3-D stochastic modeling approach in thermal inactivation: estimation of thermal survival kinetics of Escherichia coli O157:H7 in a hamburger after exposure to desiccation stress

Desiccation tolerance of pathogenic bacteria is one strategy for survival in harsh environments, which has been studied extensively. However, the subsequent survival behavior of desiccation-stressed bacterial pathogens has not been clarified in detail. Herein, we demonstrated that the effect of desiccation stress on the thermotolerance of Escherichia coli O157:H7 in ground beef was limited, and its thermotolerance did not increase. E. coli O157:H7 was inoculated into a ground beef hamburger after exposure to desiccation stress. We combined a bacterial inactivation model with a heat transfer model to predict the survival kinetics of desiccation-stressed E. coli O157:H7 in a hamburger. The survival models were developed using the Weibull model for two-dimensional pouched thin beef patties (ca. 1 mm), ignoring the temperature gradient in the sample, and a three-dimensional thick beef patty (ca. 10 mm), considering the temperature gradient in the sample. The two-dimensional (2-D) and three-dimensional (3-D) models were subjected to stochastic variations of the estimated Weibull parameters obtained from 1,000 replicated bootstrapping based on isothermal experimental observations as uncertainties. Furthermore, the 3-D model incorporated temperature gradients in the sample calculated using the finite element method. The accuracies of both models were validated via experimental observations under non-isothermal conditions using 100 predictive simulations. The root mean squared errors in the log survival ratio of the 2-D and 3-D models for 100 simulations were 0.25-0.53 and 0.32-2.08, respectively, regardless of the desiccation stress duration (24 or 72 h). The developed approach will be useful for setting appropriate process control measures and quantitatively assessing food safety levels.IMPORTANCEAcquisition of desiccation stress tolerance in bacterial pathogens might increase thermotolerance as well and increase the risk of foodborne illnesses. If a desiccation-stressed pathogen enters a kneaded food product via cross-contamination from a food-contact surface and/or utensils, proper estimation of the internal temperature changes in the kneaded food during thermal processing is indispensable for predicting the survival kinetics of desiccation-stressed bacterial cells. Various survival kinetics prediction models that consider the uncertainty or variability of pathogenic bacteria during thermal processing have been developed. Furthermore, heat transfer processes in solid food can be estimated using finite element method software. The present study demonstrated that combining a heat transfer model with a bacterial inactivation model can predict the survival kinetics of desiccation-stressed bacteria in a ground meat sample, corresponding to the temperature gradient in a solid sample during thermal processing. Combining both modeling procedures would enable the estimation of appropriate bacterial survival kinetics in solid food.

Non-destructive quality classification of rice taste properties based on near-infrared spectroscopy and machine learning algorithms

The taste quality of rice is determined by protein and amylose percentages, with low levels indicating high-quality taste in Japan. However, accurate non-destructive screening remains a challenge for the industry. We explored the use of machine learning models and near-infrared spectra to classify rice taste quality. Three models were optimized using 796 brown rice samples from Hokkaido, Japan, produced between 2008 and 2016, and tested on 278 distinct samples from the same region produced between 2017 and 2019. Logistic regression and support vector machine models outperformed the partial least-squares discriminant analysis model, achieving high accuracy (94%), f1-score (90%), average precision (0.94), and low classification error (4%) and allowing accurate non-destructive classification of rice quality. These results not only improve rice quality, post-harvest technology, and producer output in Japan but also could enhance quality control processes and foster the production of high-quality products for other agricultural goods and food commodities worldwide.

Antibacterial Effect of Melanoidins Derived From Xylose and Phenylalanine Against Bacillus cereus and Clostridium perfringens

Melanoidins produced from the combination of D-xylose and L-phenylalanine have been reported to exhibit strong antibacterial effects. This study investigated the influence of environmental factors, such as temperatures (10, 15, 20, 25, 30, 35, 40, and 45°C), pH (5.5, 6.0, 6.5, 7.0, 7.5, and 8.0), and water activity (aw: 0.99, 0.96, and 0.93), on the antibacterial effect of the melanoidins produced from the combination of D-xylose with L-phenylalanine against Bacillus cereus and Clostridium perfringens in culture media. Furthermore, freeze-dried powdered melanoidin was used to determine the minimum concentration for growth inhibition, to compare the antibacterial effect of the melanoidin with conventional food preservatives. The liquid melanoidins significantly inhibited the growth of B. cereus (up to 4 log CFU/mL at the maximum) and C. perfringens (up to 6.5 log CFU/mL at the maximum) regardless of the incubation temperatures. However, the remarkable difference between the presence and absence of the melanoidins was demonstrated in the range of 20-35°C as 4 log-cycle lower in B. cereus and 2 log-cycle lower in C. perfringens than those without the melanoidins. The antibacterial effect of the melanoidin on B. cereus was not influenced by pH from 5.5 to 7.0, which exhibited 2-3 log-cycle lower viable counts than those without the melanoidin. Only one log-cycle difference between with and without the melanoidin was shown in C. perfringens growth under the pH range of 5.5-7.0. Although there was no significant difference in the growth of B. cereus between three aw conditions, the melanoidin exhibited a significant antibacterial effect at aw 0.99 demonstrating 4 log-cycle lower viable numbers than those without the melanoidin. Minimum inhibitory concentration of the melanoidin powder for B. cereus and C. perfringens was 7 mg/mL and 15 mg/mL, respectively, regardless of the kind of foods. Furthermore, the melanoidin exhibited comparable antibacterial effect on B. cereus and C. perfringens to potassium sorbate and sodium benzoate under the same concentration as the minimum inhibitory concentration of the melanoidin, demonstrating 2 log-cycle reduction during 3 days of incubation period at 25°C. The results presented here suggest that the xylose- and phenylalanine-based melanoidin demonstrates the possibility to be an alternative food preservative.

