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Liu X, Fan L, Tan Q, Chen X, Li H, Zhao X, Zhang X. Prevalence of Toxoplasma gondii in pigs determined by ELISA based on recombinant SAG1 in Shandong province, China. Comp Immunol Microbiol Infect Dis 2022; 83:101781. [DOI: 10.1016/j.cimid.2022.101781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/22/2022] [Accepted: 02/23/2022] [Indexed: 11/16/2022]
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Puchalska M, Wiśniewski J, Klich D, Gołąb E, Jańczak D, Sokołowska J, Urbańska K, Anusz K. A serological survey of Toxoplasma gondii in polish pigs from organic farms, other housing systems and in pigs of different age groups. Acta Vet Scand 2022; 64:3. [PMID: 35130949 PMCID: PMC8822955 DOI: 10.1186/s13028-022-00623-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 01/26/2022] [Indexed: 11/10/2022] Open
Abstract
Background The consumption of raw or undercooked meat, especially pork, and offal containing infective tissue cysts is suspected to be a significant route of infection with Toxoplasma gondii. Although the use of “animal-friendly pig production systems” ensuring direct contact with the natural environment offers ethical benefits, it limits the ability to ensure animal health; it may also increase the probability of infections by pathogens such as T. gondii, and thus their entry into the food chain. This study determines the seroprevalence of T. gondii in pigs from different housing systems and farms with different hygiene standards in Poland, as well as among pigs of different age groups from farms with high hygiene standards. In total 760 pig serum samples were examined for the presence of specific antibodies using the PrioCHECK® Toxoplasma Ab porcine commercial ELISA test (Prionics, Switzerland). Results Test results with PP ≥ 20% were regarded as positive, as indicated by the manufacturer. Antibodies to T. gondii were found in 193 of 760 (25.4%) tested sera. Regarding different housing systems, antibodies were found in 117 pigs: of these, 52.6% (61/116) were from organic farms, 40.9% (47/115) from farms with low hygiene standards, 5.4% (9/167) from farms with high hygiene standards and 0% (0/40) from a farm with a high level of biosecurity. Regarding age groups, antibodies were found in 76 animals on farms with high hygiene standards: 11.1% (7/63) were pigs younger than 3 months, 0% (0/60) aged 3–4 months, 12.3% (7/57) aged 5–6 months (final fattening stage) and 43.7% (62/142) were sows aged 9 months and older. Conclusions Antibodies to T. gondii were most often found in pigs from organic and low-hygiene farms, as well as in pigs aged 9 months and older. Meat derived from seropositive animals can pose a potential source of infection for humans. As maternal antibodies to T. gondii can be present in the blood of piglets aged up to 3–4 months, serological examination is unjustified in piglets up to this age.
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Zhang P, Cui W, Wang H, Du Y, Zhou Y. High-Efficiency Machine Learning Method for Identifying Foodborne Disease Outbreaks and Confounding Factors. Foodborne Pathog Dis 2021; 18:590-598. [PMID: 33902323 PMCID: PMC8390778 DOI: 10.1089/fpd.2020.2913] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
The China National Center for Food Safety Risk Assessment (CFSA) uses the Foodborne Disease Monitoring and Reporting System (FDMRS) to monitor outbreaks of foodborne diseases across the country. However, there are problems of underreporting or erroneous reporting in FDMRS, which significantly increase the cost of related epidemic investigations. To solve this problem, we designed a model to identify suspected outbreaks from the data generated by the FDMRS of CFSA. In this study, machine learning models were used to fit the data. The recall rate and F1-score were used as evaluation metrics to compare the classification performance of each model. Feature importance and pathogenic factors were identified and analyzed using tree-based and gradient boosting models. Three real foodborne disease outbreaks were then used to evaluate the best performing model. Furthermore, the SHapley Additive exPlanation value was used to identify the effect of features. Among all machine learning classification models, the eXtreme Gradient Boosting (XGBoost) model achieved the best performance, with the highest recall rate and F1-score of 0.9699 and 0.9582, respectively. In terms of model validation, the model provides a correct judgment of real outbreaks. In the feature importance analysis with the XGBoost model, the health status of the other people with the same exposure has the highest weight, reaching 0.65. The machine learning model built in this study exhibits high accuracy in recognizing foodborne disease outbreaks, thus reducing the manual burden for medical staff. The model helped us identify the confounding factors of foodborne disease outbreaks. Attention should be paid not only to the health status of those with the same exposure but also to the similarity of the cases in time and space.
