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This study was conducted to apply the finite volume method (FVM) to solve the partial differential equation (PDE) governing the heat transfer process during meat cooking with convective surface conditions. For a one‐dimensional, round‐shaped food, such as meat balls, the domain may be divided into shells of equal thickness, with energy balance established for each adjacent shell using in the finite difference scheme (FDS) to construct a set of finite difference equations, which were then solved simultaneously using the FORTRAN language and the IVPAG subroutine of the International Mathematics and Statistics Library. The FDS is flexible for temperature‐dependent physical properties of foods, such as thermal conductivity (k), specific heat (Cp), thermal diffusivity (α), and boundary conditions, for example, surface heat transfer coefficient (h), to predict the dynamic temperature profiles in beef and chicken meat balls cooked in an oven. Once the FVM model was established and validated, it was used to simulate the dynamic temperature profiles during cooking, which were then used in combination with the general method to evaluate the thermal lethality of Shiga toxin‐producing Escherichia coli and Salmonella spp. using D and z values in ground meats during cooking. The method can be applied to design cooking processes that effectively inactivate foodborne pathogens while maintaining the quality of cooked meats and evaluate the adequacy of a cooking process. Practical Application: The temperature dependences of thermal conductivity (k) and thermal diffusivity (α) of raw ground beef and ground chicken meats were measured. These thermal properties were then used in numerical simulation to predict the dynamic heating temperature profile and thermal lethality of ground beef and chicken meat balls. The numerical simulation method may be used to optimize and evaluate thermal processes and ensure the inactivation of pathogens in meat products during cooking. [ABSTRACT FROM AUTHOR]

Small‐scale studies have shown that chlorine dioxide gas, ClO2(g), was effective for decontamination of produce, nuts, and spices. This study conducted a pilot‐scale evaluation to identify effective ClO2(g) treatment parameters for commercial‐scale applications. The gas was produced by a generator utilizing sodium chlorite and chlorine gas for decontamination of Shiga toxin‐producing Escherichia coli (STEC), Listeria monocytogenes, and Salmonella inoculated on tomatoes, blueberries, baby‐cut carrots, almonds, and peppercorns. Inoculated samples and 45 kg tomatoes in a 1,246‐L treatment chamber were exposed to various ClO2(g) concentrations (mg/L) and times 9 (hr) at 70–95% RH to determine the treatment effects on the pathogen reductions. Results showed that the treatment caused higher reductions on produce. A ClO2(g) treatment of 1 mg/L‐3 hr at 70% RH reduced 4.9–6.8, 5.1–5.6, and 4.2–6.3 log CFU/g of STEC, L. monocytogenes, and Salmonella, respectively, on produce, with the highest reductions on baby‐cut carrots. For almonds and peppercorns, ClO2(g) treatments under higher RH caused higher reductions. The treatment of 2 mg/L‐9 hr or 3 mg/L‐4 hr at 95% RH reduced >4.0 log of STEC and Salmonella on almonds, and 1 mg/L‐5 hr at 85% RH achieved >5.0 log reductions on peppercorns. Applying moisture to the surfaces of almonds caused >4.0 log reductions using 1 mg/L‐5 hr at 95% RH. This study identified effective ClO2(g) treatment parameters for achieving >4.0 log reductions of common pathogens on tomatoes, blueberries, baby‐cut carrots, almonds, and peppercorns and showed that ClO2(g) generator is suitable for large‐scale decontamination. These findings can be used for pilot‐scale ClO2(g) decontamination of these products and for testing using ClO2(g) for commercial‐scale decontamination trials. [ABSTRACT FROM AUTHOR]

This study is aimed at exploring the effect of pulmonary surfactant (PS) combined with noninvasive positive pressure ventilation on the levels of Keratin-14 (KRT-14) and Endothelin-1 (ET-1) in peripheral blood and the therapeutic effect of neonatal respiratory distress syndrome (NRDS). Altogether 137 cases of neonates with respiratory distress syndrome treated in our hospital from April 2016 to July 2018 were collected. Among them, 64 cases treated with noninvasive positive pressure ventilation were considered as the control group, and 73 cases treated with PS combined with noninvasive positive pressure ventilation were considered as the observation group. The expression of KRT-14 and ET-1 in the two groups was compared. The therapeutic effect, death, complications, and blood gas indexes PaO2, PaCO2, and PaO2/FiO2 in the two groups were compared. Receiver operating characteristic curve (ROC) was applied to analyze the diagnostic value of KRT-14 and ET-1 in the therapeutic effect of NRDS. The effective rate of the observation group was higher than that of the control group. After treatment, PaO2 and PaO2/FiO2 in both groups were notably higher than that before treatment, while PaCO2 was notably lower than that before treatment. And after treatment, the levels of PaO2 and PaO2/FiO2 in the observation group were remarkably higher than that in the control group; PaCO2 was notably lower than that in the control group. After treatment, the levels of KRT-14 and ET-1 in the two groups were remarkably lower than those before treatment, and the levels of KRT-14 and ET-1 in the observation group were considerably lower than those in the control group after treatment. ROC curve showed that the area under the curve (AUC) of KRT-14 was 0.791, and the AUC of ET-1 was 0.816. PS combined with noninvasive positive pressure ventilation can notably improve the therapeutic effect of NRDS. KRT-14 and ET-1 levels may be potential therapeutic diagnostic indicators. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop a dynamic model for predicting the growth of Listeria monocytogenes in pasteurized cow milk under fluctuating temperature conditions during storage and temperature abuse. Six dynamic temperature profiles that simulated random fluctuation patterns were designed to change arbitrarily between 4 and 30°C. The growth data collected from 3 independent temperature profiles were used to determine the kinetic parameters and construct a growth model combining the primary and secondary models using a 1-step dynamic analysis method. The results showed that the estimated minimum growth temperature and maximum cell concentration were 0.6 ± 0.2°C and 7.8 ± 0.1 log cfu/mL (mean ± standard error), with the root mean square error (RMSE) only 0.3 log cfu/mL for model development. The model and the associated kinetic parameters were validated using the data collected under both dynamic and isothermal conditions, which were not used for model development, to verify the accuracy of prediction. The RMSE of prediction was approximately 0.3 log cfu/mL for fluctuating temperature profiles, and it was between 0.2 and 1.1 log cfu/mL under certain isothermal temperatures (2–30°C). The resulting model and kinetic parameters were further validated using 3 growth curves at 4, 7, and 10°C arbitrarily selected from ComBase (www.combase.cc). The RMSE of prediction was 0.8, 0.4, and 0.5 log cfu/mL, respectively, for these curves. The validation results indicated the predictive model was reasonably accurate, with relatively small RMSE. The model was then used to simulate the growth of L. monocytogenes under a variety of continuous and square-wave temperature profiles to demonstrate its potential application. The results of this study showed that the model developed in this study can be used to predict the growth of L. monocytogenes in contaminated milk during storage. [ABSTRACT FROM AUTHOR]