An investigation into the measurement properties of the King-Devick Eye Tracking system

Objectives

Eye tracking has been gaining increasing attention as a possible assessment and monitoring tool for concussion. The King-Devick test (K-DT) was expanded to include an infrared video-oculography-based eye tracker (K-D ET). Therefore, the aim was to provide evidence on the reliability of the K-D ET system under an exercise condition.

Methods

Participants (N = 61; 26 male, 35 female; age range 19-25) were allocated to an exercise or sedentary group. Both groups completed a baseline K-D ET measurement and then either two 10-min exercise or sedentary interventions with repeated K-D ET measurements between interventions.

Results

The test-retest reliability of the K-D ET ranged from good to excellent for the different variables measured. The mean ± SD of the differences for the total number of saccades was 1.04 ± 4.01 and there was an observable difference (p = 0.005) in the trial number. There were no observable differences for the intervention (p = 0.768), gender (p = 0.121) and trial (p = 0.777) for average saccade’s velocity. The mean ± SD of the difference of the total fixations before and after intervention across both trials was 1.04 ± 3.63 and there was an observable difference in the trial number (p = 0.025). The mean ± SD of the differences for the Inter-Saccadic Interval and the fixation polyarea before and after intervention across both trials were 1.86 ± 22.99 msec and 0.51 ± 59.11 mm2 and no observable differences for the intervention, gender and trial.

Conclusion

The results provide evidence on the reliability of the K-D ET, and the eye-tracking components and demonstrate the relationship between completion time and other variables of the K-D ET system. This is vital as the use of the K-DT may be increasing and the combination of the K-DT and eye tracking as one single package highlights the need to specifically measure the reliability of this combined unit.

Experimentally observed Campylobacter jejuni survival kinetics in chicken meat products during model gastric digestion tended to be lower than model predictions

Campylobacter jejuni-related foodborne diseases are mainly attributed to the consumption of undercooked chicken meat and cross-contaminated produce. This study aimed to develop a survival kinetics model, based on the Weibull model, for predicting foodborne C. jejuni survival during gastric digestion in a model stomach. We previously confirmed that C. jejuni can survive temperatures up to 62 °C; therefore, certain types of grilled chicken skewers (yakitori) were examined for C. jejuni survival during simulated gastric digestion. C. jejuni survival on a chicken thigh following grilling was examined to confirm the foods for digestion experiments. Further, C. jejuni survival during model digestion was investigated through simultaneous digestion of raw chicken and cross-contaminated iceberg lettuce. The model stomach pH increased from 1.5 to 6.0 immediately after yakitori ingestion and did not decrease below 4.0 within 3 h of digestion. Gastric digestion did not significantly contribute to C. jejuni inactivation (<1.5 log reduction after 3 h digestion). Our model could predict C. jejuni survival kinetics in simulated gastric fluid under varying pH during model digestion. This approach can be used to predict C. jejuni survival rates following digestion to improve food safety and reduce Campylobacter-related disease outbreaks.

Is skipping the definition of primary and secondary models possible? Prediction of Escherichia coli O157 growth by machine learning

To predict bacterial population behavior in food, statistical models with specific function form have been applied in the field of predictive microbiology. Modelers need to consider the linear or non-linear relationship between the response and explanatory variables in the statistical modeling approach. In the present study, we focused on machine learning methods to skip definition of primary and secondary structure model. Support vector regression, extremely randomized trees regression, and Gaussian process regression were used to predict population growth of Escherichia coli O157 at 15 and 25 °C without defining the primary and secondary models. Furthermore, the support vector regression model was applied to predict small population of bacteria cells with probability theory. The model performance of the machine learning models were nearly equal to that of the current statistical models. Machine learning models have a potential for predicting bacterial population behavior.

Classification of food spoilage bacterial species and their sodium chloride, sodium acetate and glycine tolerance using chemometrics analysis and Raman spectroscopy

The purpose is classification of stress tolerances of spoilage bacteria using Raman spectra and chemometrics. We obtained Raman spectra of six spoilage bacteria. Classification models were constructed with support vector machine and classified food-related stress tolerance with 90% accuracy, which provides bacterial characteristics specific to environment reducing food spoilage.

Competitive growth kinetics of Campylobacter jejuni, Escherichia coli O157:H7 and Listeria monocytogenes with enteric microflora in a small-intestine model

Aims

The biological events occurring during human digestion help to understand the mechanisms underlying the dose–response relationships of enteric bacterial pathogens. To better understand these events, we investigated the growth and reduction behaviour of bacterial pathogens in an in vitro model simulating the environment of the small intestine.

Methods and Results

The foodborne pathogens Campylobacter jejuni, Listeria monocytogenes and Escherichia coli O157:H7 were cultured with multiple competing enteric bacteria. Differences in the pathogen's growth kinetics due to the relative amount of competing enteric bacteria were investigated. These growth differences were described using a mathematical model based on Bayesian inference. When pathogenic and enteric bacteria were inoculated at 1 log CFU per ml and 9 log CFU per ml, respectively, L. monocytogenes was inactivated over time, while C. jejuni and E. coli O157:H7 survived without multiplying. However, as pathogen inocula were increased, its inhibition by enteric bacteria also decreased.

