scholarly journals Modeling the Reduction of Salmonella spp. on Chicken Breasts and Wingettes during Scalding for QMRA of the Poultry Supply Chain in China

2019 ◽  
Vol 7 (6) ◽  
pp. 165 ◽  
Author(s):  
Xingning Xiao ◽  
Wen Wang ◽  
Xibin Zhang ◽  
Jianmin Zhang ◽  
Ming Liao ◽  
...  
Keyword(s):  
Supply Chain ◽  
Predictive Models ◽  
Linear Models ◽  
Weibull Model ◽  
Bacterial Reduction ◽  
Salmonella Spp ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Log Linear ◽  
Best Fit

The objective of this study was to develop predictive models for describing the inoculated Salmonella reductions on chicken during the scalding process in China. Salmonella reductions on chicken breasts at a 100 s treatment were 1.12 ± 0.07, 1.38 ± 0.01, and 2.17 ± 0.11 log CFU/g at scalding temperatures of 50, 60 and 70 °C, respectively. For chicken wingettes, 0.87 ± 0.02, 0.99 ± 0.14 and 1.11 ± 0.17 log CFU/g reductions were obtained at 50, 60 and 70 °C after the 100 s treatment, respectively. Greater bacterial reductions were observed on chicken breasts than on chicken wingettes (p < 0.05). A logistic (−1.12, 0.06) distribution could describe the bacterial reductions on chicken breasts at 50–60 °C. Weibull, exponential and log-linear models were compared for describing the bacterial reduction on chicken breasts at 70 °C and the Weibull model showed the best fit as indicated by the pseudo-R2, root mean square error (RMSE) and standard error of prediction (SEP) values. For chicken wingettes, a logistic (−0.95, 0.07) distribution could be used to describe the bacterial reduction at 50–70 °C. The developed predictive models could provide parts of the input data for microbial risk assessment of the poultry supply chain in China.

Relationship between plasma osmolality and plasma vasopressin in human subjects

1980 ◽  
Vol 238 (4) ◽  
pp. E313-E317 ◽  
Author(s):  
M. Hammer ◽  
J. Ladefoged ◽  
K. Olgaard
Keyword(s):  
Linear Models ◽  
Human Subjects ◽  
Plasma Osmolality ◽  
Metabolic Clearance ◽  
Parabolic Model ◽  
Pronounced Increase ◽  
Plasma Vasopressin ◽  
Log Linear ◽  
The Relationship ◽  
Best Fit

The relationship between plasma osmolality (pOsm) and plasma vasopressin (pAVP) was studied in 13 human subjects during dehydration. The fit of linear, log-linear, parabolic, and exponential models was tested. For all of the data, the nonlinear models had the best fit. However, when individual differences in either gain or threshold were allowed for, the linear models were better than log-linear models. Finally, analyses were made with individual data points. Linear models had the best fit in half of the subjects, whereas for the others the parabolic model gave the best fit. For those subjects investigated in the low range of the osmoregulatory curve, a linear relationship was found, whereas, for those having the most pronounced increase in pOsm, the most significant improvement was found with the parabolic model. This finding indicates that the relationship is not stable during dehydration in the whole range and that hypovolemia probably can influence the secretion rate and/or metabolic clearance rate and thereby the relationship.

scholarly journals Molecular Analyses of Fecal Bacteria and Hydrodynamic Modeling for Microbial Risk Assessment of a Drinking Water Source

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 3
Author(s):  
Olga D. Chuquimia ◽  
Viktor Bergion ◽  
Jessica Guzman-Otazo ◽  
Kaisa Sörén ◽  
Lars Rosén ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
Water Intake ◽  
Real Time Pcr ◽  
Hydrodynamic Modeling ◽  
Salmonella Spp ◽  
Molecular Analyses ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Campylobacter Spp

Safe water is a global concern, and methods to accurately monitor quality of water are vital. To assess the risks related to bacterial pathogen load in Lake Vomb that provides drinking water to the southern part of Sweden, this study combined molecular analyses of enterobacteria and bacterial pathogens in water using quantitiative real-time PCR with hydrodynamic modeling and quantitative microbial risk assessment (QMRA). A real-time PCR assay to detect enterobacteria was set up by primers targeting ssrA. Between February 2015 and May 2016, presence of ssrA gene copies as well as Campylobacter spp., Salmonella spp., and EHEC O157 DNA was analyzed by real-time PCR at several locations in the catchment of Lake Vomb and its tributaries Björkaån, Borstbäcken, and Torpsbäcken. Björkaån had the highest detected concentrations of the ssrA gene and, according to the results of hydrodynamic modeling, contributed most to the contamination of the water intake in the lake. None of the water samples were positive for genes encoding EHEC O157 and Campylobacter spp., while invA (Salmonella spp.) was present in 11 samples. The QMRA showed that the suggested acceptable risk level (daily probability of infection <2.7 × 10−7) is achieved with a 95% probability, if the Salmonella concentrations in the water intake are below 101 bacteria/100 mL. If a UV-disinfection step is installed, the Salmonella concentration at the water intake should not exceed 106 bacteria/100 mL.

