Bile-processed Coptidis Rhizoma（B-pCR）， first documented in Shengji Zonglu， is a unique processed products of Coptidis Rhizoma（CR） characterized by "mutual enhancement processing" and "enhancing the cold property of cold-natured herbs". Pig bile can enhance the bitter and cold properties of CR， yielding potent effects in purging excess fire from the liver and gallbladder. The processing increases the dissolution of alkaloids such as berberine， coptisine， and palmatine， while introducing bile acids from pig bile， including taurine-type and glycine-type cholic acids. This enhances its pharmacological effects， such as antipyretic activity， regulation of glucose and lipid metabolism disorders， and intestinal absorption. Traditional processing techniques and quality standards for B-pCR are outlined in the Shanghai Traditional Chinese Medicine（TCM） Decoction Pieces Processing Standard and the Gansu TCM Processing Standard. However， incomplete specifications for critical process parameters and quality criteria significantly impact its production and clinical application. A review of research over the past two decades on the processing history， process optimization， quality evaluation， material basis， and changes in pharmacological effects and properties of B-pCR reveals that the pretreatment method and dosage of pig bile， and processing temperature are key factors influencing its quality. Furthermore， current quality standards lack specific indicators. Additionally， the enhancement of the cold property and medicinal efficacy direction of B-pCR is not only associated with changes in alkaloid groups but also depend on the synergistic effects of bile acids. This review can provide insights for improving the quality evaluation system of B-pCR.

Retinal neovascular diseases represent a critical subset of retinal diseases that severely impair vision and can lead to blindness. In recent years, artificial intelligence(AI)has demonstrated breakthrough applications in the medical field, particularly in ophthalmology, leveraging its robust capabilities in image recognition and data analysis. Machine learning and deep learning, as core AI technologies, enable precise feature extraction from vast volumes of medical imaging data and the construction of predictive models, offering novel approaches for the auxiliary diagnosis and prognosis of retinal neovascular diseases. This review synthesizes the latest advancements in AI applications for neovascular retinal diseases, including diabetic retinopathy, retinal vein occlusion, retinopathy of prematurity, and age-related macular degeneration. It further discusses the limitations and challenges in clinical implementation. Through a comprehensive summary and analysis, this review aims to provide insights for advancing AI-driven diagnosis and treatment strategies, ultimately facilitating early detection and predictive management of these vision-threatening diseases.

In this paper， by referring to ancient and modern literature， the textual research of Inulae Flos has been conducted to clarify the name， origin， production area， quality evaluation， harvesting， processing and others， so as to provide reference and basis for the development and utilization of famous classical formulas containing this herb. After textual research， it could be verified that the medicinal use of Inulae Flos was first recorded in Shennong Bencaojing of the Han dynasty. In successive dynasties， Xuanfuhua has been taken as the official name， and it also has other alternative names such as Jinfeicao， Daogeng and Jinqianhua. The period before the Song and Yuan dynasties， the main origin of Inulae Flos was the Asteraceae plant Inula japonica， and from the Ming and Qing dynasties to the present， I. japonica and I. britannica are the primary source. In addition to the dominant basal species， there are also regional species such as I. linariifolia， I. helianthus-aquatili， and I. hupehensis. The earliest recorded production areas in ancient times were Henan， Hubei and other places， and the literature records that it has been distributed throughout the country since modern times. The medicinal part is its flower， the harvesting and processing method recorded in the past dynasties is mainly harvested in the fifth and ninth lunar months， and dried in the sun， and the modern harvesting is mostly harvested in summer and autumn when the flowers bloom， in order to remove impurities， dry in the shade or dry in the sun. In addition， the roots， whole herbs and aerial parts are used as medicinal materials. In ancient times， there were no records about the quality of Inulae Flos， and in modern times， it is generally believed that the quality of complete flower structure， small receptacles， large blooms， yellow petals， long filaments， many fluffs， no fragments， and no branches is better. Ancient processing methods primarily involved cleaning， steaming， and sun-drying， supplemented by techniques such as boiling， roasting， burning， simmering， stir-frying， and honey-processing. Modern processing focuses mainly on cleaning the stems and leaves before use. Regarding the medicinal properties， ancient texts describe it as salty and sweet in taste， slightly warm in nature， and mildly toxic. Modern studies characterize it as bitter， pungent， and salty in taste， with a slightly warm nature. Its therapeutic effects remain consistent across eras， including descending Qi， resolving phlegm， promoting diuresis， and stopping vomiting. Based on the research results， it is recommended that when developing famous classical formulas containing Inulae Flos， either I. japonica or I. britannica should be used as the medicinal source. Processing methods should follow formula requirements， where no processing instructions are specified， the raw products may be used after cleaning.