The inactivation of Salmonella on cantaloupes using hot water was investigated. The results demonstrate the utility of hot water for the inactivation of Salmonella on cantaloupes and provide a framework to producers of fresh-cut melon for the potential use of hot water as an intervention treatment.

• Mathematical relationship between D/z and the Arrhenius model was explored. • A method for reconciling these two models was identified. • The two models are practically interchangeable under certain temperature ranges. The effect of temperature on thermal inactivation of microorganisms and thermal degradation of certain chemical compounds can be either described by the Arrhenius model for the rate constant (k) or by the D/z model for the decimal reduction time (D). Although equivalent, it is difficult to directly reconcile these two models which have different model structures. This study hypothesized that the two models can be reconciled by linearization of the inverse of absolute temperature (1/T) and heating temperature (T), and the activation energy (E a) can be directly calculated from z and their relationship is independent of T. The hypothesis was validated using the z and E a of various chemical compounds, enzymes, and vegetative cells and spores of microorganisms in various substrates published in the literature. The results of this study show that the empirical models are practically reconciled. [ABSTRACT FROM AUTHOR]

Abstract Bacillus cereus is a spore-forming foodborne pathogen that can produce toxins causing emetic or diarrheal intoxication. Food poisoning caused by B. cereus is a significant public health concern as it is frequently associated with the consumption of starch-based food products, which are a staple food worldwide. The objective of this study was to investigate the growth and survival of B. cereus in cooked rice under changing temperatures between 1 and 48 °C. A one-step dynamic analysis was used to directly construct a tertiary model to describe the growth and survival of B. cereus and estimate the kinetic parameters. The results of one-step dynamic analysis showed that the minimum, optimum, and maximum growth temperatures were 8.2, 37.6, and 46.8 °C, respectively, with an optimal specific growth rate of 2.21 ln CFU/g/h or 0.96 log CFU/g/h. These parameters agreed well with the reported typical growth kinetics of this microorganism. In addition, this study found that the populations of B. cereus decreased gradually at the rate of 1.21 × 10−3 ln CFU/g/h per °C or 1.2 × 10−3 log CFU/g/h per °C below the minimum growth temperature. The tertiary model was validated using three dynamic growth and survival curves. The results showed that the root-mean-square-error of the predictions was 0.5 log CFU/g, suggesting that the model is reasonably accurate in predicting the growth of B. cereus in cooked rice. The results of this study can be used to predict the growth and survival of B. cereus and assess its risk in cooked rice or other starch-based products exposed to a relatively wide temperature range during manufacturing and distribution. Highlights • A dynamic model for growth and survival of Bacillus cereus in cooked rice was developed. • Kinetic parameters for growth and survival of B. cereus were determined. • The model was validated and may be used for risk assessment. [ABSTRACT FROM AUTHOR]