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Affiliation(s)
- Peng Zhang
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, China
- School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Wenjuan Cui
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, China
| | - Hanxue Wang
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, China
- School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Yi Du
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, China
- School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Yuanchun Zhou
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, China
- School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China
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Zeng A, Gong QL, Wang Q, Wang CR, Zhang XX. The global seroprevalence of Toxoplasma gondii in deer from 1978 to 2019: A systematic review and meta-analysis. Acta Trop 2020; 208:105529. [PMID: 32433912 DOI: 10.1016/j.actatropica.2020.105529] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Revised: 05/04/2020] [Accepted: 05/04/2020] [Indexed: 12/12/2022]
Abstract
Toxoplasma gondii infecting virtually all warm-blooded animals, including humans, is an intracellular protozoan parasite. The immunocompromised patients or pregnant women infected by Toxoplasma usually can cause encephalitis or abortion. Deer are also the important intermediate host of the parasite and people can be infected by ingesting the undercooked venison. Therefore, to raise the attention of the researchers and T. gondii infection on people in deer, we conducted the meta-analysis. All potential publications on the T. gondii infection in deer were retrieved by searching the PubMed, ScienceDirect, Springer- Link, China National Knowledge Infrastructure (CNKI), WanFang, and VIP Chinese Journal Databases. Finally, a total of 48 publications were included. The pooled seroprevalence of T. gondii infection in deer was 22.92% (95% CI 17.89-28.38) calculated by the random effect model. The seroprevalence of T. gondii infection in deer was the lowest in Asia (12.72%, 95% CI 6.29-20.89), and the highest in North America (32.21%, 95% CI 20.32-45.39). The highest point estimate of deer T. gondii in detection method subgroup was using MAT (31.28%, 95% CI 20.15-43.61). The estimated pooled seroprevalence of T. gondii infection in elk (63.50%, 95% CI 50.01-76.01) was higher than other types of deer. Our meta-regression analysis found that the subgroups including region, sampling year, age, climate, and deer species may be the main heterogeneous source in our meta-analysis. It is necessary to monitor the seroprevalence of T. gondii infection in deer at all times. Furthermore, people should be taken to precautions when ingesting the venison by cooking it well before serving to prevent the T. gondii infection via eating venison.
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Affiliation(s)
- Ao Zeng
- College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, Heilongjiang Province, 163319, China
| | - Qing-Long Gong
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin Province, 130118, China
| | - Qi Wang
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin Province, 130118, China
| | - Chun-Ren Wang
- College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, Heilongjiang Province, 163319, China.
| | - Xiao-Xuan Zhang
- College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, Shandong Province, 266109, China.
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Dubey JP, Cerqueira-Cézar CK, Murata FHA, Kwok OCH, Hill D, Yang Y, Su C. All about Toxoplasma gondii infections in pigs: 2009-2020. Vet Parasitol 2020; 288:109185. [PMID: 33271424 DOI: 10.1016/j.vetpar.2020.109185] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Toxoplasma gondii infections are common in humans and animals worldwide. Toxoplasma gondii infection in pigs continues to be of public health concern. Pigs are important for the economy of many countries, particularly, USA, China, and European countries. Among the many food animals, pigs are considered the most important for T. gondii transmission in USA and China because viable parasites have rarely been isolated from beef or indoor raised chickens. Besides public health issues, T. gondii causes outbreaks of clinical toxoplasmosis in pigs in China, associated with a unique genotype of T. gondii (ToxoDB genotype #9 or Chinese 1), rarely found in other countries. The safety of ready to eat pork products with respect to T. gondii infection is a matter of recent debate. Here, we review in detail seroprevalence, prevalence of viable and nonviable T. gondii, epidemiology, risk assessment, diagnosis, and curing of pork products containing T. gondii for the past decade. This review will be of interest to biologists, parasitologists, veterinarians, and public health workers.
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Affiliation(s)
- Jitender P Dubey
- United States Department of Agriculture, Agricultural Research Service, Beltsville Agricultural Research Center, Animal Parasitic Diseases Laboratory, Beltsville, MD 20705-2350, USA.
| | - Camila K Cerqueira-Cézar
- United States Department of Agriculture, Agricultural Research Service, Beltsville Agricultural Research Center, Animal Parasitic Diseases Laboratory, Beltsville, MD 20705-2350, USA
| | - Fernando H A Murata
- United States Department of Agriculture, Agricultural Research Service, Beltsville Agricultural Research Center, Animal Parasitic Diseases Laboratory, Beltsville, MD 20705-2350, USA
| | - Oliver C H Kwok
- United States Department of Agriculture, Agricultural Research Service, Beltsville Agricultural Research Center, Animal Parasitic Diseases Laboratory, Beltsville, MD 20705-2350, USA
| | - Dolores Hill
- United States Department of Agriculture, Agricultural Research Service, Beltsville Agricultural Research Center, Animal Parasitic Diseases Laboratory, Beltsville, MD 20705-2350, USA
| | - Yurong Yang
- Laboratory of Veterinary Pathology, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou 450002, PR China
| | - Chunlei Su
- Department of Microbiology, University of Tennessee, Knoxville, TN 37996-0845, USA
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