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AI-Enabled Strategies for Managing Microplastic Risk in Agroecosystems 基于人工智能的农业生态系统微塑料风险管理策略
IF 12.8 1区 工程技术
Engineering Pub Date : 2025-09-26 DOI: 10.1016/j.eng.2025.09.012
Peng Deng, Li Mu, Wendan Xue, Ruiqi Wang, Xiangang Hu, Xu Dong, Baoshan Xing
{"title":"AI-Enabled Strategies for Managing Microplastic Risk in Agroecosystems","authors":"Peng Deng, Li Mu, Wendan Xue, Ruiqi Wang, Xiangang Hu, Xu Dong, Baoshan Xing","doi":"10.1016/j.eng.2025.09.012","DOIUrl":"https://doi.org/10.1016/j.eng.2025.09.012","url":null,"abstract":"The continuous increase in microplastic (MP) pollution poses significant risks to human health and environmental sustainability, especially in agroecosystems. This study focused on identifying and managing MP risk to crops in agricultural soils in China, which is among the world’s largest consumers of plastic. Via the use of 3243 site-year field observations, we developed intelligent agriculture models to predict MP-related crop risks and identify key drivers, such as climate, livestock density, and fertilizer application, other than the use of agricultural plastic film. Rice was most sensitive to MPs, with an average risk quotient (RQ; unitless) of (3.76 ± 1.95), which is 2.19 and 1.93 times greater than those of maize and wheat, respectively. Climate factors are closely related to livestock density and agricultural management practices, potentially exacerbating MP risk under future conditions. Optimizing livestock density and fertilizer use levels reduced MP risk by 20.9%, 22.9%, and 20.3% and increased crop yields by 9.0%, 6.0%, and 5.6% for maize, rice, and wheat, respectively. Despite limitations related to model uncertainty and policy implementation, the proposed intelligent agriculture model provides a comprehensive basis and potential solutions for assessing and managing MP risk to crops.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"38 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145140643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Gas Versus Biomass Cooking—Landmark Trial Yields Unexpected Results 燃气与生物质烹饪——里程碑式的试验产生了意想不到的结果
IF 12.8 1区 工程技术
Engineering Pub Date : 2025-09-26 DOI: 10.1016/j.eng.2025.09.014
{"title":"Gas Versus Biomass Cooking—Landmark Trial Yields Unexpected Results","authors":"","doi":"10.1016/j.eng.2025.09.014","DOIUrl":"https://doi.org/10.1016/j.eng.2025.09.014","url":null,"abstract":"No Abstract","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"91 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145140641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Chinese Robotics Take a Big (Dance) Step Forward 中国机器人向前迈出一大步
IF 12.8 1区 工程技术
Engineering Pub Date : 2025-09-26 DOI: 10.1016/j.eng.2025.09.013
{"title":"Chinese Robotics Take a Big (Dance) Step Forward","authors":"","doi":"10.1016/j.eng.2025.09.013","DOIUrl":"https://doi.org/10.1016/j.eng.2025.09.013","url":null,"abstract":"No Abstract","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"22 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145140639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Single-Nucleus RNA Sequencing Reveals the Mechanism of Neonatal Hypoxic–Ischemic Encephalopathy and The Neuroprotection Effects of Salvianolic Acid C 单核RNA测序揭示新生儿缺氧缺血性脑病发病机制及丹酚酸C的神经保护作用
IF 12.8 1区 工程技术
Engineering Pub Date : 2025-09-25 DOI: 10.1016/j.eng.2025.09.010
Xuan Mou, Lu Li, Xinyue Liu, Aolin Zhang, Tao He, Baofeng Rao, Jiatian Zhang, Renjie Chen, Malte Spielmann, Chi Chiu Wang, Bin Cong, Xiaohui Fan
