ObjectiveTo identify potential influencing factors of urate crystal deposition at ankle/foot in patients with hyperuricemia （HUA）， and to analyze the predictive value of inflammatory indicators for urate crystal deposition in patients with different traditional Chinese medicine （TCM） syndromes， so as to provide potential reference for clinical risk assessment and individualized TCM intervention. MethodsA retrospective study was carried out with the enrollment of 231 HUA patients from The Third Affiliated People's Hospital of Fujian University of Traditional Chinese Medicine between January 2021 and December 2024. The enrolled patients were further divided into a crystal deposition-positive group （143 cases） and a crystal deposition-negative group （88 cases） according to the results of dual-energy computed tomography （CT）. Sociodemographic data， living habits， serum uric acid levels， and inflammatory indicators of the enrolled patients were collcted， and TCM syndrome differentiation was performed. Furthermore， univariate analysis was used to compare inter-group differences in clinical characteristics. MMultivariate Logistic regression was applied to identify the influencing factors of urate crystal deposition. In addition， the receiver operating characteristic （ROC） curves were plotted to evaluate the predictive efficacy of inflammatory indicators for crystal deposition across different TCM syndromes. ResultsThere were statistically significant inter-group differences in the proportion of males， age， body mass index， proportion of mental labor， rate of low water intake， and rate of high-sugar beverage consumption （P<0.05），whereas no significant difference in low exercise intensity was found between the two groups. Furthermore， compared with the negative group， the positive group had higher serum uric acid level， neutrophil-to-lymphocyte ratio （NLR）， and platelet-to-lymphocyte ratio （PLR）， but lower systemic immune-inflammation index （SIRI） （P<0.05）. Regarding the distribution of TCM syndromes， the positive group was dominated by the dampness-heat accumulation syndrome （55/143，38.46%）， while the negative group was mainly characterized by the phlegm-turbidity obstruction syndrome （44/88，50.00%）. Multivariate Logistic regression analysis revealed that high-sugar beverage consumption， elevated NLR， and elevated PLR were risk factors for urate crystal deposition ［odd ratio （OR） = 8.002， 5.377， 1.034， respectively； 95% CI 1.572-40.732， 2.179-13.270， 1.013-1.054，all P<0.05］， while SIRI was a protective factor （OR = 0.869， 95% CI 0.778-0.971， P<0.05）. In the positive group， patients with the dampness-heat accumulation syndrome exhibited the highest NLR， while the lowest PLR and SIRI， showing statistically significant differences with those of other syndromes （all P<0.05）. In addition， ROC curve analysis indicated that for the dampness-heat accumulation syndrome， the combined "NLR + PLR" model had an area under the curve （AUC） of 0.901 （95% CI 0.850-0.951， P<0.01）， with a sensitivity of 89.1% and a specificity of 79.5%； for the blood stasis-heat obstruction syndrome， the combined "NLR + PLR" model had an AUC of 0.880 （95% CI 0.825-0.934， P<0.01）， with a sensitivity of 100.0% and a specificity of 67.3%； for the liver-kidney Yin-deficiency syndrome， the single PLR model had an AUC of 0.842 （95% CI 0.731-0.952， P<0.01）， with a sensitivity of 83.3% and a specificity of 84.0%. ConclusionUrate crystal deposition in HUA patients exhibits intimate associations with high-sugar beverage consumption as well as elevated NLR and PLR levels. Meanwhile， TCM syndrome differentiation has potential correlation with inflammatory characteristics. The inflammatory indicator-based prediction model constructed based on TCM syndromes exhibits good predictive value.

