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Urban organic manure application enhances antibiotic resistance gene diversity and potential human pathogen abundance in invasive giant African snails

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Journal of Environmental sciences 2025年

作者： Zhonghui Tang Yiyue Zhang Huanyuan Shangguan An Xie Xueli Xu Yong Jiang Martin F. Breed Xin Sun Key Laboratory of Urban Environment and Health Ningbo Observation and Research Station Fujian Key Laboratory of Watershed Ecology Institute of Urban Environment Chinese Academy of Sciences Xiamen 361021 China School of Life Sciences Hebei University Baoding 071000 China Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control CAS Haixi Industrial Technology Innovation Center in Beilun Ningbo 315830 China University of the Chinese Academy of Sciences Beijing 100049 China College of Science and Engineering Flinders University Bedford Park South Australia 5042 Australia

The giant African snail ( Achatina fulica ) is an invasive species served as potential vectors for antibiotic resistance genes (ARGs) and potential human bacterial pathogens. Currently, urban green spaces receive extensive organic manure additions as part of their management, may intensify the biological contamination potential of these snail vectors, thereby increasing the risk of biological pollution in green spaces. However, the specific impacts of this practice on the microbial ecology of these invasive species remain poorly understood. Here, we investigated the effects of organic manure application on the gut microbiome of giant African snails, focusing on ARGs, bacterial community structure, and potential human bacterial pathogens. Microcosm experiments compared snail gut microbiomes in different treatments (Soil: soil samples collected after manure amendment, before any snail exposure. Feces: fecal samples collected from snails that lived on manure-amended soil. Control: fecal samples collected from snails that lived on unamended soil) using 16S rRNA high-throughput sequencing and metagenomic analysis. Our results show that manure application significantly altered gut bacterial community structure and increased ARG diversity by enriching specific high-risk ARGs (such as sul1 and sul2 in the Feces group increased by 2.89 and 2.43 times, respectively, compared to the Control group), and the introduction of eight novel ARG subtypes, despite decreasing overall ARG abundance. Moreover, the relative abundance of potential human pathogens, particularly Pseudomonadaceae, was greatly increased by manure application. These findings reveal that organic manure application in urban green spaces can potentially enhances their role as reservoirs and vectors of ARGs and human pathogens.

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Quasinormal-modes of the Kerr-Newman black hole: GW150914 and fundamental physics implications

arXiv

引用

arXiv 2021年

作者： Wang, Hai-Tian Tang, Shao-Peng Li, Peng-Cheng Fan, Yi-Zhong Purple Mountain Observatory Chinese Academy of Sciences Nanjing210023 China School of Astronomy and Space Science University of Science and Technology of China Anhui Hefei230026 China Zhuhai519082 China Center for High Energy Physics Peking University No.5 Yiheyuan Rd Beijing100871 China Department of Physics State Key Laboratory of Nuclear Physics and Technology Peking University No.5 Yiheyuan Rd Beijing100871 China School of Physics and Optoelectronics South China University of Technology Guangzhou510641 China

We develop an analytical ringdown waveform model, including both the fundamental and the overtone quasinormal modes, for charged black holes and show that it is precise enough to analyze current gravitational wave data. Applying this waveform model to GW150914, the charge to mass ratio of the remnant black hole (λf) has been constrained with the sole ringdown gravitational wave data for the first time and the 90% upper limit is λf ≤ 0.38. Correspondingly, the deviation parameter of the scalar-tensor vector gravity (αs) is limited to be αs ≤ 0.17. Our approach can be directly applied to other binary black hole mergers with loud ringdown radiation. Copyright © 2021, The Authors. All rights reserved.

关键词： Waveform analysis

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OpenClinicalAI: enabling AI to diagnose diseases in real-world clinical settings

arXiv

引用

arXiv 2021年

作者： Huang, Yunyou Wang, Nana Tang, Suqin Ma, Li Hao, Tianshu Jiang, Zihan Zhang, Fan Kang, Guoxin Miao, Xiuxia Guan, Xianglong Zhang, Ruchang Zhang, Zhifei Zhan, Jianfeng Guangxi Key Lab of Multi-Source Information Mining & Security School of Computer Science and Engineering School of Software Guangxi Normal University Guilin China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China Guilin Medical University Guilin China Department of Physiology and Pathophysiology Capital Medical University Beijing China University of Chinese Academy of Sciences China International Open Benchmark Council