Abstract Escherichia coli O157: H7, Salmonella spp., and Listeria monocytogenes are three major foodborne pathogens in meats that frequently cause serious human infections and are significant public health hazards. Many studies have reported the thermal resistance of these pathogens in various meats. Although showing some general trends, the published data vary considerably. This study aimed to develop more accurate regression models for estimating the thermal resistance by incorporating the effect of temperature and fat. Both reduced model (temperature only, or D-z model) and expanded model (temperature and fat) were developed by linear regression. The results showed that the expanded models improved the accuracy of estimation of log D. For E. coli O157:H7 in beef, greater than 93% of the variations in log D can be attributed to the expanded model, while it is greater than 96% for E. coli O157:H7 in non-beef meats, L. monocytogenes , and Salmonella spp. in poultry meats. For Salmonella spp. in non-poultry meats, 90.4% of the variations of the log D values can be attributed to the expanded model, which is significantly greater than 74% in the reduced model. For Salmonella spp. in poultry meats, both reduced and expanded models can be used, achieving greater than 94.8% accuracy in predicting the log D values. Based on Akaike Information Criterion (AIC) and F-test, the improvement in accuracy by each expanded model is statistically significant (α = 0.05), irrespective of the difference in the sources, serotypes, and isolates. The expanded models can be used to design and evaluate thermal processes for inactivating these pathogens in meat and poultry products with normal fat contents and without ingredients (salt, acidulants, or other antimicrobials) that may significantly affect the survival of these microorganisms. However, the users should know the limits of regression models and validate the models before using them in real-world applications. Highlights • Thermal resistance of E. coli O157:H7, Salmonella spp., and L. monocytogenes was evaluated. • Combined effect of temperature and fat on thermal resistance was evaluated. • More accurate regression models were developed to estimate the thermal resistance. • The models may be used to design and evaluate thermal processes for inactivating these pathogens. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the growth of Escherichia coli O157:H7 in raw ground beef under competition from background flora. The growth of E. coli O157:H7 was observed in sterile irradiated and non-irradiated raw ground beef under dynamically changing temperature conditions. A one-step dynamic analysis method was used to directly construct tertiary models for describing bacterial growth with and without competition and to estimate the kinetic parameters from dynamic growth curves to prove the hypothesis that the growth of E. coli O157:H7 was significantly affected by competition from background flora in raw ground beef. The one-step dynamic method successfully modelled the growth of E. coli O157:H7 and background flora in ground beef and the competition between the two. The estimated minimum growth temperature for E. coli O157:H7 was 7.7 °C, and the maximum cell concentration was 9.0 log CFU/g in irradiated ground beef. Under competition, the specific growth rate of E. coli O157:H7 was reduced by approximately 18% in raw ground beef. The resulting dynamic models and kinetic parameters were validated with separate dynamic growth data, showing that the Root Mean Square Error (RMSE) of prediction was <0.5 log CFU/g for both background flora and E. coli O157:H7. In addition, the models were validated with the growth data of background flora and non-O157 Shiga toxin-producing E. coli (STEC) in raw ground beef obtained in a previous study, also yielding a RMSE of <0.5 log CFU/g. This result also suggests that the growth kinetics of E. coli O157:H7 and non-O157 STEC may be similar in ground beef. The results of this study demonstrated that the one-step dynamic analysis is a useful and efficient method for investigating bacterial growth with and without competition under dynamic conditions and for developing growth kinetic models. Since the dynamic models have been validated, they can be used to predict the shelf-life of ground beef (background flora) and conduct risk assessment of E. coli O157:H7 and non-O157 STEC. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the growth kinetics of Clostridium botulinum LNT01, a non-toxigenic mutant of C. botulinum 62A, in cooked ground beef. The spores of C. botulinum LNT01 were inoculated to ground beef and incubated anaerobically under different temperature conditions to observe growth and develop growth curves. A one-step kinetic analysis method was used to analyze the growth curves simultaneously to minimize the global residual error. The data analysis was performed using the USDA IPMP-Global Fit, with the Huang model as the primary model and the cardinal parameters model as the secondary model. The results of data analysis showed that the minimum, optimum, and maximum growth temperatures of this mutant are 11.5, 36.4, and 44.3 °C, and the estimated optimum specific growth rate is 0.633 ln CFU/g per h, or 0.275 log CFU/g per h. The maximum cell density is 7.84 log CFU/g. The models and kinetic parameters were validated using additional isothermal and dynamic growth curves. The resulting residual errors of validation followed a Laplace distribution, with about 60% of the residual errors within ±0.5 log CFU/g of experimental observations, suggesting that the models could predict the growth of C. botulinum LNT01 in ground beef with reasonable accuracy. Comparing with C. perfringens , C. botulinum LNT01 grows at much slower rates and with much longer lag times. Its growth kinetics is also very similar to C. sporogenes in ground beef. The results of computer simulation using kinetic models showed that, while prolific growth of C. perfringens may occur in ground beef during cooling, no growth of C. botulinum LNT01 or C. sporogenes would occur under the same cooling conditions. The models developed in this study may be used for prediction of the growth and risk assessments of proteolytic C. botulinum in cooked meats. [ABSTRACT FROM AUTHOR]

Clostridium perfringens is a major foodborne health hazard that can cause acute gastroenteritis in consumers, and is often associated with cooked meat and poultry products. Improper cooling after cooking may allow this pathogen to grow in a product, producing an enterotoxin that causes food poisoning. This study was conducted to evaluate the effect of common ingredients, including sodium tripolyphosphate (STPP), sodium lactate (NaL), and sodium chloride (NaCl), on the germination and outgrowth of C. perfringens spores in meat products. The growth/no growth test was conducted in Shahidi Ferguson Perfringens agar mixed with STPP (0–2500 ppm), NaL (0–4%), and NaCl (0–4%) in microplates. Turbidity measurements at 600 nm were compared before and after anaerobic incubation at 46 °C to evaluate growth and no growth conditions. The dichotomous responses were analyzed by logistic regression to develop a model for estimating the growth probability of C. perfringens . The probability model was used to define the threshold of growth (probability > 0.1 or 0.2) of C. perfringens and validated using inoculated ground beef under optimum temperature. Inoculated ground beef was mixed with different combinations of STPP, NaL, and NaCl to observe growth or no growth of C. perfringens , and the probability was calculated from the formulation. If the threshold of growth was set to 0.2, the accuracy of the growth and no growth predictions was 95.7%, with 4.3% over-prediction of growth events (fail-safe). The results from this study suggested that proper combinations of STPP, NaL, and NaCl could be used to control the growth of C. perfringens in cooked beef under the optimum temperature. The results may also suggest that proper combinations of STPP, NaL, and NaCl in cooked meat and poultry products could be used to prevent the growth of C. perfringens during cooling. [ABSTRACT FROM AUTHOR]

