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.

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".

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.

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

The continuous emergence of SARS-CoV-2 variants as well as other potential future coronavirus has challenged the effectiveness of current COVID-19 vaccines. Therefore, there remains a need for alternative antivirals that target processes less susceptible to mutations, such as the formation of six-helix bundle (6-HB) during the viral fusion step of host cell entry. In this study, a novel high-throughput screening (HTS) assay employing a yeast-two-hybrid (Y2H) system was established to identify inhibitors of HR1/HR2 interaction. The compound IMB-9C, which achieved single-digit micromolar inhibition of SARS-CoV-2 and its Omicron variants with low cytotoxicity, was selected. IMB-9C effectively blocks the HR1/HR2 interaction in vitro and inhibits SARS-CoV-2-S-mediated cell-cell fusion. It binds to both HR1 and HR2 through non-covalent interaction and influences the secondary structure of HR1/HR2 complex. In addition, virtual docking and site-mutagenesis results suggest that amino acid residues A930, I931, K933, T941, and L945 are critical for IMB-9C binding to HR1. Collectively, in this study, we have developed a novel screening method for HR1/HR2 interaction inhibitors and identified IMB-9C as a potential antiviral small molecule against COVID-19 and its variants.

OBJECTIVES: To evaluate the association of GGN repeat polymorphism of androgen receptor (AR) with ovarian reserve and ovarian response in controlled ovarian stimulation (COS). METHODS: This genetic association study was conducted among a total of 361 women aged ≤40 years with basal FSH≤12 U/L undergoing the GnRH-agonist long protocol for COS in a university-affiliated IVF center. GGN repeat in the AR gene was analyzed with Sanger sequencing. The primary endpoint was the number of antral follicle counts (AFCs), and the secondary endpoints were stimulation days, total dose of gonadotropin (Gn) used, total number of retrieved oocytes, ovarian sensitivity index, and follicular output rate. RESULTS: The GGN repeat in exon 1 of the AR gene ranged from 13 to 24, and the median repeat length was 22. Based on the genotypes (S for GGN repeats <22, L for GGN repeats ≥22), the patients were divided into 3 groups: SS, SL, and LL. Generalized regression analysis indicated that the number of AFCs in group SS was significantly lower than those in group SL (adjusted β=1.8, 95% CI: 0.2-3.4, P=0.024) and group LL (adjusted β=1.5, 95% CI: 0.2-2.7, P=0.021). No significant difference was observed in the number of AFCs between group SL and group LL (P>0.05). Generalized regression analysis indicated no significant differences in ovarian stimulation parameters among the 3 groups, either before or after adjusting for confounding factors (P>0.05). CONCLUSIONS GGN repeat length on the AR gene is associated with AFC but not with ovarian response in Chinese women, indicating that AR gene polymorphisms may affect ovarian reserve.
Adult ; Female ; Humans ; Genotype ; Ovarian Follicle/cytology* ; Ovarian Reserve/genetics* ; Ovulation Induction/methods* ; Polymorphism, Genetic ; Receptors, Androgen/genetics* ; East Asian People/genetics*

Direct electrical stimulation of the human cortex can produce subjective visual sensations, yet these sensations are unstable. The underlying mechanisms may stem from differences in electrophysiological activity within the distributed network outside the stimulated site. To address this problem, we recruited 69 patients who experienced visual sensations during invasive electrical stimulation while intracranial electroencephalography (iEEG) data were recorded. We found significantly flattened power spectral slopes in distributed regions involving different brain networks and decreased integrated information during elicited visual sensations compared with the non-sensation condition. Further analysis based on minimum information partitions revealed that the reconfigured network interactions primarily involved the inferior frontal cortex, posterior superior temporal sulcus, and temporoparietal junction. The flattened power spectral slope in the inferior frontal gyrus was also correlated with integrated information. Taken together, this study indicates that the altered electrophysiological signatures provide insights into the neural mechanisms underlying subjective visual sensations.
Humans ; Male ; Female ; Adult ; Visual Perception/physiology* ; Electric Stimulation ; Middle Aged ; Young Adult ; Electrocorticography ; Electroencephalography ; Brain Mapping