Cash Saving Guidelines For ALPI

In general, reducing (increasing) immune cell motilities around optimal values reduced (increased) the number of interaction events between cells and by that the phagocytosis of C. albicans cells. In the case of PMN, reduction of cell motility and phagocytosis events was additionally associated with a decrease in the release of antimicrobial peptides contributing to the decrease in killing of C. albicans cells. This in turn lead to an increase in the number of resistant C. albicans cells reaching levels that were well-beyond those observed for paralytic monocytes (see Figure ?Figure10).10). Comparing the hypo-inflammatory condition with PMN deficiency, we found that diffusion coefficients around DG = 100 ��m2/min resembled the outcome of moderate to severe neutropenia. The bottom-up modeling approach presented here may be extended in various ways. For example, the implementation of a hybrid ABM could be envisaged where molecular interactions, e.g., as mediated by antimicrobial peptides, are not simulated in a rule-based fashion but in an explicit way by a molecular diffusion solver. Other directions of future research include (i) focusing on conditions of immune dysregulation, (ii) comparing the impact of different pathogens, and (iii) including other types of innate immune cells. Furthermore, it is conceivable to combine modeling approaches with microscopy experiments of infection scenarios in vitro in an image-based systems biology approach (Mech et al., 2014; Figge and Murphy, 2015; Medyukhina et al., 2015). First steps into this direction have recently been made, e.g., by establishing algorithms for the automated image analysis of phagocytosis assays (Mech et al., 2011; Kraibooj et al., 2014) and for the automated tracking and classification of PMN from time-lapse microscopy (Mokhtari et al., 2013; Brandes et al., 2015) that was applied in the context of comparing C. albicans and C. glabrata infection (Duggan et al., 2015a). In the future, we expect that a systems medicine approach exploiting the predictive power of virtual infection models will play an important role in the context of infectious disease diagnosis. Author contributions TL, ST, MTF: Conception and design of the investigation and work. MTF: Contribution of materials and computational resources. TL, ST, JP, MTF: Data processing, implementation and application of the computational algorithm. TL, ST, JP, KH, OK, MTF: Evaluation and analysis of the results. TL, ST, JP, KH, OK, MTF: Drafting the manuscript and revising it critically for important intellectual content and final approval of the version to be published. TL, ST, JP, KH, OK, MTF: Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and OTX015 cell line resolved.