Conclusions

Although the growth of pathogenic species was inhibited by enteric bacteria, the pathogens still survived.

Significance and Impact of the Study

Competition experiments in a small‐intestine model have enhanced understanding of the infection risk in the intestine and provide insights for evaluating dose–response relationships.

Evaluation of Strain Variability in Inactivation of Campylobacter jejuni in Simulated Gastric Fluid by Using Hierarchical Bayesian Modeling

This study was conducted to quantitatively evaluate the variability of stress resistance in different strains of Campylobacter jejuni and the uncertainty of such strain variability. We developed Bayesian statistical models with multilevel analysis to quantify variability within a strain, variability between different strains, and the uncertainty associated with these estimates. Furthermore, we measured the inactivation of 11 strains of C. jejuni in simulated gastric fluid with low pH, using the Weibullian survival model. The model was first developed for separate pH conditions and then analyzed over a range of pH levels. We found that the model parameters developed under separate pH conditions exhibited a clear dependence of survival on pH. In addition, the uncertainty of the variability between different strains could be described as the joint distribution of the model parameters. The latter model, including pH dependency, accurately predicted the number of surviving cells in individual as well as multiple strains. In conclusion, variabilities and uncertainties in inactivation could be simultaneously evaluated and interpreted via a probabilistic approach based on Bayesian theory. Such hierarchical Bayesian models could be useful for understanding individual-strain variability in quantitative microbial risk assessment. IMPORTANCE Since microbial strains vary in their growth and inactivation patterns in food materials, it is important to accurately predict these patterns for quantitative microbial risk assessment. However, most previous studies in this area have used highly resistant strains, which could lead to inaccurate predictions. Moreover, variability, including measurement errors and variability within a strain and between different strains, can contribute to predicted individual-level outcomes. Therefore, a multilevel framework is required to resolve these levels of variability and estimate their uncertainties. We developed a Bayesian predictive model for the survival of Campylobacter jejuni under simulated gastric conditions taking into account the variabilities and uncertainties. We demonstrated a high correspondence between predictions from the model and empirical measurements. The modeling procedure proposed in this study recommends a novel framework for predicting pathogen behavior, which can help improve quantitative microbial risk assessment during food production and distribution.

Rapid detection and enumeration of aerobic mesophiles in raw foods using dielectrophoresis

The concept of dielectrophoresis (DEP), which involves the movement of neutral particles by induced polarization in nonuniform electric fields, has been exploited in various biological applications. However, only a few studies have investigated the use of DEP for detecting and enumerating microorganisms in foodstuffs. Therefore, we aimed to evaluate the accuracy and efficiency of a DEP-based method for enumerating viable bacteria in three raw foods: freshly cut lettuce, chicken breast, and minced pork. The DEP separation of bacterial cells was conducted at 20 V of output voltage and 6000 to 9000 kHZ of frequency with sample conductivity of 30-70 μS/cm. The accuracy and validity of the DEP method for enumerating viable bacteria were compared with those of the conventional culture method; no significant variation was observed. We found a high correlation between the data obtained using DEP and the conventional aerobic plate count culture method, with a high coefficient of determination (R2 > 0.90) regardless of the food product; the difference in cell count data between both methods was within 1.0 log CFU/mL. Moreover, we evaluated the efficiency of the DEP method for enumerating bacterial cells in chicken breasts subjected to either freezing or heat treatment. After thermal treatment at 55 °C and 60 °C, the viable cell counts determined via the DEP method were found to be lower than those obtained using the conventional culture method, which implies that the DEP method may not be suitable for the direct detection of injured cells. In addition to its high accuracy and efficiency, the DEP method enables the determination of viable cell counts within 30 min, compared to 48 h required for the conventional culture method. In conclusion, the DEP method may be a potential alternative tool for rapid determination of viable bacteria in a variety of foodstuffs.

Bayesian Generalized Linear Model for Simulating Bacterial Inactivation/Growth Considering Variability and Uncertainty

Conventional regression analysis using the least-squares method has been applied to describe bacterial behavior logarithmically. However, only the normal distribution is used as the error distribution in the least-squares method, and the variability and uncertainty related to bacterial behavior are not considered. In this paper, we propose Bayesian statistical modeling based on a generalized linear model (GLM) that considers variability and uncertainty while fitting the model to colony count data. We investigated the inactivation kinetic data of Bacillus simplex with an initial cell count of 10⁵ and the growth kinetic data of Listeria monocytogenes with an initial cell count of 10⁴. The residual of the GLM was described using a Poisson distribution for the initial cell number and inactivation process and using a negative binomial distribution for the cell number variation during growth. The model parameters could be obtained considering the uncertainty by Bayesian inference. The Bayesian GLM successfully described the results of over 50 replications of bacterial inactivation with average of initial cell numbers of 10¹, 10², and 10³ and growth with average of initial cell numbers of 10^–1, 10⁰, and 10¹. The accuracy of the developed model revealed that more than 90% of the observed cell numbers except for growth with initial cell numbers of 10¹ were within the 95% prediction interval. In addition, parameter uncertainty could be expressed as an arbitrary probability distribution. The analysis procedures can be consistently applied to the simulation process through fitting. The Bayesian inference method based on the GLM clearly explains the variability and uncertainty in bacterial population behavior, which can serve as useful information for risk assessment related to food borne pathogens.