The objective of this work is to develop and validate a unified optimization algorithm for performing one-step global regression analysis of isothermal growth and survival curves for determination of kinetic parameters in predictive microbiology. The algorithm is incorporated with user-friendly graphical interfaces (GUIs) to develop a data analysis tool, the USDA IPMP-Global Fit. The GUIs are designed to guide the users to easily navigate through the data analysis process and properly select the initial parameters for different combinations of mathematical models. The software is developed for one-step kinetic analysis to directly construct tertiary models by minimizing the global error between the experimental observations and mathematical models. The current version of the software is specifically designed for constructing tertiary models with time and temperature as the independent model parameters in the package. The software is tested with a total of 9 different combinations of primary and secondary models for growth and survival of various microorganisms. The results of data analysis show that this software provides accurate estimates of kinetic parameters. In addition, it can be used to improve the experimental design and data collection for more accurate estimation of kinetic parameters. IPMP-Global Fit can be used in combination with the regular USDA-IPMP for solving the inverse problems and developing tertiary models in predictive microbiology. [ABSTRACT FROM AUTHOR]

Salmonella Enteritidis (SE) is a common foodborne pathogen associated with eggs and egg products. This research was conducted to study the kinetics of growth and survival of SE in liquid egg whites (LEW). A dynamic temperature profile that exposed SE to suboptimal temperatures and below the minimum growth temperature (T min ) was used with two isothermal conditions to develop kinetic models. One-step dynamic analysis was used to directly construct a tertiary model for describing the growth and survival of SE and determine the kinetic parameters. The results of kinetic analysis showed that the T min was 7.7 °C and SE may die off at a rate of 2.78 × 10 −3 log CFU/ml per h per °C below the T min . The root mean square error (RMSE) of the model was 0.5 log CFU/ml, with 76.6% of the residual errors within ±0.5 log CFU/ml of the experimental observations. The model was validated under both dynamic temperature and isothermal conditions. Both growth and survival of SE was accurately predicted, with the RMSE of validation at < 0.5 log CFU/ml. For all the validation tests, nearly 75% of the residual errors were within ±0.5 log CFU/ml of the experimental observations. This study clearly demonstrated that the one-step dynamic analysis method is an accurate and efficient method for direct construction of predictive models and estimation of the associated kinetic parameters that govern the growth and survival of microorganisms in food. Since the mathematical model has been validated, it can be used to predict the growth and survival of SE in LEW during storage and distribution and for conducting risk assessment of this microorganism. [ABSTRACT FROM AUTHOR]

Fresh fruits and vegetables are frequently contaminated with bacterial pathogens and implicated in foodborne illnesses. The objective of this study was to develop a unique surface decontamination method for produce using sodium chlorite and an acid in a sequential treatment. The surfaces of cantaloupe rinds, peels of cucumbers, stem scars of grape tomatoes, and leaves of baby spinach were inoculated with Salmonella or Listeria monocytogenes at 5 to 6 log CFU/g, submerged in 1.6 to 4% sodium chlorite solutions for 10 or 30 min, dried for 20 min, and then soaked in 6 mM hydrogen chloride (HCl) for 10 or 30 min and dried for 20 min. Control samples were treated with deionized water, sodium chlorite, HCl, or a premixed solution of sodium chlorite and HCl for comparison. The control treatments reduced the levels of both pathogens on the samples by only 0.3 to 2.9 log CFU/g, whereas the sequential treatment caused significantly higher reductions (P < 0.05) of 5.1 to 5.6 log CFU/g, effectively eliminating the inoculated pathogens. The more effective decontamination resulting from the sequential treatment was attributed to the in situ formation of chlorine dioxide within the plant tissues under the surface by the reaction between sodium chlorite absorbed by the produce and HCl. These results suggest that the sequential use of sodium chlorite and acid is a potentially effective treatment for elimination of foodborne pathogens on produce [ABSTRACT FROM AUTHOR]

This research was conducted to evaluate the feasibility of using a one-step dynamic numerical analysis and optimization method to directly construct a tertiary model to describe the growth and survival of Salmonella Paratyphi A (SPA) in a marinated roasted chicken product. Multiple dynamic growth and survival curves obtained under different fluctuating temperature conditions between 4 and 35 °C were used to determine the growth kinetics of SPA. In combination with appropriate secondary models, the study examined both growth and survival of SPA simultaneously by an integrated one-step approach using a set of differential equations. The estimated minimum growth temperature (T min ) of SPA was 8.91 °C, matching well with the growth characteristics of this microorganism. The growth at temperatures above T min and the survival below T min was accurately simulated by the predictive models. For model development, the root mean square error (RMSE) was 0.26 log CFU/g. The predictive models and kinetic parameters were validated using two dynamic growth and survival curves along with one isothermal thermal growth curve. The validation also showed that the models were accurate in predicting the growth and survival of the bacterium, with the RMSE of predictions only 0.52 log CFU/g. The errors of predictions were within normal experimental errors. The results of this work may be used to predict the change in the population of SPA in the marinated roasted chickens in the cold chain and during temperature abuse and to conduct risk assessment of this pathogen. [ABSTRACT FROM AUTHOR]

