With rapid developments in microscopy methods, highly versatile, robust and affordable implementations are needed to enable rapid and wide adoption by the biological sciences community. Here we report Squid, a quantitative imaging platform with a full suite of hardware and software components and configurations for deploying facility-grade widefield microscopes with advanced features like flat field fluorescence excitation, patterned illumination and tracking microscopy, at a fraction of the cost of commercial solutions. The open and modular nature (both in hardware and in software) lowers the barrier for deployment, and importantly, simplifies development, making the system highly configurable and experiments that can run on the system easily programmable. Developed with the goal of helping translate the rapid advances in the field of microscopy and microscopy-enabled methods, including those powered by deep learning, we envision Squid will simplify roll-out of microscopy-based applications - including at point of care and in low resource settings, make adoption of new or otherwise advanced techniques easier, and significantly increase the available microscope-hours to labs.

Theoretical modeling of curvature induced sorting of cell-membrane proteins including soft interaction potentials, shape anisotropy, and curvature anisotropy.

Centralized manufacturing and global supply chains have emerged as an efficient strategy for large-scale production of goods throughout the 20th century. However, while this system of production is highly efficient, it is not resilient. The COVID-19 pandemic has seen numerous supply chains fail to adapt to sudden changes in supply and demand, including those for goods critical to the pandemic response such as personal protective equipment. Here, we consider the production of the non-woven polypropylene filtration media used in face filtering respirators (FFRs). The FFR supply chain’s reliance on non-woven media sourced from large, centralized manufacturing facilities led to a supply chain failure. In this study, we present an alternative manufacturing strategy that allows us to move towards a more distributed manufacturing practice that is both scalable and robust. Specifically, we demonstrate that a fiber production technique known as centrifugal melt spinning can be implemented with modified, commercially-available cotton candy machines to produce nano- and microscale non-woven fibers. We evaluate several post processing strategies to transform the produced material into viable filtration media and then characterize these materials by measuring filtration efficiency and breathability, comparing them against equivalent materials used in commercially-available FFRs. Additionally, we demonstrate that waste plastic can be processed with this technique, enabling the development of distributed recycling strategies to address the growing plastic waste crisis. Since this method can be employed at small scales, it allows for the development of an adaptable and rapidly deployable distributed manufacturing network for non-woven materials that is financially accessible to more people than is currently possible.