This paper quantitatively reveals the state-of-the-art and state-of-the-practice AI systems only achieve acceptable performance on the stringent conditions that all categories of subjects are known, which we call closed clinical settings, but fail to work in real-world clinical settings. Compared to the diagnosis task in the closed setting, real-world clinical settings pose severe challenges, and we must treat them differently. We build a clinical AI benchmark named Clinical AIBench to set up real-world clinical settings to facilitate researches. We propose an open, dynamic machine learning framework and develop an AI system named OpenClinicalAI to diagnose diseases in real-world clinical settings. The first versions of Clinical AIBench and OpenClinicalAI target Alzheimer’s disease. In the real-world clinical setting, OpenClinicalAI significantly outperforms the state-of-the-art AI system. In addition, OpenClinicalAI develops personalized diagnosis strategies to avoid unnecessary testing and seamlessly collaborates with clinicians. It is promising to be embedded in the current medical systems to improve medical services. © 2021, CC BY.

关键词： Diagnosis

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Partial wave analysis of + c.c.

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Journal of High Energy Physics 2025年第2期2025卷 1-24页

作者： Ablikim, M. Achasov, M. N. Adlarson, P. Afedulidis, O. Ai, X. C. Aliberti, R. Amoroso, A. An, Q. Bai, Y. Bakina, O. Balossino, I. Ban, Y. Bao, H.-R. Batozskaya, V. Begzsuren, K. Berger, N. Berlowski, M. Bertani, M. Bettoni, D. Bianchi, F. Bianco, E. Bortone, A. Boyko, I. Briere, R. A. Brueggemann, A. Cai, H. Cai, X. Calcaterra, A. Cao, G. F. Cao, N. Cetin, S. A. Chai, X. Y. Chang, J. F. Che, G. R. Chelkov, G. Chen, C. Chen, C. H. Chen, Chao Chen, G. Chen, H. S. Chen, H. Y. Chen, M. L. Chen, S. J. Chen, S. L. Chen, S. M. Chen, T. Chen, X. R. Chen, X. T. Chen, Y. B. Chen, Y. Q. Chen, Z. J. Chen, Z. Y. Choi, S. K. Cibinetto, G. Cossio, F. Cui, J. J. Dai, H. L. Dai, J. P. Dbeyssi, A. de Boer, R. E. Dedovich, D. Deng, C. Q. Deng, Z. Y. Denig, A. Denysenko, I. Destefanis, M. De Mori, F. Ding, B. Ding, X. X. Ding, Y. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Du, M. C. Du, S. X. Duan, Y. Y. Duan, Z. H. Egorov, P. Fan, Y. H. Fang, J. Fang, S. S. Fang, W. X. Fang, Y. Fang, Y. Q. Farinelli, R. Fava, L. Feldbauer, F. Felici, G. Feng, C. Q. Feng, J. H. Feng, Y. T. Fritsch, M. Fu, C. D. Fu, J. L. Fu, Y. W. Gao, H. Gao, X. B. Gao, Y. N. Gao, Yang Garbolino, S. Garzia, I. Ge, L. Ge, P. T. Ge, Z. W. Geng, C. Gersabeck, E. M. Gilman, A. Goetzen, K. Gong, L. Gong, W. X. Gradl, W. Gramigna, S. Greco, M. Gu, M. H. Gu, Y. T. Guan, C. Y. Guo, A. Q. Guo, L. B. Guo, M. J. Guo, R. P. Guo, Y. P. Guskov, A. Gutierrez, J. Han, K. L. Han, T. T. Hanisch, F. Hao, X. Q. Harris, F. A. He, K. K. He, K. L. Heinsius, F. H. Heinz, C. H. Heng, Y. K. Herold, C. Holtmann, T. Hong, P. C. Hou, G. Y. Hou, X. T. Hou, Y. R. Hou, Z. L. Hu, B. Y. Hu, H. M. Hu, J. F. Hu, S. L. Hu, T. Hu, Y. Huang, G. S. Huang, K. X. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Y. S. Hussain, T. Hölzken, F. Hüsken, N. in der Wiesche, N. Jackson, J. Janchiv, S. Jeong, J. H. Ji, Q. Ji, Q. P. Ji, W. Ji, X. B. Ji, X. L. Ji, Y. Y. Jia, X. Q. Jia, Z. K. Jiang, D. Jiang, H. B. Jiang, P. C. Jiang, S. S. Jiang, T. J. Jiang, X. S. Jiang, Y. Jiao, J. B. Jiao, J. K. Jiao, Z. Jin, S. Jin, Y Institute of High Energy Physics Beijing People’s Republic of China Budker Institute of Nuclear Physics SB RAS (BINP) Novosibirsk Russia Novosibirsk State University Novosibirsk Russia Uppsala University Uppsala Sweden Bochum Ruhr-University Bochum Germany Zhengzhou University Zhengzhou People’s Republic of China Johannes Gutenberg University of Mainz Mainz Germany University of Turin Turin Italy INFN Turin Italy University of Science and Technology of China Hefei People’s Republic of China State Key Laboratory of Particle Detection and Electronics Beijing People’s Republic of China Southeast University Nanjing People’s Republic of China Joint Institute for Nuclear Research Dubna Russia INFN Sezione di Ferrara Ferrara Italy Peking University Beijing People’s Republic of China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing People’s Republic of China University of Chinese Academy of Sciences Beijing People’s Republic of China National Centre for Nuclear Research Warsaw Poland Institute of Physics and Technology Ulaanbaatar Mongolia INFN Laboratori Nazionali di Frascati Frascati Italy Carnegie Mellon University Pittsburgh USA University of Muenster Muenster Germany Wuhan University Wuhan People’s Republic of China Turkish Accelerator Center Particle Factory Group Istinye University Istanbul Turkey Nankai University Tianjin People’s Republic of China Moscow Institute of Physics and Technology Moscow Russia China University of Geosciences Wuhan People’s Republic of China Soochow University Suzhou People’s Republic of China Henan University Kaifeng People’s Republic of China Nanjing University Nanjing People’s Republic of China North China Electric Power University Beijing People’s Republic of China Tsinghua University Beijing People’s Republic of China Institute of Modern Physics Lanzhou People’s Republic of China Jilin University Changchun People’s Republic of China Hunan University Changsha People’s Republic of

