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Atmospheric particulate pollution  has  been  linked  to a broad  spectrum of adverse health  effects including respiratory  problems, cardiovascular  diseases, cancer and dementia.  These  effects  depend  not  only  on physical,  but  also  on  chemical  properties  of  airborne  particulate  matter  (PM)  though  to  date  it  has  proven difficult to disentangle  the relative contribution  of  PM  constituents  to  the  reported  population-level  health effects. We propose the use of “tailored” reference aerosols, combined with high-resolution optical imaging of exposed cells and state-of-the-art cell analysis methods to study the cytotoxic effects of airborne PM in vitro in a systematic way to help inform which PM metrics are associated with the induction of toxic mechanisms that can be linked to specific health effects. Need Airborne  particles  cause  serious acute and chronic human health effects, associated with several hundred thousand premature deaths in the EU each year.

For historical reasons, atmospheric particulate pollutants have been regulated for human health purposes by the mass concentration of discrete size fractions: PM10and  PM2.5 (particles  with  diameter  below  10 μm  and  2.5 μm,  respectively).  PM  mass  concentration, however, fails to capture the chemical heterogeneity of airborne particulates and is uninformative concerning the toxicologically important contributions of ultrafine particles (<100 nm), which are of negligible mass. We and  others  have  therefore  hypothesized  that PM mass concentration, whilst useful, is not the most informative metric to characterise the potential of particles to cause the disparate detrimental health effects reported in the literature. The focus on mass also precludes the application of intelligent targeting of ‘health-relevant’  constituents. 

There is  therefore  a  need  to  generate  new  data  on  the  contribution  of  PM constituents to discrete toxicological relevant pathways that can inform the causal link between the particles we breathe and the down-stream health effects. Such information is vital if new metrics, such as particle size, number concentration and chemistry, are to be integrated into the existing air quality guidelines.The current literature evaluating the associations between air pollution and adverse health outcomes has been dominated  by epidemiological  studies,  investigating the overall  healt  effects of  atmospheric air pollution, including particles, gases and mixtures. 

These studies, however, are limited in their capacity to distinguish independent effects of isolated aerosol components or properties on health. To disentangle the effects of the different aerosol properties on health, there is a need for well-defined reference aerosols generated in the laboratory. These aerosols should simulate the properties of real ambient aerosols while being stable and reproducible, with  properties  that  can  be  "tailored" according  to  the  experimental  needs  and  the  specific research questions asked. In vitro studies are essential for understanding the cause-effect relationship between airborne particles and cell/tissue  damage. 

However,  their value is fundamentally dependent on robust  in vitro to in vivo correlation. To achieve this there is a need to go beyond the traditional cell-exposure techniques and simple biological models (e.g. 2D cultures). Novel methods for cell exposure that mimic the natural inhalation routes must  be  employed and new biological models, such as lung  organoids and lung  scaffolds  (3D  multicellular structures), must be developed to provide physiologically relevant models for measuring biological effects. Cellular responses to pollutant stressors can be investigated with a combination of optical imaging techniques and  biomedical  assays. In  both cases, quantification  and  integration of data from across multiple  analytical platforms is  challenging  statistically  and  subject  to  measurement error and/or interpretive biases.  For  a meaningful  integration of multiple endpoints to establish  adverse outcome  pathways  (AOPs) in relation to specific PM properties and components, a metrology framework must be established to derive quantitative and reproducible response metrics.

PI: Dr Ian Mudway