Evidence map›Paper›PMID 24433398›Full record

ArticleBMC veterinary research2014

Occurrence and molecular characterization of Cryptosporidium in dogs in Henan Province, China.

Fuchun Jian, Meng Qi, Xiaoyi He, Rongjun Wang, Sumei Zhang, Heping Dong, Longxian Zhang

Open access · goldAbstract read
In one paragraph

Article in BMC veterinary research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.5field-weighted citation impact, top 21% of its field
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

18 citing papers in PubMed, 32 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Fuchun Jian
Meng Qi
Xiaoyi He
Rongjun Wang
Sumei Zhang
Heping Dong
Longxian ZhangCollege of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou 450002, P R, China. zhanglx8999@gmail.com.
Henan Agricultural University · CNZhengzhou University · CNCentral South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCryptosporidiosis in dogs has been reported worldwide, involving both asymptomatic and diarrheic dogs. Large-scale surveys of Cryptosporidium infection in dogs have been performed in some countries using different diagnostic methods. But, few data are available on the infection rate and molecular characteristics of Cryptosporidium spp. in dogs in China.

resultIn this study, 770 fecal samples from 66 locations in Henan Province were examined. The average Cryptosporidium infection rate was 3.8%, with dogs in kennels having the highest rate of 7.0% (χ² = 14.82, P < 0.01). The infection rate was 8.0% in dogs younger than 90 days, which was significantly higher than that in the other age groups (1.1-3.8%;χ² = 18.82, P < 0.01). No association was noted between the infection rate and the sex of the dogs. Twenty-nine Cryptosporidium-positive samples were amplified at the small subunit rRNA (SSU rRNA), 70-kDa heat shock protein (HSP70), and actin loci using PCR. Sequence analysis of these amplicons identified only Cryptosporidium canis, which showed 100% identity with the published sequences of the SSU rRNA, HSP70, and actin genes.

conclusionsOur results confirm that C. canis is popular in the dog population in China, considering the large number of dogs in China and the close contact between dogs and humans, the role of C. canis in the transmission of human cryptosporidiosis warrants attention.

Indexed as

AnimalsChinaCryptosporidiosisCryptosporidiumDog DiseasesDogsFeces

Identifiers

PMID24433398
PMCPMC3896686
OpenAlexW2064607597

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.