{"title":"Single-Nucleus RNA Sequencing Reveals the Mechanism of Neonatal Hypoxic–Ischemic Encephalopathy and The Neuroprotection Effects of Salvianolic Acid C","authors":"Xuan Mou, Lu Li, Xinyue Liu, Aolin Zhang, Tao He, Baofeng Rao, Jiatian Zhang, Renjie Chen, Malte Spielmann, Chi Chiu Wang, Bin Cong, Xiaohui Fan","doi":"10.1016/j.eng.2025.09.010","DOIUrl":"https://doi.org/10.1016/j.eng.2025.09.010","url":null,"abstract":"Neonatal hypoxic–ischemic encephalopathy (HIE), resulting from perinatal asphyxia-induced hypoxic–ischemic brain damage (HIBD), is a severe neurological disorder that impairs neurodevelopment, and no definitive therapies are available. The polyphenolic natural compound salvianolic acid C (SAC) exhibits antioxidant, anti-inflammatory, and antiapoptotic properties. In this study, we evaluated the efficacy of SAC in treating HIE via animal and human brain organoid experiments. Human brain organoids served as a translational platform for assessing natural product efficacy and clinical effect prediction. Rat brain tissues were harvested at two time points (24 h and 7 d after HIBD and SAC administration) for single-nucleus RNA sequencing. <em>In vitro</em> and <em>in vivo</em> experiments, including microarrays and gene silencing, were employed to confirm the sequencing findings. Our findings demonstrated that during the acute phase of HIBD, SAC suppressed signal transducer and activator of transcription 3<sup>+</sup> (<em>Stat3</em><sup>+</sup>) astrocyte-driven acute neuroinflammation, decreased inflammatory factor release, and maintained glial–immune homeostasis. During the subacute phase, SAC promoted oligodendrocyte differentiation and facilitated crosstalk between anti-inflammatory microglia and myelinating oligodendrocytes, establishing a regenerative microenvironment and enhancing neuregulin 3 (NRG3)–receptor tyrosine-protein kinase erbB-4 (ErbB4) signaling axis activity. These coordinated mechanisms highlight the dual capacity of SAC in mitigating early injury and driving structural repair in the later stages. This study revealed the pathophysiology of HIE and the multitarget neuroprotective effects of SAC against this disorder at single-cell resolution, advancing the mechanistic foundations for SAC-based therapies in neonatal brain injury.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"23 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145140636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Leveraging Battery Electric-Bus Charging Networks for Resilient Shared EV Charging via Deep Reinforcement Learning 基于深度强化学习的电动汽车充电网络弹性共享充电
IF 12.8 1区 工程技术
Engineering Pub Date : 2025-09-25 DOI: 10.1016/j.eng.2025.09.011
Zhengke Liu, Yunpeng Wang, Sonia Yeh, Patrick Plötz, Bin Yu, Xiaolei Ma
{"title":"Leveraging Battery Electric-Bus Charging Networks for Resilient Shared EV Charging via Deep Reinforcement Learning","authors":"Zhengke Liu, Yunpeng Wang, Sonia Yeh, Patrick Plötz, Bin Yu, Xiaolei Ma","doi":"10.1016/j.eng.2025.09.011","DOIUrl":"https://doi.org/10.1016/j.eng.2025.09.011","url":null,"abstract":"The rapid electrification of urban transportation has increased dependence on public electric-vehicle (EV) charging infrastructure, making it more vulnerable to frequent and severe disruptions. To address this issue, this study proposes utilizing underused battery electric-bus (BEB) charging networks by dynamically reallocating surplus depot chargers for public EV charging. We introduce an adaptive shared-charging coordination framework to increase the resilience of public charging services. This coordination problem is formulated as a Markov decision process (MDP) that jointly optimizes BEB charging schedules and shared charger allocation under uncertainty. To enable real-time decision-making without requiring precise forecasts of future system states, an on-policy deep reinforcement-learning (DRL) approach based on the asynchronous advantage actor-critic (A3C) algorithm is developed. A case study using real-world data from Beijing during a major urban flood demonstrates the effectiveness of the proposed adaptive shared-charging coordination framework. The results reveal that our approach significantly mitigates degradation in public charging service performance, accelerates recovery to normal operating levels, enhances user accessibility, and supports grid stability. Under an extreme scenario with only 25% of public chargers operational, the proposed strategy limits revenue losses to just 3.49%, compared with losses of 53.34% under conventional operations. Additionally, the A3C-based approach demonstrates notable training efficiency and achieves a favorable balance between short-term responsiveness and long-term system performance when benchmarked against a perfect-information optimization model, proximal policy optimization (PPO), and a greedy heuristic. These findings highlight the substantial potential of BEB charging networks as critical resilience resources for urban public EV charging infrastructure during extreme disruption events.