Signaling cascades modulate the speed of signal propagation through space

Into the Tissues: Extracellular Matrix and Its Artificial Substitutes: Cell Signalling Mechanisms

The existence of orderly structures, such as tissues and organs is made possible by cell adhesion, i.e., the process by which cells attach to neighbouring cells and a supporting substance in the form of the extracellular matrix. The extracellular matrix is a three-dimensional structure composed of collagens, elastin, and various proteoglycans and glycoproteins. It is a storehouse for multiple signalling factors. Cells are informed of their correct connection to the matrix via receptors. Tissue disruption often prevents the natural reconstitution of the matrix. The use of appropriate implants is then required. This review is a compilation of crucial information on the structural and functional features of the extracellular matrix and the complex mechanisms of cell-cell connectivity. The possibilities of regenerating damaged tissues using an artificial matrix substitute are described, detailing the host response to the implant. An important issue is the surface properties of such an implant and the possibilities of their modification.

Discovering dominant pathways and signal-response relationships in signaling networks through nonparametric approaches

A signaling pathway is a sequence of proteins and passenger molecules that transmits information from the cell surface to target molecules. Understanding signal transduction process requires detailed description of the involved pathways. Several methods and tools resolved this problem by incorporating genomic and proteomic data. However, the difficulty of obtaining prior knowledge of complex signaling networks limited the applicability of these tools. In this study, based on the simulation of signal flow in signaling network, we introduce a method for determining dominant pathways and signal response to stimulations. The model uses topology-weighted transit compartment approach and comprises four main steps which include weighting the edges, simulating signal transduction in the network (weighting the nodes), finding paths between initial and target nodes, and assigning a significance score to each path. We applied the proposed model to eighty-three signaling networks by using biologically derived source and sink molecules. The recovered dominant paths matched many known signaling pathways and suggesting a promising index to analyze the phenotype essentiality of molecule encoding paths. We also modeled the stimulus-response relations in long and short-term synaptic plasticity based on the dominant signaling pathway concept. We showed that the proposed method not only accurately determines dominant signaling pathways, but also identifies effective points of intervention in signal transduction.