Multi-scale biological and physical modelling of the tumour micro-environment.

Paced by advances in high performance computing, and algorithms for multi-physics and multi-scale simulation, a number of groups have recently established numerical models of flowing blood systems, where cell-scale interactions are explicitly resolved. To be biologically representative, these models account for some or all of: (1) fluid dynamics of the carrier flow, (2) structural dynamics of the cells and vessel walls, (3) interaction and transport biochemistry, and, (4) methods for scaling to physiologically representative numbers of cells. In this article, our interest is the modelling of the tumour micro-environment. We review the broader area of cell-scale resolving blood flow modelling, while focusing on the particular interactions of tumour cells and white blood cells, known to play an important role in metastasis.

Distilling experience into a physically interpretable recommender system for computational model selection.

Model selection is a chronic issue in computational science. The conventional approach relies heavily on human experience. However, gaining experience takes years and is severely inefficient. To address this issue, we distill human experience into a recommender system. A trained recommender system tells whether a computational model does well or poorly in handling a physical process. It also tells if a physical process is important for a quantity of interest. By accumulating this knowledge, the system is able to make recommendations about computational models. We showcase the power of the system by considering Reynolds-averaged-Navier-Stokes (RANS) model selection in the field of computational fluid dynamics (CFD). Since turbulence is stochastic, there is no universal RANS model, and RANS model selection has always been an issue. A working model recommending system saves fluid engineers years and allows junior CFD practitioners to make sensible model choices like senior ones.

Rootstocks Shape Their Microbiome-Bacterial Communities in the Rhizosphere of Different Grapevine Rootstocks.

The microbiota associated with the rhizosphere is responsible for crucial processes. Understanding how the plant and its bacterial community interact is of great importance to face the upcoming agricultural and viticultural challenges. The composition of the bacterial communities associated with the rhizosphere of grapevines is the result of the interaction between many drivers: biogeography, edaphic factors, soil management and plant genotype. The experimental design of this study aimed to reduce the variability resulting from all factors except the genotype of the rootstock. This was made possible by investigating four ungrafted grapevine rootstock varieties of the same age, grown on the same soil under the same climatic conditions and managed identically. The bacterial communities associated with the rhizosphere of the rootstocks 1103 Paulsen, 140 Ruggeri, 161-49 Couderc and Kober 5BB were characterized with the amplicon based sequencing technique, targeting regions V4-V5 of 16S rRNA gene. Linear discriminant analysis effect Size (LEfSe) analysis was performed to determine differential abundant taxa. The four rootstocks showed similarities concerning the structure of the bacteria assemblage (richness and evenness). Nonetheless, differences were detected in the composition of the bacterial communities. Indeed, all investigated rootstocks recruited communities with distinguishable traits, thus confirming the role of rootstock genotype as driver of the bacteria composition.

Localized Modeling of Biochemical and Flow Interactions during Cancer Cell Adhesion.

This work focuses on one component of a larger research effort to develop a simulation tool to model populations of flowing cells. Specifically, in this study a local model of the biochemical interactions between circulating melanoma tumor cells (TC) and substrate adherent polymorphonuclear neutrophils (PMN) is developed. This model provides realistic three-dimensional distributions of bond formation and attendant attraction and repulsion forces that are consistent with the time dependent Computational Fluid Dynamics (CFD) framework of the full system model which accounts local pressure, shear and repulsion forces. The resulting full dynamics model enables exploration of TC adhesion to adherent PMNs, which is a known participating mechanism in melanoma cell metastasis. The model defines the adhesion molecules present on the TC and PMN cell surfaces, and calculates their interactions as the melanoma cell flows past the PMN. Biochemical rates of reactions between individual molecules are determined based on their local properties. The melanoma cell in the model expresses ICAM-1 molecules on its surface, and the PMN expresses the ß-2 integrins LFA-1 and Mac-1. In this work the PMN is fixed to the substrate and is assumed fully rigid and of a prescribed shear-rate dependent shape obtained from micro-PIV experiments. The melanoma cell is transported with full six-degrees-of-freedom dynamics. Adhesion models, which represent the ability of molecules to bond and adhere the cells to each other, and repulsion models, which represent the various physical mechanisms of cellular repulsion, are incorporated with the CFD solver. All models are general enough to allow for future extensions, including arbitrary adhesion molecule types, and the ability to redefine the values of parameters to represent various cell types. The model presented in this study will be part of a clinical tool for development of personalized medical treatment programs.

C1-inhibitor for prophylaxis of xenograft rejection after pig to cynomolgus monkey kidney transplantation.