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"64 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145134325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Rapid In-Vitro Inactivation of Various SARS-CoV-2 Strains Using Ionizing Radiation: New Inactivation Patterns And Mechanistic Insights 利用电离辐射快速体外灭活多种SARS-CoV-2菌株:新的灭活模式和机制见解
IF 12.8 1区 工程技术
Engineering Pub Date : 2025-09-24 DOI: 10.1016/j.eng.2025.09.009
Wei Wang, Xiaodi Zhang, Jiageng Yu, Tianhao Weng, Zhiyang Yu, Zhigang Wu, Danrong Shi, Sufen Zhang, Xiangyun Lu, Osama Alam, Dahang Shen, Qian Bao, Qingfu Ye, Lanjuan Li, Hangping Yao
{"title":"Rapid In-Vitro Inactivation of Various SARS-CoV-2 Strains Using Ionizing Radiation: New Inactivation Patterns And Mechanistic Insights","authors":"Wei Wang, Xiaodi Zhang, Jiageng Yu, Tianhao Weng, Zhiyang Yu, Zhigang Wu, Danrong Shi, Sufen Zhang, Xiangyun Lu, Osama Alam, Dahang Shen, Qian Bao, Qingfu Ye, Lanjuan Li, Hangping Yao","doi":"10.1016/j.eng.2025.09.009","DOIUrl":"https://doi.org/10.1016/j.eng.2025.09.009","url":null,"abstract":"Ionizing radiation presents an important solution for virus inactivation. However, its efficacy for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inactivation and the underlying mechanisms remain unclear. This study demonstrates radiosensitivity and radiation-induced biological changes in SARS-CoV-2 using 20 wild-type and mutant strains. The results show that 1.2 kGy of electron beam (E-beam) or 0.9 kGy of X-ray irradiation can eliminate 99.99% of SARS-CoV-2 particles. The Delta and various Omicron variants exhibit heightened sensitivity to radiation compared to the wild-type, showing nearly 99.99% inactivation efficiency at 1.0 and 0.8 kGy. The relationship between irradiation dose and the logarithmic reduction in virus load adheres to a dose–response model, characterized by extremely narrow windows. Spike (S) protein disruption, rather than the commonly accepted nucleic acid cleavage, is identified as the primary inactivation mechanism (triggering a conformation transition of S protein from pre-fusion to post-fusion with minimal impact on nucleic acid integrity). This study introduces the concept of targeting critical proteins in coronavirus inactivation, offering valuable insight for infectious coronavirus disease control and vaccine development.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"13 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145134255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
High Fidelity and Efficiency Simulator for 6G Integrated Space–Ground Network 6G空间-地面综合网络高保真高效模拟器
IF 12.8 1区 工程技术
Engineering Pub Date : 2025-09-20 DOI: 10.1016/j.eng.2025.08.042
Haibo Zhou, Xiaoyu Liu, Xin Zhang, Xiaohan Qin, Mengyang Zhang, Yuze Liu, Weihua Zhuang, Xuemin Shen
{"title":"High Fidelity and Efficiency Simulator for 6G Integrated Space–Ground Network","authors":"Haibo Zhou, Xiaoyu Liu, Xin Zhang, Xiaohan Qin, Mengyang Zhang, Yuze Liu, Weihua Zhuang, Xuemin Shen","doi":"10.1016/j.eng.2025.08.042","DOIUrl":"https://doi.org/10.1016/j.eng.2025.08.042","url":null,"abstract":"Mega-constellation networks have recently gained significant research attention because of their potential for providing ubiquitous and high-capacity connectivity in future sixth-generation (6G) wireless communication systems. However, the high dynamics of network topology and large-scale of a mega-constellation pose new challenges to constellation simulation and performance evaluation. To address these issues, we introduce UltraStar, a high-fidelity and high-efficiency computer simulator to support the development of 6G wireless communication systems with low-Earth-orbit mega-constellation satellites. The simulator facilitates the design and performance analysis of various algorithms and protocols for network operation