Corrigendum to “Chemometrics- and AI-driven optical techniques for rapid detection of cereal grain toxins: an up-to-date comprehensive review (2020–present)” [Food Control 190 (2026) 112364] - Mengchao Lv; Qi Zhang; Hong-Ju He; Yuling Wang; Xingqi Ou (Food Control, 2026)

Chemometrics- and AI-driven optical techniques for rapid detection of cereal grain toxins: an up-to-date comprehensive review (2020–present) - Mengchao Lv; Qi Zhang; Hong-Ju He; Yuling Wang; Xingqi Ou (Food Control, 2026)

Three-dimensional thermal management: Biomass aerogel with super-hydrophilicity for high-efficiency solar evaporation via environmental energy synergy - Li Jiang; Yanyou Huang; Liangdong Ye; Yuling Lv; Ruibin Shen; Wei Wang; Yanlan Pan; Zuocai Zhang; Shaorong Lu (Desalination, 2026)

Synthetic microbial community shields wheat from cadmium: Coordinating host metabolic reprogramming and rhizosphere microenvironment regulation - Huangxin Chen; Lin Kong; Yaoyuan Zhang; Guiyin Wang; Xin Qi; Changlian Xu; Zhanbiao Yang; Zhang Cheng; Guochun Lv; Junzhuo Cai; Lilin Wang; Yongxia Jia; et al. (Journal of Hazardous Materials, 2026)

Sustainable and multifunctional organohydrogel integrating high strength, environmental resilience, and humidity sensitivity for smart healthcare monitoring - Ruibing Shen; Yanyou Huang; Li Jiang; Yuling Lv; Zuocai Zhang; Liangdong Ye; Ziwei Li; Shaorong Lu (Chemical Engineering Journal, 2026)

Stretchable multifunctional composite films with ultra-high conductivity for sustainable heating, EMI shielding, and antimicrobial applications - Yuling Lv; Yanyou Huang; Liangdong Ye; Ruibing Shen; Li Jiang; Wei Wang; Shaorong Lu (Chemical Engineering Journal, 2026)

Biomass organohydrogel toward green wearable sensors: Enhancing high and low temperature sensing properties, UV shielding properties, and long-term cycling durability - Ruibing Shen; Qiaoyan Wei; Liangdong Ye; Liling Zhang; Yanyou Huang; Yuling Lv; Ziwei Li; Zuocai Zhang; Xiaokun Han; Shaorong Lu (Chemical Engineering Journal, 2026)

Identification and driving factor analysis of land use spatial conflicts in ecologically fragile plateau areas - Yong Lv; Lina Xiu; Yuling Xue (Modeling Earth Systems and Environment, 2025)

EGF/ERBB2 blocks the endoplasmic reticulum-associated degradation to facilitate chronic obstructive pulmonary disease development by decreasing FAM8A1 via up-regulating DNMT3A - Ruonan Lv; Jing Wang; Mingrui Wan; Yuling Wang; Yanan Zhang (Functional & Integrative Genomics, 2025)

Analysis of metabolic characteristics of highly resistant grass carp bred on the basis of constitutive expression level of innate immune molecules - Yuling Wei; Bin Li; Zhe Long; Zongjun Du; Zhao Lv; Tiaoyi Xiao (Fish & Shellfish Immunology, 2025)

Molecular Characterization and Antiviral Function Against GCRV of Complement Factor D in Barbel Chub (Squaliobarbus curriculus) - Yu Xiao; Zhao Lv; Yuling Wei; Mengyuan Zhang; Hong Yang; Chao Huang; Tiaoyi Xiao; Yilin Li (Fishes, 2025)
The barbel chub (Squaliobarbus curriculus) exhibits remarkable resistance to grass carp reovirus (GCRV), a devastating pathogen in aquaculture. To reveal the molecular basis of this resistance, we investigated complement factor D (DF)—a rate-limiting serine protease governing alternative complement pathway activation. Molecular cloning revealed that the barbel chub DF (ScDF) gene encodes a 1251-bp cDNA sequence translating into a 250-amino acid protein. Crucially, bioinformatic characterization identified a unique N-glycosylation site at Asn139 in ScDF, representing a structural divergence absent in grass carp (Ctenopharyngodon idella) DF (CiDF). While retaining a conserved Tryp_SPc domain harboring the catalytic triad (His61, Asp109, and Ser204) and substrate-binding residues (Asp198, Ser219, and Gly221), sequence and phylogenetic analyses confirmed ScDF’s evolutionary conservation, displaying 94.4% amino acid identity with CiDF and clustering within the Cyprinidae. Expression profiling revealed constitutive ScDF dominance in the liver, and secondary prominence was observed in the heart. Upon GCRV challenge in S. curriculus kidney (SCK) cells, ScDF transcription surged to a 438-fold increase versus uninfected controls at 6 h post-infection (hpi; p

The structural characteristics and expression characteristics of C1S in response to GCRV infection in grass carp - Yuling Wei; Zhao Lv; Zongjun Du; Tiaoyi Xiao (Fish & Shellfish Immunology, 2025)

Winter Fallow Weeds as a Potential Organic Fertilizer Source for Improving Grain Yield in Rice - Min Huang; Ge Chen; Yuling Kang; Zhengwu Xiao; Wenjie Lv; Fangbo Cao; Jiana Chen (Journal of Soil Science and Plant Nutrition, 2025)

