Evidence map›Paper›PMID 42753027›Full record

ArticleVeterinary research communications2026

Epidemiological investigation and molecular detection of coccidial infection in yaks in parts of Qinghai Province, China.

Zijuan Zhao, Tao Zhang, Ru Meng, Zhen Zhang, Dan Jia, Zhi Li, Yong Fu, Xiuying Shen, Hong Duo, Fuyun Chen and 7 more

Abstract read
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In one paragraph

Article in Veterinary research communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

17 authors.

Zijuan ZhaoThe Academy of Animal and Veterinary Sciences, Qinghai University, Xining, 810016, China.
Tao ZhangThe Academy of Animal and Veterinary Sciences, Qinghai University, Xining, 810016, China.
Ru MengQinghai Provincial Key Laboratory of Pathogen Diagnosis for Animal Disease and Green Technical Research for Prevention and Control, Xining, 810016, China.
Zhen ZhangQinghai Provincial Key Laboratory of Pathogen Diagnosis for Animal Disease and Green Technical Research for Prevention and Control, Xining, 810016, China.
Dan JiaThe Academy of Animal and Veterinary Sciences, Qinghai University, Xining, 810016, China.
Zhi LiThe Academy of Animal and Veterinary Sciences, Qinghai University, Xining, 810016, China.
Yong FuThe Academy of Animal and Veterinary Sciences, Qinghai University, Xining, 810016, China.
Xiuying ShenThe Academy of Animal and Veterinary Sciences, Qinghai University, Xining, 810016, China.
Hong DuoThe Academy of Animal and Veterinary Sciences, Qinghai University, Xining, 810016, China.
Fuyun ChenQinghai Provincial Key Laboratory of Pathogen Diagnosis for Animal Disease and Green Technical Research for Prevention and Control, Xining, 810016, China.
Cairang ZhouzaiQinghai Provincial Key Laboratory of Pathogen Diagnosis for Animal Disease and Green Technical Research for Prevention and Control, Xining, 810016, China.
Guangping LiQinghai Provincial Key Laboratory of Pathogen Diagnosis for Animal Disease and Green Technical Research for Prevention and Control, Xining, 810016, China.
Dan HuaQinghai Provincial Key Laboratory of Pathogen Diagnosis for Animal Disease and Green Technical Research for Prevention and Control, Xining, 810016, China.
Shenghua XueQinghai Provincial Key Laboratory of Pathogen Diagnosis for Animal Disease and Green Technical Research for Prevention and Control, Xining, 810016, China.
Haiyu ZhangQinghai Provincial Key Laboratory of Pathogen Diagnosis for Animal Disease and Green Technical Research for Prevention and Control, Xining, 810016, China.
Yingna JianThe Academy of Animal and Veterinary Sciences, Qinghai University, Xining, 810016, China. jianyingna1127@163.com.
Xueyong ZhangThe Academy of Animal and Veterinary Sciences, Qinghai University, Xining, 810016, China. zhang_xyong@163.com.

Funding

The Special Project for Transformation of Scientific and Technological Achievements under the Central Government-guided Local Science and Technology Development Fund of Qinghai Provincial Department of Science and Technology No. 2026-NK-Z47the Talent and Base Project of Xizang Science and Technology Department No. XZ202401JD0012
6 · The paper itself

Abstract

To inform coccidiosis control in Qinghai's yak regions, we examined Eimeria species composition and prevalence in grazing yaks, and assessed infection associations with season and mixed sheep grazing. Age-related data were unavailable due to unrecorded birth dates in pastoral systems. From September 2024 to April 2025, 559 fecal samples from yaks with suspected coccidiosis were collected across five counties: Tianjun, Haiyan, Gangcha, Maduo, and Gonghe. DNA extracted by fecal sedimentation was subjected to nested PCR of the 18S rRNA gene; positive amplicons were sequenced and identified by BLAST. Haplotype diversity was analyzed with DnaSP v6, networks constructed with PopArt, and a neighbor-joining tree built using Nosema portugal (AF033316) as an outgroup. The overall infection prevalence was 35.6% (199/559), with all counties affected and the highest rates in Maduo (53.2%), Gangcha (43.8%), and Haiyan (38.6%). Ten Eimeria species were identified, predominated by E. bovis (9.8%), E. ahsata (9.8%), and E. auburnensis (7.0%). E. bovis (20 haplotypes) had the dominant haplotype EmbH1 across all counties; E. ahsata and E. auburnensis (10 each) had EmsH3 and EmuH4 as dominant, respectively. Phylogenetic analysis placed all ten species in well-supported clades with reference sequences, with bovine-derived Eimeria clustering together, indicating host-parasite co-evolution. These findings reveal severe endemic status and high species and haplotype diversity. An integrated strategy comprising optimized feeding management, strategic anticoccidial treatment, and environmental sanitation is essential to reduce the epidemiological burden.

Indexed as

Cattle DiseasesCoccidiosisEimeriaAnimalsCattleChinaDNA, ProtozoanFecesHaplotypesPhylogenyPolymerase Chain ReactionPrevalenceRNA, Ribosomal, 18SDNA, ProtozoanRNA, Ribosomal, 18SCoccidiosisEimeriaEpidemiological InvestigationSpecies IdentificationYaks

Identifiers

PMID42753027

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Registered trials

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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.