The clustered regularly interspaced short palindromic repeats (CRISPR)/associated protein 9 (CRISPR /Cas9) immune system is an adaptive immune system widely distributed in bacteria and archaea. It precisely defends against invasion by exogenous phages, viruses, and plasmids through sequence-specific endogenous immune response mechanisms. As the most prominent member of this family, the CRISPR/Cas9 system has evolved into the most widely applied, flexible, and efficient technical platform in the field of genome engineering due to its exceptional genome modification capabilities. Within the CRISPR/Cas9 system, the Cas9 protein, precisely guided by a single-stranded guide RNA (gRNA), can specifically recognize target DNA sequences and induce double-strand breaks. This activates the cell’s DNA repair mechanisms, enabling gene knockout, knock-in, or modification. Demonstrating significant advantages in specificity, flexibility, and operability, CRISPR/Cas9 technology has shown immense potential in the medical field, opening new avenues for modernizing traditional Chinese medicine (TCM) research. On one hand, this technology can be used to construct precise disease models and tailor personalized treatment plans. It enables in-depth elucidation of the molecular mechanisms underlying the action targets and signaling pathways of TCM formulas and active components, thereby unraveling the scientific secrets of their complex mechanisms of action. On the other hand, it demonstrates powerful tool value in improving TCM germplasm resources, identifying and screening superior varieties, evaluating the controllability of TCM quality, and producing innovative drugs, providing technical support for the standardization and precision of TCM. Simultaneously, the high-throughput omics data generated by CRISPR technology is driving artificial intelligence (AI) to construct virtual disease models and drug prediction systems. This empowers the intelligent screening of effective TCM components, the precise prediction of potential targets, and the exploration of “reducing toxicity while enhancing efficacy” through formula combinations. This synergistic innovation between CRISPR and AI aligns perfectly with precision medicine’s urgent demand for personalized, efficient drug development, injecting new momentum into the modernization and transformation of TCM. This paper first systematically reviews and explains the developmental trajectory, structural basis, and action mechanisms of the CRISPR/Cas9 system, tracing its scientific evolution from a bacterial immune system to a gene-editing tool. It then comprehensively outlines the current state of convergence between precision medicine concepts and modernization research in TCM, analyzing the synergistic points and potential spaces for their integration. Against the backdrop of rapid precision medicine advancement, this paper emphasizes how CRISPR/Cas9 gene editing technology empowers in-depth analysis of TCM mechanisms—including specific applications in disease model construction, therapeutic target validation, and multi-target network regulation studies. It further elaborates on its multidimensional practical contributions to modernizing TCM, spanning key domains such as germplasm resource innovation, bioactive compound biosynthesis, quality standardization control, and novel TCM drug development. Finally, this paper envisions the future landscape of deep integration between CRISPR technology and AI: from data-driven intelligent drug screening to high-throughput precision discovery of effective TCM components, and further to intelligent model construction based on “reducing toxicity while enhancing efficacy” mechanisms. The synergistic convergence of these multidimensional technologies will pioneer new scientific paradigms and translational pathways for TCM modernization, propelling TCM toward leapfrogging development in the era of precision medicine.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

Objective To evaluate the cost–utility of lecanemab and donanemab in the treatment of early Alzheimer’s disease （AD） in China. Methods A Markov model was developed from a societal perspective to compare standard of care （SOC）, lecanemab plus SOC, and donanemab plus SOC in terms of costs, quality-adjusted life years （QALY）, and incremental cost–utility ratios （ICUR）. Deterministic and probabilistic sensitivity analyses were conducted to assess parameter uncertainty. Results Both intervention strategies increased QALY compared with SOC but were associated with substantially higher costs, and neither was cost-effective under the current willingness-to-pay threshold. Conclusion Lecanemab and donanemab may be more appropriately considered within a multi-tiered healthcare reimbursement framework in China rather than relying solely on basic medical insurance.