Based on a sample of (2712.4 ± 14.3) × 106 ψ(3686) events collected with the BESIII detector, a partial wave analysis of the decay $$ \psi (3686)\to \Lambda {\overline{\Sigma}}^0{\pi}^0 $$ + c.c. is performed to investigate Λ* and Σ* resonances in the $$ {\pi}^0{\overline{\Sigma}}^0 $$ and π0Λ invariant mass distributions. Significant contributions are found from the Λ(1405), Λ(1520), Λ(1600), Λ(1670), Λ(1690), Λ(1800), Λ(1890), Λ(2325), Σ(1385), Σ(1660), Σ(1670), Σ(1750), and Σ(1910). The masses, widths, and production branching fractions for each component are determined. In addition, the branching fraction of $$ \psi (3686)\to \Lambda {\overline{\Sigma}}^0{\pi}^0 $$ + c.c. is measured to be (1.544 ± 0.013 ± 0.071) × 10−4 for the first time, where the first uncertainty is statistical and the second systematic.

关键词： e(+)-e(-) Experiments Branching fraction Particle and Resonance Production QCD

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Microbiome-derived bile acids contribute to elevated antigenic response and bone erosion in rheumatoid arthritis

arXiv

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arXiv 2023年

作者： Su, Xiuli Li, Xiaona Bian, Yanqin Ren, Qing Li, Leiguang Wu, Xiaohao Luan, Hemi He, Bing He, Xiaojuan Feng, Hui Cheng, Xingye Kim, Pan-Jun Tang, Leihan Lu, Aiping Xiao, Lianbo Tian, Liang Yang, Zhu Cai, Zongwei State Key Laboratory of Environmental and Biological Analysis Hong Kong Baptist University Hong Kong Department of Pharmacy Peking University Third Hospital Beijing China Institute of Arthritis Research in Integrative Medicine Guanghua Hospital Shanghai University of Traditional Chinese Medicine Shanghai China Li Ka Shing Faculty of Medicine University of Hong Kong Hong Kong Law Sau Fai Institute for Advancing Translational Medicine in Bone and Joint Diseases School of Chinese Medicine Hong Kong Baptist University Hong Kong SUSTech Academy for Advanced Interdisciplinary Studies Southern University of Science and Technology Shenzhen China Institute of Basic Research in Clinical Medicine China Academy of Chinese Medical Sciences Beijing China Department of Physics Hong Kong Baptist University Kowloon Hong Kong Department of Biology Hong Kong Baptist University Kowloon Hong Kong Institute of Computational and Theoretical Studies Hong Kong Baptist University Kowloon Hong Kong

