Populations, effect-related parameter

Sherman SS, Hollis BW, Tobin JD. Vitamin D status and related parameters in a healthy population the effects of age, sex and season. J Clin Endocrinol Metab 1990 71 405-13. 

In predicting the effects of a pollutant on population growth rate, the effects of the chemical on the values of t, I, and n are of central interest. Chemical residue data and biomarker assays that provide measures of toxic effects are relevant here because they can, in concept, be used to relate the effects of a chemical upon the individual organism to a population parameter such as survivorship or fecundity (Figures 4.5 and 4.6). Examples of this are discussed in the second part of the text, including the reduction of survivorship of sparrow hawks caused by dieldrin (Chapter 5), the... 

Experiments cannot tell us what transition states look like. The fact is that transition states cannot even be detected experimentally let alone characterized, at least not directly. While measured activation energies relate to the energies of transition states above reactants, and while activation entropies and activation volumes, as well as kinetic isotope effects, may be invoked to imply some aspects of transition-state structure, no experiment can actually provide direct information about the detailed geometries and/or other physical properties of transition states. Quite simply, transition states do not exist in terms of a stable population of molecules on which experimental measurements may be made. Experimental activation parameters provide some guide, but tell us little detail about what actually transpires in going from reactants to products. 

Tachida (1991) characterized the behavior of a population on a neutral network based on the parameter 4Mcr, where M is the population size and a is the standard deviation of the effects of mutations on the fitness. The parameter a is related to the tolerance of a residue in a protein. If cr is large, then the effect of mutations is large. Three types of behavior are identified in this model. In the case 4M[Pg.151]

The PPK approach estimates the joint distribution of population specific pharmacokinetic model parameters for a given drug. Fixed effect parameters quantify the relationship e.g. of clearance to individual physiology like function of liver, kidney, or heart. The volume of distribution is typically related to body size. Random effect parameters quantify the inter-subject variability which remains after the fixed effects have been taken into account. Then the observed concentrations will still be randomly distributed around the concentration time course predicted by the model for an individual subject. This last error term called residual variability... 

Another indirect approach to quantify biologic uncertainty is to measure the observed variability in human populations. Calabrese (1985) examined a number of parameters related to toxicokinetics (metabolism, binding of chemicals to protein and DNA, and activity levels of enzymes). In studies that included between 10 and 349 subjects, Calabrese concluded that generally 75-95% of the population fell within a range of 10-fold. However, the author s conclusion was based on the supposition that the 10-fold factor was to account for the total range of human variability as opposed to the range from an experimental no-observed-effect level to the most susceptible person. In a similar study, Hattis et al. (1987) evaluated toxicokinetic parameters in 101... 

An important parameter in the risk assessment of hazardous wastes is the no-effect level to which a population may be exposed. This level, defined as the no observed effect level (NOEL), is difficult to measure and also difficult to define accurately. Its values are based on epidemiological data and controlled animal experiments designed to determine the highest dose that wiU not produce an adverse effect. The no observed adverse effect level (NOAEL) is a variant of the NOEL in that it classifies only toxicological effects. Other measures related to the NOEL and the NOAEL are the LOEL lowest observed effect level) and LOAEL lowest observed adverse effect level), a stricter version of the LOEL. 

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