Intelligent prescription recommendation has become an important research direction in traditional Chinese medicine (TCM), offering new opportunities to support clinical decision-making and promote the modernization of TCM practice. With the rapid development of artificial intelligence (AI), a variety of computational approaches have been proposed to learn prescription patterns from clinical data and generate personalized treatment recommendations. However, despite increasing research activity, systematic and comprehensive reviews of AI-driven methods for TCM prescription recommendation remain limited. In this study, we present a comprehensive review of computational approaches for herbal prescription recommendation (HPR) in TCM. Existing methods are systematically categorized into several major paradigms, including traditional machine learning methods, topic model methods, sequential generative methods, deep learning and graph-based methods, and large language model–based frameworks. In addition to summarizing methodological developments, we also review commonly used public datasets and evaluation metrics in this field. Furthermore, representative models with publicly available implementations are experimentally evaluated on multiple benchmark datasets to provide a comparative analysis of their performance on the HPR task. Finally, we discuss the key challenges that hinder the practical deployment of intelligent prescription recommendation systems, including data heterogeneity, limited interpretability, and insufficient integration of TCM domain knowledge. Future research directions are outlined to facilitate the development of more reliable, interpretable, and clinically applicable AI-assisted HPR systems for TCM.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

As China accelerates its efforts in deep space exploration and long-duration space missions, including the operationalization of the Tiangong Space Station and the development of manned lunar missions, safeguarding astronauts’ physiological and cognitive functions under extreme space conditions becomes a pressing scientific imperative. Among the multifactorial stressors of spaceflight, microgravity emerges as a particularly potent disruptor of neurobehavioral homeostasis. Dopamine (DA) plays a central role in regulating behavior under space microgravity by influencing reward processing, motivation, executive function and sensorimotor integration. Changes in gravity disrupt dopaminergic signaling at multiple levels, leading to impairments in motor coordination, cognitive flexibility, and emotional stability. Microgravity exposure induces a cascade of neurobiological changes that challenge dopaminergic stability at multiple levels: from the transcriptional regulation of DA synthesis enzymes and the excitability of DA neurons, to receptor distribution dynamics and the efficiency of downstream signaling pathways. These changes involve downregulation of tyrosine hydroxylase in the substantia nigra, reduced phosphorylation of DA receptors, and alterations in vesicular monoamine transporter expression, all of which compromise synaptic DA availability. Experimental findings from space analog studies and simulated microgravity models suggest that gravitational unloading alters striatal and mesocorticolimbic DA circuitry, resulting in diminished motor coordination, impaired vestibular compensation, and decreased cognitive flexibility. These alterations not only compromise astronauts’ operational performance but also elevate the risk of mood disturbances and motivational deficits during prolonged missions. The review systematically synthesizes current findings across multiple domains: molecular neurobiology, behavioral neuroscience, and gravitational physiology. It highlights that maintaining DA homeostasis is pivotal in preserving neuroplasticity, particularly within brain regions critical to adaptation, such as the basal ganglia, prefrontal cortex, and cerebellum. The paper also discusses the dual-edged nature of DA plasticity: while adaptive remodeling of synapses and receptor sensitivity can serve as compensatory mechanisms under stress, chronic dopaminergic imbalance may lead to maladaptive outcomes, such as cognitive rigidity and motor dysregulation. Furthermore, we propose a conceptual framework that integrates homeostatic neuroregulation with the demands of space environmental adaptation. By drawing from interdisciplinary research, the review underscores the potential of multiple intervention strategies including pharmacological treatment, nutritional support, neural stimulation techniques, and most importantly, structured physical exercise. Recent rodent studies demonstrate that treadmill exercise upregulates DA transporter expression in the dorsal striatum, enhances tyrosine hydroxylase activity, and increases DA release during cognitive tasks, indicating both protective and restorative effects on dopaminergic networks. Thus, exercise is highlighted as a key approach because of its sustained effects on DA production, receptor function, and brain plasticity, making it a strong candidate for developing effective measures to support astronauts in maintaining cognitive and emotional stability during space missions. In conclusion, the paper not only underscores the centrality of DA homeostasis in space neuroscience but also reflects the authors’ broader academic viewpoint: understanding the neurochemical substrates of behavior under microgravity is fundamental to both space health and terrestrial neuroscience. By bridging basic neurobiology with applied space medicine, this work contributes to the emerging field of gravitational neurobiology and provides a foundation for future research into individualized performance optimization in extreme environments.