Objective: Introduce and briefly describe the status, characteristics, and writing ideas of general notice in the Chinese Pharmacopoeia 2025 edition, providing reference and suggestions for better understanding and implementation of the Chinese Pharmacopoeia 2025 edition.
Methods:This article elaborates on the content and revision of general notice in the Chinese Pharmacopoeia 2025 edition from the perspective of frame structure and main contents.
Results:Compared with other pharmacopoeias of various countries, Chinese Pharmacopoeia includes standards for traditional Chinese medicine, chemical drugs, biological products and excipients, pharmaceutical packaging materials, etc. Each section of Chinese Pharmacopoeia has its own general notice, with 34 to 48 items arranged in 11 to 12 chapters. Depending on the type of products included and the development history, the general notice in each section present differences in format and content. Given the importance and significance of the standards in Chinese Pharmacopoeia, it is necessary for the industry to coordinate and unify the general notice in various parts of Chinese Pharmacopoeia. With the introduction and revision of regulations, changes in the content of pharmacopoeias, and the application of new technologies, methods, and concepts in drug quality control, considering the unique characteristics of various drugs in quality control and supervision, Chinese Pharmacopoeia has comprehensively standardized relevant requirements. While taking into account the characteristics of the first, second, third, and fourth parts of the pharmacopoeia, it retains the characteristics of relative uniformity and the content of each part, achieving the unified standardization of the general rules of each general notice in the Chinese Pharmacopoeia 2025 edition and the coordination and consistency of common content.
Conclusion: The current version of Chinese Pharmacopoeia has undergone significant changes and improvements in both form and content. By introducing the overall situation and revised content of general notice in the Chinese Pharmacopoeia 2025 edition, pharmacopoeia users can have a deeper understanding of Chinese Pharmacopoeia and use it correctly.

The triterpenoid saponins of Centella asiatica, including asiaticoside, madecassoside, asiatic acid, and madecassic acid, are pivotal bioactive compounds of the plant. These constituents exhibit a spectrum of pharmacological activities, such as antioxidant, antitumor, and antidepressant effects, promotion of wound healing, and enhancement of microcirculation. Owing to these therapeutic properties, C. asiatica is widely employed in pharmaceutical and cosmetic industries. However, the escalating global demand for its extracts has led to potential supply shortages, prompting researchers to use multiple strategies such as multi-omics, molecular biology, and synthetic biology to conduct extensive studies. These studies encompass the elucidation of the biosynthetic pathways of triterpenoid saponins in C. asiatica, metabolic regulation, the hormonal induction of secondary metabolite synthesis, and the application of biotechnological strategies for natural product production to increase the yield of secondary metabolites in C. asiatica, or to produce active components via microbial chassis, thus satisfying market demands and promoting the sustainable exploitation of wild C. asiatica resources. This article first introduced the triterpenoid saponins of C. asiatica and their biological activities, then summarized the latest research advancements in their biosynthetic pathways, metabolic regulation, and heterologous biosynthesis, and provided an outlook on future development directions, with the aim of providing reference for comprehensive resource development and biotechnological synthesis of active components from C. asiatica.
Centella/genetics* ; Triterpenes/chemistry* ; Biosynthetic Pathways ; Humans ; Drugs, Chinese Herbal/chemistry* ; Plant Extracts

This study aims to explore the impact of host plants on the quality of Taxilli Herba and provide a theoretical basis for the quality control of Taxilli Herba. The components of Taxilli Herba from three different host plants(Morus alba, Salix babylonica, and Cinnamomum cassia) and its 3 hosts(mulberry branch, willow branch, and cinnamon branch) were detected by widely targeted metabolomics based on ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS). Principal component analysis(PCA), orthogonal partial least squares discriminant analysis(OPLS-DA), and Venn diagram were employed for analysis. A total of 717 metabolites were detected in Taxilli Herba from the three host plants and the branches of these host plants by UPLC-MS/MS. The results of PCA and OPLS-DA of Taxilli Herba from the three different host plants showed an obvious separation trend due to the different effects of host plants. The Venn diagram showed that there were 32, 8, and 26 characteristic metabolites in samples of Taxilli Herba from M. alba host, S. babylonica host, and C. cassia host, respectively. It was found by comparing the characteristic metabolites of Taxilli Herba and its hosts that each host transmits its characteristic components to Taxilli Herba, so that the Taxilli Herba contains the characteristic components of the host. The Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis showed that the differential metabolites of Taxilli Herba from the three hosts were mainly enriched in flavonoid biosynthesis, arginine and proline metabolism, and glycolysis/gluconeogenesis pathways. Furthermore, the differential metabolites enriching pathways of Taxilli Herba from the three hosts were different depending on the host. In a word, host plants have a significant impact on the metabolites of Taxilli Herba, and it may be an important factor for the quality of Taxilli Herba.
Metabolomics/methods* ; Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Quality Control ; Salix/chemistry* ; Cinnamomum aromaticum/metabolism* ; Principal Component Analysis

