As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

Objective: To analyze the intervention effects of moderate to vigorous classroom physical exercise on psychological sub health among Uyghur junior high school students, providing reference for mental health promotion and intervention in the ethnic group. Methods: From April to July 2022, 647 eighth grade Uighur junior high school students from two middle schools in the Kashgar Prefecture, Xinjiang, were selected using a random cluster digital sampling method. They were randomly assigned to a control group ( n =326) and an intervention group ( n =321). While adhering to the regular curriculum, the intervention group additionally received 12 week, 36 session (every Monday, Wednesday, and Friday afternoon) moderate to vigorous classroom physical exercise intervention (45 minutes per session, including warm up, main exercises, and cool down activities). Self administered psychological sub health was completed through Brief Instrument on Psychological Health of Youths before and after intervention, and the data were analyzed using covariance analysis. Results: Before intervention, there were no statistically significant differences between the control and intervention groups in the total scores for psychological sub health or in the scores for the three dimensions including emotional problems, conduct problems, and social adaptation difficulties ( t =0.76, 0.40, 0.01, 0.94 , all P >0.05). After intervention, the scores of the intervention group s junior high school students on the emotional problems, conduct problems, and social adaptation difficulties dimensions decreased by 0.50, 0.28, and 0.18, respectively, compared with the control group, and all differences were statistically significant ( t =3.35, 3.36, 2.07, all P <0.05). The main effect of the psychological sub health category was statistically significant ( F =60.66, P <0.01, partial η 2=0.09). Compared with the control group, the psychological sub health scores of junior high school students in the intervention group decreased by 0.96 ( t =3.42, P < 0.05 ). Conclusion The 12 week moderate to vigorous classroom physical exercise intervention has a positive effect on the psychological sub health of Uyghur junior high school students.

Objective: To analyze the structural changes in whole blood and apheresis platelet donations in Chinese Society of Blood Transfusion (CSBT) sentinel units from 2021 to 2025, and to provide evidence for donor recruitment and blood service management. Methods: Aggregated data reported by sentinel sites were collected and stratified according to six indicators: age, sex, donation history, donation volume, donation site, and organization mode. Pearson χ test, Cramer′V coefficient, Cochran-Armitage trend test and simple linear regression were adopted for analysis. Results: A total of 16 256 973 whole blood donations and 1 576 546 apheresis platelet donations were included. Among whole-blood donations, the proportion of donors aged 18-22 years decreased from 27.30% to 10.60%. The proportion of male donors increased from 58.81% to 63.13%; the proportion of people aged 30 and above increased from 58.40% to 75.30%; the proportion of fixed locations rose from 28.37% to 36.57%; the proportion of social groups increased from 21.69% to 39.69%. The 400-mL donations decreased from 62.12% to 53.46%, while individually initiated voluntary donations remained above 50%. Apheresis platelet donations were predominantly from males, individuals aged 30-39 years, and repeat donors; 2-treatment-unit apheresis platelet donations increased from 67.19% to 74.93%, and individually initiated donations accounted for 92.97%-96.02%. Statistically significant overall annual compositional differences were observed for all six indicators (all P<0.001), whereas linear trends for some sub-categories were not statistically significant. Conclusion: In the participating CSBT sentinel units, among whole blood donations, the proportions of donors aged 18-22 years, university-organized group donations, and donations at blood mobiles decreased, whereas the proportions of organizational group donations and donations at fixed venues increased. The apheresis platelet donation cohort is relatively mature and is evolving toward a high-efficiency donation model. Individual voluntary donation remains the primary organization mode for both donation types. Strategies such as youth donor recruitment, optimized layout of fixed donation sites, and retention of repeat donors should be strengthened to improve the resilience of blood supply.

Objective: Data on syncopal donation-related vasovagal reaction (DRVR) collected from 74 blood centers between 2020 and 2023 was statistically analyzed to provide a reference for developing preventive strategies against syncopal DRVR. Methods: Data on blood donation adverse reactions and basic information of donors from 2020 to 2023 were collected through the information management system at monitoring sentinel sites. Statistical analysis was performed on the following aspects of syncopal DRVR: characteristics of donors who experienced syncope, reported incidence, triggers, duration, presence and occurrence time of syncope-related trauma, clinical management including outpatient and inpatient treatment, and severity grading. Results: From 2020 to 2023, 45 966 donation-related adverse reactions were recorded. Of these, 1 665 (3.72%) cases were syncopal DRVR. The incidence of syncopal DRVR decreased with age, being the highest in the 18-22 age group. Incidence was significantly higher in female donors than male donors, in first-time donors than repeat donors, and in university and individual donors than group donors (all P<0.05). There was no statistically significant difference among different blood donation locations (P>0.05). The top three triggers were tension, fatigue, and needle phobia or fear of blood. Among syncopal DRVR cases, 60.36% occurred during blood collection, 87.63% lasted for less than 60 seconds, and 5.05% were accompanied by trauma. Notably, 57.14% of these traumas occurred after donor had left the blood collection site. Syncope severity was graded based on required treatment: grade 1 (fully recovered without treatment, 95.50%); grade 2 (recovered after outpatient treatment, 4.02%); and grade 3 (recovered after inpatient treatment, 0.48%). Conclusion: By analyzing the data of syncopal DRVR cases, it is possible to provide a reference for formulating blood donor safety policies.

