Multi-wavelength multi-direction laser light scattering for cell characterization using machine learning-based methods.

Cell identification and analysis play a crucial role in many biology- and health-related applications. The internal and surface structures of a cell are complex and many of the features are sub-micron in scale. Well-resolved images of these features cannot be obtained using optical microscopy. Previous studies have reported that the single-cell angular laser-light scattering patterns (ALSP) can be used for label-free cell identification and analysis. The ALSP can be affected by cell properties and the wavelength of the probing laser. Two cell properties, cell surface roughness and the number of mitochondria, are investigated in this study. The effects of probing laser wavelengths (blue, green, and red) and the directions of scattered light collection (forward, side, and backward) are studied to determine the optimum conditions for distinguishing the two cell properties. Machine learning (ML) analysis has been applied to ALSP obtained from numerical simulations. The results of ML analysis show that the backward scattering is the best direction for characterizing the surface roughness, while the forward scattering is the best direction for differentiating the number of mitochondria. The laser light having red or green wavelength is found to perform better than that having the blue wavelength in differentiating the surface roughness and the number of mitochondria. This study provides important insights into the effects of probing laser wavelength on gaining information about cells from their ALSP.

Convergence between global BCG vaccination and COVID-19 pandemic.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has kept the whole world in tenterhooks due to its severe life-threatening infectious disease, COVID-19. The virus is distinct from its cousins, SARS-CoV and MERS-CoV in terms of severity of the infection. The obligated killing properties of the SARS-CoV-2 virus is mediated by its unique structure. Efforts for developing vaccines for COVID-19 are ongoing, but it is unlikely to be available in the immediate future. Due to the absence of precise treatment, the investigators are discovering other effective, protective, and healing choices. However, the lower than a predictable number of SARS-CoV-2 cases in countries with fragile health systems is mystifying. Recently, there has been a buzz about the protective effect of Bacille Calmette-Guérin (BCG) vaccine in COVID-19 through long-term boosting of trained immunity. Based on epidemiological correlations, we link up that BCG vaccination adopted by different countries might influence the SARS-CoV-2 transmission patterns and/or COVID-19 associated mortality through the vaccine's capacity to confer heterologous protection. A number of clinical studies are underway to investigate this possibility but even if they prove effective-many questions will remain. Moreover, responsible stewardship of the BCG vaccine in the context of the COVID-19 epidemic is directly needed.

Quasi-3D Modeling and Efficient Simulation of Laminar Flows in Microfluidic Devices.

A quasi-3D model has been developed to simulate the flow in planar microfluidic systems with low Reynolds numbers. The model was developed by decomposing the flow profile along the height of a microfluidic system into a Fourier series. It was validated against the analytical solution for flow in a straight rectangular channel and the full 3D numerical COMSOL Navier-Stokes solver for flow in a T-channel. Comparable accuracy to the full 3D numerical solution was achieved by using only three Fourier terms with a significant decrease in computation time. The quasi-3D model was used to model flows in a micro-flow cytometer chip on a desktop computer and good agreement between the simulation and the experimental results was found.