Listeria monocytogenes is a potentially fatal foodborne pathogen that can be found in ready-to-eat seafood products, such as fresh salmon roe. Once contaminated, salmon roe must be decontaminated prior to human consumption. This study was conducted to determine the thermal inactivation kinetics of L. monocytogenes in raw salmon roe as affected by bacterial strain, temperature, and salt concentration. Three different strains of L. monocytogenes , including serotype 4b (F2365), 1/2b (F4260), and 1/2a (V7), were individually inoculated to salmon roe supplemented with salt (0–4.5%), and heated under different temperatures (57.5–65.0 °C) to evaluate the survival of the bacterium during heating and determine the D-values. Results showed that the thermal resistance (log D) of L. monocytogenes was significantly affected by bacterial strain, temperature, and salt and by their interactive effects, with strain F2365 being the most heat-resistant among all three strains tested. Salt added to salmon roe significantly increased the thermal resistance of the bacteria. For L. monocytogenes F2365, the z value of the bacterium in salmon roe was 5.99 °C, and its heat resistance increased with the level of salt in a linear manner. The results of kinetic analysis and the models obtained in this study may be used by the seafood industry to develop proper thermal processes to eliminate L. monocytogenes in raw salmon roe and to ensure microbial safety and prevent foodborne illness. [ABSTRACT FROM AUTHOR]

The objective of this study was to directly construct a tertiary growth model for Listeria monocytogenes in a simulated comminuted, non-cured cooked pork product and simultaneously determine the kinetic parameters using a combination of dynamic and isothermal growth curves. Growth studies were conducted using a cocktail of 5 strains of L. monocytogenes in cooked pork under both dynamic and isothermal temperature profiles designed to examine the effect of temperature on bacterial growth. A direct kinetic analysis method was used to construct the growth models and determine the kinetic parameters. The bacterial growth was simulated by a set of differential equations, and the temperature effect was evaluated by the cardinal parameters model. A numerical analysis and optimization method was used to simultaneously solve the different equations and search for the best fits of kinetic parameters for the growth curves and models. The estimated minimum, optimum, and maximum growth temperatures were 0, 33.0, and 42.6 °C, matching well with typical growth characteristics of this microorganism. The root-mean-square error (RMSE) of curve-fitting was 0.42 log CFU/g. The growth models and kinetic parameters were validated using both independent dynamic and isothermal growth curves to check the accuracy of the models. The results showed that the RMSE of predicted growth was 0.49 log CFU/g. The residual errors of predictions follow a Laplace distribution, with 80.3% of the residual errors falling within ±0.5 log CFU/g of the observations. This study proves that the one-step dynamic analysis with both dynamic and isothermal temperature profiles can be an effective approach for simultaneously constructing a tertiary model and determining the kinetic parameters. [ABSTRACT FROM AUTHOR]

This study was conducted to examine the growth of Salmonella Enteritidis (SE) in potato salad caused by cross-contamination and temperature abuse, and develop mathematical models to predict its growth. The growth of SE was investigated under constant temperature conditions (8, 10, 15, 20, 25, 30, and 37 °C) to evaluate the effect of temperature on growth rates and lag times. Duplicated experiments were conducted. The data set from one replicate was used to develop kinetic models and determine kinetic parameters. The data from the other replicate served as an independent data set for model validation. The growth of background microorganism (BK) was also examined. One-step kinetic analysis method was used to directly construct both primary (Huang) and secondary (Ratkowsky square-root) models. Nonlinear regression was used to minimize the global residual sum of squares (RSS) for SE and BK. The results showed that both primary and secondary models can be used to analyze the growth curves, with the kinetic parameters closely matching the characteristics of SE and BK. The validation results showed that the root-mean-square error (RMSE) was only 0.40 Log CFU/g for SE and 0.66 Log CFU/g for BK, with the residual errors of predictions following Laplace and logistic distributions, respectively. This study showed that one-step kinetic analysis is a useful and efficient method for analyzing the entire data set to directly construct primary and secondary growth models and determine kinetic parameters. Since the models are validated, they can be used to predict the growth of SE and conduct risk assessment, and to predict the microbiological shelf-life of potato salad. [ABSTRACT FROM AUTHOR]

Clostridium perfringens type A is a significant public health threat and its spores may germinate, outgrow, and multiply during cooling of cooked meats. This study applies a new C. perfringens growth model in the USDA Integrated Pathogen Modeling Program-Dynamic Prediction (IPMP Dynamic Prediction) Dynamic Prediction to predict the growth from spores of C. perfringens in cooked uncured meat and poultry products using isothermal, dynamic heating, and cooling data reported in the literature. The residual errors of predictions (observation–prediction) are analyzed, and the rootmean- square error (RMSE) calculated. For isothermal and heating profiles, each data point in growth curves is compared. The mean residual errors (MRE) of predictions range from –0.40 to 0.02 Log colony forming units (CFU)/g, with a RMSE of approximately 0.6 Log CFU/g. For cooling, the end point predictions are conservative in nature, with an MRE of –1.16 Log CFU/g for single-rate cooling and –0.66 Log CFU/g for dual-rate cooling. The RMSE is between 0.6 and 0.7 Log CFU/g. Compared with other models reported in the literature, this model makes more accurate and fail-safe predictions. For cooling, the percentage for accurate and fail-safe predictions is between 97.6% and 100%. Under criterion 1, the percentage of accurate predictions is 47.5% for single-rate cooling and 66.7% for dual-rate cooling, while the fail-dangerous predictions are between 0% and 2.4%. This study demonstrates that IPMP Dynamic Prediction can be used by food processors and regulatory agencies as a tool to predict the growth of C. perfringens in uncured cooked meats and evaluate the safety of cooked or heat-treated uncured meat and poultry products exposed to cooling deviations or to develop customized cooling schedules. This study also demonstrates the need for more accurate data collection during cooling. [ABSTRACT FROM AUTHOR]

