Concentration-effect relationship description

The linear and log-linear models are often applied approximations for the description of concentration-effect relationships in human studies when (1) the occurrence of side effects prevents the administration of higher doses or (2) the drug has a long half-life, resulting in a narrow concentration range being studied. It needs to be kept in mind that the linear and log-linear models are useful only for interpolation, but not extrapolation. 

FIGURE 7.2 Description of concentration-effect relationships base on the characteristics of a dose-response curve. 

This allows the calculation of an effect expected according to the concept of response addition for any concentration of the mixture. Again, the estimated individual effect may be taken from a concentration-response relationship derived on the basis of dose-response observations. It has to be noted that, in mixtures of many substances, the effects to be estimated for the individual contributors become rather small therefore, a high-quality estimation of the concentration response, particularly in the low effect region, is needed. In such cases, it might be useful to consider models other than the standard probit or logit functions for description of the data. 

Polymerization reactions require stringent operating conditions for continuous production of quality resins. In this paper the chain-growth polymerization of styrene initiated with n-butyllithium in the presence of a solvent is described. A perfectly mixed isothermal, constant volume reactor is employed. Coupled kinetic relationships descriptive of the initiator, monomer, polystyryl anion and polymer mass concentration are simulated. Trommsdorff effects (1) are incorporated. Controlled variables include number average molecular weight and production rate of total polymer. Manipulated variables are flow rate, input monomer concentration, and input initiator concentration. The... 

The hybrid model proposed by Zingmark et al. (26) is a straightforward way of incorporating Markov elements in an analysis of ordered categorical data. An inappropriate model—a bad descriptive model or a model with a bad predictive performance (see Ette et al. (34) Chapter 8 of this text)—would result if the correlated nature of the data is ignored and a proportional odds model is used to characterize the concentration-adverse effect relationship. Readers are referred to the article by Zingmark et al. (26) for a detailed description of the hybrid model. They also provide a NONMEM data set and control file for the implementation of the model. 

Chemesthesis. The term chemesthesis has been introduced to classify thermal and painful sensations experienced in the mouth (26). Chemesthesis refers to a chemical sensibility (mouthfeel) in which certain chemicals direcdy activate nerve fibers at the level of the basal membrane in the mouth. The sensations are analogous to similar effects at the skin surface where there is a close anatomical and functional relationship. Sensations include the "hot" of capsaicin and piperine, which are active components of chili and pepper, the coolness of menthol and the irritation of chemicals such as salt at high concentrations [FIGURE 4]. Some of the descriptive terms used to make qualitative distinctions in food sensations include pungency, freshness, tingling, burning and sharpness. 

The remainder of this book applies thermodynamics to the description of a variety of systems that are of chemical interest. Chapter 12 uses thermodynamics to describe the effects of other variables such as gravitational field, centrifugal field, and surface area on the properties of the system. Most of the focus of the chapter is on surface effects. The surface properties of pure substances are described first, including the effect of curvature on the properties of the surface. For mixtures, the surface concentration is defined and its relationship to the surface properties is described. 

It has to be remarked that the model discussed above is valid for the description of linear relationships between concentration and the response. If the concentration range has to be extended further, nonlinear effects cannot be excluded [ZWANZIGER et al., 1988]. Then the whole concentration range should be split into two experimental plans for separate treatment of the high and the low concentration levels. Accordingly, two separate linear models can be calculated for the different experimental plans. 

The majority of experimental mixture studies have analyzed the effects that arise from simultaneous exposure to chemicals. Very few studies exist where sequential exposure to several chemicals was analyzed. Only a concept founded on an understanding of the relationship between dose or concentration and exposure duration, time to effect, and recovery can hope to deal with the effect of sequential exposures. Conceptual frameworks for descriptions of time-dependent toxicity from a mechanistic perspective are available (e.g., Rozman and Doull 2000 Ashauer et al. 2006). However, the link between existing dose-time response models and a framework for mixture effect analysis from sequential exposure has yet to be made. A recent example of an interesting study that looked at sequential exposures is from Ashauer et al. (2007b), who base their analysis on a 1-compartment model for substance uptake, plus additional parameters for effect propagation and recovery. Generalizations are not yet in sight. 

The description of a colloid should include particle size, mobility, charge and their distributions, charge/mass ratio, electrical conductivity of the media, concentration and mobility of ionic species, the extent of a double layer, particle-particle and particle-substrate interaction forces and complete interfacial analysis. The application of classical characterization methods to nonaqueous colloids is limited and, for this reason, the techniques best suited to these systems will be reviewed. Characteristic results obtained with nonaqueous dispersions will be summarized. Physical aspects, such as space charge effects and electrohydrodynamics, will receive special attention while the relationships between chemical and physical properties will not be addressed. An application of nonaqueous colloids, the electrophoretic development of latent images, will also be discussed. 

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