Development of Mesoporous Silica Nanoparticle-Based Films with Tunable Arginine-Glycine-Aspartate Peptide Global Density and Clustering Levels to Study Stem Cell Adhesion and Differentiation.

Stem cell adhesion is mediated via the binding of integrin receptors to adhesion motifs present in the extracellular matrix (ECM). The spatial organization of adhesion ligands plays an important role in stem cell integrin-mediated adhesion. In this study, we developed a series of biointerfaces using arginine-glycine-aspartate (RGD)-functionalized mesoporous silica nanoparticles (MSN-RGD) to study the effect of RGD adhesion ligand global density (ligand coverage over the surface), spacing, and RGD clustering levels on stem cell adhesion and differentiation. To prepare the biointerface, MSNs were chemically functionalized with RGD peptides via an antifouling poly(ethylene glycol) (PEG) linker. The RGD surface functionalization ratio could be controlled to create MSNs with high and low RGD ligand clustering levels. MSN films with varying RGD global densities could be created by blending different ratios of MSN-RGD and non-RGD-functionalized MSNs together. A computational simulation study was performed to analyze nanoparticle distribution and RGD spacing on the resulting surfaces to determine experimental conditions. Enhanced cell adhesion and spreading were observed when RGD global density increased from 1.06 to 5.32 nmol cm-2 using highly clustered RGD-MSN-based films. Higher RGD ligand clustering levels led to larger cell spreading and increased formation of focal adhesions. Moreover, a higher RGD ligand clustering level promoted the expression of alkaline phosphatase in hMSCs. Overall, these findings indicate that both RGD global density and clustering levels are crucial variables in regulating stem cell behaviors. This study provides important information about ligand-integrin interactions, which could be implemented into biomaterial design to achieve optimal performance of adhesive functional peptides.

Optimization of Media Change Intervals through Hydrogels Using Mathematical Models.

Three-dimensional cell culture in engineered hydrogels is increasingly used in tissue engineering and regenerative medicine. The transfer of nutrients, gases, and waste materials through these hydrogels is of utmost importance for cell viability and response, yet the translation of diffusion coefficients into practical guidelines is not well established. Here, we combined mathematical modeling, fluorescent recovery after photobleaching, and hydrogel diffusion experiments on cell culture inserts to provide a multiscale practical approach for diffusion. We observed a dampening effect of the hydrogel that slowed the response to concentration changes and the creation of a diffusion gradient in the hydrogel by media refreshment. Our designed model combined with measurements provides a practical point of reference for diffusion coefficients in real-world culture conditions, enabling more informed choices on hydrogel culture conditions. This model can be improved in the future to simulate more complicated intrinsic hydrogel properties and study the effects of secondary interactions on the diffusion of analytes through the hydrogel.

Sex-Specific Computational Models of Kidney Function in Patients With Diabetes.

The kidney plays an essential role in homeostasis, accomplished through the regulation of pH, electrolytes and fluids, by the building blocks of the kidney, the nephrons. One of the important markers of the proper functioning of a kidney is the glomerular filtration rate. Diabetes is characterized by an enlargement of the glomerular and tubular size of the kidney, affecting the afferent and efferent arteriole resistance and hemodynamics, ultimately leading to chronic kidney disease. We postulate that the diabetes-induced changes in kidney may exhibit significant sex differences as the distribution of renal transporters along the nephron may be markedly different between women and men, as recently shown in rodents. The goals of this study are to (i) analyze how kidney function is altered in male and female patients with diabetes, and (ii) assess the renal effects, in women and men, of an anti-hyperglycemic therapy that inhibits the sodium-glucose cotransporter 2 (SGLT2) in the proximal convoluted tubules. To accomplish these goals, we have developed computational models of kidney function, separate for male and female patients with diabetes. The simulation results indicate that diabetes enhances Na+ transport, especially along the proximal tubules and thick ascending limbs, to similar extents in male and female patients, which can be explained by the diabetes-induced increase in glomerular filtration rate. Additionally, we conducted simulations to study the effects of diabetes and SGLT2 inhibition on solute and water transport along the nephrons. Model simulations also suggest that SGLT2 inhibition raises luminal [Cl-] at the macula densa, twice as much in males as in females, and could indicate activation of the tubuloglomerular feedback signal. By inducing osmotic diuresis in the proximal tubules, SGLT2 inhibition reduces paracellular transport, eventually leading to diuresis and natriuresis. Those effects on urinary excretion are blunted in women, in part due to their higher distal transport capacity.

A multi-domain shear-stress dependent diffusive model of cell transport-aided dialysis: analysis and simulation.

Kidney dialysis is the most widespread treatment method for end-stage renal disease, a debilitating health condition common in industrialized societies. While ubiquitous, kidney dialysis suffers from an inability to remove larger toxins, resulting in a gradual buildup of these toxins in dialysis patients, ultimately leading to further health complications. To improve dialysis, hollow fibers incorporating a cell-monolayer with cultured kidney cells have been proposed; however, the design of such a fiber is nontrivial. In particular, the effects of fluid wall-shear stress have an important influence on the ability of the cell layer to transport toxins. In the present work, we introduce a model for cell-transport aided dialysis, incorporating the effects of the shear stress. We analyze the model mathematically and establish its well-posedness. We then present a series of numerical results, which suggest that a hollow-fiber design with a wavy profile may increase the efficiency of the dialysis treatment. We investigate numerically the shape of the wavy channel to maximize the toxin clearance. These results demonstrate the potential for the use of computational models in the study and advancement of renal therapies.

Modeling indoxyl sulfate transport in a bioartificial kidney: Two-step binding kinetics or lumped parameters model for uremic toxin clearance?

Toxin removal by the kidney is deficient in a patient suffering from end-stage kidney disease (ESKD), and current dialysis therapies are insufficient in subsidizing this loss. A bioartificial kidney (BAK) aspires to offer ESKD patients a more effective alternative to dialysis. Mathematical models are necessary to support further developments and improve designs for the BAK before clinical trials. The BAK differentiates itself from dialysis by incorporating a living proximal tubule cell monolayer to account for the active transport of protein-bound uremic toxins, namely indoxyl sulfate (IS) in this study. Optimizing such a device is far from trivial due to the non-intuitive spatiotemporal dynamics of the IS removal process. This study used mathematical models to compare two types of active transport kinetics. i.e., two-step binding and lumped parameter. The modeling results indicated that the transporter density is the most influential parameter for the IS clearance. Moreover, a uniform distribution of transporters increases the IS clearance, highlighting the need for a high-quality, functional proximal tubule monolayer in the BAK. In summary, this study contributed to an improved understanding of IS transport in the BAK, which can be used along with laboratory experiments to develop promising renal replacement therapies in the future.