ObjectiveThe development trend and knowledge structure of the research on human use experience （HUE） of traditional Chinese medicine （TCM） were systematically reviewed， and the core challenges and future directions were identified. This study aims to provide reference for the construction of a scientific and feasible research and development framework and evidence transformation system. MethodsLiterature related to "human use experience" published from January 1， 2019 to July 31， 2025 was retrieved from the China National Knowledge Infrastructure （CNKI）， Wanfang， China Science and Technology Journal Database （VIP）， and PubMed databases. Bibliometric visualization was conducted using Excel， VOSviewer， and CiteSpace， followed by in-depth reading and thematic summarization of core literature. ResultsA total of 181 papers were included for bibliometric analysis， with 45 articles used for in-depth thematic mining. The analysis showed that the number of publications on HUE research has increased in a stepwise manner over the past five years. Yang Zhongqi （24 times） was the core of the author network， the journal with the highest number of publications was China Journal of Chinese Materia Medica， the institutions publishing the most articles were mainly research institutions， regulatory agencies， hospitals， and universities， high-frequency keywords included "new TCM drugs"， "real-world studies"， and "clinical comprehensive evaluation"， keyword clustering analysis formed three major clusters： Policy orientation， application fields， and methodological approaches. Thematic analysis reveals that HUE-based evaluation should be integrated throughout the research and development process， encompassing three dimensions： TCM theory， clinical value， and pharmaceutical fundamentals， with toxic herbs and compatibility contraindications being key foci. Data collection primarily relies on empirical data， while real-world data constitute the primary source for clinical research， with efficacy and safety as the shared core. Data management emphasizes quality control and statistical analysis； however， the management of bias and confounding remains a critical bottleneck in evidence transformation. In practice， HUE-based approaches have successfully supported the registration and evaluation of multiple categories of new TCM drugs. ConclusionThe research on HUE of TCM has formed a policy-driven pattern characterized by， rapid development and close link with regulatory practice. A technical framework covering the whole chain of research and development has been constructed with clinical value as the core， which provides methodological basis and strategy reference for the scientific transformation of HUE of TCM from "experience" to "evidence".

OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

Objective: To explore the impact of different blood donation scenarios on population characteristics and blood donation behaviors, and to provide a basis for precise blood donation recruitment. Methods: Eligible voluntary blood donors with complete records from four scenarios in Xi'an: medical institutions, cultural tourism SITES, commercial superstores, and blood centers. After a preliminary analysis of overall donor characteristics across the four scenarios, three core subgroups were defined based on scenarios and donor population differences: the medical subgroup (aged 30-39 years), the blood center subgroup (aged 30-39 years), and the cultural tourism and commercial superstore subgroup (aged 18-29 years). Baseline characteristics, blood donation behaviors, and blood test results were compared among the subgroups. Results: The blood donors in all four scenarios were mainly male, but the proportion of female donors in the medical scenario was the highest (26.4%, 8 878/33 634). In terms of age distribution, the cultural tourism and commercial superstore scenarios were dominated by donors aged 18-29, while the blood center and medical scenarios were dominated by those aged 30-39, with the highest proportion of donors over 40 in the medical scenario. The occupational and educational composition of blood donors in the blood center scenario spanned a wide range, exhibiting a clear bipolar distribution. Significant differences were observed in baseline characteristics, blood donation behaviors, and blood test results among the three core subgroups (P<0.001). The medical subgroup was mainly composed of enterprise/industrial workers and married individuals, with high proportions of first-time blood donors, and the highest unqualified rate of infectious indicators (2.0%, 274/13 509). The cultural tourism and commercial superstore subgroup was mainly unmarried and students, featured high proportions of large-volume donations and evening donations, and had a relatively high unqualified rate for ALT (0.4%, 130/31 443). The blood center subgroup had a complex population structure, a high proportion of repeat blood donors (45.3%, 6449/14 225), and moderate results in all test indicators. Conclusion: There is an inherent correlation between the attributes of blood donation scenarios, population characteristics, and blood donation behaviors. The differences among the three core subgroups provide a clear basis for precise scenario operation. By constructing transformation channels between different scenarios and optimizing scenario-specific strategies, the structure of blood donors can be improved, thereby supporting the sustainable development of voluntary blood donation.