Application of growth rate from kinetic model to calculate stochastic growth of a bacteria population at low contamination level

Traditional predictive microbiology is not suited for cell growth predictions for low-level contamination, where individual cell heterogeneity becomes apparent. Accordingly, we simulated a stochastic birth process of bacteria population using kinetic parameters. We predicted the variation in behavior of Salmonella enterica serovar Typhimurium cells at low inoculum density. The modeled cells were grown in tryptic soy broth at 25 °C. Kinetic growth parameters were first determined empirically for an initial cell number of 10⁴ cells. Monte Carlo simulation based on the growth kinetics and Poisson distribution for different initial cell numbers predicted the results of 50 replicate growth experiments with the initial cell number of 1, 10, and 64 cells. Indeed, measured behavior of 85% cells fell within the 95% prediction area of the simulation. The calculations link the kinetic and stochastic birth process with Poisson distribution. The developed model can be used to calculate the probability distribution of population size for exposure assessment and for the evaluation of a probability that a pathogen would exceed critical contamination level during food storage.

Predicting sensory evaluation of spinach freshness using machine learning model and digital images

The visual perception of freshness is an important factor considered by consumers in the purchase of fruits and vegetables. However, panel testing when evaluating food products is time consuming and expensive. Herein, the ability of an image processing-based, nondestructive technique to classify spinach freshness was evaluated. Images of spinach leaves were taken using a smartphone camera after different storage periods. Twelve sensory panels ranked spinach freshness into one of four levels using these images. The rounded value of the average from all twelve panel evaluations was set as the true label. The spinach image was removed from the background, and then converted into a gray scale and CIE-Lab color space (L*a*b*) and Hue, Saturation and Value (HSV). The mean value, minimum value, and standard deviation of each component of color in spinach leaf were extracted as color features. Local features were extracted using the bag-of-words of key points from Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features). The feature combinations selected from the spinach images were used to train machine learning models to recognize freshness levels. Correlation analysis between the extracted features and the sensory evaluation score showed a positive correlation (0.5 < r < 0.6) for four color features, and a negative correlation (‒0.6 < r < ‒0.5) for six clusters in the local features. The support vector machine classifier and artificial neural network algorithm successfully classified spinach samples with overall accuracy 70% in four-class, 77% in three-class and 84% in two-class, which was similar to that of the individual panel evaluations. Our findings indicate that a model using support vector machine classifiers and artificial neural networks has the potential to replace freshness evaluations currently performed by non-trained panels.

Visceral fat accumulation and left atrial phasic function in the general population

Background

Obesity carries independent risk for incident atrial fibrillation (AF), although the impact of abdominal fat distribution on LA morphological and functional remodeling is not fully elucidated. Speckle-tracking echocardiography is a novel and sensitive tool that allows quantification and detection of subtle alterations in left atrial (LA) phasic function.

Purpose

This study aimed to investigate whether increased visceral adiposity is independently associated with impaired LA phasic function in a community-based cohort.

Methods

We included 527 participants without overt cardiac disease who underwent laboratory testing, abdominal computed tomographic examination and speckle-tracking echocardiography. Abdominal adiposity was quantitatively assessed as visceral fat area (VFA) and subcutaneous fat area (SFA) at the level of the umbilicus. Speckle-tracking echocardiography was performed to assess LA phasic function including reservoir, conduit and pump strain as well as left ventricular global longitudinal strain (LVGLS).

Results

Mean age was 57±10 years and 362 of the participants (69%) were men. LA reservoir and conduit strain were decreased according to the VFA quartiles (both p&lt;0.05), whereas there was no significant difference in LA volume index and LA pump strain. When stratified by SFA, there was no significant differences in LA volume index and all LA phasic strain across the quartiles. In multivariable analysis, VFA as continuous variable was significantly associated with LA conduit strain, independent of traditional cardiovascular risk factors, pertinent laboratory parameters and LV morphology and function including LVGLS (standardized b=−0.146, p=0.011). Representative cases are shown in the Figure.

Conclusion

In a sample of the general population, VFA accumulation was independently associated with worse LA conduit strain, which may be involved in the pathophysiological mechanism of obesity-related AF.

Funding Acknowledgement

Type of funding source: Foundation. Main funding source(s): Yamauchi Susumu Scholarship for Cardiovascular Research

Association between insulin resistance and left ventricular diastolic dysfunction in non-diabetic general population

Background

Insulin resistance due to visceral fat accumulation plays a central role in the development of diabetic mellitus and subsequent cardiovascular disease. Abdominal obesity and diabetic mellitus are associated with the progression of left ventricular diastolic dysfunction which is the major structural abnormality in patients with heart failure. However, whether insulin resistance influences left ventricular diastolic dysfunction in non-diabetic subjects is unclear.

Purpose

In this study, we aimed to clarify the association between insulin resistance and left ventricular diastolic dysfunction in non-diabetic general population.