This research applied a new 1-step methodology to directly construct a tertiary model that describes the growth of Clostridium perfringens in cooked turkey meat under dynamically cooling conditions. The kinetic parameters of the growth models were determined by numerical analysis and optimization using multiple dynamic growth curves. The models and kinetic parameters were validated using independent growth curves obtained under various cooling conditions. The results showed that the residual errors (ε) of the predictions followed a Laplace distribution that is symmetric with respect to ε = 0. For residual errors, 90.6% are within ±0.5 Log CFU/g and 73.4% are ±0.25 Log CFU/g for all growth curves used for validation. For relative growth <1.0 Log CFU/g, 88.9% of the residual errors are within ±0.5 Log CFU/g, and 63.0% are within ±0.25 Log CFU/g. For relative growth of <2.0 Log CFU/g, 92.7% of the residual errors are within ±0.5 Log CFU/g, and 70.3% are within ±0.25 Log CFU/g. The scale and distribution of residual errors clearly suggests that the models and estimated kinetic parameters are reasonably accurate in predicting the growth of C. perfringens. Monte Carlo simulation was used to estimate the probabilities of >1.0 and 2.0 Log CFU/g relative growth of C. perfringens in the final products at the end of cooling. This probabilistic process analysis approach provides a new alternative for estimating and managing the risk of a product and can help the food industry and regulatory agencies assess the safety of cooked meat in the event of cooling deviation. [ABSTRACT FROM AUTHOR]

Clostridium sporogenes PA 3679 is a common surrogate for proteolytic Clostridium botulinum for thermal process development and validation. However, little information is available concerning the growth kinetics of C. sporogenes in food. Therefore, the objective of this study was to investigate the growth kinetics of C. sporogenes in cooked beef under different temperature conditions. Ground beef samples, inoculated with C. sporogenes spores, were incubated at temperatures between 8 and 47 °C to examine the growth of this microorganism. Two primary models (Huang and Baranyi models) were used to analyze the growth data. The Ratkowsky square-root model was used as the secondary model to evaluate the effect of temperature on bacterial growth rate and lag time. The USDA IPMP 2013, a free data analysis tool for predictive microbiology, was used in data analysis. No growth of C. sporogenes was observed at temperatures below 15 °C for up to 25 days. At temperatures between 20 and 47 °C, C. sporogenes grew in cooked beef. The growth curves could be analyzed by both Huang and Baranyi models. The root mean squared error (RMSE) was 0.375 for the Huang model, and 0.441 for the Baranyi model with a global h 0 of 10.46. The nominal minimum growth temperature (T 0 ) estimated from the Huang model was 15.5 °C, which was 12.7 °C for the Baranyi model. The maximum growth temperature was 48.0 and 48.3 °C for the Baranyi and Huang models, respectively. The lag times and specific growth rates of C. sporogenes observed in this study were reasonably close to the data reported in the literature for C. botulinum under comparable conditions, suggesting that C. sporogenes may be used as a potential surrogate for evaluating the growth of C. botulinum in cooked meats during cooling. However, a direct comparison of growth kinetics between the two microorganisms is needed to confirm the suitability of C. sporogenes as a surrogate of C. botulinum . [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the growth kinetics of Listeria monocytogenes in unsalted and salted (3%) salmon roe. Growth curves, developed using inoculated samples incubated at constant temperatures between 5 and 30 °C, were analyzed by curve-fitting to the Huang and Baranyi models using the USDA IPMP 2013. The experimental results showed that L. monocytogenes in salted samples exhibited approximately 40% longer lag times than the cells in unsalted samples under the same temperature condition, while the rates of bacterial growth were not affected by the addition of salt. The Ratkowsky square-root (RSR) model, Huang square-root (HSR) model, and an Arrhenius-type model were all shown suitable for evaluating the effect of temperature on specific growth rates. The estimated nominal minimum growth temperature in the RSR model was −0.5 °C, whereas the minimum growth temperature in HSR model was 2.57 °C. The HSR models may be more suitable for describing the temperature effect in salted salmon roe. The lag times of L. monocytogenes were found to change log-linearly with the specific growth rates. The mean h 0 in the Baranyi model was 0.742 in unsalted samples and 1.193 in salted samples, and did not appear to change with temperature in a systematic manner. In summary, kinetic models were developed for examining the effect of temperature on growth of L. monocytogenes in unsalted and salted salmon roe samples. The results may be used by the food industry and regulatory agencies to estimate the growth of L. monocytogenes in salmon roe, and to conduct risk assessments of this microorganism. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus is a Gram-positive spherically-shaped bacterium capable of producing heat-stable enterotoxins that cause acute gastrointestinal diseases. The growth of this pathogen in food is a major threat to public health worldwide. Potato salad is a frequent vehicle for infection and food poisoning caused by S. aureus. Therefore, the objective of this study was to investigate the growth kinetics of S. aureus in cooked potato and potato salad. Samples of potato cubes and potato salad inoculated with S. aureus were incubated at temperatures between 8 and 43 °C to observe its growth for developing growth models. No growth was observed at 8 °C. The experimental results showed that the growth curves did not exhibit lag phases, and can be described by a 3-parameter logistic model. A one-step kinetic analysis approach was used to simultaneously analyze all growth curves by direct construction of both the primary and secondary (Ratkowsky square root) models using nonlinear regression to minimize the global residual error. The estimated nominal minimum growth temperature of S. aureus was 6.12 °C in potato cubes and 8.80 °C in potato salad. The estimated maximum growth temperatures of S. aureus in potato cubes and potato salad were very close to each other (46.3 and 46.8 °C, respectively). On the average, the specific growth rates of S. aureus in potato cubes were approximately 70% higher than those in potato salad. This study suggests that cooked potato and potato salad should be stored below 6 °C or above 47 °C to prevent the growth of S. aureus. The mathematical models and kinetic parameters can be used to accurately evaluate the effect of temperature abuse on the growth of S. aureus and conduct risk assessments of S. aureus in cooked potato and potato salad. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop a new approach using a one-step approach to directly construct predictive models for describing the growth of Salmonella Enteritidis (SE) in liquid egg white (LEW) and egg yolk (LEY). A five-strain cocktail of SE, induced to resist rifampicin at 100 mg/L, was used to inoculate LEW and LEY. Kinetic studies were conducted isothermally at different temperatures between 8 and 43 °C to generate growth curves at each temperature. This study first solved an inverse problem globally, using the growth curves to estimate the temperature-dependent kinetic parameters, and then applied the parameters to predict growth (a forward problem). Once the growth curves were generated, they were assembled and analyzed using nonlinear regression to determine kinetic parameters of both primary and secondary models in one step, with an objective to minimize the global residual sum of squares (RSS) for the entire data set. For growth in LEW, a three-parameter logistic model was used. For growth in LEY, the Huang model was used as the primary model. The Ratkowsky square-root model was used to evaluate the growth rates. The results showed that the one-step approach resulted in accurate estimation of the kinetic parameters that were used later to successfully predict the growth of SE in LEY and LEW. The estimated nominal minimum growth temperatures of SE were 7.4 °C and 9.9 °C, while the estimated maximum growth temperatures were 45.2 °C and 46.8 °C, respectively, in LEW and LEY. As a validation, the predictive models were tested with independent growth curves of SE in LEY and LEW at 37 °C. The root mean square error (RMSE) was only 0.36 and 0.28 log CFU/ml over a total scale of 8.4 and 7.8 log CFU/ml, respectively, for the growth models of SE in LEY and LEW, suggesting that the one-step approach can generate accurate models for predicting the growth of SE in LEY and LEW. The results from this study can be used to predict the growth of SE and evaluate the safety of LEY and LEW. [ABSTRACT FROM AUTHOR]

