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 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.

Objective Through visual analysis of literatures related to the treatment of chronic glomerulonephritis(CGN),the research hotspots and trends in this field were discussed.Methods Relevant literatures from CNKI,Wanfang Data Knowledge Service Platform,VIP,SinoMed,PubMed from 2010 to 2024 were retrieved,and analyzed using CiteSpace 6.2.R4 software.Results A total of 8887 articles in Chinese and 117 articles in English were included.The countries,institutions and authors who published most were China,the Affiliated Hospital for Liaoning University of Traditional Chinese Medicine and Wang Yiping.The research hotspots mainly focued on therapeutic drugs and clinical efficacy,and the research trend tended to be the treatment mechanism.Conclusion To further strengthen collaboration among different countries,institutions and authors,and to delve deeper into the mechanistic studies of CGN,will effectively promote the research progress in this field.

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 retrospectively analyze the results of serum beta-amyloid 42(Aβ42)tests conducted in the laboratory and explore potential issues associated with this testing.Methods All the Aβ42 test data collected up to the initiation of this study were compiled,and the positive rates for various diagnoses,including Alzheimer's disease(AD),cognitive decline,and dementia were ana-lyzed.Accuracy of the test kit was preliminarily validated using the kit's own reference,mouse brain tissue,and in vitro cultured cell-based reference samples.Results Data from 546 patients were col-lected,with 166 positive cases(positive rate of 30.4％).Among them,3 out of 6 AD patients tested positive;among 149 patients diagnosed with cognitive decline and 59 dementia patients,there were 29 and 24 positive cases respectively,with positive rates of 19.5％and 40.7％.The kit's detection of its own reference was affected by the serum matrix and failed to effectively detect positive mouse brain tissue and cellular reference samples.The kit's detection was generally unaffected by the amyloid precursor protein(APP)of Aβ,but it did not demonstrate good recovery rates for its own reference samples added to various clinical serum specimens.Conclusion The positive rate of serum Aβ42 test results in laboratory is lower than expected,and the accuracy of the test kit may require further improvement.

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.

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.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.