Evidence map›Paper›PMID 25343501›Full record

ArticlePloS one2014

Prevalence and molecular characterization of Cryptosporidium in goats across four provincial level areas in China.

Rongsheng Mi, Xiaojuan Wang, Yan Huang, Peng Zhou, Yuxuan Liu, Yongjun Chen, Jun Chen, Wei Zhu, Zhaoguo Chen

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed.

  1. Article
  2. Article
  3. Molecular and Epidemiological Investigation ofPathogens (Basel, Switzerland) · 2025
    Article
  4. Article
  5. Article
  6. Prevalence ofVeterinary sciences · 2024
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  7. Article
  8. Investigation and genetic polymorphism analysis of rodents infected withFrontiers in cellular and infection microbiology · 2024
    Article
  9. Molecular Characterization ofAnimals : an open access journal from MDPI · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. SubtypingPathogens (Basel, Switzerland) · 2021
    Article
  14. Microorganisms · 2021
    Article
  15. Prevalence and Characterization ofFrontiers in cellular and infection microbiology · 2021
    Article
  16. Article
  17. Review
  18. Article
  19. Molecular characterization ofInternational journal for parasitology. Parasites and wildlife · 2019
    Article
  20. Molecular identification and phylogenetic analysis ofInternational journal for parasitology. Parasites and wildlife · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Rongsheng MiKey Laboratory of Animal Parasitology of Ministry of Agriculture, Animal-borne Food Safety Research Center of Chinese Academy of Agricultural Sciences, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai, China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, China.
Xiaojuan WangKey Laboratory of Animal Parasitology of Ministry of Agriculture, Animal-borne Food Safety Research Center of Chinese Academy of Agricultural Sciences, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai, China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, China.
Yan HuangKey Laboratory of Animal Parasitology of Ministry of Agriculture, Animal-borne Food Safety Research Center of Chinese Academy of Agricultural Sciences, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai, China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, China.
Peng ZhouKey Laboratory of Animal Parasitology of Ministry of Agriculture, Animal-borne Food Safety Research Center of Chinese Academy of Agricultural Sciences, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai, China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, China.
Yuxuan LiuKey Laboratory of Animal Parasitology of Ministry of Agriculture, Animal-borne Food Safety Research Center of Chinese Academy of Agricultural Sciences, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai, China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, China.
Yongjun ChenKey Laboratory of Animal Parasitology of Ministry of Agriculture, Animal-borne Food Safety Research Center of Chinese Academy of Agricultural Sciences, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai, China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, China.
Jun ChenLvxiang Town Agricultural Technology Extension Station of Jinshan District, Shanghai, China.
Wei ZhuTengzhou Animal Husbandry and Veterinary Technology Service Center, Tengzhou, China.
Zhaoguo ChenKey Laboratory of Animal Parasitology of Ministry of Agriculture, Animal-borne Food Safety Research Center of Chinese Academy of Agricultural Sciences, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai, China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study assessed the prevalence, species and subtypes of Cryptosporidium in goats from Guangdong Province, Hubei Province, Shandong Province, and Shanghai City of China. Six hundred and four fecal samples were collected from twelve goat farms, and the overall infection rate was 11.4% (69/604). Goats infected with Cryptosporidium were found in eleven farms across four provincial areas, and the infection rate ranged from 2.9% (1/35) to 25.0% (9/36). Three Cryptosporidium species were identified. Cryptosporidium xiaoi (45/69, 65.2%) was the dominant species, followed by C. parvum (14/69, 20.3%) and C. ubiquitum (10/69, 14.5%). The infection rate of Cryptosporidium spp. was varied with host age and goat kids were more susceptible to be infected than adult goats. Subtyping C. parvum and C. ubiquitum positive samples revealed C. parvum subtype IIdA19G1 and C. ubiquitum subtype XIIa were the most common subtypes. Other C. parvum subtypes were detected as well, such as IIaA14G2R1, IIaA15G1R1, IIaA15G2R1 and IIaA17G2R1. All of these subtypes have also been detected in humans, suggesting goats may be a potential source of zoonotic cryptosporidiosis. This was the first report of C. parvum subtypes IIaA14G2R1, IIaA15G1R1 and IIaA17G2R1 infecting in goats and the first molecular identification of C. parvum and its subtypes in Chinese goats.

Indexed as

AnimalsChinaCryptosporidiosisCryptosporidiumGoat DiseasesGoatsHumansPhylogenyPrevalence

Identifiers

PMID25343501
PMCPMC4208816

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.