ObjectiveTo explore the potential mechanism of Huoxue Xiaoyi Formula （活血消异方， HXF） in treating ovarian endometriosis （OEM） from the perspective of T follicular helper （Tfh） cells and the Janus kinase/signal transducer and activator of transcription （JAK/STAT） signaling pathway. MethodsForty-five female SD rats with normal estrous cycles were randomly divided into three groups， HXF group， model group， and normal group， with 15 rats in each group. A rat model of OEM was established by autologous endometrial tissue implantation. After successful modeling， the treatment group received HXF at 5.85 g/（kg·d） by gavage for 14 consecutive days. The model group and normal group received 1 mL/d of normal saline by gavage. RNA-sequencing data from human proliferative-phase endometriotic and normal endometrial tissues were downloaded from the GEO database. Transcriptomic sequencing was used to analyze gene expression in rat ovarian ectopic tissues and normal uterine tissues， and comparisons were made with human data to verify JAK/STAT pathway activation in proliferative-phase ectopic tissues. Immunohistochemistry was used to detect the positive expression of CXC chemokine receptor 5 （CXCR5） and interleukin-21 （IL-21） in rat ovarian ectopic and normal uterine tissues. Western Blotting was performed to detect the protein levels of IL-21， IL-21 receptor （IL-21R）， Janus kinase 1 （JAK1）， signal transducer and activator of transcription 6 （STAT6）， and B-cell lymphoma 2 （Bcl-2）. Tfh cell infiltration was analyzed using immune cell infiltration methods. ResultsGene set enrichment analysis showed that the JAK/STAT pathway was significantly activated in human proliferative-phase endometriotic tissues compared to normal endometrial tissues. Similarly， the JAK/STAT pathway was markedly activated in rat ovarian ectopic tissues in the model group compared to the normal group， but suppressed in the HXF group compared to the model group. Compared with normal uterine tissues， ovarian ectopic tissues in the model group showed increased Tfh cell infiltration scores， higher CXCR5 and IL-21 expression， and elevated levels of IL-21， IL-21R， JAK1， STAT6， and Bcl-2 proteins. Compared with the model group， HXF group showed reduced CXCR5 and IL-21 expression and decreased protein levels of IL-21， IL-21R， JAK1， STAT6， and Bcl-2. ConclusionHXF may suppress activation of the JAK/STAT signaling pathway in ovarian endometriotic tissues by inhibiting IL-21 secretion from Tfh cells.

Objective:To investigate the efficacy of radiotherapy in patients with advanced esophageal cancer receiving first-line chemoimmunotherapy.Methods:A retrospective analysis was conducted on the data of 137 patients with Stage Ⅳ esophageal squamous cell carcinoma (ESCC) treated at our hospital from January 2018 to May 2023. These patients were divided into two groups: a group treated with first-line chemoimmunotherapy combined with radiotherapy (chemoimmunotherapy + radiotherapy group, n = 43) and a group treated with only chemoimmunotherapy ( n = 94). Inverse probability of treatment weighting (IPTW) was applied to balance baseline characteristics between the groups. With overall survival (OS) and progression-free survival (PFS) as study endpoints, the survival data were analyzed using the Kaplan-Meier method, the log-rank test, and the Cox regression method. Results:Before calibration, the chemoimmunotherapy + radiotherapy group significantly outperformed the sole chemoimmunotherapy group in median PFS (13.6 months vs. 7.0 months; HR: 0.501, 95% CI: 0.309-0.811, P = 0.005). After calibration using the COX proportional-hazards model for age, gender, Eastern Cooperative Oncology Group (ECOG) performance status, smoking history, T/N/M stage, and tumor location, the chemoimmunotherapy + radiotherapy group still had significant advantages in PFS (14.7 months vs. 7.0 months; HR: 0.441, 95% CI: 0.261-0.745, P = 0.002). IPTW analysis further confirmed this trend (13.9 months vs. 7.0 months; HR: 0.492, 95% CI: 0.304-0.795, P < 0.001). Specifically, the median OS of the chemoimmunotherapy + radiotherapy group demonstrated significant improvement in all analyses: pre-calibration (29.5 months vs. 18.0 months; HR: 0.507, 95% CI: 0.297-0.867, P = 0.013), after calibration using the Cox model (27.5 months vs. 16.7 months; HR: 0.470, 95% CI: 0.266-0.830, P = 0.009), and after calibration using IPTW (29.5 months vs. 16.9 months; HR: 0.448, 95% CI: 0.262-0.764, P < 0.001). Conclusions:The combination of radiotherapy and first-line chemoimmunotherapy can significantly improve survival outcomes of patients with advanced ESCC, suggesting its potential as a standard treatment strategy.

