An outcome-wide analysis of maternal air pollution exposure and adverse pregnancy outcomes in intrahepatic cholestasis of pregnancy - Xueqi Li; Xiuling Zhu; Daijuan Chen; Yajie Zhao; Xixi Deng; Yongchi Zhan; Bing Guo; Tingting Xu; Xiaodong Wang (Atmospheric Environment, 2025)

Analysis of population structure and genetic diversity of Camellia tachangensis in Guizhou based on SNP markers - Dejun Huang; Suzhen Niu; Dingchen Bai; Zhifei Zhao; Caiyun Li; Xiuling Deng; Yihan Wang (Molecular Biology Reports, 2024)
Background Camellia tachangensis F. C. Zhang is a five-compartment species in the ovary of tea group plants, which represents the original germline of early differentiation of some tea group plants. Methods and results In this study, we analyzed single-nucleotide polymorphisms (SNPs) at the genome level, constructed a phylogenetic tree, analyzed the genetic diversity, and further investigated the population structure of 100 C. tachangensis accessions using the genotyping-by-sequencing (GBS) method. A total of 91,959 high-quality SNPs were obtained. Population structure analysis showed that the 100 C. tachangensis accessions clustered into three groups: YQ-1 (Village Group), YQ-2 (Forest Group) and YQ-3 (Transition Group), which was further consistent with the results of phylogenetic analysis and principal component analyses (PCA). In addition, a comparative analysis of the genetic diversity among the three populations (Forest, Village, and Transition Groups) detected the highest genetic diversity in the Transition Group and the highest differentiation between Forest and Village Groups. Conclusions C. tachangensis plants growing in the forest had different genetic backgrounds from those growing in villages. This study provides a basis for the effective protection and utilization of C. tachangensis populations and lays a foundation for future C. tachangensis breeding.

Galectin-3-centered paracrine network mediates cardiac inflammation and fibrosis upon β-adrenergic insult - Guomin Hu; Jimin Wu; Huijun Gu; Xiangning Deng; Wenli Xu; Shan Feng; Shuaixing Wang; Yao Song; Zhengda Pang; Xiuling Deng; Aleksandr E. Vendrov; Nageswara R. Madamanchi; et al. (Science China Life Sciences, 2023)