22,51 Hepatocytic differentiation proceeds following

exposure to fibronectin27 in the absence of Notch signaling.22 Allen Cowley Jr, Chairman of Physiology at the University of Wisconsin and editor of Physiological Genomics, has written: “At its core, systems biology represents a renewed recognition that biology is best understood by taking a coordinated, integrative systems view. In practice, systems biology means the application of many currently defined disciplines with the goal of bringing together information from the smallest units of the biological system (genes) to help understand the function of the whole organism.”52 Certainly, studies of individual cell types, specific cell: cell interactions, molecular intracellular signaling pathways, and genomic analyses have elucidated many DR mechanisms and behaviors. However, the point of cell and molecular biology reductivism was AZD1208 order to make things simple enough to study when our tools were insufficiently click here complex for modeling cell:cell and cell:matrix interactions at the tissue level. We should not lose sight of the actual goal, however, of reintegrating these data

into what might be considered a sub-branch of systems biology as considered by Dr Cowley, namely, tissue biology, the level of scientific analysis most appropriate to considerations by academic pathologists who concern themselves, first and foremost, with considerations of the tissue level of scale.25,53,54 DRs, similar to all stem cell systems in all organs, fully reveal their physiologic behaviors only at the tissue level.47,48,55 Thus, a tissue biology approach is needed for full understanding. Complexity theory suggests that cells and matrix interact as members of complex adaptive systems.54,56,57

Such systems can change their community-level self-organization so that the community as a whole can adapt to a changing environment. This approach opens up the possibility of computerized, agent-based modeling of cell:cell and cell:matrix interactions to test hypotheses generated from molecular and cell biological data.54,58 This class of computational modeling simulates the actions and interactions of autonomous agents (such old as cells and matrix elements) with a view to assessing their effects on the system as a whole. This methodology has been fruitfully and extensively applied in studying the participation of hematopoietic stem cells in homeostasis or in pathophysiology, in particular neoplasia (reviewed by Roeder59). A recent application to liver disease has been presented by Hoehme et al. in which they modeled data derived from immunohistochemistry and confocal microscopy of murine hepatic regeneration following CCl4 injury.