Hand degloving injury represents one of the most severe forms of hand trauma, characterised by challenging treatment and a complex prognostic outcome. It is crucial to effectively utilise the degloved tissues in emergency or primary repair of a hand degloving injury. This consensus provides a comprehensive review of the existing literature on definition, classification, emergency assessment, debridement, judgment of skin viability, in situ repair of the degloved skin, and adjunctive treatment for degloving injury of hand. Based on conclusion of both domestic and international experiences, this expert consensus on the classification of hand degloving injury and the emergency repair with the avulsed skin is established, aiming to provide a guidance to surgeons on standardised treatment strategy and improve the management of hand degloving injury.

Objective To investigate the correlation between arterial stiffness(AS)and incident chronic kidney disease(CKD)among the elderly individuals taking health checkup.Methods A retrospective study was conducted on 857 elderly individuals without CKD at baseline who taking physical exams in our medical center from December 2009 to May 2021.Their clinical and labora-tory data were collected.Brachial-ankle pulse wave velocity(baPWV)was used to assess the se-verity of AS,and then the subjects were divided into normal elasticity group(201 cases),and moderate(490 cases)and severe AS group(166 cases).Kaplan-Meier curves were plotted to dis-play cumulative incidence rates of incident CKD across different AS groups.Restricted cubic splines(RCS)and Cox regression models were applied to analyze the correlation of baPWV and incident CKD risk.Results The severe AS group had significantly advanced age,greater ratio of hypertension,larger waist circumference,higher HR,SBP and DBP,increased urinary albumin/creatinine ratio(UACR),elevated levels of TG and fasting blood glucose,and baPWV than the normal elasticity group(P＜0.05).During the follow-up period,37 participants developed CKD.The incidence of CKD was obviously higher in the severe AS group than the normal arterial elas-ticity group(9.04％vs 3.48％).RCS analysis revealed a U-shaped relationship between baPWV and incident CKD risk.When baPWV ≥1 400 cm/s,each standard deviation increase in baPWV indicates the risk of incident CKD increasing by 71％(HR=1.71,95％CI:1.30-2.25,P＜0.01).Regardless of adjustment for covariates or not,baPWV remained positive correlation with inci-dent CKD risk(P＜0.05).Conclusion Among the elderly individuals undergoing health check-up,increased AS severity is significantly associated with higher risk of incident CKD when baP-WV ≥1400 cm/s.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Human NAD(P)H: quinone oxidoreductase 1 (NQO1) is a flavoenzyme expressed at high levels in multiple solid tumors, making it an attractive target for anticancer drugs. Bioactivatable drugs targeting NQO1, such as β-lapachone (β-lap), are currently in clinical trials for the treatment of cancer. β-Lap selectively kills NQO1-positive (NQO1⁺) cancer cells by inducing reactive oxygen species (ROS) via catalytic activation of NQO1. In this study, we demonstrated that cryptotanshinone (CTS), a naturally occurring compound, induces NQO1-dependent necrosis without affecting NQO1 activity. CTS selectively kills NQO1⁺ cancer cells by inducing NQO1-dependent necrosis. Interestingly, CTS directly binds to NQO1 but does not activate its catalytic activity. In addition, CTS enables activation of JNK1/2 and PARP, accumulation of iron and Ca²⁺, and depletion of ATP and NAD⁺. Furthermore, CTS selectively suppressed tumor growth in the NQO1⁺ xenograft models, which was reversed by NQO1 inhibitor and NQO1 shRNA. In conclusion, CTS induces NQO1-dependent necrosis via the JNK1/2/iron/PARP/NAD⁺/Ca²⁺ signaling pathway. This study demonstrates the non-enzymatic function of NQO1 in inducing cell death and provides new avenues for the design and development of NQO1-targeted anticancer drugs.