The Critical Importance of Spatial and Temporal Scales in Designing and Interpreting Immune Cell Migration Assays.

Intravital microscopy and other direct-imaging techniques have allowed for a characterisation of leukocyte migration that has revolutionised the field of immunology, resulting in an unprecedented understanding of the mechanisms of immune response and adaptive immunity. However, there is an assumption within the field that modern imaging techniques permit imaging parameters where the resulting cell track accurately captures a cell's motion. This notion is almost entirely untested, and the relationship between what could be observed at a given scale and the underlying cell behaviour is undefined. Insufficient spatial and temporal resolutions within migration assays can result in misrepresentation of important physiologic processes or cause subtle changes in critical cell behaviour to be missed. In this review, we contextualise how scale can affect the perceived migratory behaviour of cells, summarise the limited approaches to mitigate this effect, and establish the need for a widely implemented framework to account for scale and correct observations of cell motion. We then extend the concept of scale to new approaches that seek to bridge the current "black box" between single-cell behaviour and systemic response.

A Novel Ventilator Design for COVID-19 and Resource-Limited Settings.

There has existed a severe ventilator deficit in much of the world for many years, due in part to the high cost and complexity of traditional ICU ventilators. This was highlighted and exacerbated by the emergence of the COVID-19 pandemic, during which the increase in ventilator production rapidly overran the global supply chains for components. In response, we propose a new approach to ventilator design that meets the performance requirements for COVID-19 patients, while using components that minimise interference with the existing ventilator supply chains. The majority of current ventilator designs use proportional valves and flow sensors, which remain in short supply over a year into the pandemic. In the proposed design, the core components are on-off valves. Unlike proportional valves, on-off valves are widely available, but accurate control of ventilation using on-off valves is not straightforward. Our proposed solution combines four on-off valves, a two-litre reservoir, an oxygen sensor and two pressure sensors. Benchtop testing of a prototype was performed with a commercially available flow analyser and test lungs. We investigated the accuracy and precision of the prototype using both compressed gas supplies and a portable oxygen concentrator, and demonstrated the long-term durability over 15 days. The precision and accuracy of ventilation parameters were within the ranges specified in international guidelines in all tests. A numerical model of the system was developed and validated against experimental data. The model was used to determine usable ranges of valve flow coefficients to increase supply chain flexibility. This new design provides the performance necessary for the majority of patients that require ventilation. Applications include COVID-19 as well as pneumonia, influenza, and tuberculosis, which remain major causes of mortality in low and middle income countries. The robustness, energy efficiency, ease of maintenance, price and availability of on-off valves are all advantageous over proportional valves. As a result, the proposed ventilator design will cost significantly less to manufacture and maintain than current market designs and has the potential to increase global ventilator availability.

An Integrated Pipeline for Combining in vitro Data and Mathematical Models Using a Bayesian Parameter Inference Approach to Characterize Spatio-temporal Chemokine Gradient Formation.

All protective and pathogenic immune and inflammatory responses rely heavily on leukocyte migration and localization. Chemokines are secreted chemoattractants that orchestrate the positioning and migration of leukocytes through concentration gradients. The mechanisms underlying chemokine gradient establishment and control include physical as well as biological phenomena. Mathematical models offer the potential to both understand this complexity and suggest interventions to modulate immune function. Constructing models that have powerful predictive capability relies on experimental data to estimate model parameters accurately, but even with a reductionist approach most experiments include multiple cell types, competing interdependent processes and considerable uncertainty. Therefore, we propose the use of reduced modeling and experimental frameworks in complement, to minimize the number of parameters to be estimated. We present a Bayesian optimization framework that accounts for advection and diffusion of a chemokine surrogate and the chemokine CCL19, transport processes that are known to contribute to the establishment of spatio-temporal chemokine gradients. Three examples are provided that demonstrate the estimation of the governing parameters as well as the underlying uncertainty. This study demonstrates how a synergistic approach between experimental and computational modeling benefits from the Bayesian approach to provide a robust analysis of chemokine transport. It provides a building block for a larger research effort to gain holistic insight and generate novel and testable hypotheses in chemokine biology and leukocyte trafficking.