Quantitative Microbial Risk Assessment for Campylobacter Foodborne Illness in Raw Beef Offal Consumption in South Korea

2017 ◽  
Vol 80 (4) ◽  
pp. 609-618 ◽  
Author(s):  
Jiyeon Jeong ◽  
Jeeyeon Lee ◽  
Heeyoung Lee ◽  
Soomin Lee ◽  
Sejeong Kim ◽  
...  
Keyword(s):  
South Korea ◽  
Predictive Models ◽  
Storage Temperature ◽  
Foodborne Illness ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Consumption Frequency ◽  
Campylobacter Spp ◽  
Home Consumption

ABSTRACT This study evaluated the risk of Campylobacter foodborne illness caused by the intake of raw beef offal in South Korea. The prevalence of Campylobacter spp. in raw beef offal (liver and tripe) was investigated by plating samples on modified charcoal-cefoperazone-deoxycholate agar with Preston enrichment broth. Data were collected about storage temperature and length of storage of raw beef offal, and probabilistic distributions for the data were determined, using @RISK software. Predictive models were developed to describe the fate of Campylobacter in raw beef offal, and the amount and frequency of consumption and dose-response model were surveyed. Subsequently, these data were used to estimate the risk of Campylobacter foodborne illness caused by the intake of raw beef offal. Of 80 beef offal samples, 1 (1.25%) was contaminated with Campylobacter jejuni. Predictive models were used for exposure assessment. An exponential distribution was selected to represent beef offal consumption by people who eat this occasionally, with a mean of 60.2 g and 3.6% monthly consumption frequency. Simulations using @RISK predicted that the probability of Campylobacter foodborne illness per person per month is 1.56 × 10−5 for home consumption and 1.74 × 10−5 for restaurant consumption in South Korea, which indicates the risk of Campylobacter foodborne illness by intake of raw beef offal in South Korea.

Assessment of E. coli and Salmonella spp. infection risks associated with different fecal sludge disposal practices in Thailand

2009 ◽  
Vol 8 (2) ◽  
pp. 355-364 ◽  
Author(s):  
A. Yajima ◽  
T. Koottatep
Keyword(s):  
High Water ◽  
Developed Countries ◽  
World Health ◽  
Quantitative Microbial Risk Assessment ◽  
Salmonella Spp ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Risk Levels ◽  
E Coli ◽  
Fecal Sludge

The proper management of fecal sludge (FS), to block the transmission pathways of pathogens, is rarely enforced in many parts of the world. Health risks associated with different disposal practices of FS in peri-urban settings of a large metropolis in Thailand were assessed; Tha Klong sub-district with indiscriminate FS dumping, and Klong Luang sub-district which has an FS treatment system. The study showed that indiscriminate FS dumping from along the canal banks and discharge of market waste were likely the major sources of E. coli and Salmonella spp. in contamination of the canal water. The increased microbial pathogen concentrations near the FS treatment facility also indicated contamination risks from poorly designed treatment facilities. Quantitative microbial risk assessment (QMRA) indicated very high water-related infection risk levels compared to the actual locally recorded disease occurrences. These results indicated that the QMRA model needs to be modified to take account of immunological differences between populations in developed countries, where the model was developed, and developing countries. In addition, further sensitivity factors are needed to reflect different societal behavior patterns, and therefore contact with potentially contaminated water, in different sub-populations of many less developed communities.

scholarly journals Evaluation of the Thermal Inactivation of a Salmonella Serotype Oranienburg Strain During Cocoa Roasting at Conditions Relevant to the Fine Chocolate Industry

2021 ◽  
Vol 12 ◽  
Author(s):  
Runan Yan ◽  
Gabriella Pinto ◽  
Rebecca Taylor-Roseman ◽  
Karen Cogan ◽  
Greg D’Alesandre ◽  
...  
Keyword(s):  
Foodborne Pathogens ◽  
Thermal Inactivation ◽  
Linear Models ◽  
Control Point ◽  
Weibull Model ◽  
Inactivation Kinetics ◽  
Critical Control Point ◽  
Chocolate Industry ◽  
Weibull Models ◽  
Log Linear