Rheumatoid arthritis (RA) is a chronic, disabling and incurable autoimmune disease. It has been widely recognized that gut microbial dysbiosis is an important contributor to the pathogenesis of RA, although distinct alterations in microbiota have been associated with this disease. Yet, the metabolites that mediate the impacts of the gut microbiome on RA are less well understood. Here, with microbial profiling and non-targeted metabolomics, we revealed profound yet diverse perturbation of the gut microbiome and metabolome in RA patients in a discovery set. In the Bacteroides-dominated RA patients, differentiation of gut microbiome resulted in distinct bile acid profiles compared to healthy subjects. Predominated Bacteroides species expressing bile salt hydrolase (BSH) and 7α-hydroxysteroid dehydrogenase (HSDH) increased, leading to elevated secondary bile acid production in this subgroup of RA patients. Reduced serum fibroblast growth factor-19 and dysregulated bile acids were evidence of impaired farnesoid X receptor-mediated signaling in the patients. This gut microbiota-bile acid axis was correlated to anti-citrullinated peptide antibody (ACPA). The patients from the validation sets demonstrated that ACPA-positive patients have more abundant bacteria expressing BSH and 7alpha-HSDH but less Clostridium scindens expressing 7alphadehydroxylation enzymes, together with dysregulated microbial bile acid metabolism and more severe bone erosion than ACPA-negative ones. Mediation analyses revealed putative causal relationships between the gut microbiome, bile acids, and ACPA-positive RA, supporting a potential causal effect of Bacteroides species in increasing levels of ACPA and bone erosion mediated via disturbing bile acid metabolism. These results provide insights into the role of gut dysbiosis in RA in a manifestation-specific manner, as well as the functions of bile acids in this gut-joint axis, which may be a potential intervention target for precisely controlling RA

关键词： Erosion

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AI-aided short-term decision making of rockburst damage scale in underground engineering

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Underground Space 2025年

作者： Chukwuemeka Daniel Shouye Cheng Xin Yin Zakaria Mohamed Barrie Yucong Pan Quansheng Liu Feng Gao Minsheng Li Xing Huang School of Urban Construction Wuhan University of Science and Technology Wuhan 430065 China Department of Civil Engineering Pan African University Institute for Basic Sciences Technology and Innovation Jomo Kenyatta University of Agriculture and Technology Nairobi P.O. Box 62000-00200 Kenya Research Institute of Mine Construction Tiandi Science and Technology Company Limited Beijing 100013 China State Key Laboratory of Intelligent Coal Mining and Strata Control Beijing 100013 China School of Civil Engineering Wuhan University Wuhan 430072 China Department of Architecture and Civil Engineering City University of Hong Kong Hong Kong 999077 China State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil Mechanics Chinese Academy of Sciences Wuhan 430071 China

Rockbursts pose severe risks to underground engineering projects, including mining and tunnelling, where sudden rock failures can lead to substantial infrastructure damage and loss of human lives. An accurate assessment of rockburst damage is essential for safety and effective risk mitigation. This study investigates the effectiveness of ensemble machine learning models optimized through Bayesian optimization (BO) in predicting rockburst damage scales. Nine classifier algorithms, including random forest (RF), were evaluated using a dataset of 254 samples. The research considered factors such as stress conditions, support system capacity, excavation span, geological characteristics, seismic magnitude, peak particle velocity, and rock density as input variables. The rockburst damage scale, categorized into four severity levels based on displaced rock mass, served as the target variable. Among the models evaluated, BO-RF model demonstrated the highest predictive accuracy and generalization capability, achieving 92% testing accuracy. BO-RF model also ranked top in a multi-criteria evaluation framework. This devised ranking system underscores the importance of evaluating model performance on both training and unseen testing data to ensure robust generalization. The findings underscore the effectiveness of BO-RF in enhancing rockburst risk assessment and providing reliable predictive insights for underground engineering applications.

