trade networks are as well markedly different? Aerospace and Common Earth Materials seem quite different in those respects, and thus, they are good candidates to explore that research issue. Its comparison allowed to evidence and discuss some methodological problems in applying social network analysis, and especially in using it to compare different networks. In particular, it is underlined the difficulty to handle valued networks when value variance is very high, and to combine three groups of indicators: simple, hierarchy focused, and strictly topological. The comparative analysis employed 32 indicators either at network or sub-network level, like for core-periphery analysis, which indicate clear and marked diversity only in terms of hierarchical degree and topological aspects. A first conclusion is that the two examined trade networks are following a similar path and, excepted for few indicators, they seem to be rather similar even at a deeper structural level. Hence, one (or more) of three implications can be drawn: 1) the global value networks corresponding to the two sectors are not so markedly different; 2) they are substantially different but such a diversity does not produce a significant difference in terms of international trade networks; 3) there are some methodological problems that prevent differences to be evidence and require a more refined and modified comparison. A second conclusion is that trade patterns of both sectors are rather unstable.

According to modern international economics, and especially evolutionary economic geography, a country industry characteristics influence the structure of its international trade. Following this view, this chapter moves from the following basic research issue: if two sectors are very different according to market, economic and technological aspects, should we expect that its corresponding international trade networks are as well markedly different? Aerospace and Common Earth Materials seem quite different in those respects, and thus, they are good candidates to explore that research issue. Its comparison allowed to evidence and discuss some methodological problems in applying social network analysis, and especially in using it to compare different networks. In particular, it is underlined the difficulty to handle valued networks when value variance is very high, and to combine three groups of indicators: simple, hierarchy focused, and strictly topological. The comparative analysis employed 32 indicators either at network or sub-network level, like for core-periphery analysis, which indicate clear and marked diversity only in terms of hierarchical degree and topological aspects. A first conclusion is that the two examined trade networks are following a similar path and, excepted for few indicators, they seem to be rather similar even at a deeper structural level. Hence, one (or more) of three implications can be drawn: 1) the global value networks corresponding to the two sectors are not so markedly different; 2) they are substantially different but such a diversity does not produce a significant difference in terms of international trade networks; 3) there are some methodological problems that prevent differences to be evidence and require a more refined and modified comparison. A second conclusion is that trade patterns of both sectors are rather unstable.