搜索结果：Fundamental research

The incidence and mortality of malignant tumors remain persistently high, while current clinical chemotherapeutic agents are often limited by significant drug resistance and adverse reactions. Consequently, small-molecule compounds derived from traditional Chinese medicine(TCM) have emerged as a focus in anti-tumor research owing to their advantages of multi-targeting action and low toxicity. As the core active component of Glycyrrhiza uralensis, glycyrrhizic acid(GA) is an oleanane-type pentacyclic triterpenoid saponin, constituting 5%-11% of the total content of G. uralensis. Its anti-tumor activity has been validated across various tumor systems, with mechanisms of action encompassing key processes such as cell cycle arrest, induction of tumor cell apoptosis, inhibition of tumor angiogenesis, blockage of invasion and metastasis, regulation of the tumor immune microenvironment(TIME), and alleviation of chronic inflammation. In terms of its therapeutic value, the combination of glycyrrhizic acid with other agents, such as tanshinone Ⅱ_A(Chinese medicine) or cisplatin(conventional chemotherapy) can achieve enhanced efficacy, reduced toxicity, targeted delivery, and reversal of drug resistance. This positions GA as possessing dual values, functioning both as a therapeutic agent and as a drug delivery carrier. This review systematically summarized the anti-tumor pharmacological activities, mechanisms, combined medication potential, and safety profiles of GA. It elaborated on the network mechanism of core regulatory hubs, analyzed the limitations of current research, and proposed targeted strategies for clinical translation. This work aims to provide a reference for the transition of GA from fundamental research to clinical application, while also offering a paradigm for the development of anti-tumor small-molecule compounds from TCM.

Medical education is fundamental to developing clinical competence, directly influencing care quality and patient safety. Traditional teaching models have long faced structural limitations, including scarce physical resources and restricted clinical exposure, which hinder the training of versatile professionals needed in modern health care. Virtual simulation (VS), by providing a high-fidelity, repeatable, and low-risk learning environment, offers a promising solution to these challenges. This narrative article reviews recent applications of VS in basic medicine, clinical medicine, and nursing education. Although existing evidence supports its educational benefits, most studies rely on short-term, small-sample designs and lack evaluation of long-term clinical transfer or cost-effectiveness. Persistent issues include high device heterogeneity and insufficient integration of nontechnical skills training. Future efforts should prioritize multicenter longitudinal research, platform standardization, and the incorporation of artificial intelligence to enable personalized adaptive learning-moving VS toward a core component of medical education.

TCM is a treasure of Chinese civilization and a potential key to solving modern medical challenges. Research on the pharmacodynamic material basis, action targets, and mechanisms based on the traditional efficacy of TCM has become a consensus. Clarifying the pharmacodynamic material basis of TCM is not only a fundamental issue in TCM research but also a critical step in deciphering the complex TCM systems. However, the complexity of TCM systems poses significant challenges to the research of their pharmacodynamic material basis, leaving the pharmacodynamic material basis of treating diseases in most TCM largely unclear, which greatly limits people's scientific understanding of TCM in treating diseases. Currently, the research on the pharmacodynamic material basis of TCM has formed an interdisciplinary methodological system. Various methods have shown unique advantages, but they all have the common problem of being unable to balance the holistic view of TCM and research precision. The knock-out/knock-in technique can precisely disassemble and controllably integrate the complex TCM system and is a key technique to solve the challenges in the research of TCM material basis. Based on this, this paper proposed a new paradigm for identifying the material basis based on the knock-out/knock-in technique. This paradigm integrates the intrinsic connection among traditional efficacy, material basis, and action targets, aiming to provide new ideas for the research on the material basis of TCM and methodological support for the TCM modernization.