关键词： Underground engineering Rockburst damage scale Short-term decision making Ensemble learning Bayesian optimization AdaBoost Adaptive boosting BO Bayesian optimization CatBoost Categorical boosting CSS Capacity of the support system ERT Extremely randomized trees FSC Factor of stress condition GBDT Gradient boosting decision tree GM Geological mode LCE Local cascade ensemble LightGBM Light gradient boosting machine ML Machine learning MSI Magnitude of seismic incident PPV Peak particle velocity RDS Rockburst damage scale RF Random forest RGF Regularized greedy forest SE Span of excavation XGBoost Extreme gradient boosting ρ Rock density

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Chromosome-scale assembly and evolution of the tetraploid Salvia splendens (Lamiaceae) genome

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Horticulture Research 2021年第1期8卷 2721-2735页

作者： Kai-Hua Jia Hui Liu Ren-Gang Zhang Jie Xu Shan-Shan Zhou Si-Qian Jiao Xue-Mei Yan Xue-Chan Tian Tian-Le Shi Hang Luo Zhi-Chao Li Yu-Tao Bao Shuai Nie Jing-Fang Guo Ilga Porth Yousry AEl-Kassaby Xiao-Ru Wang Charles Chen Yves Van de Peer Wei Zhao Jian-Feng Mao Beijing Advanced Innovation Center for Tree Breeding by Molecular Design National Engineering Laboratory for Tree BreedingKey Laboratory of Genetics and Breeding in Forest Trees and Ornamental PlantsMinistry of EducationCollege of Biological Sciences and TechnologyBeijing Forestry UniversityBeijing 100083China Ori(Shandong)Gene Science and Technology Co. LtdWeifang 261000 ShandongChina Department des Sciences du Bois et de la Foret Facultede Foresteriede Geographie et GeomatiqueUniversite LavalQuebec CityQC G1V 0A6Canada Department of Forest and Conservation Sciences Faculty of ForestryUniversity of British ColumbiaVancouverBC V6T 1Z4Canada Department of Ecology and Environmental Science UmeåPlant Science CentreUmeåUniversitySE-90187 UmeåSweden Department of Biochemistry and Molecular Biology 246 Noble Research CenterOklahoma State UniversityStillwaterOKUSA Department of Plant Biotechnology and Bioinformatics Ghent UniversityGhentBelgium VIB Center for Plant Systems Biology 9052 GhentBelgium Centre for Microbial Ecology and Genomics Department of BiochemistryGenetics and Microbiology GeneticsUniversity of PretoriaPrivate Bag X20Pretoria 0028South Africa College of Horticulture Academy for Advanced Interdisciplinary StudiesNanjing Agricultural UniversityNanjing 210095China

Polyploidization plays a key role in plant evolution,but the forces driving the fate of homoeologs in polyploid genomes,i.e.,paralogs resulting from a whole-genome duplication(WGD)event,remain to be ***,we present a chromosome-scale genome assembly of tetraploid scarlet sage(Salvia splendens),one of the most diverse ornamental *** found evidence for three WGD events following an older WGD event shared by most eudicots(theγevent).A comprehensive,spatiotemporal,genome-wide analysis of homoeologs from the most recent WGD unveiled expression asymmetries,which could be associated with genomic rearrangements,transposable element proximity discrepancies,coding sequence variation,selection pressure,and transcription factor binding site *** observed differences between homoeologs may reflect the first step toward sub-and/or *** assembly provides a powerful tool for understanding WGD and gene and genome evolution and is useful in developing functional genomics and genetic engineering strategies for scarlet sage and other Lamiaceae species.

关键词： species evolution assembly

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Corrigendum to ‘Economic and environmental analysis of bio-succinic acid production: From established processes to a new continuous fermentation approach with in-situ electrolytic extraction’ [Chemical Engineering Research and Design Volume 179, March 2022, Pages 401–414]

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Chemical Engineering Research and Design 2022年 184卷 637-638页

作者： Enrico Mancini Rofice Dickson Serena Fabbri Isuru A. Udugama Humzaa Imtiaz Ullah Srikanth Vishwanath Krist V. Gernaey Jianquan Luo Manuel Pinelo Seyed Soheil Mansouri Department of Chemical and Biochemical Engineering Technical University of Denmark Kgs. Lyngby Denmark Department of Chemistry & Chemical Engineering SBA School of Science and Engineering Lahore University of Management Sciences (LUMS) Lahore 54792 Pakistan Quantitative Sustainability Assessment Group Department of Technology Management and Economics Technical University of Denmark Kgs. Lyngby Denmark Department of Chemical Systems Engineering the University of Tokyo Tokyo Japan State Key Laboratory of Biochemical Engineering Institute of Process Engineering Chinese Academy of Sciences Beijing China

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Tuning the SERS activity and plasmon-driven reduction of p-nitrothiophenol on a Ag@MoS2 film

Tuning the SERS activity and plasmon-driven reduction of p-n...

