Dataset Information

Development and Application of an Alert System to Detect Cases of Food Poisoning in Japan.

ABSTRACT: Recent public health concerns regarding commercial food products have increased the need to develop an automated method to detect food product-related health events. We developed and verified a method for the early detection of potentially harmful events caused by commercial food products. We collected data from daily internet-based questionnaires examining the presence or absence of symptoms and information about food purchased by the respondents. Using these data, we developed a method to detect possible health concerns regarding commercialized food products. To achieve this, we combined the signal detection method used in the reporting system of adverse effects of pharmaceutical products and the Early Aberration Reporting System (EARS) used by the United States Centers for Disease Control. Whiteleg shrimp (Litopenaeus vannamei), which had odds ratio and Odds(-) of 8.99 and 4.13, respectively, was identified as a possible causative food product for diarrhea and vomiting. In conclusion, this study demonstrated that food distributors can implement post-marketing monitoring of the safety of food products purchased via the internet.

SUBMITTER: Maeyashiki A

PROVIDER: S-EPMC4883778 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Development and Application of an Alert System to Detect Cases of Food Poisoning in Japan.

Maeyashiki Akie A Akahane Manabu M Sugiura Hiroaki H Ohkusa Yasushi Y Okabe Nobuhiko N Imamura Tomoaki T

PloS one 20160527 5

Recent public health concerns regarding commercial food products have increased the need to develop an automated method to detect food product-related health events. We developed and verified a method for the early detection of potentially harmful events caused by commercial food products. We collected data from daily internet-based questionnaires examining the presence or absence of symptoms and information about food purchased by the respondents. Using these data, we developed a method to dete ...[more]

PMID: 27231884

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Project description:IntroductionBacillus cereus is a ubiquitous opportunistic human pathogen that causes food intoxications worldwide. However, the genomic characteristics and pathogenic mechanisms of B. cereus are still unclear.MethodsHere, we isolated and purified nine strains of B. cereus (LY01-LY09) that caused vomiting, diarrhea and other symptoms from four foodborne outbreaks happened in Guizhou Province in southwest China from June to September 2021. After colony observation, Gram staining, microscopic examination and biochemical test, they were identified as B. cereus. The genomic characteristics, phylogenetic relationships and virulence factors of the isolated strains were analyzed at the genome level. Genome sequencing, comparative genomic analysis, secondary metabolite analysis and quantitative PCR were utilized to give a thorough exploration of the strains.ResultsWe obtained the genome maps of LY01-LY09 and found that LY01-LY09 had a complex interspecific relationship with B. anthracis and B. thuringiensis. We also observed a contraction of gene families in LY01-LY09, and the contracted families were mainly associated with prophage, which contributed to the species diversity of B. cereus. The Hsp20 gene family underwent a rapid evolution in LY01-LY09, which facilitated the adaptation of the strains to adverse environmental conditions. Moreover, the LY01-LY09 strains exhibited a higher copy number in the non-ribosomal polypeptide synthetase (NRPS) genes and carried the complete cereulide synthetase (ces) gene cluster sequences. Considering that the NRPS system is a classical regulatory mechanism for emetic toxin synthesis, we hypothesized that LY01-LY09 could synthesize emetic toxins through the regulation of ces gene clusters by the NRPS system.DiscussionThese findings are important for further investigation into the evolutionary relationship between B. cereus and their related species, as well as the underlying mechanisms governing the synthesis and secretion of bacterial toxins.

Project description:BackgroundA prediction model of mortality for patients with acute poisoning has to consider both poisoning-related characteristics and patients' physiological conditions; moreover, it must be applicable to patients of all ages. This study aimed to develop a scoring system for predicting in-hospital mortality of patients with acute poisoning at the emergency department (ED).MethodsThis was a retrospective analysis of the Injury Surveillance Cohort generated by the Korea Center for Disease Control and Prevention (KCDC) during 2011-2018. We developed the new-Poisoning Mortality Scoring system (new-PMS) to generate a prediction model using the derivation group (2011-2017 KCDC cohort). Points were computed for categories of each variable. The sum of these points was the new-PMS. The validation group (2018 KCDC cohort) was subjected to external temporal validation. The performance of new-PMS in predicting mortality was evaluated using area under the receiver operating characteristic curve (AUROC) for both the groups.ResultsOf 57,326 poisoning cases, 42,568 were selected. Of these, 34,352 (80.7%) and 8216 (19.3%) were enrolled in the derivation and validation groups, respectively. The new-PMS was the sum of the points for each category of 10 predictors. The possible range of the new-PMS was 0-137 points. Hosmer-Lemeshow goodness-of-fit test showed adequate calibration for the new-PMS with p values of 0.093 and 0.768 in the derivation and validation groups, respectively. AUROCs of the new-PMS were 0.941 (95% CI 0.934-0.949, p < 0.001) and 0.946 (95% CI 0.929-0.964, p < 0.001) in the derivation and validation groups, respectively. The sensitivity, specificity, and accuracy of the new-PMS (cutoff value: 49 points) were 86.4%, 87.2%, and 87.2% and 85.9%, 89.5%, and 89.4% in the derivation and validation groups, respectively.ConclusionsWe developed a new-PMS system based on demographic, poisoning-related variables, and vital signs observed among patients at the ED. The new-PMS showed good performance for predicting in-hospital mortality in both the derivation and validation groups. The probability of death increased according to the increase in the new-PMS. The new-PMS accurately predicted the probability of death for patients with acute poisoning. This could contribute to clinical decision making for patients with acute poisoning at the ED.

Dataset Information

Development and Application of an Alert System to Detect Cases of Food Poisoning in Japan.

Publications

Development and Application of an Alert System to Detect Cases of Food Poisoning in Japan.

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