Da Qinjiaotang is the 54^th formula of the 100 formulas in the Catalogue of Ancient Classical Formulas （the first batch） ，and it originated from the Collection of Writings on the Mechanism of Disease， Suitability of Qi， and Safeguarding of Life Discussed in Plain Questions. Da Qinjiaotang is composed of Gentiana macrophylla， Glycyrrhizae Radix et Rhizoma， Ligusticum chuanxiong， Angelica sinensis， Paeonia lactiflora， Asari Radix et Rhizoma， Notopterygium incisum， Saposhnikoviae Radix， Scutellariae Radix， Gypsum， Angelica dahurica， Atractylodis Macrocephalae Rhizoma， Rehmanniae Radix， Rehmanniae Radix Praeparata， Poria， and Angelicae Pubescentis Radix. It is a classical formula for treating strokes. Da Qinjiaotang is widely used in modern clinical practices for treating ischemic stroke， peripheral facial paralysis， cervical spondylosis， rheumatic arthritis， neurodermatitis， and other multisystem diseases. Therefore， following the Principles of Textual Research on the Key Information of Ancient Classical Famous Formulas， the authors collected the ancient Chinese medical literature of Da Qinjiaotang by the method of bibliometrics and screened out 177 valid data， involving 100 ancient books of traditional Chinese medicine. Based on the historical evolution， composition， dosage， method of preparation， and preparation of the original medicinal materials of Da Qinjiaotang， a systematic study was carried out. It was found that among the 175 records of the main diseases and syndromes， stroke （144） was the most， accounting for 82.29% of the total diseases and syndromes. Later generations mostly followed the practice of LIU Wansu in using Da Qinjiaotang to treat stroke caused by "weak blood and inability to nourish tendon"， featuring "hands and feet cannot move， stiff tongue hinders speaking"， as well as other symptoms， such as slant of the mouth， hemiplegia， numbness of the limbs， paroxysmal pain， and acerbic syncope. The treatment scope was expanded， covering tendon dryness， clonic convulsion， spasm syndrome， and arthralgia syndrome. At the same time， it was found that there was a controversy between "internal wind" and "external wind" in the treatment of stroke by Da Qinjiaotang. LIU Wansu thought that stroke was caused by internal factors， created the theory of "hot stroke"， and used Da Qinjiaotang to treat "internal wind". Many doctors in later generations focused on treating the "external wind" of "internal deficiency and evil". There were 76 valid data on the composition of drugs， 59 of which had doses for each drug. It was suggested to use the modern conversion dosage of the original formula， with 41.30 g per dose. The drug should be boiled in 600 mL water until 300 mL， decocted once， and taken in a warm state after removing the dregs anytime. Through the analysis and study of the ancient books about Da Qinjiaotang， the paper clarified its historical evolution and confirmed its key information， so as to provide the ancient literature evidence for the research and development of the classical famous formula Daqinjiaotan and its better clinical application.