To systematically investigate the Chinese food market for food-grade microbial strains in 2025, clarify the fundamental attributes such as the concept, classification, and efficacy types of these strains, analyze differences in domestic and international policies, standards, and management models, assess the current market development status and core issues. A combination of literature review and field survey was adopted. First, the evolution, definition, classification system, and efficacy types of food-grade microbial strains were systematically reviewed. Second, differences in the policy frameworks and management models for food-grade microbial strains between domestic and international contexts were compared. Finally, based on survey data collected from 470 ordinary food products containing food-grade microbial strains from July to October 2025, quantitative and qualitative analyses of market size, product characteristics, and existing issues were conducted. The food-grade microbial strains have a long history of application, with their concepts and classifications continuously refined as biotechnology advances. In 2022, both domestic and international lists of microbial strains were updated, and the reclassification of lactobacilli had a significant impact on the food industry. The Chinese market for food-grade microbial strains showed sustained growth, reaching a terminal market size of 134.89 billion yuan in 2024. Products were diversifying and becoming more refined, with composite microbial agent-containing products dominating the market. However, issues such as non-standard labeling, unauthorized functional claims for ordinary foods, and insufficient support for food-grade microbial strain testing technology persisted. Additionally, while both domestic and international regulations prioritized safety and emphasized strain-specific characteristics, notable differences existed in regulatory classification, approval process design, and health claim requirements. The Chinese food market for food-grade microbial strains has significant growth potential. However, addressing existing issues requires multifaceted measures, including strengthening full-chain supervision of labeling standards, improving the inspection and testing technology system for food-grade microbial strains, strictly regulating the functional claims of ordinary foods, and enhancing the core competitiveness of domestic enterprises. These efforts will help resolve current market challenges and promote the industry's sustainable development toward standardization and high quality.

The UK LLC Citizen Panel is a research and public engagement project which is the first proof of concept of an innovative model of learning in data research governance, proposed by Understanding Patient Data (UDPD). The Citizen Panel was designed in two stages, co-designed by a Steering Group and comprising of 15 members, with 50% participants from LPS collaborating with UK LLC and 50% public members from seldom-heard voices in longitudinal research. The Panel operated in two rounds, held six online meetings and two hybrid workshops. The Citizen Panel conducted an end-to-end assessment (audit) of the UK LLC application process and provided two sets of innovative recommendations to UK LLC. This model enhanced scrutiny and audit of the UK LLC data access process, evolved the UPD data learning model for research governance and shifted the UPD idea towards a circular and reflective model of work, built on multiple feedback loops and embedded in co-design, mutual learning, dialogue and deliberation with public members from minoritized groups often under-represented in longitudinal research. The UK LLC Citizen Panel provided novel and important insights on the UK LLC data access process and decision making. The Panel could expand its impact beyond UK LLC to improve the UK's data infrastructure landscape and a model for national and international research organisations. The UK LLC Citizen Panel model is fundamental to good ethical practice and building trust with publics, inclusion of underserved and underrepresented groups and for broader dialogue between citizens and science.

Super-converged generative information network (SoGIN) envisions the integration of human-physical and digital networks, with development requirements centered on space-air-ground integration, computing-storage-sensing-intelligence integration, and availability-reliability-trustworthiness integration. Following the new development paradigm of decoupling network support environments from application network systems, SoGIN would build an AI-empowered, highly integrated, efficiently collaborative, trustworthy intelligent information network system based on the deep integration of digital-operation-information-communication technology (DOICT). This provides the foundational support environment for realizing 6G visions. This paper discusses the challenges and fundamental theoretical issues faced by SoGIN. Firstly, the development vision and demands of SoGIN are elaborated. Then, the theoretical and technical challenges in achieving the vision of SoGIN are analyzed. Finally, related theoretical and technical practices about polymorphic network environments, cloud-native-based super-converged network infrastructures, new cybersecurity paradigm, cyberspace resilience empowered by endogenous security and safety (ESS), and the physical foundation of next-generation digital systems technology based on wafer-level computing are described.

Against the backdrop of the commercialization of 5G-Advanced (5G-A) and the conceptualization of 6G, the Mobile Information Network (MINet)-a futuristic network paradigm centered on extreme connectivity and multi-dimensional integration-has emerged to transcend the limitations of traditional mobile networks, which focus solely on isolated communication services. MINet is designed to support the full lifecycle of information services, integrating communication with advanced computing, artificial intelligence (AI), and big data to achieve ubiquitous extreme connectivity and deliver integrated information services encompassing different elements. At its core, MINet's competitive edge lies in the "One Extreme and Three Integrations" framework: this framework takes "ubiquitous extreme connectivity" as the foundational performance pillar and relies on three functional directions: "communication-sensing-computing-intelligence convergence," "space-terrestrial integration," and "digital-physical integration". To operationalize this framework, DOICT (Data, Operation, Intelligence, Computing, and Telecommunication) convergence serves as a critical enabler: it underpins the design of MINet's scalable core networks and edge intelligence systems, while supporting key technological innovations. This paper reviews the foundational theories, network architectures, key technologies, and devices driving the development of MINet, and also highlights critical challenges in MINet's development, including design considerations, application requirements, sustainable and low-carbon. Ultimately, as MINet evolves from 5G-A to 6G, the synergy of its core paradigm (MINet), technical framework ("One Extreme and Three Integrations"), and enabling mechanism (DOICT convergence) will bridge the physical and digital worlds, fostering transformative applications in immersive experiences, industrial automation, and smart society.