BACKGROUND: Early rejection of discordant porcine xenografts in primate recipients is initiated by the intragraft binding of either preformed (hyperacute xenograft rejection) or induced (acute vascular rejection) antiporcine recipient antibodies with subsequent complement activation via the classical pathway. We have investigated the efficacy of the supplemental administration of C1-inhibitor (C1-INH), a specific inhibitor of the classical complement activation pathway, for prophylaxis of xenograft rejection in a pig to primate kidney xenotransplantation setting. METHODS: Based on the results of pharmacokinetic studies performed in two nontransplanted monkeys, supplemental C1-INH therapy was administered daily to three Cynomolgus monkeys receiving a life-supporting porcine kidney transplant together with cyclophosphamide-induction/cyclosporine A/mycophenolat-mofetil/steroid immunosuppressive therapy. RESULTS: In the three monkeys receiving porcine kidney xenografts and continuous C1-INH treatment none of the grafts underwent hyperacute rejection; all xenografts showed initial function. Recipient survival was 13, 15, and 5 days. No graft was lost due to acute vascular rejection. All animals died with a functioning graft (latest creatinine 96, 112, and 96 micromol/liter) due to bacterial septicemia. CONCLUSION: We conclude that, in our model, supplemental C1-INH therapy together with a standard immunosuppressive regimen can be helpful for prevention of xenograft rejection in a pig to primate kidney xenotransplantation setting. The optimal dose and duration of C1-INH treatment, however, has yet to be determined.

Study of local hydrodynamic environment in cell-substrate adhesion using side-view µPIV technology.

Tumor cell adhesion to the endothelium under shear flow conditions is a critical step that results in circulation-mediated tumor metastasis. This study presents experimental and computational techniques for studying the local hydrodynamic environment around adherent cells and how local shear conditions affect cell-cell interactions on the endothelium in tumor cell adhesion. To study the local hydrodynamic profile around heterotypic adherent cells, a side-view flow chamber assay coupled with micro particle imaging velocimetry (µPIV) technique was developed, where interactions between leukocytes and tumor cells in the near-endothelial wall region and the local shear flow environment were characterized. Computational fluid dynamics (CFD) simulations were also used to obtain quantitative flow properties around those adherent cells. Results showed that cell dimension and relative cell-cell positions had strong influence on local shear rates. The velocity profile above leukocytes and tumor cells displayed very different patterns. Larger cell deformations led to less disturbance to the flow. Local shear rates above smaller cells were observed to be more affected by relative positions between two cells.

Effects of the Tumor-Leukocyte Microenvironment on Melanoma-Neutrophil Adhesion to the Endothelium in a Shear Flow.

The primary cause of cancer mortality is not attributed to primary tumor formation, but rather to the growth of metastases at distant organ sites. Tumor cell adhesion to blood vessel endothelium (EC) and subsequent transendothelial migration within the circulation are critical components of the metastasis cascade. Previous studies have shown polymorphonuclear neutrophils (PMNs) may facilitate melanoma cell adhesion to the EC and subsequent extravasation under flow conditions. The melanoma cell-PMN interactions are found to be mediated by the binding between intercellular adhesion molecule-1 (ICAM-1) on melanoma cells and ß(2) integrin on PMNs and by endogenously secreted interleukin 8 (IL-8) within the tumor-leukocyte microenvironment. In this study, the effects of fluid convection on the IL-8-mediated activation of PMNs and the binding kinetics between PMNs and melanoma cells were investigated. Results indicate that the shear rate dependence of PMN-melanoma cell adhesion and melanoma cell extravasation is due, at least partly, to the convection of tumor-secreted proinflammatory cytokine IL-8.

Design of a side-view particle imaging velocimetry flow system for cell-substrate adhesion studies.

Experimental models that mimic the flow conditions in microcapillaries have suggested that the local shear stresses and shear rates can mediate tumor cell and leukocyte arrest on the endothelium and subsequent sustained adhesion. However, further investigation has been limited by the lack of experimental models that allow quantitative measurement of the hydrodynamic environment over adherent cells. The purpose of this study was to develop a system capable of acquiring quantitative flow profiles over adherent cells. By combining the techniques of side-view imaging and particle image velocimetry (PIV), an in vitro model was constructed that is capable of obtaining quantitative flow data over cells adhering to the endothelium. The velocity over an adherent leukocyte was measured and the shear rate was calculated under low and high upstream wall shear. The microcapillary channel was modeled using computational fluid dynamics (CFD) and the calculated velocity profiles over cells under the low and high shear rates were compared to experimental results. The drag force applied to each cell by the fluid was then computed. This system provides a means for future study of the forces underlying adhesion by permitting characterization of the local hydrodynamic conditions over adherent cells.