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1. Investigation of Material Transport Through Triply Periodic Minimal Surface (TPMS) Bone Scaffolds Using Computational Fluid Dynamics (CFD)

   https://doi.org/10.1115/MSEC2024-123878  

   Coburn, Brandon; Salary, Roozbeh “Ross” (June 2024, American Society of Mechanical Engineers (ASME))

   Abstract Cell-laden, scaffold-based tissue engineering methods have been successfully utilized for the treatment of bone fractures and diseases, caused by factors such as trauma, tumors, congenital anomalies, and aging. In such methods, the rate of scaffold biodegradation, transport of nutrients and growth factors, as well as removal of cell metabolic wastes at the site of injury are critical fluid-dynamics factors, affecting cell proliferation and ultimately tissue regeneration. Therefore, there is a critical need to identify the underlying material transport mechanisms and factors associated with cell-seeded, scaffold-based bone tissue engineering. The overarching goal of this study is to contribute to patient-specific, clinical treatment of bone pathology. The overall objective of the work is to establish computational fluid dynamics (CFD) models to identify: (i) the consequential mechanisms behind internal and external material transport through/over porous bone scaffolds and (ii) optimal triply periodic minimal surface (TPMS) scaffold designs toward cell-laden bone fracture treatment. In this study, 10 internal-flow and 10 external-flow CFD models were established using ANSYS, correspondingly based on 10 single-unit TPMS bone scaffold designs, where the geometry of each design was parametrically created using Rhinoceros 3D software. The influence of several design parameters, such as surface representation iteration, merged toggle iso value, and wall thickness, on geometry accuracy as well as computational time, was investigated in order to obtain computationally efficient and accurate CFD models. The fluid properties (such as density and dynamic viscosity) as well as the boundary conditions (such as no-slip condition, inlet flow velocity, and pressure outlet) of the CFD models were set based on clinical/research values reported in the literature as well as according to the fundamentals of internal/external Newtonian flow modeling. Several fluid characteristics, including flow velocity, flow pressure, and wall shear stress, were analyzed to observe material transport internally through and externally over the TPMS scaffold designs. Regarding the internal flow CFD modeling, it was observed that “P.W. Hybrid” (i.e., Design #7) had the highest-pressure output, with “Neovius” (i.e., Design #1) following second to it. These two designs have a relatively flatter surface area. In addition, “Schwarz P” (i.e., Design #2) was the lowest pressure output of all 10 TPMS designs. “Neovius” and “Schwarz P” had the highest and lowest values of wall shear stress. Besides, the velocity streamlines analysis showed an increase in velocity along the curved sections of the scaffolds’ geometry. Regarding the external flow CFD modeling, it was observed that “Neovius” yielded the highest-pressure output within the inlet section, which contains the area of the highest-pressure location. Furthermore, “Diamond” (i.e., Design #8) displayed having the highest values of wall shear stress due to the results of fluid interaction that accrues with complex curved structures. Also, when we look at designs like “Schwarz G”, the depiction of turbulent motion can be seen along the internal curved sections of the structure. As the external velocity streamlines decrease within the inner channels of the designs, this will lead to an increased pressure buildup due to the intrinsic interactions between the fluid with the walls. Overall, the outcomes of this study pave the way for optimal design and fabrication of complex, bone-like tissues with desired material transport properties for cell-laden, scaffold-based treatment of bone fractures. 

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2. A machine learning approach to predict cellular mechanical stresses in response to chemical perturbation

   https://doi.org/10.1016/j.bpj.2023.07.016  

   SubramanianBalachandar, VigneshAravind; Islam, Md. Mydul; Steward, R.L. (September 2023, Biophysical Journal)

   Mechanical stresses generated at the cell-cell level and cell-substrate level have been suggested to be important in a host of physiological and pathological processes. However, the influence various chemical compounds have on the mechan- ical stresses mentioned above is poorly understood, hindering the discovery of novel therapeutics, and representing a barrier in the field. To overcome this barrier, we implemented two approaches: 1) monolayer boundary predictor and 2) discretized window predictor utilizing either stepwise linear regression or quadratic support vector machine machine learning model to predict the dose-dependent response of tractions and intercellular stresses to chemical perturbation. We used experimental traction and intercellular stress data gathered from samples subject to 0.2 or 2 mg/mL drug concentrations along with cell morphological prop- erties extracted from the bright-field images as predictors to train our model. To demonstrate the predictive capability of our ma- chine learning models, we predicted tractions and intercellular stresses in response to 0 and 1 mg/mL drug concentrations which were not utilized in the training sets. Results revealed the discretized window predictor trained just with four samples (292 im- ages) to best predict both intercellular stresses and tractions using the quadratic support vector machine and stepwise linear regression models, respectively, for the unseen sample images. 

