A comparison of murine and human alveolar macrophage responses to urban particulate matter.

There is increasing evidence linking mortality, increased asthma morbidity, and other respiratory disorders to increases in fine airborne particulate matter (PM) concentrations. However, there are only limited data dealing with the biological mechanisms that ultimately lead to the reported health effects. Rodents are frequently used as an animal model to help elucidate the mechanisms of toxicity that may provide clues for the understanding of PM toxicity in humans; however, the relationships between murine and human PM toxicity have not been established. PM is known to target the pulmonary epithelium and resident alveolar macrophages (AM). PM can initiate cytotoxic effects on the AM including apoptosis and necrosis, depending on the particle concentration, which may be central to the pathological effects just described. This study examined AM apoptosis and necrosis initiated by PM in AM from humans and BALB/c mice in an in vitro exposure model. Freshly isolated AM from human volunteers were incubated with seven different residual fractions of PM1648 derived from organic solvent extractions, high-temperature heating and acid digestions that change the surface characteristics of the original PM. These results were compared to the analogous murine experiments. The results suggested that, at the same concentration of PM, the trend of toxicity and the posttreatment effects observed in BALB/c and human AM have a similar pattern. Altering the surface chemistry by removal of one or more PM components, such as through the various treatments conducted in this study, is sufficient to alter PM bioactivity in both human and murine AM in a similar manner. In addition, the human and murine models were compared with regard to in vitro cytotoxicity using PM(2.5) particles. The cytotoxic PM(2.5) effects were identical in both human and mouse models. Regression analysis revealed that the BALB/c mouse is a suitable model for PM cytotoxicity of AM as it is a good predictive model for the human AM responses.