As the dominant dosage form in clinical practice of TCM, solid preparations face core challenges concerning quality stability and consistent therapeutic efficacy. Clinical observations have revealed efficacy variations among different preparation forms of the same TCM or even among products of the same preparation from different manufacturers. Such variations are attributed not only to the complexity of the production process but also to the physicochemical states of the drug substances, among which crystal forms likely serve as a critical factor influencing the drug state and subsequent efficacy divergence. TCM crystal forms, as a fundamental microscopic attribute of active ingredients in TCM, directly determine physicochemical properties and biological activities of drugs, representing a root cause of quality fluctuation and efficacy variation. Currently, significant progress has been made in the study of TCM crystal forms based on TCM active ingredients and compound preparations. A comprehensive technical framework encompassing preparation, characterization, and property analysis has been established. Its core value lies in revealing the scientific essence of "identical composition but heterogeneous activity", and it is expected to provide quantitative and precise technical support for quality control across the entire TCM industry chain. However, research on the crystal forms of TCM solid preparations remains a major challenge. Whether it concerns the discovery, characterization, and identification of preferred crystal forms in Chinese patent medicines, or the quality control of crystal forms of Chinese patent medicines and their impact on clinical efficacy, these areas remain largely unexplored territory awaiting further investigation. This article proposed the crystal form issues in TCM solid preparations. It comprehensively reviewed the research landscape of TCM crystal forms, spanning from single components to compound preparations, systematically elucidated the associated technical systems and category characteristics of TCM crystal forms, and innovatively proposed a crystal form-based strategy for quality control. This perspective provides a novel research framework for enhancing the quality control of TCM solid preparations and discovering new formula-derived nanoparticle drugs, holding significant importance for enhancing the standardization of TCM solid preparations, ensuring clinical efficacy, and advancing the development of TCM nanoscience.

Traditional asymptotic information-theoretic studies of the fundamental limits of wireless communication systems primarily rely on some ideal assumptions, such as infinite blocklength and vanishing error probability. While these assumptions enable tractable mathematical characterizations, they fail to capture the stringent requirements of some emerging next-generation wireless applications, such as ultra-reliable low latency communication and ultra-massive machine type communication, in which it is required to support a much wider range of features including short-packet communication, extremely low latency, and/or low energy consumption. To better support such applications, it is important to consider finite-blocklength information theory. In this paper, we present a comprehensive review of the advances in this field, followed by a discussion on the open questions. Specifically, we commence with the fundamental limits of source coding in the non-asymptotic regime, with a particular focus on lossless and lossy compression in point-to-point (P2P) and multiterminal cases. Next, we discuss the fundamental limits of channel coding in P2P channels, multiple access channels, and emerging massive access channels. We further introduce recent advances in joint source and channel coding, highlighting its considerable performance advantage over separate source and channel coding in the non-asymptotic regime. In each part, we review various non-asymptotic achievability bounds, converse bounds, and approximations, as well as key ideas behind them, which are essential for providing engineering insights into the design of future wireless communication systems.

While distinct pragmatic profiles are well-documented, grammatical abilities in autistic children show considerable heterogeneity: some exhibit grammatical difficulties, while others demonstrate age-appropriate grammar. Yet, one construction remains underinvestigated: passives of psychological/mental state verbs ("remember", "love"). This is critical because young children are known to comprehend passives of agentive verbs ("kiss", "push") via an adjectival passive strategy before acquiring passive grammar. This strategy fails for psychological verbs, making them the true test of passive knowledge. Despite extensive research in typically developing (TD) populations and populations with other neurodevelopmental conditions, there is little research examining both types of verbal passive in English-speaking autistic children. We examined comprehension of agentive and psychological passives, short and long, in 48 autistic children divided into those with co-occurring language impairment (ALI, n = 26, mean age: 11;10), and those without (ALN, n = 22, mean age = 11;02), compared to two control groups matched on non-verbal reasoning (TD-Match-ALI, n = 22, mean age: 5;11 and TD-Match-ALN, n = 22, mean age: 10;03), on a sentence-matching task. Children with ALN demonstrated age-appropriate performance across all constructions. In contrast, children with ALI performed at or below chance on both agentive and psychological passives, indicating absence of the adjectival strategy, and a profile distinct from all other groups including younger TD children. The findings reveal distinct developmental trajectories: children with ALN show age-appropriate grammatical development, while children with ALI demonstrate fundamental syntactic impairments. These results highlight the importance of testing psychological verb passives to accurately identify grammatical difficulties that standardised assessments may miss.