Cocoa roasting produces and enhances distinct flavor of chocolate and acts as a critical control point for inactivation of foodborne pathogens in chocolate production. In this study, the inactivation kinetics of Salmonella enterica subsp. enterica serotype Oranienburg strain was assessed on whole cocoa beans using roasting protocols relevant to the fine chocolate industry. Beans were inoculated with 107–108 log10 CFU/bean of Salmonella Oranienburg and roasted at 100–150°C for 2–100 min. A greater than 5 log10 reduction of S. Oranienburg was experimentally achieved after 10-min roasting at 150°C. Data were fitted using log-linear and Weibull models. The log-linear models indicated that the roasting times (D) needed to achieve a decimal reduction of Salmonella at 100, 110, 115, 120, 130, and 140°C were 33.34, 18.57, 12.92, 10.50, 4.20, and 1.90 min, respectively. A Weibull model indicated a decrease in the Salmonella inactivation rate over time (β &lt; 1). Statistical analysis indicated that the Weibull model fitted the data better compared to a log-linear model. These data demonstrate the efficacy of cocoa roasting in inactivation of Salmonella and may be used to guide food safety decision-making.

scholarly journals Analysis of Traffic Accidents Caused by Drivers by Using Log-Linear Models

1970 ◽  
Vol 24 (6) ◽  
pp. 495-504 ◽  
Author(s):  
Hülya Olmuş ◽  
Semra Erbaş
Keyword(s):  
Odds Ratio ◽  
Relative Frequency ◽  
Traffic Accidents ◽  
Linear Models ◽  
Linear Modelling ◽  
Accident Severity ◽  
Modelling Effort ◽  
Log Linear ◽  
Best Fit ◽  
Multiple Interactions

Log-linear modelling is advanced as a procedure to identify factors that underlie the relative frequency of occurrence of various characteristics. The purpose of this study is to present a modelling effort using log-linear models to estimate the relationships between driver’s fault and carelessness and the traffic variables such as gender, accident severity, and accident time. The study was conducted in four different districts in Ankara, the capital of Turkey. There were 1,325 people selected for the study; and they were asked whether they had been in an accident. Four hundred and forty-eight of them answered that they had been involved in an accident. As drivers, 276 out of 448 people, namely 61.6%, had traffic accidents. The data on the variables, namely gender, driver’s fault and carelessness, accident severity and accident time, were collected through a questionnaire survey. Detailed information has been created based on this information. The analysis showed that the best-fit model regarding these variables was the log-linear model. Furthermore, the odds ratio between these variables, the associations of the factors with the accident severity and the contributions of various factors, and the multiple interactions between these variables were assessed. The obtained results provide valuable information in regard to preventing undesired consequences of traffic accidents.

Quantitative microbial risk assessment of Salmonella and Enterococcus in Marina Reservoir and catchments

2015 ◽  
Vol 10 (3) ◽  
pp. 527-531 ◽  
Author(s):  
S. G. Goh ◽  
H. M. Fang ◽  
S. Y. Chang ◽  
Karina Y. H. Gin
Keyword(s):  
Risk Assessment ◽  
Environmental Protection Agency ◽  
The United States ◽  
Quantitative Microbial Risk Assessment ◽  
Salmonella Spp ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Simulation Techniques ◽  
Guideline Values ◽  
Microbial Risks

This study assesses the infection risks associated with non-swimming recreational activities in Marina Reservoir, Singapore. Apart from serving as a reservoir for potable water use, Marina Reservoir is also a place where various water recreations are carried out. Quantitative microbial risk assessment (QMRA) was applied to Marina Reservoir and its four main feeders. QMRA was performed based on the occurrence data of the potential pathogen, Salmonella spp. and bacteria indicator, Enterococcus spp. through Monte Carlo simulation techniques. The results suggest that microbial risks from Salmonella and Enterococcus at the reservoir were below the United States Environmental Protection Agency (USEPA) acceptable freshwater recreational illness rate of 0.8%. All upstream catchments showed acceptable microbial risks from Salmonella. However, the probability of gastrointestinal illness risks calculated for Enterococcus exceeded the USEPA guideline values in one of the upstream catchments, but far enough upstream from recreational areas that are used frequently.

scholarly journals Quantitative Microbial Risk Assessment of Drinking Water Quality to Predict the Risk of Waterborne Diseases in Primary-School Children

2020 ◽  
Vol 17 (8) ◽  
pp. 2774 ◽  
Author(s):  
Jamil Ahmed ◽  
Li Ping Wong ◽  
Yan Piaw Chua ◽  
Najeebullah Channa ◽  
Rasool Bux Mahar ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Drinking Water ◽  
Primary School ◽  
School Children ◽  
Primary School Children ◽  
Quantitative Microbial Risk Assessment ◽  
Waterborne Diseases ◽  
Salmonella Spp ◽  
Microbial Risk Assessment ◽  
Microbial Risk

