In situ-Like Aerosol Inhalation Exposure for Cytotoxicity Assessment Using Airway-on-Chips Platforms

Lung exposure to inhaled particulate matter (PM) is known to injure the airway epithelium via inflammation, a phenomenon linked to increased levels of global morbidity and mortality. To evaluate physiological outcomes following PM exposure and concurrently circumvent the use of animal experiments, in vitro approaches have typically relied on traditional assays with plates or well inserts. Yet, these manifest drawbacks including the inability to capture physiological inhalation conditions and aerosol deposition characteristics relative to in vivo human conditions. Here, we present a novel airway-on-chip exposure platform that emulates the epithelium of human bronchial airways with critical cellular barrier functions at an air-liquid interface (ALI). As a proof-of-concept for in vitro lung cytotoxicity testing, we recapitulate a well-characterized cell apoptosis pathway, induced through exposure to 2 μm airborne particles coated with αVR1 antibody that leads to significant loss in cell viability across the recapitulated airway epithelium. Notably, our in vitro inhalation assays enable simultaneous aerosol exposure across multiple airway chips integrated within a larger bronchial airway tree model, under physiological respiratory airflow conditions. Our findings underscore in situ-like aerosol deposition outcomes where patterns depend on respiratory flows across the airway tree geometry and gravitational orientation, as corroborated by concurrent numerical simulations. Our airway-on-chips not only highlight the prospect of realistic in vitro exposure assays in recapitulating characteristic local in vivo deposition outcomes, such platforms open opportunities toward advanced in vitro exposure assays for preclinical cytotoxicity and drug screening applications.

Ventilation-induced jet suggests biotrauma in reconstructed airways of the intubated neonate

We investigate respiratory flow phenomena in a reconstructed upper airway model of an intubated neonate undergoing invasive mechanical ventilation, spanning conventional to high-frequency ventilation (HFV) modes. Using high-speed tomographic particle image velocimetry, we resolve transient, three-dimensional flow fields and observe a persistent jet flow exiting the endotracheal tube whose strength is directly modulated according to the ventilation protocol. We identify this synthetic jet as the dominating signature of convective flow under intubated ventilation. Concurrently, our in silico wall shear stress analysis reveals a hitherto overlooked source of ventilator-induced lung injury as a result of jet impingement on the tracheal carina, suggesting damage to the bronchial epithelium; this type of injury is known as biotrauma. We find HFV advantageous in mitigating the intensity of such impingement, which may contribute to its role as a lung protective method. Our findings may encourage the adoption of less invasive ventilation procedures currently used in neonatal intensive care units.

Publisher's Note: Effect of reaction-step-size noise on the switching dynamics of stochastic populations [Phys. Rev. E 93, 052117 (2016)]

This corrects the article DOI: 10.1103/PhysRevE.93.052117.

Effect of reaction-step-size noise on the switching dynamics of stochastic populations

In genetic circuits, when the messenger RNA lifetime is short compared to the cell cycle, proteins are produced in geometrically distributed bursts, which greatly affects the cellular switching dynamics between different metastable phenotypic states. Motivated by this scenario, we study a general problem of switching or escape in stochastic populations, where influx of particles occurs in groups or bursts, sampled from an arbitrary distribution. The fact that the step size of the influx reaction is a priori unknown and, in general, may fluctuate in time with a given correlation time and statistics, introduces an additional nondemographic reaction-step-size noise into the system. Employing the probability-generating function technique in conjunction with Hamiltonian formulation, we are able to map the problem in the leading order onto solving a stationary Hamilton-Jacobi equation. We show that compared to the "usual case" of single-step influx, bursty influx exponentially decreases the population's mean escape time from its long-lived metastable state. In particular, close to bifurcation we find a simple analytical expression for the mean escape time which solely depends on the mean and variance of the burst-size distribution. Our results are demonstrated on several realistic distributions and compare well with numerical Monte Carlo simulations.