and deployment. We propose a systematic, scalable, and comprehensive simulation architecture for the high-fidelity modeling of network configurations and for performing high-efficiency simulations of network operations and management capabilities, while providing users with intuitive visualizations. We capture heterogeneous topology characteristics by establishing an environment update algorithm that incorporates real ephemeris data for satellite orbit prediction, sun outages, and link handovers. For a realistic simulation of software and hardware configurations, we develop a network simulator version 3 based network model to support networking protocol extensions. We propose a message passing interface-based parallel and distributed approach with multiple cores or machines to achieve high simulation efficiency in large and complex network scenarios. Experimental results demonstrate the high fidelity and efficiency of UltraStar can help pave the way for 6G integrated space–ground networks.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"4 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Review on Liquid-Ammonia Injection and Combustion for Engine Applications 液氨喷射与燃烧技术在发动机中的应用综述
IF 12.8 1区 工程技术
Engineering Pub Date : 2025-09-20 DOI: 10.1016/j.eng.2025.09.008
Hao Wu, Fahad Almatrafi, Moez Ben Houidi, Tiegang Fang, William L. Roberts
{"title":"A Review on Liquid-Ammonia Injection and Combustion for Engine Applications","authors":"Hao Wu, Fahad Almatrafi, Moez Ben Houidi, Tiegang Fang, William L. Roberts","doi":"10.1016/j.eng.2025.09.008","DOIUrl":"https://doi.org/10.1016/j.eng.2025.09.008","url":null,"abstract":"This comprehensive review examines the application of liquid-ammonia injection and combustion in engine systems, highlighting the potential of liquid ammonia as a carbon-neutral fuel alternative. The study synthesizes recent advancements in liquid-ammonia injection and combustion technologies, addressing critical domains such as fundamental fuel properties, injection and spray dynamics, combustion behavior, and engine performance. Key challenges are identified, including ammonia’s high latent heat of vaporization, slow flame-propagation speed, narrow flammability range, and elevated NO<em><sub>x</sub></em> emissions, while emphasizing the need for optimized injection strategies and nozzle designs to enhance atomization and mixing. The research findings indicate that liquid-ammonia injection can significantly reduce greenhouse gas emissions, with dual-fuel modes (e.g., ammonia–diesel) proving effective in overcoming ammonia’s low reactivity. Studies show that both low-pressure and high-pressure dual fuel-injection modes can achieve substantial emission reductions, with high-pressure injections offering better thermal efficiency and lower NO<em><sub>x</sub></em> emissions. Innovative approaches, such as turbulent jet ignition, stratified fuel injection, and hydrogen co-injection, have been explored to improve ignition efficiency and combustion stability. Future research should prioritize the development of integrated solutions that combine advanced combustion technologies, optimized engine designs, and effective emission-control strategies. Collaboration between academia, industry, and policymakers will be crucial in driving the adoption of ammonia as a sustainable fuel alternative.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"2017 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Task-Driven Design Approach for 6G AI-Native Architecture 6G ai原生架构的任务驱动设计方法
IF 12.8 1区 工程技术
Engineering Pub Date : 2025-09-17 DOI: 10.1016/j.eng.2025.09.005
Xiaoyun Wang, Lu Lu, Qin Li, Qi Sun, Nanxiang Shi, Ziqi Chen, Tao Sun
