Paul H. Morgan

Binding of formaldehyde to human and rat nasal mucus and bovine serum albumin

The function of the nasal mucociliary apparatus, an important airway defense mechanism, is inhibited by inhaled formaldehyde. Nasal mucus, which contains significant concentrations of glycoprotein and soluble proteins, is an integral component of this system. This investigation addresses some reactions of formaldehyde with human and rat mucus in vitro in comparison with a model protein, bovine serum albumin. [14C]Formaldehyde was incubated with reconstituted preparations of human and rat nasal mucus or bovine serum albumin. Formaldehyde adducts, stabilized by sodium cyanoborohydride reduction to methylamines, were separated by Sepharose 2B gel filtration. [14C]Formaldehyde bound exclusively to one component of nasal mucus which had an elution volume identical to that of albumin. There was no detectable binding to the large molecular weight glycoproteins. The time course of reaction of formaldehyde to free amino groups was then measured using the fluorescamine technique. Formaldehyde binding was characterized by an initial fast phase (less than 2 min) followed by a slower phase which appeared to approach equilibrium (greater than 60 min). The rate of binding to human and rat nasal mucus was similar to albumin. Irreversible binding of formaldehyde to albumin was insignificant within the first 60 min indicating the reversibility of binding during this time. These data indicate that within the first 60 min, formaldehyde reacts rapidly and reversibly with nasal mucus and that it binds primarily to one component of nasal mucus. Gel filtration analysis suggests this component may be albumin although other low molecular weight proteins cannot be ruled out.

Use of resampling techniques to estimate the variance of parameters in pharmacological assays when experimental protocols preclude independent replication: An example using schild regressions

Estimates of variance in pharmacological assays are usually made by repeating the experiment with different tissues. Biological factors, such as the inability to wash a drug from tissue, may preclude the type of replication that is appropriate for the statistics of interest. For example, in Schild regressions, replication is usually done at each concentration of antagonist. In some test systems, replication of dose-response curves is not possible. For example, some persistent agonists cannot be removed from tissues after exposure, while in other systems, rapid desensitization severely alters tissue sensitivity to repeated challenge with agonist. In this paper, we demonstrate how a statistical resampling method, bootstrapping, can be used to derive estimates of the confidence intervals for pA2, pKB, and slope from Schild plots. This method utilizes the speed of the computer to estimate variance by repeatedly resampling the data. The advantage to this method is that it can be used for many different experimental designs. For a data set obtained from a Schild regression of atenolol antagonism of isoproterenol in the guinea pig left atrium, bootstrap estimates of confidence limits were calculated for cases where dose ratios were derived from the same tissue and randomly paired tissues. These estimates showed good agreement with estimates obtained using conventional analytical methods, thus suggesting that this method may be useful in practice.

A mathematical model for analysis of pharmacologically induced changes in the kinetics of cardiac muscle

A mathematical model of the isometric contraction of cardiac muscle is developed and utilized to characterize the inotropic and lusitropic effects of cardioactive compounds in isolated guinea pig left atria. In contrast to metrics that are based on minima and maxima of an isometric twitch and its derivative function, the entire time course of the twitch is used to quantify the kinetics of the contraction-relaxation cycle. The model relates observed tension to a time-dependent activation function that describes generation of internal force and a coupling function that determines mechanical response to the activation function. The model is structured so that it is suitable for nonlinear curve fitting to observed data. Results obtained using the model for fitting experimental data from tissues treated with different classes of cardioactive compounds agree with more qualitative results presented by other authors. Experiments using the model to fit data over an extended (90 min) time course revealed differences in the kinetic profiles of milrinone and forskolin. Computer simulations that demonstrate the effect of each model parameter on twitch kinetics are presented, and the relationships between the model and other theoretical and empirical models of cardiac muscle are discussed. The mathematical model is useful to enable a more quantitative understanding of the kinetics of cardiac muscle contraction and relaxation and identify compounds that may be selective for inotropic or lusitropic effects.