Primary-school children in low- and middle-income countries are often deprived of microbiologically safe water and sanitation, often resulting in a high prevalence of gastrointestinal diseases and poor school performance. We used Quantitative Microbial Risk Assessment (QMRA) to predict the probability of infection in schoolchildren due to consumption of unsafe school water. A multistage random-sampling technique was used to randomly select 425 primary schools from ten districts of Sindh, Pakistan, to produce a representative sample of the province. We characterized water supplies in selected schools. Microbiological testing of water resulted in inputs for the QMRA model, to estimate the risks of infections to schoolchildren. Groundwater (62%) and surface water (38%) were identified as two major sources of drinking water in the selected schools, presenting varying degrees of health risks. Around half of the drinking-water samples were contaminated with Escherichia coli (49%), Shigella spp. (63%), Salmonella spp. (53%), and Vibrio cholerae (49%). Southern Sindh was found to have the highest risk of infection and illness from Campylobacter and Rotavirus. Central and Northern Sindh had a comparatively lower risk of waterborne diseases. Schoolchildren of Karachi were estimated to have the highest probability of illness per year, due to Campylobacter (70%) and Rotavirus (22.6%). Pearson correlation was run to assess the relationship between selected pathogens. V. cholerae was correlated with Salmonella spp., Campylobacter, Rotavirus, and Salmonella spp. Overall, the risk of illness due to the bacterial infection (E. coli, Salmonella spp., V. cholerae, Shigella, and Campylobacter) was high. There is a dire need for management plans in the schools of Sindh, to halt the progression of waterborne diseases in school-going children.

scholarly journals Quantitative Microbial Risk Assessment Based on Whole Genome Sequencing Data: Case of Listeria monocytogenes

2020 ◽  
Vol 8 (11) ◽  
pp. 1772
Author(s):  
Patrick Murigu Kamau Njage ◽  
Pimlapas Leekitcharoenphon ◽  
Lisbeth Truelstrup Hansen ◽  
Rene S. Hendriksen ◽  
Christel Faes ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Listeria Monocytogenes ◽  
Stress Response ◽  
Predictive Models ◽  
Population Heterogeneity ◽  
Whole Genome Sequencing Data ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
The Impact

The application of high-throughput DNA sequencing technologies (WGS) data remain an increasingly discussed but vastly unexplored resource in the public health domain of quantitative microbial risk assessment (QMRA). This is due to challenges including high dimensionality of WGS data and heterogeneity of microbial growth phenotype data. This study provides an innovative approach for modeling the impact of population heterogeneity in microbial phenotypic stress response and integrates this into predictive models inputting a high-dimensional WGS data for increased precision exposure assessment using an example of Listeria monocytogenes. Finite mixture models were used to distinguish the number of sub-populations for each of the stress phenotypes, acid, cold, salt and desiccation. Machine learning predictive models were selected from six algorithms by inputting WGS data to predict the sub-population membership of new strains with unknown stress response data. An example QMRA was conducted for cultured milk products using the strains of unknown stress phenotype to illustrate the significance of the findings of this study. Increased resistance to stress conditions leads to increased growth, the likelihood of higher exposure and probability of illness. Neglecting within-species genetic and phenotypic heterogeneity in microbial stress response may over or underestimate microbial exposure and eventual risk during QMRA.

scholarly journals Critical Analysis of Pork QMRA Focusing on Slaughterhouses: Lessons from the Past and Future Trends

Foods ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1704
Author(s):  
Ammar Hdaifeh ◽  
Tahreem Khalid ◽  
Géraldine Boué ◽  
Enda Cummins ◽  
Sandrine Guillou ◽  
...  
Keyword(s):  
Critical Analysis ◽  
Risk Mitigation ◽  
Future Research ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Diseases ◽  
Salmonella Spp ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Research Activities ◽  
Meta Analyses

Foodborne microbial diseases have a significant impact on public health, leading to millions of human illnesses each year worldwide. Pork is one of the most consumed meat in Europe but may also be a major source of pathogens introduced all along the farm-to-fork chain. Several quantitative microbial risk assessment (QMRA) have been developed to assess human health risks associated with pork consumption and to evaluate the efficiency of different risk reduction strategies. The present critical analysis aims to review pork QMRA. An exhaustive search was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology. It resulted in identification of a collection of 2489 papers including 42 on QMRA, after screening. Among them, a total of 29 studies focused on Salmonella spp. with clear concern on impacts at the slaughterhouse, modeling the spreading of contaminations and growth at critical stages along with potential reductions. Along with strict compliance with good hygiene practices, several potential risk mitigation pathways were highlighted for each slaughterhouse step. The slaughterhouse has a key role to play to ensure food safety of pork-based products but consideration of the whole farm-to-fork chain is necessary to enable better control of bacteria. This review provides an analysis of pork meat QMRA, to facilitate their reuse, and identify gaps to guide future research activities.

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