Investigating the Influence of Heterogeneity Within Cell Types on Microvessel Network Transport.

Background: Current research on the biophysics of circulating tumor cells often overlooks the heterogeneity of cell populations, focusing instead on average cellular properties. This study aims to address the gap by considering the diversity of cell biophysical characteristics and their implications on cancer spread. Methods: We utilized computer simulations to assess the influence of variations in cell size and membrane elasticity on the behavior of cells within fluid environments. The study controlled cell and fluid properties to systematically investigate the transport of tumor cells through a simulated network of branching channels. Results: The simulations revealed that even minor differences in cellular properties, such as slight changes in cell radius or shear elastic modulus, lead to significant changes in the fluid conditions that cells experience, including velocity and wall shear stress (p < 0.001). Conclusion: The findings underscore the importance of considering cell heterogeneity in biophysical studies and suggest that small variations in cellular characteristics can profoundly impact the dynamics of tumor cell circulation. This has potential implications for understanding the mechanisms of cancer metastasis and the development of therapeutic strategies.

Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts.

Simulations of cancer cell transport require accurately modeling mm-scale and longer trajectories through a circulatory system containing trillions of deformable red blood cells, whose intercellular interactions require submicron fidelity. Using a hybrid CPU-GPU approach, we extend the advanced physics refinement (APR) method to couple a finely-resolved region of explicitly-modeled red blood cells to a coarsely-resolved bulk fluid domain. We further develop algorithms that: capture the dynamics at the interface of differing viscosities, maintain hematocrit within the cell-filled volume, and move the finely-resolved region and encapsulated cells while tracking an individual cancer cell. Comparison to a fully-resolved fluid-structure interaction model is presented for verification. Finally, we use the advanced APR method to simulate cancer cell transport over a mm-scale distance while maintaining a local region of RBCs, using a fraction of the computational power required to run a fully-resolved model.

High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory.

The ability to track simulated cancer cells through the circulatory system, important for developing a mechanistic understanding of metastatic spread, pushes the limits of today's supercomputers by requiring the simulation of large fluid volumes at cellular-scale resolution. To overcome this challenge, we introduce a new adaptive physics refinement (APR) method that captures cellular-scale interaction across large domains and leverages a hybrid CPU-GPU approach to maximize performance. Through algorithmic advances that integrate multi-physics and multi-resolution models, we establish a finely resolved window with explicitly modeled cells coupled to a coarsely resolved bulk fluid domain. In this work we present multiple validations of the APR framework by comparing against fully resolved fluid-structure interaction methods and employ techniques, such as latency hiding and maximizing memory bandwidth, to effectively utilize heterogeneous node architectures. Collectively, these computational developments and performance optimizations provide a robust and scalable framework to enable system-level simulations of cancer cell transport.

Studies on sorption kinetics and sorption isotherm for pervaporative separation of benzene from model pyrolysis gasoline using insitu nano silver/polyvinyl alcohol membrane.

Pyrolysis gasoline (Py gas) is used as an octane enhancer of gasoline as it is rich in aromatics. However, removal of carcinogenic benzene from Py gas before blending with gasoline is important to meet the fuel specifications. The main focus of this present study is to determine the sorption kinetics and sorption isotherm of a fabricated insitu nano silver/polyvinyl alcohol (insitu nano Ag/PVA) membrane for pervaporative separation of benzene from model Py gas [mixture of benzene (aromatic) and 1-octene (aliphatic)]. The thickness, surface morphological structure (Atomic Force Microscopy) and degree of swelling of the fabricated membrane were determined. The highest pervaporation separation index achieved for the selected system was 14.259 kg/m2/h at 303 K, with 30 volume% benzene in model Py gas using a downstream pressure of 1 mm of Hg. The sorption kinetics of benzene in insitu nano Ag/PVA membrane obeyed the Elovich model while the Temkin isotherm model fitted the experimental data of the chosen system most accurately.

A data-driven approach to modeling cancer cell mechanics during microcirculatory transport.

In order to understand the effect of cellular level features on the transport of circulating cancer cells in the microcirculation, there has been an increasing reliance on high-resolution in silico models. Accurate simulation of cancer cells flowing with blood cells requires resolving cellular-scale interactions in 3D, which is a significant computational undertaking warranting a cancer cell model that is both computationally efficient yet sufficiently complex to capture relevant behavior. Given that the characteristics of metastatic spread are known to depend on cancer type, it is crucial to account for mechanistic behavior representative of a specific cancer's cells. To address this gap, in the present work we develop and validate a means by which an efficient and popular membrane model-based approach can be used to simulate deformable cancer cells and reproduce experimental data from specific cell lines. Here, cells are modeled using the immersed boundary method (IBM) within a lattice Boltzmann method (LBM) fluid solver, and the finite element method (FEM) is used to model cell membrane resistance to deformation. Through detailed comparisons with experiments, we (i) validate this model to represent cancer cells undergoing large deformation, (ii) outline a systematic approach to parameterize different cell lines to optimally fit experimental data over a range of deformations, and (iii) provide new insight into nucleated vs. non-nucleated cell models and their ability to match experiments. While many works have used the membrane-model based method employed here to model generic cancer cells, no quantitative comparisons with experiments exist in the literature for specific cell lines undergoing large deformation. Here, we describe a phenomenological, data-driven approach that can not only yield good agreement for large deformations, but explicitly detail how it can be used to represent different cancer cell lines. This model is readily incorporated into cell-resolved hemodynamic transport simulations, and thus offers significant potential to complement experiments towards providing new insights into various aspects of cancer progression.

Computational Framework to Evaluate the Hydrodynamics of Cell Scaffold Geometries.

The fluid dynamics of microporous materials are important to many biomedical processes such as cell deposition in scaffold materials, tissue engineering, and bioreactors. Microporous scaffolds are frequently composed of suspensions of beads that have varying topology which, in turn, informs their hydrodynamic properties. Previous work has shown that shear stress distributions can affect the response of cells in microporous environments. Using computational fluid dynamics, we characterize localized differences in fluid flow attributes such wall shear stress and velocity to better understand the fluid dynamics underpinning microporous device function. We evaluated whether bead packings with similar void fractions had different fluid dynamics as characterized by the distribution of velocity magnitudes and wall shear stress and found that there are differences despite the similarities in void fraction. We show that another metric, the average distance to the nearest wall, can provide an additional variable to measure the porosity and susceptibility of microporous materials to high shear stress. By increasing our understanding of the impact of bead size on cell scaffold fluid dynamics we aim to increase the ability to predict important attributes such as loading efficiency in these devices.