Methods

We examined 2,572 non-diabetic subjects with preserved left ventricular systolic function (ejection fraction ≥50%) and without a past history of diabetic mellitus, heart failure, coronary artery disease, atrial fibrillation, stroke, moderate to severe valvular disease, who underwent medical check-ups at the University of Tokyo Hospital from January 2009 to December 2018. Diabetes mellitus was defined as fasting glucose level ≥126 mg/dL or a subject's use of oral antidiabetic medications or insulin. We calculated the Homeostasis Model Assessment-Insulin Resistance (HOMA-IR) score [HOMA-IR = fasting glucose (mg/dL) × insulin (μU/mL) / 405], and defined insulin resistance as HOMA-IR ≥2.5. Left ventricular diastolic function was assessed by echocardiography, using tissue doppler analysis (E/E' ratio in septal and lateral). Visceral adiposity was assessed as visceral fat volume measured by computed tomography scanner.

Results

Mean age was 53.3±9.8 years, and 1,746 subjects (67.9%) were male. Overall, HOMA-IR was 1.1 on average, and HOMA-IR ≥2.5 was observed in 5.0% of study population. BMI and the prevalence of obesity were higher in subjects with HOMA-IR ≥2.5 than in those without. There was no significant difference in left ventricular ejection fraction between HOMA-IR ≥2.5 and ≤2.5. E/E' ratio in septal and lateral were higher in subjects with HOMA-IR ≥2.5 than in those without. Multivariable logistic regression analysis demonstrated that obesity and waist circumference, visceral fat volume were independently associated with HOMA-IR ≥2.5, however, age, hypertension, hypercholesterolemia were not. Further, multiple regression analysis including insulin resistance, age, male gender, obesity, hypertension, hypercholesterolemia, cigarette smoking and visceral fat volume, showed that insulin resistance was an independent determinant of increasing E/E' in both septal and lateral, whereas visceral fat volume was not (Figure 1).

Conclusion

The results of the present study suggest that insulin resistance due to visceral fat accumulation might be associated with the development of left ventricular diastolic dysfunction in non-diabetic general population without overt cardiovascular disease.

Figure 1

Funding Acknowledgement

Type of funding source: None

Relationship between Histological Grade and Histopathological Appearance in Canine Mammary Carcinomas

Canine mammary carcinomas are common tumours in female dogs and histopathological examination has an important role in identifying whether they are benign or malignant. The latest and most commonly used histological grading system was established by Peña et al. (2013) and is based on the extent of tubule formation, nuclear pleomorphism and number of mitoses. Before the establishment of this grading system, tumour size and classical histological indicators of malignancy such as lymphovascular invasion, infiltration into surrounding tissue, necrosis and presence of a micropapillary pattern were important predictors of biological behaviour. However, the system of Peña et al. does not consider tumour size or these histological features. Clarifying the association of these features and histological grade, especially in grade II and III carcinomas, is important. In this study, we confirmed that the system of Peña et al. is effective for predicting biological behaviour and that evaluation of histological features of malignancy reinforced histological grade, as determined by the system of Peña et al., especially in grade II carcinomas.

Describing the Individual Spore Variability and the Parameter Uncertainty in Bacterial Survival Kinetics Model by Using Second-Order Monte Carlo Simulation

The objective of this study was to separately describe the fitting uncertainty and the variability of individual cell in bacterial survival kinetics during isothermal and non-isothermal thermal processing. The model describing bacterial survival behavior and its uncertainties and variabilities during non-isothermal inactivation was developed from survival kinetic data for Bacillus simplex spores under fifteen isothermal conditions. The fitting uncertainties in the parameters used in the primary Weibull model was described by using the bootstrap method. The variability of individual cells in thermotolerance and the true randomness in the number of dead cells were described by using the Markov chain Monte Carlo (MCMC) method. A second-order Monte Carlo (2DMC) model was developed by combining both the uncertainties and variabilities. The 2DMC model was compared with reduction behavior under three non-isothermal profiles for model validation. The bacterial death estimations were validated using experimentally observed surviving bacterial count data. The fitting uncertainties in the primary Weibull model parameters, the individual thermotolerance heterogeneity, and the true randomness of inactivated spore counts were successfully described under all the iso-thermal conditions. Furthermore, the 2DMC model successfully described the variances in the surviving bacterial counts during thermal inactivation for all three non-isothermal profiles. As a template for risk-based process designs, the proposed 2DMC simulation approach, which considers both uncertainty and variability, can facilitate the selection of appropriate thermal processing conditions ensuring both food safety and quality.

Describing Uncertainty in Salmonella Thermal Inactivation Using Bayesian Statistical Modeling

Uncertainty analysis is the process of identifying limitations in scientific knowledge and evaluating their implications for scientific conclusions. In the context of microbial risk assessment, the uncertainty in the predicted microbial behavior can be an important component of the overall uncertainty. Conventional deterministic modeling approaches which provide point estimates of the pathogen's levels cannot quantify the uncertainty around the predictions. The objective of this study was to use Bayesian statistical modeling for describing uncertainty in predicted microbial thermal inactivation of Salmonella enterica Typhimurium DT104. A set of thermal inactivation data in broth with water activity adjusted to 0.75 at 9 different temperature conditions obtained from the ComBase database (www.combase.cc) was used. A log-linear microbial inactivation was used as a primary model while for secondary modeling, a linear relation between the logarithm of inactivation rate and temperature was assumed. For comparison, data were fitted with a two-step and a global Bayesian regression. Posterior distributions of model's parameters were used to predict Salmonella thermal inactivation. The combination of the joint posterior distributions of model's parameters allowed the prediction of cell density over time, total reduction time and inactivation rate as probability distributions at different time and temperature conditions. For example, for the time required to eliminate a Salmonella population of about 107 CFU/ml at 65°C, the model predicted a time distribution with a median of 0.40 min and 5th and 95th percentiles of 0.24 and 0.60 min, respectively. The validation of the model showed that it can describe successfully uncertainty in predicted thermal inactivation with most observed data being within the 95% prediction intervals of the model. The global regression approach resulted in less uncertain predictions compared to the two-step regression. The developed model could be used to quantify uncertainty in thermal inactivation in risk-based processing design as well as in risk assessment studies.