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作者： Miao, Peng Ma, Yan Sun, Mengtao Li, Jing Xu, Ping School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin150001 China Beijing Key Laboratory for Magneto-Photoelectrical Composite and Interface Science Center for Green Innovation School of Mathematics and Physics University of Science and Technology Beijing Beijing100083 China Key Laboratory of Photochemical Conversion and Optoelectronic Materials Technical Institute of Physics and Chemistry Chinese Academy of Sciences Beijing100190 China

The combination of plasmonic metal nanostructures with semiconductors has been widely applied in plasmon-driven photocatalysis. Here, a uniform Ag@MoS2 hybrid film is fabricated by depositing MoS2 onto a thin Ag film via the pulsed laser deposition (PLD) technique. The thickness and crystallinity of MoS2 can be adjusted by controlling the PLD deposition time and temperature, respectively. With the assistance of surface-enhanced Raman scattering (SERS) analysis, the Raman enhancement uniformity of the substrate and plasmon-driven reaction of p-nitrothiophenol (PNTP) dimerizing into p,p′-dimercaptobenzene (DMAB) are carefully studied on Ag@MoS2 film substrates with different MoS2 crystallinities. The Raman enhancement decreases with increased MoS2 thickness, due to the weakened electromagnetic field enhancement as suggested by finite-difference time-domain (FDTD) simulations. The increased crystallinity of MoS2 can efficiently accelerate the hot electron transfer process, resulting in the enhancement of SERS activity and the improved efficiency of the plasmon-driven reaction. This study may pave the way for the design of other uniform metal-semiconductor hybrids for use as SERS substrates and photocatalysts. © 2019 The Royal Society of Chemistry.

关键词： Molybdenum compounds

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Characterizing flash drought patterns in Eastern China based on high-resolution and long-term soil moisture fusion data

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Journal of Hydrology 2025年 661卷

作者： Junhan Zeng Xing Yuan Haoyu Yang Peng Ji Xiaoyong Xu School of Hydrology and Water Resources Nanjing University of Information Science and Technology Nanjing 210044 China State Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources Nanjing University of Information Science and Technology Nanjing 210044 China Department of Chemical and Physical Sciences University of Toronto Mississauga Mississauga ON Canada Department of Geography Geomatics and Environment University of Toronto Mississauga Mississauga ON Canada

Influenced by global environmental change, the increasing flash droughts have raised the demand for reliable root zone soil moisture (SM) data for drought monitoring. However, existing model-based products exhibit uncertainties and limitations in accuracy and spatial resolution, in-situ or satellite datasets fail to provide long-term records for comprehensive flash drought analysis. This study has developed a high-resolution (0.0625°) Soil Moisture Integrated Fusion (SMIF) dataset spanning from 1979 to 2022 for flash drought analysis in Eastern China. The fusion framework is constructed by using an advanced LightGBM machine learning algorithm, integrating multi-source SM data including observations from 1321 in-situ stations, high-resolution and long-term land model simulation, and reanalyzed and satellite retrievals, as well as long-term auxiliary meteorological variables. Independent validation reveals a 25% to 88% improvement in KGE for temporal prediction accuracy compared to existing SM products at both site and regional scales, such as ERA5 and GLDASv2.1 reanalysis data. As a result, SMIF performs well in capturing spatiotemporal evolution of flash droughts, including Yangtze River mega flash drought events in 2013 and 2022. Compared with the 44-year SMIF dataset, ERA5 overestimates flash drought frequency by 48% in Sichuan Basin and 31% in Yangtze and Huai River basins, while GLDASv2.1 underestimates flash drought frequency by 49% in northern regions. The newly generated SMIF dataset effectively reduces the limitations of current root zone SM products in terms of accuracy, spatial resolution, and temporal coverage for flash drought characterization, which is useful for application in agriculture, water resource management, and environmental sustainability.

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