Clinical and zebrafish studies of truncating SF3B2-variants in craniofacial microsomia - Dan Xia; Xiaofang Peng; Zihao Deng; Shuyun Deng; Zhanwen He; Jieming Zhang; Xiaoqin Xiao; Xi Sun; Xiao Qian; Xueyuan Zhang; Liyang Liang; Xiaojuan Li (Human Genetics, 2026)

Robust identification of known and unknown weeds with crop center localization based on Open-set object detection - Lamin L. Janneh; Leilei He; Bryan Gilbert Murengam; Xiaojuan Liu; Mbemba Hydara; Man Xia; Rui Li; Yanxin Zhang; Longsheng Fu (Precision Agriculture, 2026)

Inhibition of RBM25 preserves cardiac mitochondrial homeostasis and attenuates ischemic heart failure - Shu Liu; Hong Ding; Kejuan Li; Xiaowei Zhang (Journal of Molecular Histology, 2026)

Two Contributions to the Hypogeous Boletales of China: A Novel Rhizopogon Species and a New National Record of Turmalinea persicina - Jia Li; Chang Xu; Tai‐Jie Yu; Wen‐Hao Zhang; Xiu‐Juan Li; Yu‐Xian Gao; Yuan‐Tian Lu; Li‐Ping Tang (New Zealand Journal of Botany, 2026)
Hypogeous Boletales are ectomycorrhizal fungi with sequestered hymenophores; some species are ecologically valuable as edible mushrooms. Despite their ecological and economical importance, the diversity of this group in China remains poorly understood. In this study, we performed phylogenetic analyses based on four loci (ITS, LSU, TEF1‐α , and RPB2 ) and detailed morphological examinations of specimens belonging to Rhizopogon (Rhizopogonaceae) and Turmalinea (Boletaceae). We describe and illustrate R. sinoevadens , a new species from China, and report the first Chinese record of T. persicina , a species originally described from Japan. These discoveries underscore the previously underestimated diversity of hypogeous Boletales in China and provide a foundation for future taxonomic and ecological studies.

Identification of KL29 type acinetobacter baumannii phage of obolenskvirus subfamily and tail-associated depolymerase activity - Jinpan Wei; Tao Yu; Qiang Wang; Can Wang; Xuefeng Li; Guoping Lu; Lijuan Li; Aihui Xu; Lei Zhao (Archives of Virology, 2026)

The microalga Scenedesmus quadricauda mitigates 17α-ethynylestradiol toxicity via enhanced photosynthesis and antioxidant activity - Xiaomin Wu; Tan-Duc Nguyen; Shaolong Zhang; Qingshi Chen; Hanying Zhang; Wanying Zhu; Syed Shabi Ul Hassan Kazmi; Wenhua Liu; Xiaojuan Liu; Zhen Wang (Marine Pollution Bulletin, 2026)

Stage-specific transcriptomic analysis reveals progressive immune activation, imbalance and escape during rhabdovirus infection in golden pompano (Trachinotus anak) - Yucong Huang; Heng Sun; Haoyu Wang; Wenjie Zheng; Xiaojuan Li; Deqi Wu; Weicong Li; Haiqing Li; Jia Cai; Liqun Wang (Aquaculture, 2026)

Divergent responses of abundant and rare archaeal taxa to spatial heterogeneity in coastal sandy soils - Taotao Wei; Shuangtao Zhang; Xiaojuan Li; Binwei Wu; Qixin Lv; Tingting Duan; Hanzhou Li; Shi-Xiao Luo; Xin Qian (Applied Soil Ecology, 2025)

Factors influencing the global distribution of soil free-living nitrogen fixation in terrestrial ecosystems - Hongkai Liao; Chunli Zheng; Juan Li; Jian Long; Yaying Li; Huaiying Yao (Applied Soil Ecology, 2025)

Soil viruses regulate soil nutrient cycling through themselves and their effects on host functioning to impede the growth of continuously planted Casuarina equisetifolia - Yu-Hua Wang; Lei Hong; Yi Lin; Miao-En Qiu; Jian-Juan Li; Qing-Xu Zhang; Xiao-Li Jia; Yu-Lin Wang; Li-Yuan Wang; Yang-Xin Luo; Wen-Xiong Lin; Hai-Bin Wang; et al. (Applied Soil Ecology, 2025)

Effects of cropland abandonment succession on soil microorganism and multifunctionality in the arid zone of Northwest China - Yujie Zhou; Yiheng Zhang; Wanying Li; Juan Li; Zhijuan Li; Yangquanwei Zhong (Applied Soil Ecology, 2025)

Dynamics and resilience of earthworm fecal microbiomes under distinct feeding regimes - Ziyan Pan; Petr Heděnec; Qiang Lin; Lingjuan Li; Amirah Alias; Fang Deng; Jan Frouz (Applied Soil Ecology, 2025)

Spatial variations of the relationships between bacterial diversity and forest ecosystem multifunctionality in the Qinling Mountains, China - Manya Luo; Xia Jia; Yonghua Zhao; Xuan Ye; Kun Ren; Qi Mu; Shuaizhi Kang; Huanyuan Wang; Juan Li (Applied Soil Ecology, 2024)

Analysis of growth inhibition of continuously planted Casuarina equisetifolia in relation to characteristic soil microbial functions and nutrient cycling - Yu-Hua Wang; Lei Hong; Jian-Juan Li; Qing-Xu Zhang; Ai-Qi Wang; Shao-Xiong Lin; Ming-Yue Hu; Yi-Ling Chen; Wen-Xiong Lin; Hai-Bin Wang; Ze-Yan Wu (Applied Soil Ecology, 2024)

Deep learning for visual recognition and detection of aquatic animals: A review - Juan Li; Wenkai Xu; Limiao Deng; Ying Xiao; Zhongzhi Han; Haiyong Zheng (Reviews in Aquaculture, 2023)
The ocean is an important ecosystem, and aquatic animals play an important role in the biological world, especially in aquaculture. How to accurately and intelligently recognise and detect aquatic animals is one of the urgent problems in the field of underwater biological detection. The wide applications of artificial intelligence (AI), especially deep learning (DL), provide new opportunities and challenges for the efficient and intelligent exploration of aquatic animals. DL has been widely used in the visual recognition and detection of terrestrial animals, but it is in the early stages of use for aquatic animals due to the complexity of underwater environment and the difficulty of data acquisition. Here, this article reviews the current application status of DL for aquatic animals, potential challenges and future directions. The key advances of DL algorithms applied to the visual recognition and detection of aquatic animals are generalised, including datasets, algorithms and performance. The applications of DL are summarised in aquatic animals, including image detection, video detection, species classification, biomass estimation, behaviour analysis and food safety. Furthermore, the challenges are summed up and classified in the object recognition and detection domain for aquatic animals. Finally, further research direction is discussed and the conclusions are drawn. The key advances of DL in the recognition and detection of aquatic animals will help to further excavate and extend the application of DL in the field of marine biological exploration.