Characterization of the Concentration-Dependence of Solute Diffusivity and Partitioning in a Model Dextran–Agarose Transport System

Abstract

This study reports experimental measurements of solute diffusivity and partition coefficient for various solute concentrations and gel porosities, and proposes novel constitutive relations to describe these observed values. The longer-term aim is to explore the theoretical ramifications of accommodating variations in diffusivity and partition coefficient with solute concentration and tissue porosity, and investigate whether they might suggest novel mechanisms not previously recognized in the field of solute transport in deformable porous media. The study implements a model transport system of agarose hydrogels to investigate the effect of solute concentration and hydrogel porosity on the transport of dextran polysaccharides. The proposed phenomenological constitutive relations are shown to provide better fits of experimental results than prior models proposed in the literature based on the microstructure of the gel. While these constitutive models were developed for the transport of dextran in agarose hydrogels, it is expected that they may also be applied to the transport of similar molecular weight solutes in other porous media. This quantification can assist in the application of biophysical models that describe biological transport in deformable tissues, as well as the cell cytoplasm.

Silk microfiber-reinforced silk hydrogel composites for functional cartilage tissue repair

“…Acellular agarose and silk constructs were soaked in a saturated (0.5 mg ml −1 ) 70 kDa fluorescein-conjugated dextran solution (Invitrogen, Carlsbad, CA) for over 24 h. Samples were placed on an Olympus Fluoview FV1000 confocal microscope and diffusion properties were measured via fluorescent recovery after photobleaching (FRAP) of a thin line using a 405 nm laser for 30 s. Images (320 × 320 pixels) were acquired using a 20× objective before, during and after the photobleaching process. FRAP analysis was performed using a custom MATLAB code according to Albro et al [38], which fits the FRAP images to the Gaussian equation $Ifalse(x,tfalse)=\frac{M}{\sqrt{\pi w^2}}{e}^{-x^2/w^2}$, where I is the fluorescence intensity as a function of position ( x ) and time ( t ), M is the total amount of bleached species and w is related to the diffusion coefficient, D , by the equation w 2 = 4 Dt . A linear regression was applied to a plot of w 2 against t (r 2 ≈ 0.99) to acquire a value for D .…”

Agarose Hydrogel Characterization for Regenerative Medicine Applications: Focus on Engineering Cartilage

“…The transport properties of agarose, governed by solute diffusivity and water transport by hydraulic permeability, have been well described empirically and via modeling using various solutes ( Fig. 16.2), either biologically relevant or in the size range of molecules pertinent to tissue engineering [13][14][15]. Knowledge of such properties is paramount to its utility as a scaffold for tissue engineering.…”

“…The scaffold must allow for import of nutrients and chemical factors, export of cellular waste products, and retention of cell synthesized ECM components. As mentioned earlier, the balancing of these parameters can be performed easily as transport within the gel is governed by diffusion limitations associated with agarose concentration: the denser the gel, the smaller the average pore size, and the lower the diffusivity [15]. Diffusion length is a key limiting factor in tissue engineering ( Fig.…”

“…Agarose gel stiffness is also related to its thermal history: the temperatures of gelation, storage, and mechanical testing [20,21]. While agarose density is important, a solute's concentration and size also affect diffusivity and limit or improve transport [13,15]. Small molecules, such as oxygen and glucose, freely diffuse through an agarose scaffold.…”

Parameter-dependent behavior of articular cartilage: 3D mechano-electrochemical computational model

“…So far, the common method to accomplish that, are specific experimental assays (Pearle et al 2005;Albro et al 2009;Virén et al 2009). However, these techniques require high costs and elevate time consuming.…”