Since the promulgation of the first Drug Administration Law of the People's Republic of China 40 years ago in 1984, China has undergone four main stages in the traditional Chinese medicine(TCM) regulation: the initial establishment of TCM regulation rules(1984-1997), the formation of a modern TCM regulatory system(1998-2014), the reform of the review and approval system for new TCM drugs(2015-2018), and the construction of a scientific regulation system for TCM(2019-2024). Over the past five years, a series of milestone achievements of TCM regulation in China have been achieved in the six aspects, including its strategic objectives and the establishment of a science-based regulatory system, the reform of the review and approval system for new TCM drugs, the optimization and improvement of the TCM standard system and its formation mechanism, comprehensive enhancement of regulatory capabilities for TCM safety, international harmonization of TCM regulation and its role in promoting innovation. Looking ahead, centered on advancing TCMRS to establish a sound regulatory framework tailored to the unique characteristics of TCM, TCM regulation will evolve into new reform patterns, advancing and extending across eight critical fronts, including the legal framework and policy architecture, the review and approval system for new TCM drugs, the quality standard and management system of TCM, the comprehensive quality & safety regulation and traceability system, the research and transformation system for TCMRS, AI-driven innovations in TCM regulation, the coordination between high-quality industrial development and high-level regulation, and the leadership in international cooperation and regulatory harmonization. In this way, a unique path for the development of modern TCM regulation with Chinese characteristics will be pioneered.
Humans ; China ; Drugs, Chinese Herbal/standards* ; History, 20th Century ; History, 21st Century ; Medicine, Chinese Traditional/trends*

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures

PURPOSE: To investigate the incidence and influencing factors of bone loss in patients with spinal cord injury (SCI). METHODS: A retrospective case-control study was conducted. Patients with SCI in our hospital from January 2019 to March 2023 were collected. According to the correlation between bone mineral density (BMD) at different sites, the patients were divided into the lumbar spine group and the hip joint group. According to the BMD value, the patients were divided into the normal bone mass group (t > -1.0 standard deviation) and the osteopenia group (t ≤ -1.0 standard deviation). The influencing factors accumulated as follows: gender, age, height, weight, cause of injury, injury segment, injury degree, time after injury, start time of rehabilitation, motor score, sensory score, spasticity, serum value of alkaline phosphatase, calcium, and phosphorus. The trend chart was drawn and the influencing factors were analyzed. SPSS 26.0 was used for statistical analysis. Correlation analysis was used to test the correlation between the BMD values of the lumbar spine and bilateral hips. Binary logistic regression analysis was used to explore the influencing factors of osteoporosis after SCI. p < 0.05 was considered statistically significant. RESULTS: The incidence of bone loss in patients with SCI was 66.3%. There was a low concordance between bone loss in the lumbar spine and the hip, and the hip was particularly susceptible to bone loss after SCI, with an upward trend in incidence (36% - 82%). In this study, patients with SCI were divided into the lumbar spine group (n = 100) and the hip group (n = 185) according to the BMD values of different sites. Then, the lumbar spine group was divided into the normal bone mass group (n = 53) and the osteopenia group (n = 47); the hip joint group was divided into the normal bone mass group (n = 83) and the osteopenia group (n = 102). Of these, lumbar bone loss after SCI is correlated with gender and weight (p = 0.032 and < 0.001, respectively), and hip bone loss is correlated with gender, height, weight, and time since injury (p < 0.001, p = 0.015, 0.009, and 0.012, respectively). CONCLUSIONS The incidence of bone loss after SCI was high, especially in the hip. The incidence and influencing factors of bone loss in the lumbar spine and hip were different. Patients with SCI who are male, low height, lightweight, and long time after injury were more likely to have bone loss.
Humans ; Spinal Cord Injuries/complications* ; Male ; Female ; Retrospective Studies ; Incidence ; Adult ; Bone Density ; Middle Aged ; Case-Control Studies ; Osteoporosis/etiology* ; Lumbar Vertebrae ; Bone Diseases, Metabolic/etiology* ; Aged ; Risk Factors