Regulated cell death (RCD) in hemocytes: Adaptive mechanisms to BDE-47 stress in marine mussel (Mytilus edulis) - Yingying Yang; Zhen Che; Qian Liu; Mengxue Xu; Yongshun Jiang; Xiaocheng Wang; You Wang; Zhongyuan Zhou (Marine Environmental Research, 2026)

Precision measurement of the Ds*+-Ds+ meson mass difference - M. Ablikim; M.N. Achasov; P. Adlarson; X.C. Ai; R. Aliberti; A. Amoroso; Q. An; Y. Bai; O. Bakina; Y. Ban; H.-R. Bao; V. Batozskaya; et al. (Science Bulletin, 2026)

Polystyrene microplastics disrupt the blood-testis barrier via CEBPB-driven lysosomal autophagy and induce ferroptosis-like injury in human sperm, compromising embryo development - Man Wu; Lei Li; Tianxin Zhao; Yuling Mao; Jiajing Lin; Xiaomin Li; Yanling Bai; Feixue Han; Shuyan Chen; Tianwen Peng; Chen Liao; Xin Ye; et al. (Journal of Hazardous Materials, 2026)

Multiscale magnetic-dielectric coupling in nano-micro-macro Fe/Fe3O4@C aerogels via confinement strategy for broadband electromagnetic wave absorption - Xianlin Zhan; Mengqiu Huang; Bicheng Li; Ge Ma; Wenbin You; Yun Tang; Lei Wang; Renchao Che (Chemical Engineering Journal, 2026)

Maternal effects enhance offspring performance in the marine rotifer Brachionus plicatilis after exposure to BDE-47 and its photodegradation product BDE-28 - Na Lu; Chunchen Liu; Keyu Lu; Zhen Che; Boyuan Wang; You Wang; Yingying Yang (Journal of Oceanology and Limnology, 2026)

Built-in electric field constructed by asymmetric electron cloud distribution for facilitating photocatalytic H2O2 production in covalent organic frameworks - Chuanxue You; Yue Zhou; Meiting Yang; Jingyang Li; Bo Hu; Yunchao Ma; Linlin Liu; Chunbo Liu; Guangbo Che (Journal of Environmental Chemical Engineering, 2026)

Synergistic coupling in magnetic-dielectric heterojunction aerogel via local selenization strategy with wide-frequency electromagnetic wave dissipation - Jinbo Ming; Lei Wang; Mengqiu Huang; Wenbin You; Zhengchen Wu; Fengyun Wang; Renchao Che (Chemical Engineering Journal, 2026)

Rational engineering of ketoreductase SsSDR1 for stereoselectivity inversion toward 3-N-substituted azacyclic ketones - Xiao Qiu; Changli Che; Lichun Tang; Bin Qin; Wenhe Zhang; Xian Jia; Song You (Bioresource Technology, 2026)

Experimental study of airbag off-wall tunnels model under strike-slip fault dislocation - Qiang Hui; Feng Gao; Xukai Tan; Xiaolong Che; Zhaoyang Xiong; Dongmei You (Tunnelling and Underground Space Technology, 2026)

High-density magnetic-carbon interfaces in NiCu@C heterojunction toward broadband electromagnetic wave absorption - Zhikai Yan; Mengqiu Huang; Longjun Rao; Wenbin You; Biao Zhao; Lei Wang; Limin Wu; Ruixuan Zhang; Wei Li; Renchao Che (Chemical Engineering Journal, 2025)

Sources and light absorption of brown carbon in urban areas of the Sichuan Basin, China: Contribution from biomass burning and secondary formation - Chao Peng; Mi Tian; Guangming Shi; Shumin Zhang; Xin Long; Hanxiong Che; Jie Zhong; Xiangyu You; Zhier Bao; Fumo Yang; Xin Qi; Chongzhi Zhai; et al. (Atmospheric Research, 2025)

