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Dynamic Fluid Flow Exacerbates the (Pro-)Inflammatory Effects of Aerosolised Engineered Nanomaterials In Vitro
Nanomaterials, Volume: 12, Issue: 19, Start page: 3431
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The majority of in vitro studies focusing upon particle–lung cell interactions use static models at an air–liquid interface (ALI). Advancing the physiological characteristics of such systems allows for closer resemblance of the human lung, in turn promoting 3R strategies. PATROLS (EU Hori-zon 2020 N...
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The majority of in vitro studies focusing upon particle–lung cell interactions use static models at an air–liquid interface (ALI). Advancing the physiological characteristics of such systems allows for closer resemblance of the human lung, in turn promoting 3R strategies. PATROLS (EU Hori-zon 2020 No.760813) aimed to use a well-characterised in vitro model of the human alveolar ep-ithelial barrier to determine how fluid-flow dynamics would impact the outputs of the model following particle exposure. Using the QuasiVivoTM (Kirkstall Ltd., York, UK) system, fluid-flow conditions were applied to an A549 + dTHP-1 cell co-culture model cultured at the ALI. DQ12 and TiO2 (JRCNM01005a) were used as model particles to assess the in vitro systems’ sensitivity. Us-ing a quasi- and aerosol (VitroCell Cloud12, VitroCell Systems, Germany) exposure approach, cell cultures were exposed over 24hrs at IVIVE concentrations of 1 and 10 (DQ12) and 1.4 and 10.4 (TiO2) µg/cm2, respectively. We compared static and fluid flow conditions after both these expo-sure methods. The co-culture was subsequently assessed for its viability, membrane integrity and (pro-)inflammatory response (IL-8 and IL-6 production). The results suggested that the addition of fluid flow to this alveolar co-culture model can influence the viability, membrane integrity and inflammatory responses dependent on the particle type and exposure.
in vitro; micro-fluidics; fluid flow; co-culture; lung; nanoparticles; aerosol exposure; quasi-ALI exposure
Faculty of Medicine, Health and Life Sciences
This research was funded by the PATROLS project, European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No: 760813.