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Microbial growth result

Nonoxidizing Antimicrobials. Nonoxidizing antimicrobials usually control growths by one of two mechanisms. In one, microbes are inhibited or killed as a result of damage to the ceU membrane. In the other, microbial death results from damage to the biochemical machinery involved in energy production or energy utilization. [Pg.272]

KL-a and v for the 10 litres/min airflow rate for the 15 litre aeration system was 0.0509 h-1 and 1.3 ms 1. From the experimental results, the microbial growth was not at the optimum stage for the reasons mentioned earlier. Nevertheless, a reduction of around 95% can be achieved for carbohydrate reduction. However, further studies should be earned out for optimisation of the treatment and to improve COD reduction for pharmaceutical waste-water treatment. [Pg.48]

Chloroform (CHCI3) has a narrow spectrum of activity. It has been used extensively as a preservative in pharmaceuticals since the last century though recently has had limitations placed on its use. Marked reductions in concentration may occur through volatilization from products resulting in the possibility of microbial growth. [Pg.219]

The importance of including soil-based parameters in rhizosphere simulations has been emphasized (56). Scott et al. u.sed a time-dependent exudation boundary condition and a layer model to predict how introduced bacteria would colonize the root environment from a seed-based inoculum. They explicitly included pore size distribution and matric potential as determinants of microbial growth rate and diffusion potential. Their simulations showed that the total number of bacteria in the rhizosphere and their vertical colonization were sensitive to the matric potential of the soil. Soil structure and pore size distribution was also predicted to be a key determinant of the competitive success of a genetically modified microorganism introduced into soil (57). The Scott (56) model also demonstrated that the diffusive movement of root exudates was an important factor in determining microbial abundance. Results from models that ignore the spatial nature of the rhizosphere and treat exudate concentration as a spatially averaged parameter (14) should therefore be treated with some caution. [Pg.351]

The interpretation of sterility results is divided into two stages by the USP relative to the type of sterility failure if one occurs. If sterility failure of the test samples occurred because of improper aseptic technique or as a fault of the test itself, stage 1 may be repeated with the same sample size. Sample size is doubled in a stage 2 testing, which is performed if microbial growth is observed in stage 1 and there is no reason to believe that the test was invalid. The only absolute method to guarantee the sterility of a batch would be to test every vial or ampoule. [Pg.414]

Mn2+ active transport system in Staphylococcus aureus. These metal-microbe interactions result in decrease microbial growth, abnormal morphological changes, and inhibition of biochemical processes in individual (Akmal et al. 2005a,b). The toxic effects of metals can be seen on a community level as well. In response to metal toxicity, overall community numbers and diversity decrease. Soil is a living system where all biochemical activities proceed through enzymatic processes. Heavy metals have also adverse effects on enzyme activities (Fig. 1). [Pg.306]

Odour will return in treated slurry as a result of post treatment fermentation. The concentration of readily fermentable substrates, measured as BOD5, provide an indicator of this problem. In continuous culture without oxygen limitation the BOD5 can be described by a model derived from the Monod (13) model of microbial growth (14). The supernatant BOD5 (g/1) from treatment at 15 to 45°C, was described by equation 3 and the whole BOD5 by equations 4 and 5(15). [Pg.301]

Microbiologists have developed ways to model microbial growth and, using assumptions related to the expected behavior of organisms under different environmental conditions, these models are then coupled with dose-response models with the result that risks (responses) can be estimated, given a certain degree of knowledge about initial microbe counts and the environmental conditions (related... [Pg.271]


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