Extracellular vesicles derived from bone marrow mesenchymal stem cells ameliorate liver fibrosis via micro-7045-5p - Zhejun Liu; Xiaodan Jiang; Hongjie You; Zuoqing Tang; Yun Ma; Niancong Che; Wenlan Liu; Chongyang Ma (Molecular and Cellular Biochemistry, 2025)

Multifunctional integrated polyphenol-copper nanozymes for sepsis-induced acute liver injury via ameliorating endoplasmic reticulum stress and reprogramming inflammatory microenvironment - Dandan Che; Yao Xiao; Xiaoyong Zhang; Kai Zhu; Wanyi Chen; Guoxing You; Yongming Yao; Hong Zhou; Gan Chen (Chemical Engineering Journal, 2025)

Measurement of the decay Ξ 0 → Λ γ with entangled Ξ 0 Ξ ¯ 0 pairs - M. Ablikim; M.N. Achasov; P. Adlarson; O. Afedulidis; X.C. Ai; R. Aliberti; A. Amoroso; Q. An; Y. Bai; O. Bakina; I. Balossino; Y. Ban; et al. (Science Bulletin, 2025)

Anthropogenic drought monitoring using socio-hydrological modeling for surface water deficit: Lessons from Northern Taiwan - Che-You Liu; Pin-Yi Huang; Shao-Yiu Hsu; Ching-Pin Tung; Kuo-Wei Liao (Journal of Hydrology, 2025)

Extracellular vesicles derived from bone marrow mesenchymal stem cells ameliorate chronic liver damage via microRNA-136-5p - Xiaodan Jiang; Zhejun Liu; Hongjie You; Zuoqing Tang; Yun Ma; Ruifang Nie; Zheng Yang; Niancong Che; Wenlan Liu (Molecular and Cellular Biochemistry, 2025)

Situation Awareness-Based Safety Assessment Method for Human–Autonomy Interaction Process Considering Anchoring and Omission Biases - Shengkui Zeng; Qidong You; Jianbin Guo; Haiyang Che (Journal of Marine Science and Engineering, 2025)
Autonomy is being increasingly used in domains like maritime, aviation, medical, and civil domains. Nevertheless, at the current autonomy level, human takeover in the human–autonomy interaction process (HAIP) is still critical for safety. Whether humans take over relies on situation awareness (SA) about the correctness of autonomy decisions, which is distorted by human anchoring and omission bias. Specifically, (i) anchoring bias (tendency to confirm prior opinion) causes the imperception of key information and miscomprehending correctness of autonomy decisions; (ii) omission bias (inaction tendency) causes the overestimation of predicted loss caused by takeover. This paper proposes a novel HAIP safety assessment method considering effects of the above biases. First, an SA-based takeover decision model (SAB-TDM) is proposed. In SAB-TDM, SA perception and comprehension affected by anchoring bias are quantified with the Adaptive Control of Thought-Rational (ACT-R) theory and Anchoring Adjustment Model (AAM); behavioral utility prediction affected by omission bias is quantified with Prospect Theory. Second, guided by SAB-TDM, a dynamic Bayesian network is used to assess HAIP safety. A case study on autonomous ship collision avoidance verifies effectiveness of the method. Results show that the above biases mutually contribute to seriously threaten HAIP safety.