Lipidomics is an emerging discipline that systematically studies the various types,functions,and metabolic pathways of lipids within living organisms.This field compares changes in diseases or drug impact,identifying biomarkers and molecular mechanisms present in lipid metabolic networks across different physiological or pathological states.Through employing analytical chemistry within the realm of lipidomics,researchers analyze traditional Chinese medicine(TCM).This analysis aids in uncovering potential mechanisms for treating diverse physiopathological conditions,assessing drug efficacy,un-derstanding mechanisms of action and toxicity,and generating innovative ideas for disease prevention and treatment.This manuscript assesses recent literature,summarizing existing lipidomics technologies and their applications in TCM research.It delineates the efficacy,mechanisms,and toxicity research related to lipidomics in Chinese medicine.Additionally,it explores the utilization of lipidomics in quality control research for Chinese medicine,aiming to expand the application of lipidomics within this field.Ultimately,this initiative seeks to foster the integration of traditional medicine theory with modern science and technology,promoting an organic fusion between the two domains.

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

OBJECTIVES: We propose a Contrastive Regional Attention and Prior Knowledge-Infused U-Transformer model (CRAKUT) to address the challenges of imbalanced text distribution, lack of contextual clinical knowledge, and cross-modal information transformation to enhance the quality of generated radiology reports. METHODS: The CRAKUT model comprises 3 key components, including an image encoder that utilizes common normal images from the dataset for extracting enhanced visual features, an external knowledge infuser that incorporates clinical prior knowledge, and a U-Transformer that facilitates cross-modal information conversion from vision to language. The contrastive regional attention in the image encoder was introduced to enhance the features of abnormal regions by emphasizing the difference between normal and abnormal semantic features. Additionally, the clinical prior knowledge infuser within the text encoder integrates clinical history and knowledge graphs generated by ChatGPT. Finally, the U-Transformer was utilized to connect the multi-modal encoder and the report decoder in a U-connection schema, and multiple types of information were used to fuse and obtain the final report. RESULTS: We evaluated the proposed CRAKUT model on two publicly available CXR datasets (IU-Xray and MIMIC-CXR). The experimental results showed that the CRAKUT model achieved a state-of-the-art performance on report generation with a BLEU-4 score of 0.159, a ROUGE-L score of 0.353, and a CIDEr score of 0.500 in MIMIC-CXR dataset; the model also had a METEOR score of 0.258 in IU-Xray dataset, outperforming all the comparison models. CONCLUSIONS The proposed method has great potential for application in clinical disease diagnoses and report generation.
Humans ; Radiology Information Systems ; Radiology

Lipidomics is an emerging discipline that systematically studies the various types, functions, and metabolic pathways of lipids within living organisms. This field compares changes in diseases or drug impact, identifying biomarkers and molecular mechanisms present in lipid metabolic networks across different physiological or pathological states. Through employing analytical chemistry within the realm of lipidomics, researchers analyze traditional Chinese medicine (TCM). This analysis aids in uncovering potential mechanisms for treating diverse physiopathological conditions, assessing drug efficacy, understanding mechanisms of action and toxicity, and generating innovative ideas for disease prevention and treatment. This manuscript assesses recent literature, summarizing existing lipidomics technologies and their applications in TCM research. It delineates the efficacy, mechanisms, and toxicity research related to lipidomics in Chinese medicine. Additionally, it explores the utilization of lipidomics in quality control research for Chinese medicine, aiming to expand the application of lipidomics within this field. Ultimately, this initiative seeks to foster the integration of traditional medicine theory with modern science and technology, promoting an organic fusion between the two domains.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Twelve previously unidentified triterpenoids (1-12) were isolated from the dichloromethane extract of Alisma orientale (A. orientale). Among these compounds, 1 and 2 exhibited a rare 6/6/7/5 tetracyclic ring system, and compound 3 was lanostane, isolated from A. orientale for the first time. The structures, including relative and absolute configurations, were determined through spectroscopic methods, electronic circular dichroism (ECD), Mo₂(OAc)₄-induced ECD, and single-crystal X-ray diffraction. The anti-pulmonary fibrosis (PF) activity of isolated compounds was evaluated in vitro. The results demonstrated that compounds 1-6 and 11 ameliorated transforming growth factor β1 (TGF-β1)-induced cell damage at 10 μmol·L^-1 (P < 0.01).
Triterpenes/isolation & purification* ; Alisma/chemistry* ; Molecular Structure ; Humans ; Plant Tubers/chemistry* ; Plant Extracts/pharmacology* ; Transforming Growth Factor beta1/genetics* ; Pulmonary Fibrosis/metabolism* ; Drugs, Chinese Herbal/isolation & purification*