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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. 

As the impact of COVID-19 on society became apparent, the engineering and scientific community recognized the need for innovative solutions. Two potential roadmaps emerged: developing short-term solutions to address the immediate needs of the healthcare communities and developing mid/long-term solutions to eliminate the over-arching threat. However, in a truly global effort, researchers from all backgrounds came together in tackling this challenge. Short-term efforts have focused on re-purposing existing technologies and leveraging additive manufacturing techniques to address shortages in personal protective equipment and disinfection. More basic research efforts with mid-term and long-term impact have emphasized developing novel diagnostics and accelerating vaccines. As a foundational technology, photonics has contributed directly and indirectly to all efforts. This perspective will provide an overview of the critical role that the photonics field has played in efforts to combat the immediate COVID-19 pandemic as well as how the photonics community could anticipate contributing to future pandemics of this nature. 

UV-C exposure is an effective disinfectant for a range of bacteria and viruses. As such, UV-C treatment, in combination with a chemical wipe, is a common cleaning protocol in medical facilities. Given the increase in severe bacterial and viral agents in society, having access to environmentally friendly disinfectant methods is of increasing interest. In response, we designed, constructed, and validated a UV-C disinfection system from readily accessible components. To improve the UV-C intensity, the enclosure interior was coated with chrome paint. The system is validated usingBacillus cereus, a gram-positive endospore-forming bacteria.