Catalytic decomposition is a key technology for the removal of ozone (O3). Practical application scenarios require catalysts with superior O3 decomposition performance at ambient temperatures, high humidity, and high space velocities. In this review, the strategies for the design of catalysts with efficient and stable O3 decomposition performance are presented, and the three factors that limit the catalytic decomposition of O3 at ambient temperature (insufficient active sites, competitive adsorption of H2O and O3 molecules, and difficult desorption of intermediate oxygen species) are systematically summarized for the first time. Subsequently, the research progress in recent years is categorized and summarized in terms of addressing the three factors limiting O3 decomposition, which in turn suggests the shortcomings of current research and the focus of future research.

HR-positive HER2-low-expressing breast cancer is a unique subtype that has been refined from the traditional HER2 binary classification system in recent years, accounting for nearly 60% of the overall incidence of breast cancer. It has significant value for precise diagnosis and treatment research. This review systematically elaborates on the epidemiological characteristics, biological basis, diagnostic technology progress, and treatment strategy evolution of this subtype. HR-positive HER2-low-expressing breast cancer is characterized by the dominance of the estrogen receptor pathway and the core molecular feature of the intersection of HER2 low-expression signals. Its diagnosis requires a balance between the fundamental role of endocrine therapy and the precise screening of anti-HER2 targeted therapy. In terms of diagnosis, the initial screening by immunohistochemistry combined with fluorescence in situ hybridization has formed a standardized process. The integration of digital pathology, next-generation sequencing, and circulating tumor DNA in liquid biopsy technologies has effectively improved diagnostic accuracy and dynamic monitoring capabilities. In terms of treatment, endocrine therapy is the cornerstone, and the CDK4/6 inhibitor combination regimen is the standard for advanced first-line treatment. Antibody-drug conjugates, especially deruxtecan, have significantly improved patient prognosis and reshaped the treatment landscape. In summary, HR-positive HER2-low-expressing breast cancer has entered the era of individualized precise treatment guided by molecular typing. In the future, further exploration of new biomarkers, optimization of combination therapy strategies, and high-quality clinical research are needed to continuously improve patient survival outcomes.

Family caregivers often face significant challenges in coping with the critical phases of their loved one's illness. These experiences can impose substantial burdens on their daily lives. This study explores the mediating role of resourcefulness in the relationship between coping self-efficacy and family caregivers' burden. A descriptive correlational research design is used to examine the relationship between the study variables and how demographic characteristics influence them. The study included 370 family caregivers, with a response rate of 61.7%. Approximately 41.6% of family caregivers were aged 30-39&#x2009;years, and more than half were male. Total family caregiver burden showed moderate negative correlations with total coping self-efficacy (r&#x2009;=&#x2009;-0.683, p&#x2009;<&#x2009;0.001) and total resourcefulness (r&#x2009;=&#x2009;-0.799, p&#x2009;<&#x2009;0.001). Despite a strong negative correlation between family caregiver burden and personal resourcefulness (r&#x2009;=&#x2009;-0.937, p&#x2009;<&#x2009;0.001), a weak negative correlation with the social resourcefulness subscale (r&#x2009;=&#x2009;-0.263, p&#x2009;<&#x2009;0.001) was observed. Moreover, the path analysis model highlights the substantial effects of both personal resourcefulness (-0.380, CR&#x2009;=&#x2009;-36.022, p&#x2009;<&#x2009;0.001) and social resourcefulness (-0.150, CR&#x2009;=&#x2009;-12.258, p&#x2009;<&#x2009;0.001) on reducing caregiver burden, indicating that resourcefulness is a negative predictor of caregiver burden. Personal resourcefulness significantly mediates the adverse effect of caregiver burden on coping self-efficacy, underscoring the potential of nursing interventions to support caregivers and improve ICU outcomes. Nursing interventions incorporate strategies such as family-centred care, targeted education, coping-skills training and collaborative goal setting to foster family reliance on personal resourcefulness, which plays a fundamental role in managing their burdens and surpasses the impact of social support alone.