Stochastic modeling of variability in survival behavior of Bacillus simplex spore population during isothermal inactivation at the single cell level using a Monte Carlo simulation

The control of bacterial reduction is important to maintain food safety during thermal processing. The goal of this study was to illustrate and describe variability in bacterial population behavior during thermal processing as a probability distribution based on individual cell heterogeneity regarding heat resistance. Toward this end, we performed a Monte Carlo simulation via computer, and compared and validated the simulated estimations with observed values. Weibullian fitted parameters were estimated from the kinetic survival data of Bacillus simplex during thermal treatment at 94 °C. The variability in reductions of bacterial sporular populations was illustrated using Monte Carlo simulation based on the Weibull distribution of the parameters. In particular, variabilities in viable spore counts and survival probability of the B. simplex spore population were simulated in various replicates. We also experimentally determined the changes in survival probability and distributions of survival spore counts; notably, these were successfully predicted by the Monte Carlo simulation based on the kinetic parameters. The kinetic parameter-based Monte Carlo simulation could thus successfully illustrate bacterial population behavior variability during thermal processing as a probability distribution. The simulation approach may contribute to improving food quality through risk-based processing designs and enhance risk assessment model accuracy.

Stochastic simulation for death probability of bacterial population considering variability in individual cell inactivation time and initial number of cells

Decimal reduction time (D-value) based on the first-order survival kinetics model is not sufficient for reliable estimation of the bacterial survivors of inactivation treatment because the model does not consider inactivation curvature. However, even though doubt exists in the calculation of D-value, it is still widely used for risk assessment and sterilisation time estimation. This paper proposes an approach for estimating the time-to-inactivation and death probability of bacterial population that considers individual cell heterogeneity and initial number of cells via computer simulation. In the proposed approach, Weibull and Poisson distributions are respectively used to provide individual cell inactivation time variability and initial number of cells variability. Our simulation results show that the time-to-inactivation significantly depends on kinetics curvature and initial number of cells. For example, with increases in the initial number of cells, the respective variance of the time-to-inactivation of log-linear, concave downward curve, and concave upward curve remains constant, decreases, and increases, respectively. The death probability contour plot was successfully generated via our computer simulation approach without using D-value estimation. Further, the death probability calculated using our stochastic approach was virtually the same as that obtained using inactivation kinetics. We validated the simulation by using literature data for acid inactivation of Salmonella population. The results of this study indicate that inactivation curvature can replace D-value extrapolation to estimate the death probability of bacterial population. Further, our computer simulation facilitates realistic estimation of the time-to-inactivation of bacterial population. The R code used for the above stochastic calculation is outlined.

Rheology and Foaming of Long-Chain Branched Ethylene-Tetrafluoroethylene Copolymer and Its Blends

The long-chain branched ethylene-tetrafluoroethylene copolymer (B-ETFE) was synthesized by radical polymerization using ethylene, tetrafluoroethylene, termonomer, and a very small amount of divinyl monomer. We studied melt rheology under shear and elongational flow, and foamability for B-ETFE, comparing with conventional linear ETFE. Addition of a small amount of the divinyl monomer had a considerable impact on the melt rheology of ETFE and its blends. The observed non-linear elongational behavior and emergence of long relaxation time components can be explained by long-chain branching in the modified ETFE. B-ETFE and its blends showed excellent foaming processability: uniform and smaller cell sizes and much higher cell number densities than those of linear ETFE. To the best of our knowledge, this is the first report of the enhancement of the melt rheology of ETFE from the viewpoint of modification of its molecular architecture.

Cytomegalic Inclusion Disease caused by Cytomegalovirus Infection in the Salivary Glands of an African Hedgehog (Atelerix arbiventris)

Cytomegalic inclusion disease (CID) in the salivary gland of African hedgehogs (Atelerix arbiventris) has been reported before, and is suspected to reflect a cytomegalovirus infection. However, a recent ultrastructural study reported that African hedgehog CID reflected oncocytic metaplasia, mimicking a cytomegalovirus infection. We examined the submandibular and sublingual salivary glands of a 1-year-old male African hedgehog. Histologically, there were multiple foci composed of cytomegalic cells with intranuclear inclusion bodies. Ultrastructurally, viral particles (109-118 nm in diameter) were observed in the nuclei of the cytomegalic cells. There were numerous vesicles containing various numbers of enveloped viruses in the cytoplasm. We also attempted to detect viral DNA fragments by degenerate polymerase chain reaction and obtained amplicons of a predicted size. Phylogenetic analysis indicated that the virus is a betaherpesvirus, comparatively related to human and rodent cytomegaloviruses. The present study suggested that African hedgehog CIDs also include those caused by the cytomegalovirus.