Physiological high shear stress (HSS), a frictional force generated by flowing blood, is essential for endothelial homeostasis under normal physiological conditions. HSS suppresses atherosclerosis by inhibiting endothelial inflammation. However, the molecular mechanisms underlying this process have not been fully elucidated. Here, we report that HSS downregulated the mRNA and protein levels of ras homolog family member J (RHOJ) in endothelial cells (ECs). Silencing endogenous RHOJ expression decreased the mRNA and protein levels of proinflammatory vascular cell adhesion molecule 1 (VCAM-1) and intercellular cell adhesion molecule 1 (ICAM-1) in ECs, leading to a reduction in monocyte adhesion to ECs. Conversely, the overexpression of RHOJ had the opposite effect. RNA-sequencing analysis uncovered several differentially expressed genes (such as yes-associated protein 1 (YAP1),heme oxygenase-1 (HO1), and monocyte chemoattractant protein-1 (MCP1)) and pathways (such as nuclear factor-kappa B (NF-κB), fluid shear stress and atherosclerosis, and cell adhesion pathways) as RHOJ targets. Additionally, HSS was observed to alleviate endothelial inflammation by inhibiting RHOJ expression. Finally, methylated RNA immunoprecipitation sequencing (MeRIP-seq) illustrated that fluid shear stress regulates RHOJ expression in an N6-methyladenosine (m6A)-dependent manner. Mechanistically, the RNA m6A writer, methyltransferase 3 (METTL3), and the RNA m6A readers, YTH N6-methyladenosine RNA-binding protein F 3 (YTHDF3) and YTH N6-methyladenosine RNA-binding protein C 1/2 (YTHDC1/2), are involved in this process. Taken together, our data demonstrate that HSS-induced downregulation of RHOJ contributes to endothelial homeostasis by suppressing endothelial inflammation and that RHOJ inhibition in ECs is a promising therapeutic strategy for endothelial dysfunction. [Display omitted] • RHOJ is a novel mechanosensitive Rho GTPase. • RHOJ plays a key role in modulating endothelial inflammation. • Atheroprotective shear stress regulates RHOJ expression in an m6A-dependent manner. [ABSTRACT FROM AUTHOR]

