No abstract

Cell activity is coordinated by dynamic interactions with the extracellular matrix, often through stimuli-mediated spatiotemporal stiffening and softening. Dynamic changes in mechanics occur in vivo through enzymatic or chemical means, processes which are challenging to reconstruct in cell culture materials. Here we present a magnetoactive hydrogel material formed by embedding magnetic particles in a hydrogel matrix whereby elasticity can be modulated reversibly by attenuation of a magnetic field. We show orders of magnitude change in elasticity using low magnetic fields and demonstrate reversibility of stiffening with simple permanent magnets. The broad applicability of this technique is demonstrated with two therapeutically relevant bioactivities in mesenchymal stem cells: secretion of proangiogenic molecules, and dynamic control of osteogenesis. The ability to reversibly stiffen cell culture materials across the full spectrum of soft tissue mechanics, using simple materials and commercially available permanent magnets, will make this approach viable for a broad range of laboratory environments.

Hematopoietic stem cells (HSC) reside in unique bone marrow niches and are influenced by signals from surrounding cells, the extracellular matrix (ECM), ECM-bound or diffusible biomolecules. Here we describe the use of a three-dimensional hydrogel to alter the balance of HSC-generated autocrine feedback and paracrine signals generated by co-cultured niche-associated cells. We report shifts in HSC proliferation rate and fate specification in the presence of lineage positive (Lin+) niche cells. Hydrogels promoting autocrine feedback enhanced expansion of early hematopoietic progenitors while paracrine signals from Lin+ cells increased myeloid differentiation. We report thresholds where autocrine vs. paracrine cues alter HSC fate transitions, and were able to selectively abrogate the effects of matrix diffusivity and niche cell co-culture via the use of inhibitory cocktails of autocrine or paracrine signals. Together, these results suggest diffusive biotransport in three-dimensional biomaterials are a critical design element for the development of a synthetic stem cell niche.

We construct a microstructure-based constitutive model that successfully predicts experimental rheology signatures that no other model has previously described. The experimental observations are the low-dimensional descriptions of asymptotically nonlinear oscillatory shear [Ewoldt and Bharadwaj, Rheol. Acta 52, 201–209 (2013)], also known as medium-amplitude oscillatory shear, characterized by four frequency-dependent material measures: [e1](ω), [e3](ω), [v1](ω) and [v3](ω). These slightly nonlinear rheological measurements are the systematic step beyond linear viscoelastic characterization. The material is a transiently crosslinked polymeric hydrogel of aqueous polyvinyl alcohol cross-linked by sodium tetraborate (borax) [Bharadwaj and Ewoldt, J. Rheol. 59, 557–592 (2015)], which shows nonlinear elastic stiffening inferred from [e1](ω) > 0. Here, we hypothesize that the appropriate physical model is a transient network of strain-stiffening elastic elements. We rationalize that all nonlinearities are driven by the instantaneous stretch magnitude Q between junctions, either through strain-stiffening of network elements or through deformation-assisted network structuring. These two physical aspects are embedded into a single nonlinear parameter that successfully captures both elastic energy storage ([e1](ω) and [e3](ω)]) and viscous energy dissipation ([v1](ω) and [v3](ω)), including frequency-dependent sign changes. Analytical results are derived for all four asymptotic nonlinearities. The quantitative agreement provides fit parameters that are related to molecular features and network architecture. While the work here is focused on a specific polymeric system, it represents the broad potential contribution of asymptotic, leading-order nonlinearities to enable structure-rheology insight, constitutive model development, and model selection for soft materials in general.

Rheologists have expectations for signatures of linear viscoelastic properties, such as shapes of G′(ω) and G″(ω). Medium amplitude (or asymptotically-nonlinear) oscillatory shear (MAOS) provides additional nonlinear rheological information with low dimensional, well-defined material functions [Ewoldt and Bharadwaj, Rheol. Acta 52, 201–209 (2013)]. Here, we develop expectations of signatures (or fingerprints) for the four asymptotically-nonlinear material functions associated with MAOS, [e1](ω), [e3](ω), [v1](ω), [v3](ω). Although the linear fingerprints may be identical for different models, the asymptotically-nonlinear fingerprints may be different in magnitude, frequency-scaling, curve shapes, and sign changes. To perform the analysis, we collect/translate a library of available analytical strain-controlled MAOS fingerprints for seven different constitutive models. Using this library, we identify general trends and highlight key differences of asymptotic-nonlinear viscoelasticity. Asymptotic nonlinearities for all models considered here obey the terminal regime inter-relations and frequency scaling predicted by Bharadwaj and Ewoldt [J. Rheol. 58, 891–910 (2014)]. Unlike the positive linear viscoelastic measures, at least one of the four asymptotic nonlinearities changes signs with Deborah number (De). Following sign interpretations of Ewoldt and Bharadwaj [Rheol. Acta 52, 201–209 (2013)], we show that nonlinearities tend to be driven by strain-rates at small De, and by strains at large De, a trend observed for nearly all the constitutive models studied here, the exception being the model for dilute rigid dumbbell suspensions of Bird et al. [J. Chem. Phys. 140, 074904 (2014)]. Some constitutive models exhibit multiple sign changes at intermediate De and there may be no universal behavior of asymptotically-nonlinear fingerprints in this regime. Therefore, frequency-dependent signatures can be material-specific. This will allow inverse problems to infer structure, select models, and fit model parameters using asymptotically-nonlinear signatures. To illustrate this aspect, we demonstrate a fingerprint matching exercise with experimental measurements on a transiently cross-linked hydrogel system. We find that currently available model fingerprints can match the qualitative magnitudes and frequency dependence, but not the signs of the experimental transient network response.