Olympic torch flap: one-stop option for simultaneous brow, upper and lower lid reconstruction in post burn patients

Facial units reconstruction in a post burn patient poses tough challenges. Simultaneous brow and lid reconstruction is one of them. This article presents a 45-year-old epileptic male with burn of complete face. The task of reconstructing the brow, upper and lower lids was successfully accomplished using a modification of the Guyuron postauricular fasciocutaneous flap, after initial grafting and radial forearm flap reconstruction of forehead and other parts of the face. The article gives a single-stop solution for simultaneous reconstruction of brow and lids using a random pattern extension of the traditional postauricular flap, thus proving the excellent vascularity and hence durability of the flap in spite of a 180 degrees change in the orientation of the flap with respect to the axis.

The Relation between Hamstring Strain Injury and Physical Characteristics of Japanese Collegiate Sepak Takraw Players

The aim of this study was to investigate the injuries in Japanese collegiate sepak takraw players. We primarily focused on hamstring strain injury (HSI), and investigated the associated physical characteristics. The study included 77 Japanese collegiate sepak takraw players who were interviewed; data were collected regarding injuries sustained by them during the game within the past year. The hip range of motion (ROM) was measured. The total number of injuries was 48 in a year. The rate of HSI was the highest (31.3%) among all the injuries. All HSIs occurred in the dominant leg because of the sunback spike. Using the Mann-Whitney U test, significant differences in age and sport-related experience were observed between the injured group and uninjured group. Upon using logistic regression analysis, the presence of a HSI was found to be associated with the sport-related experience (adjusted odds ratio [OR], 0.30; 95% confidence interval [CI], 0.12-0.77) and the hip extension ROM (adjusted OR, 0.81; 95% CI, 0.66-0.99) after adjusting for sex, sport-related experience, and the hip ROM. HSI is the most common injury in Japanese collegiate sepak takraw players. Short sport-related experience and small hip extension ROM are related with the occurrence of HSI.

Survival Kinetics of Salmonella enterica and Enterohemorrhagic Escherichia coli on a Plastic Surface at Low Relative Humidity and on Low-Water Activity Foods

We investigated the survival kinetics of Salmonella enterica and enterohemorrhagic Escherichia coli under various water activity (a_w) conditions to elucidate the net effect of a_w on pathogen survival kinetics and to pursue the development of a predictive model of pathogen survival as a function of a_w. Four serotypes of S. enterica (Stanley, Typhimurium, Chester, and Oranienburg) and three serotypes of enterohemorrhagic E. coli ( E. coli O26, E. coli O111, and E. coli O157:H7) were examined. These bacterial strains were inoculated on a plastic plate surface at a constant relative humidity (RH) (22, 43, 58, 68, or 93% RH, corresponding to the a_w) or on a surface of almond kernels (a_w 0.58), chocolate (a_w 0.43), radish sprout seeds (a_w 0.58), or Cheddar cheese (a_w 0.93) at 5, 15, or 25°C for up to 11 months. Under most conditions, the survival kinetics were nonlinear with tailing regardless of the storage a_w, temperature, and bacterial strain. For all bacterial serotypes, there were no apparent differences in pathogen survival kinetics on the plastic surface at a given storage temperature among the tested RH conditions, except for the 93% RH condition. Most bacterial serotypes were rapidly inactivated on Cheddar cheese when stored at 5°C compared with their inactivation on chocolate, almonds, and radish sprout seeds. Distinct trends in bacterial survival kinetics were also observed between almond kernels and radish sprout seeds, even though the a_ws of these two foods were not significantly different. The survival kinetics of bacteria inoculated on the plastic plate surface showed little correspondence to those of bacteria inoculated on food matrices at an identical a_w. Thus, these results demonstrated that, for low-a_w foods and/or environments, a_w alone is insufficient to account for the survival kinetics of S. enterica and enterohemorrhagic E. coli .

Atomic step-and-terrace surface of polyimide sheet for advanced polymer substrate engineering

Typical thermostable and flexible polyimide polymers exhibit many excellent properties such as strong mechanical and chemical resistance. However, in contrast to single-crystal substrates like silicon or sapphire, polymers mostly display disordered and rough surfaces, which may result in instability and degradation of the interfaces between thin films and polymer substrates. As a step toward the development of next-generation polymer substrates, we here report single-atom-layer imprinting onto the polyimide sheets, resulting in an ultrasmooth 0.3 nm high atomic step-and-terrace surface on the polyimides. The ultrasmooth polymer substrates are expected to be applied to the fabrication of nanostructures such as superlattices, nanowires, or quantum dots in nanoscale-controlled electronic devices. We fabricate smooth and atomically stepped indium tin oxide transparent conducting oxide thin films on the imprinted polyimide sheets for future use in organic-based optoelectronic devices processed with nanoscale precision. Furthermore, toward 2D polymer substrate nanoengineering, we demonstrate nanoscale letter writing on the atomic step-and-terrace polyimide surface via atomic force microscopy probe scratching.

'Transfer out' tuberculosis patients: treatment outcomes after cross-checking registers, 2012-2013, Lusaka, Zambia

SETTING

Lusaka, Zambia.

OBJECTIVE

To assess the actual treatment outcomes of 'transfer out' (TO) cases at a diagnostic centre in Lusaka, in the third and fourth quarters of 2012, and to see the impact of this cross-check in treatment success rates (TSR) in 2013 and early 2014.

