Construction of A New Dose–Response Model for Staphylococcus aureus Considering Growth and Decay Kinetics on Skin (original) (raw)
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Acta Chimica Slovaca
The growth of Staphylococcus aureus 2064 isolate in model nutrient broth was studied as affected by temperature and water activity using principles and models of predictive microbiology. Specific rates resulting from growth curves fitted by the Baranyi model were modelled by the secondary Ratkowsky model for suboptimal temperature range (RTKsub) as well as the Ratkowsky extended model (RTKext) and cardinal model (CM) in the whole temperature range. With the biological background of the RTKext model, cardinal values of temperature Tmin = 6.06 °C and Tmax = 47.9 °C and water activity aw min = 0.859 were calculated and validated with cardinal values estimated by CM (Tmin = 7.72 °C, Tmax = 46.73 °C, aw min = 0.808). CM also provided other cardinal values, Topt = 40.63 °C, aw opt = 0.994, as well as optimal specific growth rate of 1.97 h–1 (at Topt and aw opt). To evaluate the goodness of fit of all models, mathematical and graphical validation was performed and the statistical indices p...
Modeling the growth boundary of Staphylococcus aureus for risk assessment purposes
Journal of food protection, 2001
Knowing the precise boundary for growth of Staphylococcus aureus is critical for food safety risk assessment, especially in the formulation of safe, shelf-stable foods with intermediate relative humidity (RH) values. To date, most studies and resulting models have led to the presumption that S. aureus is osmotolerant. However, most studies and resulting models have focused on growth kinetics using NaCl as the humectant. In this study, glycerol was used to investigate the effects of a glass-forming nonionic humectant to avoid specific metabolic aspects of membrane ion transport. The experiments were designed to produce a growth boundary model as a tool for risk assessment. The statistical effects and interactions of RH (84 to 95% adjusted by glycerol), initial pH (4.5 to 7.0 adjusted by HC1), and potassium sorbate (0, 500, or 1,000 ppm) or calcium propionate (0, 500, or 1,000 ppm) on the aerobic growth of a five-strain S. aureus cocktail in brain heart infusion broth were explored. I...
A comparison of microbial dose–response models fitted to human data
Regulatory Toxicology and Pharmacology, 2004
A study of eight mathematical dose-response models for microbial risk assessment was conducted using infectivity and illness data on a variety of microbial pathogens from published studies with human volunteers. The purpose was to evaluate variability among the models for human microbial dose-response data in order to determine whether two-parameter models might suffice for most microbial dose-response data or whether three-parameter models should generally be fitted. Model variability was measured in terms of estimated ED 01 s and ED 10 s, with the view that these effective dose levels correspond to the lower and upper limits of the 1-10% risk range generally recommended for establishing benchmark doses in risk assessment. An investigation of the ranks of the ED 01 and ED 10 values among the models led to the conclusion that the two-parameter models captured at least as much uncertainty as the three-parameter models for the data examined. A further evaluation of the two-parameter models did not result in the selection of one ''best'' model, but it did provide some insights into the modelsÕ relative behavior. The model uncertainty analysis proposed by Kang et al. [Regulat. Toxicol. Pharmacol. 32 (2000) 68] using four two-parameter models was reinforced.
Predictive Modeling of Staphylococcus aureus Growth in Raw Milk
2011
Gwamegi (semidry Pacific saury [Cololabis saira]) is a Korean food made by a traditional method of repeated freezing and de-freezing during winter. The present study aimed at developing predictive modeling of S. aureus growth on Gwamegi as a function of temperature (10-35 o C). Modified Gompertz, Baranyi, and logistic primary models were fitted to experimental values. Polynomial quadratic, nonlinear Arrhenius and square root models were selected as secondary models and analyzed using specific growth rate (µ max) and lag time (λ) values obtained from the primary models. Based on the optimized models derived from the Baranyi and square root equations for µ max , its r 2 and mean square error (MSE) were 0.991 and 0.00058, and bias factor (B f) and accuracy factor (A f) were 1.0087 and 1.0801, respectively. The logistic and polynomial quadratic equations for λ, its r 2 and MSE were 0.989 and 0.22834, B f and A f were 0.9742 and 1.0271, respectively. These predictive models can provide basic information for quantitative microbial risk assessment of Gwamegi and other processed semidried seafood.
International Journal of Food Microbiology, 2009
The microbial behaviour of five enterotoxigenic strains of Staphylococcus aureus was studied in the growth/ no growth domain. A polynomial logistic regression equation was fitted using a stepwise method to study the interaction of temperature (8, 10, 13, 16 and 19°C), pH (4.5; 5.0; 5.5; 6.0; 6.5 7.0 and 7.5) and water activity (A w) (19 levels ranging from 0.867 to 0.999) on the probability of growth. Out of the 284 conditions tested, 146 were chosen for model data and 138 intermediate conditions for validation data. A growth/no growth transition was obtained by increasing the number of replicates per condition (n = 30) in comparison to other published studies. The logistic regression model showed a good performance since 96.6% (141 out of 146 conditions) of the conditions for model data and 92.0% (127 out of 138 conditions) for validation data were correctly classified. The predictions indicated an abrupt growth/no growth interfaces occurred at low levels of temperature, pH and A w. At 8°C, S. aureus grew only at optimum levels of pH and A w while at temperatures above 13°C, growth of S. aureus was observed at pH = 4.5 and A w = 0.96 (13°C), 0.941 (16°C) and 0.915 (19°C). The optimal pH at which growth of S. aureus was detected earlier was 6.5. However, a slight decrease of the probability of growth was noticed in the pH interval of 7.0-7.5 at more stringent conditions. The ability of S. aureus to grow at low A w was shown since growth was detected at A w = 0.867 (T = 19°C; pH = 7.0). Finally, a comparison of model predictions with literature data on growth/no growth responses of S. aureus in culture media and cooked meat was made. Model predictions agreed with published data in 94% of growth cases and in 62% of no growth cases. The latter discordance is highly associated to other environmental factors (such as other preservatives, strains etc.) included in published models that did not match the ones included in our study. This study can help manufacturers in making decision on the most appropriate formulations for food products in order to prevent S. aureus growth and enterotoxin production along their shelf-life.