Da Qinjiaotang is the 54^th formula of the 100 formulas in the Catalogue of Ancient Classical Formulas （the first batch） ，and it originated from the Collection of Writings on the Mechanism of Disease， Suitability of Qi， and Safeguarding of Life Discussed in Plain Questions. Da Qinjiaotang is composed of Gentiana macrophylla， Glycyrrhizae Radix et Rhizoma， Ligusticum chuanxiong， Angelica sinensis， Paeonia lactiflora， Asari Radix et Rhizoma， Notopterygium incisum， Saposhnikoviae Radix， Scutellariae Radix， Gypsum， Angelica dahurica， Atractylodis Macrocephalae Rhizoma， Rehmanniae Radix， Rehmanniae Radix Praeparata， Poria， and Angelicae Pubescentis Radix. It is a classical formula for treating strokes. Da Qinjiaotang is widely used in modern clinical practices for treating ischemic stroke， peripheral facial paralysis， cervical spondylosis， rheumatic arthritis， neurodermatitis， and other multisystem diseases. Therefore， following the Principles of Textual Research on the Key Information of Ancient Classical Famous Formulas， the authors collected the ancient Chinese medical literature of Da Qinjiaotang by the method of bibliometrics and screened out 177 valid data， involving 100 ancient books of traditional Chinese medicine. Based on the historical evolution， composition， dosage， method of preparation， and preparation of the original medicinal materials of Da Qinjiaotang， a systematic study was carried out. It was found that among the 175 records of the main diseases and syndromes， stroke （144） was the most， accounting for 82.29% of the total diseases and syndromes. Later generations mostly followed the practice of LIU Wansu in using Da Qinjiaotang to treat stroke caused by "weak blood and inability to nourish tendon"， featuring "hands and feet cannot move， stiff tongue hinders speaking"， as well as other symptoms， such as slant of the mouth， hemiplegia， numbness of the limbs， paroxysmal pain， and acerbic syncope. The treatment scope was expanded， covering tendon dryness， clonic convulsion， spasm syndrome， and arthralgia syndrome. At the same time， it was found that there was a controversy between "internal wind" and "external wind" in the treatment of stroke by Da Qinjiaotang. LIU Wansu thought that stroke was caused by internal factors， created the theory of "hot stroke"， and used Da Qinjiaotang to treat "internal wind". Many doctors in later generations focused on treating the "external wind" of "internal deficiency and evil". There were 76 valid data on the composition of drugs， 59 of which had doses for each drug. It was suggested to use the modern conversion dosage of the original formula， with 41.30 g per dose. The drug should be boiled in 600 mL water until 300 mL， decocted once， and taken in a warm state after removing the dregs anytime. Through the analysis and study of the ancient books about Da Qinjiaotang， the paper clarified its historical evolution and confirmed its key information， so as to provide the ancient literature evidence for the research and development of the classical famous formula Daqinjiaotan and its better clinical application.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

ObjectiveTo explore the construction of a machine learning model for the diagnosis of traditional Chinese medicine （TCM） syndromes in chronic cough and the optimization of this model using the Voting ensemble algorithm. MethodsA retrospective analysis was conducted using clinical data from 921 patients with chronic cough treated at the Respiratory Department of Dongfang Hospital， Beijing University of Chinese Medicine. After standardized processing， 84 clinical features were extracted to determine TCM syndrome types. A specialized dataset for TCM syndrome diagnosis in chronic cough was formed by selecting syndrome types with more than 50 cases. The synthetic minority over-sampling technique （SMOTE） was employed to balance the dataset. Four base models， logistic regression （LR）， decision tree （dt）， multilayer perceptron （MLP）， and Bagging， were constructed and integrated using a hard voting strategy to form a Voting ensemble model. Model performance was evaluated using accuracy， recall， precision， F1-score， receiver operating characteristic （ROC） curve， area under the curve （AUC）， and confusion matrix. ResultsAmong the 921 cases， six syndrome types had over 50 cases each， phlegm-heat obstructing the lung （294 cases）， wind pathogen latent in the lung （103 cases）， cold-phlegm obstructing the lung （102 cases）， damp-heat stagnating in the lung （64 cases）， lung yang deficiency （54 cases）， and phlegm-damp obstructing the lung （53 cases）， yielding a total of 670 cases in the specialized dataset. High-frequency symptoms among these patients included cough， expectoration， odor-induced cough， throat itchiness， itch-induced cough， and cough triggered by cold wind. Among the four base models， the MLP model showed the best diagnostic performance （test accuracy： 0.9104； AUC： 0.9828）. Compared with the base models， the Voting ensemble model achieved superior performance with an accuracy of 0.9289 on the training set and 0.9253 on the test set， showing a minimal overfitting gap of 0.0036. It also achieved the highest AUC （0.9836） in the test set， outperforming all base models. The model exhi-bited especially strong diagnostic performance for damp-heat stagnating in the lung （AUC： 0.9984） and wind pathogen latent in the lung （AUC： 0.9970）. ConclusionThe Voting ensemble algorithm effectively integrates the strengths of multiple machine learning models， resulting in an optimized diagnostic model for TCM syndromes in chronic cough with high accuracy and enhanced generalization ability.

