Microbial models development

A new concept for improved CSO impact assessment must include physical and microbial characteristics and processes. As far as the microbial heterotrophic transformations are concerned, intensive investigations have shown that suspended particles originating from sewer sediments follow the concept for wastewater depicted in Figure 5.5 (Vollertsen and Hvitved-Jacobsen, 1998 Vollertsen and Hvitved-Jacobsen, 1999 Vollertsen et al., 1999). This finding is important, because it shows that the concept and corresponding model developed for transformations of wastewater in sewers... 

The studies on phospholipid bilayers with defined amounts of charged component are helpful to explain the partition characteristics in biological membranes. Liposome water partition data of propranolol in lipids from kidney epithelial cells (a common model system in pharmaceutical sciences for the uptake into the gastrointestinal tract) have been successfully described with partition models developed for pure bilayers or defined mixtures [159]. Since lipophilic cations and anions can be used as probes for the membrane potential, their interaction with microbial and mitochondrial membranes has been studied... 

Fig.7. General strategy for the development of a microbial model of metabolism of a drug...

A number of experimental studies have established that both microbial and chemical degradation can be approximately described by first-order kinetics (24). Most pesticide models employ such an approach. As with linear sorption, this relatively naive representation of a fundamentally more complicated process is a simplifying assumption to make mathematical solutions possible and data requirements reasonable. Implicit in the assumption is the belief that the accuracy of simulation of pesticide fate is more dependent upon other factors than a very precise representation of the degradation process. These factors include spatial and temporal variability of the degradation process itself as affected by water, temperature, substrate, and pH, and variability in the transport of pesticide through the soil profile. There is little information to substantiate this assumption, although some field experiments on water and solute movement (discussed below) indicate it to be reasonable at this point in model development. 

Several approaches are utilized in the development of microbial models of mammalian metabolism. The model could be either retrospective, prospective, or parallel in relation to the mammalian studies [26]. 

The Parallel Approach This approach involves the simultaneous study of biotransformations in mammalian and microbial species. Most studies to date have been retrospective, but the trend is to make such studies more prospective. Occasionally, it is difficult to find a clear cut distinction between those approaches. In a "retrospective" study (i.e., the mammalian routes of metabolism have already been explored), the microbial model, isolated metabolites, or analytical systems developed may be used in a prospective fashion to confirm tentative metabolites or explore... 

In the water quality model developed by Burke and McCleary (20), correlations are established between the levels of various pollutants (phenols, cyanides, and ammonia), and selected environmental parameters (pH, river flow, temperature, microbial biomass). The data required for this analysis were collected over a nine-month period at four monitoring stations along a river. 

Two other broad areas of food preservation have been studied with the objective of developing predictive models. En2yme inactivation by heat has been subjected to mathematical modeling in a manner similar to microbial inactivation. Chemical deterioration mechanisms have been studied to allow the prediction of shelf life, particularly the shelf life of foods susceptible to nonen2ymatic browning and Hpid oxidation. 

H. Van der Werf and W. Verstraete, Estimation of active soil microbial biomass by mathematical analysis of respiration curves development and verification of the model. Soil Biol. Biochem. 19 252 (1987). 

---