Performance of Convolutional Neural Network Models in Meningioma Segmentation in Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis - Ting-Wei Wang; Jia-Sheng Hong; Wei-Kai Lee; Yi-Hui Lin; Huai-Che Yang; Cheng-Chia Lee; Hung-Chieh Chen; Hsiu-Mei Wu; Weir Chiang You; Yu-Te Wu (Neuroinformatics, 2024)
Background Meningioma, the most common primary brain tumor, presents significant challenges in MRI-based diagnosis and treatment planning due to its diverse manifestations. Convolutional Neural Networks (CNNs) have shown promise in improving the accuracy and efficiency of meningioma segmentation from MRI scans. This systematic review and meta-analysis assess the effectiveness of CNN models in segmenting meningioma using MRI. Methods Following the PRISMA guidelines, we searched PubMed, Embase, and Web of Science from their inception to December 20, 2023, to identify studies that used CNN models for meningioma segmentation in MRI. Methodological quality of the included studies was assessed using the CLAIM and QUADAS-2 tools. The primary variable was segmentation accuracy, which was evaluated using the Sørensen–Dice coefficient. Meta-analysis, subgroup analysis, and meta-regression were performed to investigate the effects of MRI sequence, CNN architecture, and training dataset size on model performance. Results Nine studies, comprising 4,828 patients, were included in the analysis. The pooled Dice score across all studies was 89% (95% CI: 87–90%). Internal validation studies yielded a pooled Dice score of 88% (95% CI: 85–91%), while external validation studies reported a pooled Dice score of 89% (95% CI: 88–90%). Models trained on multiple MRI sequences consistently outperformed those trained on single sequences. Meta-regression indicated that training dataset size did not significantly influence segmentation accuracy. Conclusion CNN models are highly effective for meningioma segmentation in MRI, particularly during the use of diverse datasets from multiple MRI sequences. This finding highlights the importance of data quality and imaging sequence selection in the development of CNN models. Standardization of MRI data acquisition and preprocessing may improve the performance of CNN models, thereby facilitating their clinical adoption for the optimal diagnosis and treatment of meningioma.

Standardization in global environmental antibiotic resistance genes (ARGs) surveillance - Xuemei Mao; Xiaole Yin; Yu Yang; You Che; Xiaoqing Xu; Yu Deng; Liguan Li; Tong Zhang (Critical Reviews in Environmental Science and Technology, 2024)

Long-term addition of organic manure stimulates the growth and activity of comammox in a subtropical Inceptisol - Yu Zeng; Che Tan; Lei Zhang; Lelin You; Wanning Zheng; Hao Chen; Hongyun Peng; Chunyan Wu; Yongchao Liang (Science of The Total Environment, 2024)

Silicate melt immiscibility as the cause of large-scale rare-metal mineralization in a peralkaline granite system: The case of the Baerzhe deposit in NE China - Hui-Min Su; Shao-Yong Jiang; Tao Jin; Yu-Ying Che; Xin-You Zhu (Lithos, 2024)

Toxicity evaluation of silica nanoparticles for delivery applications - Yue Tan; Dawei Yu; Jiayao Feng; Huimin You; Yan Bai; Jincan He; Hua Cao; Qishi Che; Jiao Guo; Zhengquan Su (Drug Delivery and Translational Research, 2023)

Challenges and engineering application of landfill leachate concentrate treatment - Qian Li; Hanlin Cui; Yihao Li; Xin Song; Wenzong Liu; Yongxuan Wang; Haimeng Hou; Hongbo Zhang; You Li; Fan Wang; Jun Song; Hanfeng Ye; et al. (Environmental Research, 2023)

Impact of commercial cooking on urban PM2.5 and O3 with online data-assisted emission inventory - Yingzhi Yuan; Yun Zhu; Che-Jen Lin; Shuxiao Wang; Yanghong Xie; Haixian Li; Jia Xing; Bin Zhao; Mengmeng Zhang; Zhiqiang You (Science of The Total Environment, 2023)

Thiophanate-methyl induces notochord toxicity by activating the PI3K-mTOR pathway in zebrafish (Danio rerio) embryos - Xiaofang Che; Yong Huang; Keyuan Zhong; Kun Jia; You Wei; Yunlong Meng; Wei Yuan; Huiqiang Lu (Environmental Pollution, 2023)

Oxygen vacancies endow atomic cobalt-palladium oxide clusters with outstanding oxygen reduction reaction activity - Thomas Yang; Dinesh Bhalothia; Hong-Wei Chang; Che Yan; Amisha Beniwal; You-Xun Chang; Shun-Chi Wu; Po-Chun Chen; Kuan-Wen Wang; Sheng Dai; Tsan-Yao Chen (Chemical Engineering Journal, 2023)