As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

Trauma is the main cause of death and disability. Patients with severe trauma have hemorrhagic shock, traumatic coagulopathy and other diseases, which increase the risk of death. Platelets are important in the hemostatic response, but their function is rapidly dysregulated in trauma patients, leading to traumatic coagulopathy, blood loss, and early death. In addition to their role in hemostasis, platelets act as coordinators of the initial immune response, which can lead to immunothrombosis, organ dysfunction, and increased late mortality. At present, the treatment of post traumatic platelet dysfunction is mainly based on early hemostasis, and late prevention and treatment of thrombosis and organ dysfunction. In this review, the characteristics, underlying mechanisms, diagnosis and treatment strategies of platelet dysfunction in different periods are summarized, to provide ideas for studying the mechanism of platelet dysfunction after trauma and the treatment strategy for trauma patients.
Humans ; Wounds and Injuries/therapy* ; Blood Platelets/metabolism* ; Blood Platelet Disorders/etiology* ; Animals ; Hemostasis

Objective To investigate the value of ultrasonographic features combined with immunohistochemistry in predicting axillary lymph node metastasis in middle-aged women with breast cancer.Methods A retrospective analysis was conducted on 827 middle-aged female breast cancer patients who underwent surgical treatment at the Affiliated Hospital of Chengde Medical University from June 2017 to June 2023.Ultrasonographic and immunohistochemical information was collected,and the patients were randomly allocated into a training set(579 patients)and a validation set(248 patients).Univariate and multivariate Logistic regression analyses were performed to identify ultrasonographic and immunohistochemical risk factors associated with axillary lymph node metastasis in these patients,and a nomogram model was developed.Receiver operating characteristic curves and calibration curves were established to evaluate the performance of the nomogram model,and clinical decision curves were built to assess the clinical value of the model.Results The maximum diameter,morphology,boundary,calcification,and expression of human epidermal growth facor receptor 2 and Ki-67 in breast cancer lesions were identified as risk factors for predicting axillary lymph node metastasis in middle-aged women.The areas under the curve of the nomogram model on the training and validation sets were 0.747(0.707-0.787)and 0.714(0.647-0.780),respectively.Calibration curves and clinical decision curves indicated good consistency and performance of the model.Conclusion The nomogram model constructed based on ultrasonographic features and immunohistochemistry of the primary breast cancer lesion demonstrates high value in predicting axillary lymph node metastasis in middle-aged women with breast cancer.
Humans ; Female ; Breast Neoplasms/diagnostic imaging* ; Middle Aged ; Lymphatic Metastasis/diagnostic imaging* ; Axilla ; Retrospective Studies ; Nomograms ; Ultrasonography ; Immunohistochemistry ; Lymph Nodes/diagnostic imaging* ; Risk Factors ; Ki-67 Antigen

Objective To characterize the temporal dynamics of endophytic community and key metabolites during the growth developmental stages of Artemisia indica and to explore the effects of endophytes on the medicinal material quality of A.indica from the perspective of microorganism combined with the correlation analysis.Methods In this study,high-throughput sequencing was performed to obtain the temporal dynamics of diversity and composition of endophytic community during the growth stages of A.indica.Key metabolites quantitative analysis were performed using high-performance liquid chromatography and ultraviolet spectrophotometry.Spearman's correlation analysis was further conducted to identify the endophytic communities that were significantly correlated with metabolites.Results There were significant differences in the diversity and composition of endophytic communities during the growth stages of A.indica.Linear discriminant analysis efect size(LEfSe)analyses identified some potential microbial biomarkers,such as Firmicutes,Massilia,Pantoea,Alternaria,Didymella,and Trichomerium.The abundances of some genera were significantly and positively correlated with the content of total polyphenols and total flavonoids(P<0.05),such as Curtobacterium,Pantoea,Tilletiopsis,and Dissoconium.The abundances of Pseudozyma,Ralstonia,and Pleospora were significantly and positively correlated with Chlorogenic acid,Isochlorogenic acid B,Isochlorogenic acid A,and Isochlorogenic acid C(P<0.05).Conclusion This work described the distribution of endophytes and key metabolites during the development stages of A.indica.Some endophytic communities with significant correlation of key metabolites were identified,which provided valuable information to guide the isolation of endophytic strains related to key metabolites and improve the quality of A.indica.