To gain an in-depth understanding of the clinical application of Rehmanniae Radix during the Qing Dynasty and to clarify its specifications and corresponding therapeutic effects， this study took Rehmanniae Radix in the prescriptions documented in Research on Medical Cases of the Qing Imperial Court as the research subject. According to historical medical literature， a comprehensive investigation was conducted on the specifications， therapeutic efficacy， frequency of use， dosage， and seasonal patterns of Rehmanniae Radix employed by imperial physicians. The findings revealed that Rehmanniae Radix in the medical cases of the Qing court was primarily classified into three categories： Xiaoshengdi， Zhongshengdi， and Dashengdi. Xiaoshengdi was also referred to as Xishengdi or Cishengdi， all denoting dried Rehmanniae Radix. The term Xishengdi was inconsistently defined in the literature. It should refer to the slender variant of dried Rehmanniae Radix and was utilized as a specific specification in the medical cases of the Qing court. In contrast， the wild fresh roots of Rehmanniae Radix， described as "as slender as fingers"， were commonly documented as fresh Rehmanniae Radix in these medical cases. There were variations in Rehmanniae Radix size and grading between historical and contemporary standards. Furthermore， therapeutic differences were observed among Rehmanniae Radix specifications in the medical cases of the Qing court. Xiaoshengdi and Zhongshengdi exhibited slightly stronger blood-cooling and heat-clearing effects while maintaining a non-cloying Yin-nourishing property. In contrast， Dashengdi demonstrated a greater emphasis on Yin supplementation with relatively milder heat-clearing activity. In the medical cases of the Qing court， the dosage of Rehmanniae Radix in different specifications was usually 11.2-18.7 g per dose， typically administered twice daily. Rehmanniae Radix in different specifications exhibits variations in efficacy， which can provide evidence-based insights for precise clinical application.

BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

BACKGROUND:Inter-limb asymmetry is a common phenomenon observed during human growth and development.Prolonged specialized training can lead to specific adaptations in inter-limb asymmetry among athletes.OBJECTIVE:To review the formation causes,manifestations,and impacts of inter-limb asymmetry on sports performance,and provide an overview of the relevant assessment methods and intervention strategies.METHODS:A literature search was conducted in the CNKI,WanFang,PubMed,and Web of Science databases from their inception to September 2024.The search terms included"asymmetry,asymmetries,asymmetric,asymmetrical,imbalance,strength,power,force,jump,sprint,athletic performance,anthropometry,injury"in English and Chinese.After excluding duplicate publications,irrelevant content,and conference papers,a total of 131 articles were finally included for analysis.RESULTS AND CONCLUSION:(1)Inter-limb asymmetry can be influenced by various factors including genetics,task demands,training regimens,injuries,fatigue,and limb preference.These factors lead to being primarily manifested in anatomical structure,strength performance,and task-specific asymmetry.(2)An increase in inter-limb asymmetry can result in impaired performance in bilateral in-phase symmetric movements.However,the relationship between increased inter-limb asymmetry and bilateral out-of-phase symmetric movements remains unclear and requires further investigation.(3)Training interventions have been shown to effectively mitigate inter-limb asymmetry,with unilateral training demonstrating superior outcomes compared with bilateral training.The choice of training methods and content should be tailored to meet the specific demands of the sport.(4)To further clarify the relationship between inter-limb asymmetry and athletic performance,it is recommended that future research adopt the concept of"task specificity"in inter-limb asymmetry.This includes standardizing study designs,selecting sensitive testing methods and indicators,unifying calculation methods to provide more high-quality evidence,and establishing categorized warning threshold standards for inter-limb asymmetry in different sports.

ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

Both hyperlipidemic acute pancreatitis and fatty liver disease are associated with lipid metabolism disorders and are commonly comorbid with each other in clinical practice. The pathogenesis of such comorbidity involves the interaction between multiple factors such as hypertriglyceridemia， metabolic syndrome， obesity， and insulin resistance， and these factors may form a vicious cycle and jointly promote disease progression. In clinical practice， hyperlipidemic acute pancreatitis is characterized by severe disease conditions， a high incidence rate of complications， a high mortality rate， and a tendency for recurrence， and it can easily lead to multi-organ damage and even multiple organ failure without timely treatment， posing a serious threat to the life of patients. Starting from the various signaling pathways associated with hyperlipidemic acute pancreatitis comorbid with fatty liver disease， this article discusses the potential molecular mechanisms of synergistic pathogenesis between hyperlipidemic acute pancreatitis and fatty liver disease， so as to provide a reference for the early prevention and treatment of such comorbidity.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.