Evidence map›Paper›PMID 38755395›Full record

ArticleScientific reports2024

Cryptosporidium spp. in large-scale sheep farms in China: prevalence and genetic diversity.

Qianming Zhao, Meng Qi, Bo Jing, Fuchun Jian, Pihong Gong, Chenyang Lu, Yaqun Yan, Zhiyang Pei, Changshen Ning

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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.

Qianming ZhaoCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, People's Republic of China.
Meng QiCollege of Animal Science and Technology, Tarim University, Alar, 843300, Xinjiang, People's Republic of China.
Bo JingCollege of Animal Science and Technology, Tarim University, Alar, 843300, Xinjiang, People's Republic of China.
Fuchun JianCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, People's Republic of China.
Pihong GongCollege of Animal Science and Technology, Tarim University, Alar, 843300, Xinjiang, People's Republic of China.
Chenyang LuCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, People's Republic of China.
Yaqun YanSchool of Life Science and Agronomy, ZhouKou Normal University, Zhoukou, 466001, Henan, People's Republic of China.
Zhiyang PeiCollege of Animal Science and Technology, Tarim University, Alar, 843300, Xinjiang, People's Republic of China.
Changshen NingCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, People's Republic of China. nnl1986@163.com.

Funding

Earmarked Fund for China Modern Agro-industry Technology Research System nycytx-38
6 · The paper itself

Abstract

Cryptosporidium spp. are significant zoonotic intestinal parasites that induce diarrhea and even death across most vertebrates, including humans. Previous studies showed that sheep are important hosts for Cryptosporidium and that its distribution in sheep is influenced by geography, feeding patterns, age, and season. Environmental factors also influence the transmission of Cryptosporidium. Molecular studies of Cryptosporidium in sheep have been conducted in only a few regions of China, and studies into the effect of sheep-housing environments on Cryptosporidium transmission are even rarer. To detect the prevalence of Cryptosporidium in large-scale sheep-housing farms, a total of 1241 fecal samples were collected from sheep, 727 environmental samples were taken from sheep housing, and 30 water samples were collected in six regions of China. To ascertain the existence of the parasite and identify the species of Cryptosporidium spp., we conducted nested PCR amplification of DNA extracted from all samples using the small-subunit (SSU) rRNA gene as a target. For a more in-depth analysis of Cryptosporidium spp. subtypes, C. xiaoi-and C. ubiquitum-positive samples underwent separate nested PCR amplification targeting the 60 kDa glycoprotein (gp60) gene. The amplification of the Cryptosporidium spp. SSU rRNA gene locus from the whole genomic DNA of all samples yielded a positive rate of 1.2% (20/1241) in fecal samples, 0.1% (1/727) in environmental samples, and no positive samples were found in water samples. The prevalence of Cryptosporidium spp. infection in large-scale housed sheep was 1.7%, which was higher than that in free-ranging sheep (0.0%). The highest prevalence of infection was found in weaning lambs (6.8%). Among the different seasons, the peaks were found in the fall and winter. The most prevalent species were C. xiaoi and C. ubiquitum, with the former accounting for the majority of infections. The distribution of C. xiaoi subtypes was diverse, with XXIIIc (n = 1), XXIIId (n = 2), XXIIIe (n = 2), and XXIIIl (n = 4) identified. In contrast, only one subtype, XIIa (n = 9), was found in C. ubiquitum. In this study, C. xiaoi and C. ubiquitum were found to be the predominant species, and Cryptosporidium was found to be present in the environment. These findings provide an important foundation for the comprehensive prevention and management of Cryptosporidium in intensively reared sheep. Furthermore, by elucidating the prevalence of Cryptosporidium in sheep and its potential role in environmental transmission, this study deepens our understanding of the intricate interactions between animal health, environmental contamination, and public health dynamics.

Indexed as

CryptosporidiosisCryptosporidiumFarmsFecesGenetic VariationSheep DiseasesAnimalsChinaPhylogenyPrevalenceSheepChinaCryptosporidium spp.EnvironmentalFecesLarge-scale sheep farmsMolecular epidemiologySheep

Identifiers

PMID38755395
PMCPMC11099184

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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.