DESIGN AND METHOD

In this retrospective cohort study, treatment outcomes for new bacteriologically positive tuberculosis (TB) cases referred from the diagnostic centre were reviewed and compared with those at the receiving treatment units.

RESULTS

Of 49 (58%) cases referred to three treatment units, the treatment outcomes of nine had to be updated at the diagnostic centre, which reduced the proportion of TO cases from 17.6% to 11.8% and increased the TSR to 70.6% from 64.7%.

CONCLUSION

The review and cross-checking of the TB registers at the diagnostic and treatment units led to a significant reduction in non-assessed cases, suggesting that the TB registers in the diagnostic and treatment units should be cross-checked regularly. There is also need for a complementary intervention to reduce the proportion of TOs associated with high loss to follow-up and non-evaluated TO rates.

Do bacterial cell numbers follow a theoretical Poisson distribution? Comparison of experimentally obtained numbers of single cells with random number generation via computer simulation

We investigated a bacterial sample preparation procedure for single-cell studies. In the present study, we examined whether single bacterial cells obtained via 10-fold dilution followed a theoretical Poisson distribution. Four serotypes of Salmonella enterica, three serotypes of enterohaemorrhagic Escherichia coli and one serotype of Listeria monocytogenes were used as sample bacteria. An inoculum of each serotype was prepared via a 10-fold dilution series to obtain bacterial cell counts with mean values of one or two. To determine whether the experimentally obtained bacterial cell counts follow a theoretical Poisson distribution, a likelihood ratio test between the experimentally obtained cell counts and Poisson distribution which parameter estimated by maximum likelihood estimation (MLE) was conducted. The bacterial cell counts of each serotype sufficiently followed a Poisson distribution. Furthermore, to examine the validity of the parameters of Poisson distribution from experimentally obtained bacterial cell counts, we compared these with the parameters of a Poisson distribution that were estimated using random number generation via computer simulation. The Poisson distribution parameters experimentally obtained from bacterial cell counts were within the range of the parameters estimated using a computer simulation. These results demonstrate that the bacterial cell counts of each serotype obtained via 10-fold dilution followed a Poisson distribution. The fact that the frequency of bacterial cell counts follows a Poisson distribution at low number would be applied to some single-cell studies with a few bacterial cells. In particular, the procedure presented in this study enables us to develop an inactivation model at the single-cell level that can estimate the variability of survival bacterial numbers during the bacterial death process.

Abundance and genetic damage of barn swallows from Fukushima

A number of studies have assessed or modeled the distribution of the radionuclides released by the accident at the Fukushima-Daiichi Nuclear Power Plant (FDNPP). Few studies however have investigated its consequences for the local biota. We tested whether exposure of barn swallow (Hirundo rustica) nestlings to low dose ionizing radiation increased genetic damage to their peripheral erythrocytes. We estimated external radiation exposure by using thermoluminescent dosimeters, and by measuring radioactivity of the nest material. We then assessed DNA damage by means of the neutral comet assay. In addition, we conducted standard point-count censuses of barn swallows across environmental radiation levels, and estimated their abundance and local age ratio. Radioactivity of nest samples was in the range 479-143,349 Bq kg(-1), while external exposure varied between 0.15 and 4.9 mGy. Exposure to radioactive contamination did not correlate with higher genetic damage in nestlings. However, at higher levels of radioactive contamination the number of barn swallows declined and the fraction of juveniles decreased, indicating lower survival and lower reproduction and/or fledging rate. Thus, genetic damage to nestlings does not explain the decline of barn swallows in contaminated areas, and a proximate mechanism for the demographic effects documented here remains to be clarified.

Positive association between serum thymic stromal lymphopoietin and anti-citrullinated peptide antibodies in patients with rheumatoid arthritis

Thymic stromal lymphopoietin (TSLP) has been suggested recently to play an important role in the pathophysiology of rheumatoid arthritis (RA). However, there is little information on serum TSLP concentrations in RA and its clinical significance. The present study investigated whether serum TSLP concentrations were affected in patients with RA. Using an enzyme-linked immunosorbent assay (ELISA), we measured TSLP concentrations in the serum obtained from 100 patients with RA, 60 patients with osteoarthritis (OA) and 34 healthy volunteers. We also investigated the correlation between serum TSLP concentrations and clinical parameters of disease activity in RA [disease activity score using 28 joint counts (DAS28)-C-reactive protein (CRP), DAS28-erythrocyte sedimentation rate (ESR), Clinical Disease Activity Index (CDAI]), patient's/-physician's Visual Analogue Scale (VAS), swollen joints count, tender joints count, CRP, ESR and matrix metalloproteinase-3 (MMP-3) concentrations]. In addition, we investigated the correlation between serum TSLP concentrations and anti-citrullinated peptide antibody (ACPA) and serum tumour necrosis factor (TNF)-α. Serum TSLP levels in patients with RA were significantly higher than those in patients with OA and in healthy volunteers. Interestingly, serum TSLP concentrations were correlated significantly with ACPA titres, but not with other clinical parameters. There was a significant increase in serum TSLP concentrations in patients with RA, which was correlated positively with serum ACPA titres. These findings suggest that in patients with RA, TSLP may play a role in ACPA production by B cells.

Enhanced thermal, mechanical and fire-retarding properties of polystyrene sulphonate-grafted-nanosilica/polypropylene composites

The addition of pSS-grafted-nanosilica to PP showed enhanced fire retardancy as assessed by mass loss, cone calorimetry and LOI measurements.