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3. Shear stress magnitude and transforming growth factor-βeta 1 regulate endothelial to mesenchymal transformation in a three-dimensional culture microfluidic device

   https://doi.org/10.1039/C6RA16607E  

   Mina, Sara G.; Wang, Wei; Cao, Qingfeng; Huang, Peter; Murray, Bruce T.; Mahler, Gretchen J. (January 2016, RSC Advances)

   Normal fibroblasts are present within the extracellular matrix (ECM). They can become activated, leading to increased proliferation and ECM protein secretion such as collagen type I to promote tissue remodeling. These cells are also involved in adult pathologies including cancer metastasis and cardiac and renal fibrosis. One source of activated fibroblasts is endothelial to mesenchymal transformation (EndMT), in which endothelial cells lose their cell–cell and cell–ECM adhesions, gain invasive properties, and become mesenchymal cells. While EndMT is well characterized in developmental biology, the mechanisms and functional role of EndMT in adult physiology and pathology have not been fully investigated. A microfluidic device with an incorporated three-dimensional ECM chamber was developed to study the role of combined steady fluid shear stress magnitudes and transforming growth factor-βeta 1 (TGF-β1) on EndMT. Low (1 dyne per cm 2 ) steady shear stress and TGF-β1 exposure induced EndMT in endothelial cells, including upregulation of mesenchymal protein and gene expression markers. Cells exposed to TGF-β1 and high (20 dynes per cm 2 ) steady shear stress did not undergo EndMT, and protein and gene expression of mesenchymal markers was significantly downregulated. Mesenchymally transformed cells under static conditions with and without TGF-β1 showed significantly more collagen production when compared to fluidic conditions. These results confirm that both low shear stress and TGF-β1 induce EndMT in endothelial cells, but this process can be prevented by exposure to physiologically relevant high shear stress. These results also show conditions most likely to cause tissue pathology. 

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4. Evaluation of Flow-Induced Shear in a Porous Microfluidic Slide: CFD Analysis and Experimental Investigation

   https://doi.org/10.3390/fluids10060160  

   Neves, Manoela; Aparnasai_Reddy, Gayathri; Niyingenera, Anitha; Delaney, Norah; Meng, Wilson S; Zakerzadeh, Rana (June 2025, Fluids)

   Microfluidic devices offer well-defined physical environments that are suitable for effective cell seeding and in vitro three-dimensional (3D) cell culture experiments. These platforms have been employed to model in vivo conditions for studying mechanical forces, cell–extracellular matrix (ECM) interactions, and to elucidate transport mechanisms in 3D tissue-like structures, such as tumor and lymph node organoids. Studies have shown that fluid flow behavior in microfluidic slides (µ-slides) directly influences shear stress, which has emerged as a key factor affecting cell proliferation and differentiation. This study investigates fluid flow in the porous channel of a µ-slide using computational fluid dynamics (CFD) techniques to analyze the impact of perfusion flow rate and porous properties on resulting shear stresses. The model of the µ-slide filled with a permeable biomaterial is considered. Porous media fluid flow in the channel is characterized by adding a momentum loss term to the standard Navier–Stokes equations, with a physiological range of permeability values. Numerical simulations are conducted to obtain data and contour plots of the filtration velocity and flow-induced shear stress distributions within the device channel. The filtration flow is subsequently measured by performing protein perfusions into the slide embedded with native human-derived ECM, while the flow rate is controlled using a syringe pump. The relationships between inlet flow rate and shear stress, as well as filtration flow and ECM permeability, are analyzed. The findings provide insights into the impact of shear stress, informing the optimization of perfusion conditions for studying tissues and cells under fluid flow. 

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5. Estimation of shear stress heterogeneity along capillary segments in angiogenic rat mesenteric microvascular networks

   https://doi.org/10.1111/micc.12830  

   Hu, Nien‐Wen; Lomel, Banks M; Rice, Elijah W; Hossain, Mir_Md Nasim; Sarntinoranont, Malisa; Secomb, Timothy W; Murfee, Walter L; Balogh, Peter (November 2023, Microcirculation)

   Abstract ObjectiveFluid shear stress is thought to be a regulator of endothelial cell behavior during angiogenesis. The link, however, requires an understanding of stress values at the capillary level in angiogenic microvascular networks. Critical questions remain. What are the stresses? Do capillaries experience similar stress magnitudes? Can variations explain vessel‐specific behavior? The objective of this study was to estimate segment‐specific shear stresses in angiogenic networks. MethodsImages of angiogenic networks characterized by increased vascular density were obtained from rat mesenteric tissues stimulated by compound 48/80‐induced mast cell degranulation. Vessels were identified by perfusion of a 40 kDa fixable dextran prior to harvesting and immunolabeling for PECAM. Using a network flow‐based segment model with physiologically relevant parameters, stresses were computed per vessel for regions across multiple networks. ResultsStresses ranged from 0.003 to 2328.1 dyne/cm²and varied dramatically at the capillary level. For all regions, the maximum segmental shear stresses were for capillary segments. Stresses along proximal capillaries branching from arteriole inlets were increased compared to stresses along capillaries in more distal regions. ConclusionsThe results highlight the variability of shear stresses along angiogenic capillaries and motivate new discussions on how endothelial cells may respond in vivo to segment‐specific microenvironment during angiogenesis. 

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