{"title":"A Task-Driven Design Approach for 6G AI-Native Architecture","authors":"Xiaoyun Wang, Lu Lu, Qin Li, Qi Sun, Nanxiang Shi, Ziqi Chen, Tao Sun","doi":"10.1016/j.eng.2025.09.005","DOIUrl":"https://doi.org/10.1016/j.eng.2025.09.005","url":null,"abstract":"The deep integration of mobile networks with artificial intelligence (AI) has emerged as a pivotal driving force for the sixth-generation (6G) mobile network. AI-native 6G represents a paradigm shift for mobile networks, as it not only embeds AI into network components to enhance network intelligence and automation but also transforms 6G into a foundational infrastructure for enabling pervasive AI applications and services. This paper proposes a novel 6G AI-native architecture. The challenges and requirements for the AI-native 6G mobile network are first analyzed, followed by the development of a task-driven approach for architecture design based on insights from system theory. Then, a 6G AI-native architecture is proposed, featuring the integration of distributed AI data and computing components with layered centralized collaborative control and flexible on-demand deployment. Key components and procedures for the 6G AI-native architecture are also discussed in detail. Finally, standardization practices for the convergence of mobile networks and AI in fifth-generation (5G) networks are analyzed, and an outlook on the standardization of AI-native design in 6G is given. This paper aims to provide not only theoretical insights into AI-native architecture design methodology but also a comprehensive 6G AI-native architecture that lays a foundation for the transition from mobile communications toward mobile information services in the 6G era.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"77 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145072174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
MedMeta: An AI-Enabled and Genomics-Based Database for Functional Profiling of Secondary Metabolites in Medicinal Species MedMeta:一个基于人工智能和基因组学的数据库,用于药用物种次生代谢物的功能分析
IF 12.8 1区 工程技术
Engineering Pub Date : 2025-09-17 DOI: 10.1016/j.eng.2025.09.007
Fanbo Meng, Guiyang Zhang, Wenke Xiao, Yufei Mao, Yun Shu, Xiuping Yang, Guoqing Xu, Xinyu Tang, Mengqing Zhang, Zhiyu Liu, Xunzhi Zhang, Shengjie You, Bin Wang, Zhiyin Yu, Shilin Chen, Wei Chen
{"title":"MedMeta: An AI-Enabled and Genomics-Based Database for Functional Profiling of Secondary Metabolites in Medicinal Species","authors":"Fanbo Meng, Guiyang Zhang, Wenke Xiao, Yufei Mao, Yun Shu, Xiuping Yang, Guoqing Xu, Xinyu Tang, Mengqing Zhang, Zhiyu Liu, Xunzhi Zhang, Shengjie You, Bin Wang, Zhiyin Yu, Shilin Chen, Wei Chen","doi":"10.1016/j.eng.2025.09.007","DOIUrl":"https://doi.org/10.1016/j.eng.2025.09.007","url":null,"abstract":"Medicinal resources contain a vast array of secondary metabolites that play critical roles in disease treatment, health maintenance, and drug discovery. Nevertheless, challenges such as biosynthetic complexity and species-specific variability have long hindered their systematic exploration. Recent advances in omics technologies and artificial intelligence (AI)-driven approaches have opened new avenues via which to decode biosynthetic pathways and discover secondary metabolites using omics-level data. In this study, we present MedMeta, a curated and integrative database that connects secondary metabolites with genomic, biochemical, and pharmacological information across 1035 medicinal species documented in eight authoritative global pharmacopoeias. MedMeta comprises 146 101 predicted active secondary metabolites, 196 356 biosynthetic pathways, and an extensive set of annotated molecular targets. As a proof of principle, we employed MedMeta to investigate three representative Apiaceae species—<em>Pucedanum praeruptorum</em>, <em>Angelica sinensis</em>, and <em>Apium graveolens</em>—demonstrating its ability to uncover species-specific metabolite profiles, validate enzymatic functions, and identify compounds with important therapeutic potential. Overall, MedMeta can provide a powerful and scalable platform for natural product research, supporting both fundamental studies and applied biomedical applications. This database offers an invaluable resource for compound discovery, synthetic biology, geoherbalism studies, and the modern application of traditional medicinal systems.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"125 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145072175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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