Rodent models are a mainstay of traumatic brain injury (TBI) research, including investigations into the pathophysiology and treatment of this condition. However, there are fundamental molecular and cellular differences between rodent and human neurons, as well as other cells of the brain. Brain organoids derived from human pluripotent stem cells recapitulate key features of the human brain and have been used to model a variety of neurological disorders. Here, we developed a novel in vivo model of human TBI based on controlled cortical impact (CCI) injuries of human organoid grafts transplanted into the brains of young adult rats. Cortical organoids derived from human induced pluripotent stem cells (iPSCs) were grown for 50-60 days in vitro before transplantation into rat visual cortex. Injures were performed 2 months later, and histological outcomes were examined at 7 or 30 days after injury. Injury cavities in the integrated grafts were identified at both endpoints with a progression toward larger cavities sizes with time. The injured human tissue exhibited evidence of neuroinflammation with elevated numbers of IBA1+ cells and axonal injury with APP+ cells. There was evidence of increased cell proliferation in the injured grafts acutely after injury that decreased with time. The injured grafts also showed evidence of phosphorylated tau aggregates and accumulation of PNAG, a polysaccharide associated with microbial pathogens. These results support the feasibility of using human organoid grafts in rats as a model of TBI, potentially including the study of long-term neurodegeneration and microbial penetration of the brain after injury.

Electromyography (EMG) is fundamental to clinical assessment, rehabilitation, neuromuscular research, and human-machine interfaces. Despite decades of use, no widely adopted standard exists for organizing and sharing EMG data, limiting reusability and large-scale data aggregation. We present EMG-BIDS, an extension to the Brain Imaging Data Structure (BIDS) that standardizes the organization of EMG recordings. EMG-BIDS addresses challenges unique to EMG, including diverse electrode types (surface or intramuscular, single channel to high-density arrays), heterogeneous electrode placements across anatomical locations, montages (e.g., monopolar or bipolar sensor designs), and the critical need for transparent documentation of sensor positioning. The specification introduces hierarchical coordinate systems that link local electrode grids to anatomical landmarks, enabling precise and reproducible placement documentation. EMG-BIDS is now part of BIDS as of version 1.11.0, supported by existing tools, including MNE-BIDS and EEGLAB. We demonstrate the specification through public datasets, including high-density surface EMG recordings. EMG-BIDS provides the foundation for FAIR (Findable, Accessible, Interoperable, Reusable) EMG data sharing, enabling meta-analyses, multi-site studies, and machine learning applications that require standardized, well-documented datasets.

Dental caries remains the most prevalent chronic condition globally, yet conventional diagnostic methods often fail to detect early lesions. Biophotonics, the study of light-tissue interactions, provides a new diagnostic pathway by exploiting the inherent optical properties of enamel and dentin. Over the past decades, research has connected laboratory spectroscopy, molecular chemistry and clinical imaging to define how light-based diagnostics can reveal the earliest biochemical signatures of demineralization. Conventional diagnostic methods, including visual examination and radiography, remain indispensable but are limited in their ability to detect early subsurface lesions, assess lesion activity and characterize the biological status of affected tissues. Recent advances in biophotonics can be exploited to generate clinically relevant biomarkers of disease initiation and progression. This review examines the translational pathway linking fundamental photonic phenomena in dental hard tissues to contemporary caries detection technologies and biologically guided treatment strategies. Emphasis is placed on light transmission and fluorescence-based technologies, fluorescence spectroscopy, Raman spectroscopy, multiphoton microscopy, second harmonic generation (SHG), two-photon excited fluorescence (2PEF) and optical coherence tomography (OCT). Experimental investigations have demonstrated that dentinal collagen degradation is associated with a progressive reduction in the SHG/2PEF ratio, while fluorescence and Raman studies have identified porphyrin derivatives and advanced glycation end-products as major contributors to the red fluorescence observed in active carious lesions. Beyond diagnosis, contemporary developments in minimally invasive dentistry increasingly integrate photonic biomarkers into the Bioactive Dental Concept, where lesion activity, cavitation status and individual caries risk guide the selection of preventive, minimally invasive and restorative interventions. Within this framework, photonic technologies may serve not only as diagnostic adjuncts but also as biological decision-support tools. Future integration of multimodal imaging, artificial intelligence and bioactive restorative materials may further enhance the precision and personalization of caries management. This evolution exemplifies the broader potential of biophotonics to bridge fundamental optical science and clinical oral healthcare.