Modeling the Growth of Bacteria Streptococcus sobrinus Using Exponential Regression
Pesquisa Brasileira em Odontopediatria e Clínica Integrada
Objective: To build an exponential regression model based on parameter estimation. Material and Methods: We developed a simple mathematical model to simulate the growth of bacteria and the exponential growth is often used to model population growth as such cell growth while the exponential decay is portraying a declining or decreases in the size of the population. An exponential regression method was used to fit the data and estimate growth parameter values Streptococcus sobrinus using statistical software SPSS version 20. Results: Based on the results of the parameter estimates, which is constant are 83.039 and b1 is 0.005 while R-square is 0.952. According to the R-Square results obtained, the model is good and appropriate. Conclusion: The model can be used to find the potential biological parameters, which may be able to predict the treatment outcome. This study helps researchers to understand the specific growth rate(s), which can be used to best grow the organism.
Applied and Environmental Microbiology, 2002
The formulation of shelf-stable intermediate-moisture products is a critical food safety issue. Therefore, knowing the precise boundary for the growth-no-growth interface of Staphylococcus aureus is necessary for food safety risk assessment. This study was designed to examine the effects of various humectants and to produce growth boundary models as tools for risk assessment. The molecular mobility and the effects of various physical properties of humectants, such as their glass transition temperatures, their membrane permeability, and their ionic and nonionic properties, on S. aureus growth were investigated. The effects of relative humidity (RH; 84 to 95%, adjusted by sucrose plus fructose, glycerol, or NaCl), initial pH (4.5 to 7.0, adjusted by HCl), and potassium sorbate concentration (0 or 1,000 ppm) on the growth of S. aureus were determined. Growth was monitored by turbidity over a 24-week period. Toxin production was determined by enterotoxin assay. The 1,792 data points generated were analyzed by LIFEREG procedures (SAS Institute, Inc., Cary, N.C.), which showed that all parameters studied significantly affected the growth responses of S. aureus. Differences were observed in the growth-no-growth boundary when different humectants were used to achieve the desired RH values in both the absence and the presence of potassium sorbate. Sucrose plus fructose was most inhibitory at neutral pH values, while NaCl was most inhibitory at low pH values. The addition of potassium sorbate greatly increased the no-growth regions, particularly when pH was <6.0. Published kinetic growth and survival models were compared with boundary models developed in this work. The effects of solutes and differences in modeling approaches are discussed.
Growth characterisation of Staphylococcus aureus in milk: a quantitative approach
Czech Journal of Food Sciences, 2009
Staphylococcus aureus is a pathogenic bacterium that induces several of human illnesses. The staphylococcal enterotoxin (SE) production as the results of previous growth of toxigenic strains is the most crucial problem which may lead to the staphylococcal food poisoning outbreaks in humans. That is why the growth of three strains of Staphylococcus aureus was characterised in milk and modelled in dependence of temperature. For the lag phase duration of S. aureus 2064, the Davey model was used with the following result: ln(1/lag) = 1.973 – 87.92/T + 285.09/T2 (R2 = 0.962). The dependence of the growth rate on incubation temperature was modelled by the Ratkowsky square root model and Gibson in sub-optimal and whole temperature range, respectively. The validation of both models showed high significance of the growth rate data fitting. The optimal temperature of Topt = 38.5°C was resulted from Gibson model for the S. aureus 2064 growth in milk. For practical purpose, the time necessary f...
Modelling the inactivation of Staphylococcus aureusat moderate heating temperatures
Czech Journal of Food Sciences, 2021
The survival of bacterial contaminants at moderate processing temperatures is of interest to many food producers, especially in terms of the safety and quality of the final products. That is why the heat resistance of Staphylococcus aureus 2064, an isolate from artisanal Slovakian cheese, was studied in the moderate temperature range (57–61 °C) by the capillary method. The fourth decimal reduction time t4Dand z-values were estimated in two steps by traditional log-linear Bigelow and non-linear Weibull models. In addition, a one-step fitting procedure using the Weibull model was also applied. All the approaches provided comparable t4D-values resulting in the following z-values of 11.8 °C, 12.3 °C and 11.3 °C, respectively. Moreover, the one-step approach takes all the primary data into z-value calculation at once, thus providing a more representative output at the reasonable high coefficient of determination R2 = 0.961.
Mathematical Biosciences and Engineering, 2019
In this paper both deterministic and stochastic models are developed to explore the roles that antibiotic exposure and environmental contamination play in the spread of antibiotic-resistant bacteria, such as methicillin-resistant Staphylococcus aureus (MRSA), in hospitals. Uncolonized patients without or with antibiotic exposure, colonized patients without or with antibiotic exposure, uncontaminated or contaminated healthcare workers, and free-living bacteria are included in the models. Under the assumption that there is no admission of the colonized patients, the basic reproduction number R 0 is calculated. It is shown that when R 0 < 1, the infection-free equilibrium is globally asymptotically stable; when R 0 > 1, the infection is uniformly persistent. Numerical simulations and sensitivity analysis show that environmental cleaning is a critical intervention, and hospitals should use antibiotics properly and as little as possible. The rapid and efficient treatment of colonized patients, especially those with antibiotic exposure, is key in controlling MRSA infections. Screening and isolating colonized patients at admission, and improving compliance with hand hygiene are also important control strategies.