Literature DB >> 24951834

Global geographic distribution of Trichinella species and genotypes.

Haralambos Feidas1, Marc K Kouam2, Vaia Kantzoura3, Georgios Theodoropoulos4.   

Abstract

Maximum entropy ecological niche modeling was utilized to describe the global geographic distribution of Trichinella species and genotypes and to assess their invasive risk in new areas other than the ones currently known. Also, space-time scan statistic was utilized to identify global spatiotemporal clusters of infection. A database containing 3209 records for 12 species and genotypes identified at the International Trichinella Reference Center (ITRC) as well as climate, elevation, and land cover data extracted from various databases were used. Ecological niche modeling implemented in the Maxent program indicated new potential ranges for T. spiralis (T1), T. nativa (T2), T. britovi (T3), T. pseudospiralis (T4), T. murrelli (T5), T6, T. papuae (T10), and T. zimbabwensis (T11). The area under the curve values for the test data of the models ranged from 0.901 to 0.998, indicating that the models were very good to excellent. The most important bioclimatic factor in modeling the ranges for T. spiralis (T1), T. nativa (T2), T. britovi (T3), T6, and T. zimbabwensis (T11) was temperature, for T. pseudospiralis (T4) and T. papuae (T10) was precipitation, and for T. murrelli (T5) was land cover. T. spiralis (T1), T. britovi (T3), and T. pseudospiralis (T4) had the same primary land cover which was "Grass Crops". The primary land covers were "Conifer Boreal Forest" for T. nativa (T2), "Cool Fields and Woods" for T. murrelli (T5), "Upland Tundra" for T6, "Tropical Rainforest" for T. papuae (T10), and "Crops and Town" for T. zimbabwensis (T11). The scan statistic analyses revealed the presence of significant spatiotemporal clusters (p<0.05) for T. spiralis (T1), T. nativa (T2), T. britovi (T3), T. pseudospiralis (T4), T. murrelli (T5), T6, and T. nelsoni (T7). No significant clusters were found for T. papuae (T10) and T. zimbabwensis (T11).
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bioclimatic factors; Cluster; Land cover; Maxent program; Space–time scan statistic; Trichinella

Mesh:

Year:  2014        PMID: 24951834     DOI: 10.1016/j.meegid.2014.06.009

Source DB:  PubMed          Journal:  Infect Genet Evol        ISSN: 1567-1348            Impact factor:   3.342


  5 in total

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Authors:  Bin Tang; Mingyuan Liu; Libo Wang; Shenye Yu; Haining Shi; Pascal Boireau; Vasile Cozma; Xiuping Wu; Xiaolei Liu
Journal:  Parasit Vectors       Date:  2015-02-05       Impact factor: 3.876

2.  Lipid profile of Trichinella papuae muscle-stage larvae.

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Journal:  Sci Rep       Date:  2020-06-23       Impact factor: 4.379

3.  Trichinella britovi infection and muscle distribution in free-living martens (Martes spp.) from the Głęboki Bród Forest District, Poland.

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Journal:  Int J Parasitol Parasites Wildl       Date:  2020-06-17       Impact factor: 2.674

4.  Bioinformatic Prediction and Production of Four Recombinant Proteins from Different Developmental Stages of Trichinella spiralis and Testing of Their Diagnostic Sensitivity in Mice.

Authors:  Cheng-Cheng Zhai; Xiao-Lei Liu; Xue Bai; Ze-Jun Jia; Shao-Hong Chen; Li-Guang Tian; Lin Ai; Bin Tang; Ming-Yuan Liu; Xiu-Ping Wu; Jia-Xu Chen
Journal:  Iran J Parasitol       Date:  2021 Jan-Mar       Impact factor: 1.012

5.  Trichinella spiralis and T. britovi in North-Eastern Romania: A Six-Year Retrospective Multicentric Survey.

Authors:  Olimpia Iacob; Ciprian Chiruță; Mihai Mareș
Journal:  Vet Sci       Date:  2022-09-17
  5 in total

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