Although global brain science research has progressed rapidly in recent decades, several fundamental questions in neuroscience remain unresolved. In particular, the physical mechanism underlying neural signal transmission remains controversial, and the carriers responsible for neural information storage and retrieval have not yet been fully clarified. These unresolved issues motivate us to re-examine the processes of neural information generation, transmission, integration, storage, and retrieval from multiple perspectives. A key observation is that neural electromagnetic activities are closely associated with time. Their duration, temporal structure, and dynamic evolution play crucial roles in neural information processing. In this work, we analyze neural electromagnetic activities from the perspective of temporal scales (referred to here as the “time course”). By reviewing and integrating findings from previous studies, we examine the characteristic time requirements and dynamic features of neural processes occurring at different stages of information processing. These stages include neural signal generation, signal transmission along axons, synaptic integration, synaptic plasticity, and memory formation and retrieval. Based on this temporal analysis, we outline a framework describing neural electromagnetic activities across a wide range of time scales, spanning from microseconds to minutes, hours, or even longer periods associated with long-term memory, which suggests that neural information processing involves multiple physical processes operating at different time levels. Rapid electromagnetic events may occur on microsecond scales, whereas electrophysiological phenomena such as action potentials typically last on the order of milliseconds. Longer time scales are associated with synaptic plasticity and memory-related processes. From this perspective, we propose that the physical carrier of neural information may be transient electromagnetic pulses with durations on the microsecond scale. In this framework, action potentials can be interpreted as the macroscopic electrophysiological manifestation of underlying electromagnetic processes triggered by ionic currents across neuronal membranes. Rather than being the fundamental neural signal itself, the action potential may represent a measurable membrane-level response associated with the successful activation of these electromagnetic events. Moreover, we discuss a possible mechanism for long-term memory storage. Considering the apparent temporal contradiction between the millisecond-scale excitation of neurons and the long-term persistence of memories, we believe that long-term memory information may be stored within neural network topologies formed by electrical synapse coupling. Such structures, referred to as electrically coupled memory networks (ECMNs), may enable neurons within the same network to respond rapidly and synchronously to stimuli, thereby facilitating efficient memory retrieval. Overall, this study emphasizes the importance of considering the temporal organization of neural electromagnetic activities when interpreting neural signaling mechanisms. It may provide new insights into the physical nature of neural information carriers and the mechanisms of memory storage and retrieval. Furthermore, highlighting the potential role of electromagnetic interactions in neural activity may contribute to the development of new theoretical frameworks and experimental approaches in neuroscience. Such perspectives may also offer valuable references for future research on neural coding, brain function mechanisms, and neuromodulation technologies.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Sarcopenia is a clinical syndrome characterized by a decrease in skeletal muscle strength and quality， often accompanied by adverse outcomes such as falls， loss of function and weakness. The pathogenesis of sarcopenia is complex， and studies have shown that dysfunction due to impaired mitochondrial quality control is an important pathological factor in the occurrence and development. Traditional Chinese medicine（TCM） has been widely favoured for regulating mitochondrial homeostasis and preventing sarcopenia by virtue of its multi-target and multi-pathway advantages. They can play a role in the prevention and treatment of sarcopenia by regulating the mitochondrial quality control system to inhibit the occurrence of mitochondrial oxidative stress， regulate the balance of mitochondrial dynamics， inhibit mitochondrial autophagy， promote mitochondrial biosynthesis， resist the occurrence of mitochondrial apoptosis， and maintain the mitochondrial calcium and protein homeostasis. Based on this， the paper reviewed the relationship between mitochondrial quality control and sarcopenia， as well as the mechanism of TCM in intervening the mitochondrial quality control system to treat sarcopenia， in order to provide a new idea for the prevention and treatment of sarcopenia by TCM and to a theoretical basis for the clinical research on TCM intervention in sarcopenia.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

Objective To establish a method for predicting the risk of endometrial cancer(EC)and endometrial atypical hyperplasia(AH)in women with postmenopausal bleeding(PMB)by collecting clinical data on routine medical history.Methods The clinical data of a total of 408 PMB patients admitted to Fuxing Hospital,Capital Medical University were consecutively collected in this retrospective study from December 2013 to December 2023.According to the results of endometrial pathology,patients were divided into case group and control group.EC and AH were included in the malignant group(case group)and the other endometrial pathologies were included in the non-malignant group(control group).Clinical data,including clinical history,high risk factors,and common gynecological ultrasound measurement indicators,were collected and studied by univariate and multivariate Logistic regression analysis.Results The mean age of 408 patients was(60.4±7.8)years.A total of 74 cases(18.1％)were in case group and 334 cases(81.9％)were in control group.Based on Logistic regression analysis,the best predictors of endometrial malignant lesions were selected to create a"LRDNT"(light bleeding,recurrent bleeding,diabetes,non-uniform echogenicity & thickness)model.LRDNT scores range from 0 to 22.The score of LRDNT ≥15 has the largest Yoden index,and the sensitivity to predict endometrial malignant lesions is 79.73％,the specificity is 80.84％,and the prediction accuracy is 80.64％.Conclusions The risk prediction model LRDNT,which combines clinical information and common gynecological ultrasound measurement indicators of PMB patients,can help clinicians classify patients at high and low risk of endometrial malignant lesions,and optimize the strategy of diagnosis and treatment.