Publications by authors named "Lian-Qin Shi"
Parasit Vectors
March 2019
Article Synopsis
- - The study focused on the prevalence and genotypes of Giardia duodenalis in black-boned sheep and goats, native breeds from Yunnan Province, China, highlighting its public health impact and economic significance.
- - Fecal samples from 661 animals were analyzed, revealing a significantly higher infection rate in sheep (21.8%) compared to goats (4.8%), with variations noted across different counties and age groups.
- - Both zoonotic and animal-specific assemblages of G. duodenalis were identified, with assemblage E being the most common; a total of 16 multilocus genotypes were discovered, emphasizing the diversity of the infection in these breeds.
Infect Genet Evol
November 2018
Article Synopsis
- Enterocytozoon bieneusi is a widespread pathogen in sheep and goats that poses risks to livestock development and public health, but limited research exists on native breeds in China.
- In a study in Yunnan province, 70 out of 661 fecal specimens (about 10.59%) tested positive for the pathogen in both black-boned sheep and goats, with no significant prevalence difference between the two species.
- Twelve genotypes of E. bieneusi were identified, including ten known variants and two new ones, with phylogenetic analysis showing some of these genotypes are zoonotic, indicating potential transmission to humans and the need for better infection management strategies among local livestock.
Article Synopsis
- Microsporidiosis is a significant zoonotic disease that can cause severe diarrhea, but there is a lack of data on the prevalence of Enterocytozoon bieneusi in Asiatic black bears in southwestern China.
- A study found that the overall prevalence of E. bieneusi among these bears was 19.75%, with the highest rate (33.33%) found in Xishuangbanna.
- The research identified four known genotypes and 13 novel genotypes of the parasite, highlighting the potential zoonotic risks associated with E. bieneusi in this region and providing essential data for future prevention and control efforts.