For health reasons, people are consuming fresh-cut fruits with or without minimal processing and, thereby, exposing themselves to the risk of foodborne illness if such fruits are contaminated with bacterial pathogens. This study investigated survival and growth parameters of Escherichia coli O157:H7, Salmonella, Listeria monocytogenes, and aerobic mesophilic bacteria transferred from cantaloupe rind surfaces to fresh-cut pieces during fresh-cut preparation. All human bacterial pathogens inoculated on cantaloupe rind surfaces averaged ~4.8 log CFU/cm², and the populations transferred to fresh-cut pieces before washing treatments ranged from 3 to 3.5 log CFU/g for all pathogens. A nisin-based sanitizer developed in our laboratory and chlorinated water at 1,000 mg/liter were evaluated for effectiveness in minimizing transfer of bacterial populations from cantaloupe rind surface to fresh-cut pieces. Inoculated and uninoculated cantaloupes were washed for 5 min before fresh-cut preparation and storage of fresh-cut pieces at 5 and 10 °C for 15 days and at 22°C for 24 h. In fresh-cut pieces from cantaloupe washed with chlorinated water, only Salmonella was found (0.9 log CFU/g), whereas E. coli O157:H7 and L. monocytogenes were positive only by enrichment. The nisin-based sanitizer prevented transfer of human bacteria from melon rind surfaces to fresh-cut pieces, and the populations in fresh-cut pieces were below detection even by enrichment. Storage temperature affected survival and the growth rate for each type of bacteria on fresh-cut cantaloupe. Specific growth rates of E. coli O157:H7, Salmonella, and L. monocytogenes in fresh-cut pieces were similar, whereas the aerobic mesophilic bacteria grew 60 to 80% faster and had shorter lag phases. [ABSTRACT FROM AUTHOR]

Starchy roots, tubers, and plantain (RTP) are the staple food in sub-Saharan Africa (SSA), and also important energy sources in Asia, Europe, and America. In this work, inorganic arsenic (iAs) in these crops was separated and enriched by solid phase extraction (SPE), and quantified by hydride generation-atomic fluorescence spectrometry (HG-AFS). Overall, iAs in these crops ranged from 0.9 to 14.1 ng g −1 wet weight. Long-term cancer risk associated with iAs intake from these crops was assessed by Monte Carlo simulation based on iAs concentrations and historical consumption and population data. For 19 high RTP consuming SSA countries, life-time cancer risk was low with a mean target risk at 6.3 × 10 −5 and a margin of exposure at 72. [ABSTRACT FROM AUTHOR]

The main objective of this study was to develop the primary and secondary models to describe the growth kinetics of Salmonella as well as background microorganisms in raw, shucked oysters. Samples, inoculated with a cocktail of two Salmonella serotypes, S. Typhimurium (CICC22956) and S. Enteritidis (CICC21482), were incubated at 4, 8, 12, 16, 20, 25, 30, 33, 37, 40, and 43 °C. Growth of Salmonella was observed at all temperatures, except at 4 °C. The background microorganisms grew at all temperatures. All growth curves clearly exhibited lag, exponential and stationary phases, and were analyzed using the Huang growth model. Three secondary models (Ratkowsky square-root, Huang square-root, and Cardinal parameter models) were compared for evaluating the effect of temperature on bacterial growth rates. Data analysis was performed using IPMP 2013, a free predictive microbiology software tool developed by the USDA ARS. The Cardinal parameters model underestimated the specific rates of the microorganisms at low temperatures. The Huang square-root model was more suitable than the Ratkowsky square-root model for describing the effect of temperature on growth of Salmonella , while the Ratkowsky square-root model, on the other hand, was more suitable for background microorganisms. For both Salmonella and background microorganisms, the logarithms of the lag phase were expressed as linear functions of the logarithms of specific growth rates. The results of this study can be used by the food retailers and regulatory agencies to estimate the microbial shelf-life of raw, shucked oysters. [ABSTRACT FROM AUTHOR]

The objective of this research was to develop a new one-step methodology that uses a dynamic approach to directly construct a tertiary model for prediction of the growth of Clostridium perfringens in cooked beef. This methodology was based on simultaneous numerical analysis and optimization of both primary and secondary models using multiple dynamic growth curves obtained under different conditions. Once the models were constructed, the bootstrap method was used to calculate the 95% confidence intervals of kinetic parameters, and a Monte Carlo simulation method was developed to validate the models using the growth curves not previously used in model development. The results showed that the kinetic parameters obtained from this study accurately matched the common characteristics of C. perfringens , with the optimum temperature being 45.3 °C. The results also showed that the predicted growth curves matched accurately with experimental observations used in validation. The mean of residuals of the predictions is − 0.02 log CFU/g, with a standard deviation of only 0.23 log CFU/g. For relative growths < 1 log CFU/g, the residuals of predictions are < 0.4 log CFU/g. Overall, 74% of the residuals of predictions are < 0.2 log CFU/g, 7.7% are > 0.4 log CFU/g, while only 1.5% are > 0.8 log CFU/g. In addition, the dynamic model also accurately predicted four isothermal growth curves arbitrarily chosen from the literature. Finally, the Monte Carlo simulation was used to provide the probability of > 1 and 2 log CFU/g relative growths at the end of cooling. The results of this study will provide a new and accurate tool to the food industry and regulatory agencies to assess the safety of cooked beef in the event of cooling deviation. [ABSTRACT FROM AUTHOR]