The pervasive accumulation of micro(nano)plastics (MNPs) in the environment establishes them as persistent contaminants, posing a significant threat to ecosystem integrity and human health. This review synthesizes the environmental journey of MNPs by framing them as dynamic colloidal particles and mechanistically tracing their pathway from source to biological uptake. We discuss fundamental interfacial processes, including DLVO and non-DLVO interactions, straining, and air-water interface capture, governing MNP mobility and retention in porous media. These processes control MNP dispersal and potential to contaminate groundwater and agricultural systems. The interplay of colloidal properties (size, shape, surface chemistry) with environmental parameters is examined to explain exposure routes. We also detail how this colloidal behavior dictates bioavailability, facilitating MNP uptake in plants and soil fauna and amplifying their role as vectors for co-contaminants and antibiotic resistance genes. Human biomonitoring studies reveal MNPs in blood, stool, placenta, and bronchoalveolar lavage fluid. Systematic review evidence indicates associations with cardiovascular inflammation, endothelial dysfunction, and fibrosis; in vitro studies demonstrate PS MP-induced reductions in human sperm motility, vitality, and fertility-related gene expression; and cross-sectional studies link higher fecal MNP concentrations to gut microbiota dysbiosis, including increased abundance of harmful bacteria and decreased beneficial taxa. However, causation remains unestablished due to methodological heterogeneity and the predominance of cross-sectional designs. By integrating colloid science with ecotoxicology and exposure science, this review bridges the gap between MNP physical transport and adverse health outcomes, provides a framework for risk assessment, and highlights urgent research priorities, including standardized methods, longitudinal studies, and human-relevant models.

Cellular heterogeneity is a fundamental determinant of diverse physiological and pathological processes, yet its functional manifestation, the dynamic secretion of proteins, remains challenging to interrogate on the single-cell level. Traditional methods, while invaluable, are constrained by limited multiplexing capacity, inadequate temporal resolution, and reliance on specialized infrastructure, impeding the comprehensive dissection of cellular diversity. Microfluidic technologies have emerged as transformative platforms that address these limitations, enabling high-throughput, multiparameter secretion profiling with spatiotemporal precision. This review systematically synthesizes recent advances in microfluidic single-cell secretion analysis. We first examined the conceptual framework underlying cellular heterogeneity and the inherent constraints of conventional approaches. Subsequently, we analyze core microfluidic principles for single-cell manipulation, focusing on microstructures for isolation and strategies for capturing and quantifying the secreted proteins. We then explored the expanding applications of these technologies across biological and biomedical research. Finally, we discuss emerging opportunities at the convergence of microfluidics with multiomics integration and artificial intelligence, outlining future trajectories for this rapidly evolving field.

In recent years, extensive coalbed methane (CBM) development practices have shown that high-water-production CBM wells commonly suffer from low or even no gas production, which constitutes a major cause of inefficient CBM development. The characterization of cross-formational flow pathways for extraneous water leakage recharge and the analysis of water production mechanisms are critical for the efficient development of coalbed methane (CBM) resources in high-water-yield regions. This study integrates regional geological, geophysical, and CBM well production data sets from a typical high-water-yield district (i.e., Sanjiao coalbed methane field, east Ordos basin, China) to systematically investigate the water production mechanisms of CBM wells. Water-conducting channels between the coal seam and adjacent aquifers were precisely delineated via the coupling of seismic and well-logging data. A novel parameter, "water production per unit liquid level drop", was proposed to quantitatively assess the water production capacity of individual wells. Based on our previous fundamental research about water source identification and aquifer classification, multiple correlation analysis was performed to determine the main water-supplying layers and primary controlling factors of water production for wells targeting the No. 8 + 9 coal seam. The extent of regional structural deformation was quantified through trend surface analysis and stratigraphic attitude variation examination, then utilized in the mapping of water production risk in the study area. Results indicate that the produced water of CBM wells is predominantly derived from the limestone aquifers (i.e., L1, L2, L3, L4, and L5 limestone aquifers) of the Taiyuan Formation. The limestone aquifers exhibit strong heterogeneity in fracture development, with the L2-L4 aquifers demonstrating well vertical connectivity. The L1 and L4 aquifers are identified as the main water-producing layers, and water production is primarily governed by the cumulative width of vertical conductive channels. High water production risk is mainly distributed in areas with intense structural activities and well-developed conductive channels. Based on these findings, an extraneous water recharge model was established, incorporating the identified main water-producing layers and vertical fracture system characteristics. This model clarifies the geological mechanism by which fractures and faults regulate peripheral water intrusion into the coal seam, thereby elucidating the planar distribution pattern of water production in coal-bearing areas. These insights provide valuable theoretical and technical references for understanding high water production mechanisms and optimizing development strategies in this and other CBM blocks with similar geological backgrounds.