Characterization of the effects of an airborne mixture of chemicals on the respiratory tract and smoothing polynomial spline analysis of the data.

We expanded a previously published (Vijayaraghavan et al. 1994) computerized system to analyze the breathing pattern of unanesthetized mice in order better to recognize and quantify the effects of an airborne mixture of chemicals at three different levels of the respiratory tract. The airborne chemical mixture used was a machining fluid. Such fluids are widely used in industry and a large number of workers are exposed to these airborne mixtures. We found this mixture to be capable of inducing three types of effects on the respiratory tract: sensory irritation of the upper respiratory tract (S), airflow limitation along the conducting airways (A) and pulmonary irritation (P). Depending upon the exposure concentration, mainly S or P effects were obtained but an A effect was also identified. The three types of effects occurred at various times during the exposures and, furthermore, within a group of exposed animals some exhibited one type of effect while others exhibited another type. In order to analyze such complex data sets, two statistical methods for smoothing polynomial splines were utilized: the maximum likelihood (ML) method and generalized cross validation (GCV) method. The results indicated the previous methods used to characterize a single effect of airborne chemicals can now be extended to evaluate mixtures likely to induce multiple types of effects. However, statistical analysis methods, either the ML or GCV methods, or other appropriate methods are needed to evaluate the responses obtained due to the complex effects that a mixture can induce in comparison to single chemicals.