The role of MASP1 in the complement system and expression characteristics in response to GCRV infection in grass carp - Yuling Wei; Zhao Lv; Tiaoyi Xiao; Zongjun Du (Fish & Shellfish Immunology, 2024)

Expert Consensus on Big Data Collection of Skin and Appendage Disease Phenotypes in Chinese - Shuang Zhao; Zhongling Luo; Ying Wang; Xinghua Gao; Juan Tao; Yong Cui; Aijun Chen; Daxing Cai; Yan Ding; Heng Gu; Jianying Gu; Chao Ji; et al. (Phenomics, 2024)

Assessing and predicting indoor environmental quality in 13 naturally ventilated urban residential dwellings - Huimin Yao; Xiong Shen; Wentao Wu; Yuling Lv; V. Vishnupriya; Hong Zhang; Zhengwei Long (Building and Environment, 2024)

Experimental study of building natural ventilation with pendulum velocity anemometer - Yuling Lv; Min Wang; Wentao Wu; Wenzhe Shang; Huimin Yao; Jianwei Li; Gerald DS. Quoie Jr; Hong Zhang; Xiong Shen (Building and Environment, 2024)

Structural comparison and expression function analysis of BF/C2 in Ctenopharyngodon idella and Squaliobarbus curriculus - Yuling Wei; Zhao Lv; Qiaolin Liu; Jianbo Yu; Yu Xiao; Zongjun Du; Tiaoyi Xiao (Fish & Shellfish Immunology, 2023)

Boron doping g-C3N4 supported Cu2O for photocatalytic reforming of xylose into lactic acid - Yanting Lv; Weiyong Shao; Yuling Kong; Nanhua Li; Xinrui Huang; Zhihao Tang; Murong Gong; Lizi Li; Weiqi Wei (Journal of Environmental Chemical Engineering, 2023)

The effect of vacancy defective Mg (0001) surface on hydrogenation of Ni-Mg-CNTs: A mechanistic investigation - Congwen Duan; Mengmeng Wu; Xinya Wang; Dong Fu; Yuling Zhang; Wei Lv; Lianxi Hu; Ming Li; Fei Wang; Ying Wu (Fuel, 2023)

Ameliorative effect of calcium poly(aspartic acid) (PASP-Ca) and calcium poly-γ-glutamic acid (γ-PGA-Ca) on soil acidity in different horizons - Fei Kang; Qilin Lv; Jingbiao Fan; Yun Zhang; Yuling Song; Xueqin Ren; Shuwen Hu (Environmental Science and Pollution Research, 2023)

Immobilizing arsenic in soil via amine metal complex: a case study using iron-ethylenediamine - Qilin Lv; Tairan Zhou; Tianhao Wang; Shuhan Wang; Yanning Ge; Yuling Song; Xueqin Ren; Shuwen Hu (Environmental Science and Pollution Research, 2023)

Interaction mechanism between zein and β-lactoglobulin: Insights from multi-spectroscopy and molecular dynamics simulation methods - Chengzhi Liu; Nan Lv; Yuling Song; Lijuan Dong; Min Huang; Qing Shen; Gerui Ren; Ruibo Wu; Binju Wang; Zexing Cao; Hujun Xie (Food Hydrocolloids, 2023)

Assimilation Research of Wind Stress Drag Coefficient Based on the Linear Expression - Junli Xu; Yuling Nie; Kai Ma; Wenqi Shi; Xianqing Lv (Journal of Marine Science and Engineering, 2021)
The wind stress drag coefficient plays an important role in storm surge models. This study reveals the influences of wind stress drag coefficients, which are given in form of formulas and inverted by the data assimilation method, on the storm surge levels in the Bohai Sea, Yellow Sea, and East China Sea during Typhoon 7008. In the process of data assimilation, the drag coefficient is based on the linear expression Cd = (a + b × U10) × 10−3 (generally speaking, a and b are empirical parameters determined by observed data). The results showed that the performance of the data assimilation method was far superior to those of drag coefficient formulas. Additionally, the simulated storm surge levels obviously changed in the neighborhood of typhoon eye. Furthermore, the effect of initial values of a and b in the Cd expression on the storm surge levels was also investigated when employing the data assimilation method. The results indicated that the simulation of storm surge level was the closest to the observation when a and b were simultaneously equal to zero, whereas the simulations had slight differences when the initial values of a and b were separately equal to the drag coefficients from the work of Smith, Wu, and Geernaert et al.. Therefore, we should choose appropriate initial values for a and b by using the data assimilation method. As a whole, the data assimilation method is much better than drag coefficient parameterization formulas in the simulation of storm surges.

Abnormal Brain Structure and Function in First-Episode Childhood- and Adolescence-Onset Schizophrenia: Association with Clinical Symptoms - Yanhong Xia; Dan Lv; Yinghui Liang; Haisan Zhang; Keyang Pei; Rongrong Shao; Yali Li; Yan Zhang; Yuling Li; Jinghua Guo; Luxian Lv; Suqin Guo (Neuroscience Bulletin, 2019)

Remediation of Cr(VI)-Contaminated Soil Using the Acidified Hydrazine Hydrate - Yameng Ma; Fangfang Li; Yuling Jiang; Weihua Yang; Lv Lv; Haotian Xue; Yangyang Wang (Bulletin of Environmental Contamination and Toxicology, 2016)