Detection of Vestibular Schwannoma on Triple-parametric Magnetic Resonance Images Using Convolutional Neural Networks - Tzu-Hsuan Huang; Wei-Kai Lee; Chih-Chun Wu; Cheng-Chia Lee; Chia-Feng Lu; Huai-Che Yang; Chun-Yi Lin; Wen-Yuh Chung; Po-Shan Wang; Yen-Ling Chen; Hsiu-Mei Wu; Wan-You Guo; et al. (Journal of Medical and Biological Engineering, 2021)
Purpose The first step in typical treatment of vestibular schwannoma (VS) is to localize the tumor region, which is time-consuming and subjective because it relies on repeatedly reviewing different parametric magnetic resonance (MR) images. A reliable, automatic VS detection method can streamline the process. Methods A convolutional neural network architecture, namely YOLO-v2 with a residual network as a backbone, was used to detect VS tumors from MR images. To heighten performance, T1-weighted–contrast-enhanced, T2-weighted, and T1-weighted images were combined into triple-channel images for feature learning. The triple-channel images were cropped into three sizes to serve as input images of YOLO-v2. The VS detection effectiveness levels were evaluated for two backbone residual networks that downsampled the inputs by 16 and 32. Results The results demonstrated the VS detection capability of YOLO-v2 with a residual network as a backbone model. The average precision was 0.7953 for a model with 416 × 416-pixel input images and 16 instances of downsampling, when both the thresholds of confidence score and intersection-over-union were set to 0.5. In addition, under an appropriate threshold of confidence score, a high average precision, namely 0.8171, was attained by using a model with 448 × 448-pixel input images and 16 instances of downsampling. Conclusion We demonstrated successful VS tumor detection by using a YOLO-v2 with a residual network as a backbone model on resized triple-parametric MR images. The results indicated the influence of image size, downsampling strategy, and confidence score threshold on VS tumor detection.

Biological Protective Effects Against Vibrio Infections in Grouper Larvae Using the Strombidium sp. NTOU1, a Marine Ciliate Amenable for Scaled-Up Culture and With an Excellent Bacteriovorous Ability - Hung-Yun Lin; Wei-Yu Yeh; Sheng-Fang Tsai; Kuo-Ping Chiang; John Han-You Lin; Che-Chia Tsao; Han-Jia Lin (Frontiers in Marine Science, 2020)

Geological significance of the former Xiong’er Volcanic Belt on the southwestern margin of the North China Craton - Guanxu Chen; Jinhai Luo; Huan Xu; Jia You; Yifei Li; Zichen Che (Frontiers of Earth Science, 2019)

Transgenic silkworms secrete the recombinant glycosylated MRJP1 protein of Chinese honeybee, Apis cerana cerana - Zhengying You; Qiujie Qian; Yiran Wang; Jiaqian Che; Lupeng Ye; Lirong Shen; Boxiong Zhong (Transgenic Research, 2017)

Engineering Pseudomonas putida KT2440 for simultaneous degradation of organophosphates and pyrethroids and its application in bioremediation of soil - Zhenqiang Zuo; Ting Gong; You Che; Ruihua Liu; Ping Xu; Hong Jiang; Chuanling Qiao; Cunjiang Song; Chao Yang (Biodegradation, 2015)

A measurement of summertime dry deposition of ambient air particulates and associated metallic pollutants in Central Taiwan - Guor-Cheng Fang; Hung-Che Chiang; Yu-Cheng Chen; You-Fu Xiao; Chia-Ming Wu; Yu-Chen Kuo (Environmental Geochemistry and Health, 2015)

Construction of a Tn5-Tagged Mutant Library of Xanthomonas oryzae pv. oryzicola as An Invaluable Resource for Functional Genomics - Hua-Song Zou; Liang Yuan; Wei Guo; Yu-Rong Li; Yi-Zhou Che; Li-Fang Zou; Gong-You Chen (Current Microbiology, 2011)