A statistical algorithm for assessing cellular alignment

Deterministic Integration of Biological and Soft Materials onto 3D Microscale Cellular Frameworks

Complex 3D organizations of materials represent ubiquitous structural motifs found in the most sophisticated forms of matter, the most notable of which are in life-sustaining hierarchical structures found in biology, but where simpler examples also exist as dense multilayered constructs in high-performance electronics. Each class of system evinces specific enabling forms of assembly to establish their functional organization at length scales not dissimilar to tissue-level constructs. This study describes materials and means of assembly that extend and join these disparate systems-schemes for the functional integration of soft and biological materials with synthetic 3D microscale, open frameworks that can leverage the most advanced forms of multilayer electronic technologies, including device-grade semiconductors such as monocrystalline silicon. Cellular migration behaviors, temporal dependencies of their growth, and contact guidance cues provided by the nonplanarity of these frameworks illustrate design criteria useful for their functional integration with living matter (e.g., NIH 3T3 fibroblast and primary rat dorsal root ganglion cell cultures).

Gradient static-strain stimulation in a microfluidic chip for 3D cellular alignment

Cell alignment is a critical factor to govern cellular behavior and function for various tissue engineering applications ranging from cardiac to neural regeneration. In addition to physical geometry, strain is a crucial parameter to manipulate cellular alignment for functional tissue formation. In this paper, we introduce a simple approach to generate a range of gradient static strains without external mechanical control for the stimulation of cellular behavior within 3D biomimetic hydrogel microenvironments. A glass-supported microfluidic chip with a convex flexible polydimethylsiloxane (PDMS) membrane on the top was employed for loading the cells suspended in a prepolymer solution. Following UV crosslinking through a photomask with a concentric circular pattern, the cell-laden hydrogels were formed in a height gradient from the center (maximum) to the boundary (minimum). When the convex PDMS membrane retracted back to a flat surface, it applied compressive gradient forces on the cell-laden hydrogels. The concentric circular hydrogel patterns confined the direction of hydrogel elongation, and the compressive strain on the hydrogel therefore resulted in elongation stretch in the radial direction to guide cell alignment. NIH3T3 cells were cultured in the chip for 3 days with compressive strains that varied from ~65% (center) to ~15% (boundary) on hydrogels. We found that the hydrogel geometry dominated the cell alignment near the outside boundary, where cells aligned along the circular direction, and the compressive strain dominated the cell alignment near the center, where cells aligned radially. This study developed a new and simple approach to facilitate cellular alignment based on hydrogel geometry and strain stimulation for tissue engineering applications. This platform offers unique advantages and is significantly different from the existing approaches owing to the fact that gradient generation was accomplished in a miniature device without using an external mechanical source.

Quantifying cellular alignment on anisotropic biomaterial platforms

How do we quantify cellular alignment? Cellular alignment is an important technique used to study and promote tissue regeneration in vitro and in vivo. Indeed, regenerative outcomes are often strongly correlated with the efficacy of alignment, making quantitative, automated assessment an important goal for the field of tissue engineering. There currently exist various classes of algorithms, which effectively address the problem of quantifying individual cellular alignments using Fourier methods, kernel methods, and elliptical approximation; however, these algorithms often yield population distributions and are limited by their inability to yield a scalar metric quantifying the efficacy of alignment. The current work builds on these classes of algorithms by adapting the signal processing methods previously used by our group to study the alignment of cellular processes. We use an automated, ellipse-fitting algorithm to approximate cell body alignment with respect to a silk biomaterial scaffold, followed by the application of the normalized cumulative periodogram criterion to produce a scalar value quantifying alignment. The proposed work offers a generalized method for assessing cellular alignment in complex, two-dimensional environments. This method may also offer a novel alternative for assessing the alignment of cell types with polarity, such as fibroblasts, endothelial cells, and mesenchymal stem cells, as well as nuclei.