BACKGROUND:Total hip and knee arthroplasty is widely used in the elderly population,but there is a lack of accurate prediction methods for unplanned readmission and postoperative complications. OBJECTIVE:To investigate the effect of the Rothman index on unplanned readmission and complications in elderly patients undergoing total hip and knee arthroplasty. METHODS:A total of 153 patients who underwent elective total hip and knee arthroplasty from December 2020 to December 2022 in Ward Area One,Department of Orthopedics,The First People's Hospital of Zunyi were selected as the study subjects.According to whether they were unplanned readmission within 90 days after discharge,they were divided into a readmission group(n=21)and a non-readmission group(n=132).The general data of all patients were collected through the electronic medical record system,including gender,age,body mass index,diabetes mellitus,hypertension,and surgical joint type.The Rothman index was evaluated according to the literature.Postoperative complications were counted. RESULTS AND CONCLUSION:(1)There was no significant difference in gender,body mass index,surgical joint type,and length of hospital stay between the readmission group and the non-readmission group(P>0.05).There were significant differences in the number of comorbidities,age,and Rothman score between the two groups(P<0.05).(2)The results of multivariate Logistics regression analysis showed that the number of comorbidities,age,and Rothman score were independent influencing factors for readmission 90 days after total hip and knee arthroplasty in elderly patients with hip and knee diseases(P<0.05).(3)The results of receiver operating characteristic curve analysis exhibited that the area under the curve of the Rothman index for predicting readmission 90 days after total hip and knee arthroplasty was 0.824;the sensitivity was 80.85%;the specificity was 78.85%;the maximum Youden index was 0.597,and the optimal cutoff value was 46 points.(4)The incidence of total complications in elderly patients with Rothman<46 was higher than that in elderly patients with Rothman≥46(P<0.05).(5)It is concluded that the Rothman index can accurately predict unplanned readmission after total hip and knee arthroplasty in elderly patients with hip and knee joint diseases.Simultaneously,patients with Rothman index of less than 46 points have a higher overall risk of complications and poor joint recovery,which can be used to improve postoperative management of patients in clinical practice.

Objective:To analyze the risk factors of internalizing problems in adolescents aged 12 to 18 years,and provide supporting evidence for the scientific prevention and effective control of internalizing problems in adolescents.Methods:By systematically searching the Chinese and English databases such as CNKI,VIP,Wan-fang,PubMed,Web of Science,Psychology and Behavioral Sciences Collection,PsycInfo,PsycArticles and ERIC,literature on risk factors of internalizing problems among adolescents in the past 22 years was collected,and non-clinical literature using CBCL or YSR or TRF scales to measure related internalizing problems were included.Meta analysis was performed using CMA3.0,with r as the effect size indicator and random effects model combined with the effect size of risk factors.Results:Finally,77 and 18 risk factors literatures were included,including 7 risk fac-tors of individuals,7 risk factors of family,and 4 risk factors of school/community.The average correlation between family risk factors and internalizing problems of adolescents was the highest.Among family risk factors,parent-child attachment had the highest correlation.Conclusion:Individual risk factors,family risk factors and school/com-munity risk factors are significantly positively correlated with adolescent internalizing problems,and family risk fac-tors(especially parent-child attachment quality)have the highest correlation with adolescent internalizing problems.