Search for: All records

Ascertaining the collective viability of cells in different cell culture conditions has typically relied on averaging colorimetric indicators and is often reported out in simple binary readouts. Recent research has combined viability assessment techniques with image-based deep-learning models to automate the characterization of cellular properties. However, further development of viability measurements to assess the continuity of possible cellular states and responses to perturbation across cell culture conditions is needed. In this work, we demonstrate an image processing algorithm for quantifying features associated with cellular viability in 3D cultures without the need for assay-based indicators. We show that our algorithm performs similarly to a pair of human experts in whole-well images over a range of days and culture matrix compositions. To demonstrate potential utility, we perform a longitudinal study investigating the impact of a known therapeutic on pancreatic cancer spheroids. Using images taken with a high content imaging system, the algorithm successfully tracks viability at the individual spheroid and whole-well level. The method we propose reduces analysis time by 97% in comparison with the experts. Because the method is independent of the microscope or imaging system used, this approach lays the foundation for accelerating progress in and for improving the robustness and reproducibility of 3D culture analysis across biological and clinical research. 

Biomaterials are being developed as therapeutics for spinal cord injury (SCI) that can stabilize and bridge acute lesions and mediate the delivery of transgenes, providing a localized and sustained reservoir of regenerative factors. For clinical use, direct injection of biomaterial scaffolds is preferred to enable conformation to unique lesions and minimize tissue damage. While an interconnected network of cell-sized macropores is necessary for rapid host cell infiltration into—and thus integration of host tissue with—implanted scaffolds, injectable biomaterials have generally suffered from a lack of control over the macrostructure. As genetic vectors have short lifetimes in vivo, rapid host cell infiltration into scaffolds is a prerequisite for efficient biomaterial-mediated delivery of transgenes. We present scaffolds that can be injected and assembled in situ from hyaluronic acid (HA)-based, spherical microparticles to form scaffolds with a network of macropores (∼10 μm). The results demonstrate that addition of regularly sized macropores to traditional hydrogel scaffolds, which have nanopores (∼10 nm), significantly increases the expression of locally delivered transgene to the spinal cord after a thoracic injury. Maximal cell and axon infiltration into scaffolds was observed in scaffolds with more regularly sized macropores. The delivery of lentiviral vectors encoding the brain-derived neurotrophic factor (BDNF), but not neurotrophin-3, from these scaffolds further increased total numbers and myelination of infiltrating axons. Modest improvements to the hindlimb function were observed with BDNF delivery. The results demonstrate the utility of macroporous and injectable HA scaffolds as a platform for localized gene therapies after SCI.