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 investigate the characteristics of mitochondrial translational initiation factor 2 （MTIF2） gene methylation and its association with the development and progression of hepatocellular carcinoma （HCC）. MethodsMethSurv and EWAS Data Hub were used to perform the standardized analysis and the cluster analysis of MTIF2 methylation samples， including survival curve analysis， methylation signature analysis， the association of tumor signaling pathways， and a comparative analysis based on pan-cancer database. The independent-samples t test was used for comparison between two groups； a one-way analysis of variance was used for comparison between multiple groups， and the least significant difference t-test was used for further comparison between two groups. The Cox proportional hazards model was used to perform the univariate and multivariate survival analyses of methylation level at the CpG site. The Kaplan-Meier method was used to investigate the survival differences between the patients with low methylation level and those with high methylation level， and the Log-likelihood ratio method was used for survival difference analysis. ResultsGlobal clustering of MTIF2 methylation showed that there was no significant difference in MTIF2 gene methylation level between different races， ethnicities， BMI levels， and ages. The Kaplan-Meier survival curve analysis showed that the patients with N-Shore hypermethylation of the MTIF2 gene had a significantly better prognosis than those with hypomethylation （hazard ratio ［HR］=0.492， P<0.001）， while there was no significant difference in survival rate between the patients with different CpG island and S-Shore methylation levels （P>0.05）. The methylation profile of the MTIF2 gene based on different ages， sexes， BMI levels， races， ethnicities， and clinical stages showed that the N-Shore and CpG island methylation levels of the MTIF2 gene decreased with the increase in age， and the Caucasian population had significantly lower N-Shore methylation levels of the MTIF2 gene than the Asian population （P<0.05）； the patients with clinical stage Ⅳ had significantly lower N-Shore and CpG island methylation levels of the MTIF2 gene than those with stage Ⅰ/Ⅱ （P<0.05）. Clinical validation showed that the patients with stage Ⅲ/Ⅳ HCC had a significantly lower methylation level of the MTIF2 gene than those with stage Ⅰ/Ⅱ HCC and the normal population （P<0.05）. ConclusionN-Shore hypomethylation of the MTIF2 gene is a risk factor for the development and progression of HCC.

Hepatic encephalopathy is a difficult and critical disease with rapid progression and limited treatment methods in the field of liver disease， and it is urgently needed to make breakthroughs in its pathogenesis. Selection of appropriate prevention and treatment strategies is of great importance in delaying disease progression and reducing the incidence and mortality rates. This article reviews the theory of “turbid toxin pathogenesis” and related prevention and treatment strategies for hepatic encephalopathy in traditional Chinese medicine/Zhuang medicine， proposes a new theory of “turbid toxin pathogenesis”， analyzes the scientific connotations of “turbid”， “toxin”， and the theory of “turbid toxin pathogenesis”， and constructs the “four-step” prevention and treatment strategies for hepatic encephalopathy， thereby establishing the new clinical prevention and treatment regimen for hepatic encephalopathy represented by “four prescriptions and two techniques” and clarifying the effect mechanism and biological basis of core prescriptions and techniques in the prevention and treatment of hepatic encephalopathy， in order to provide a reference for the prevention and treatment of hepatic encephalopathy.

Breast cancer is a kind of malignant tumor with a complex mechanism， and its morbidity and mortality are increasing year by year， which seriously threatens women's health. At present， the main clinical treatments are surgical resection， radiotherapy， chemotherapy， and drug therapy， but they are often accompanied by side effects and adverse reactions， which affect the therapeutic effect. Traditional Chinese medicine （TCM） has the advantages of multi-component and multi-target treatment in the fight against breast cancer. The wnt/β-catenin signaling pathway is one of the classic pathways in cancer research. Abnormally activated Wnt/β-catenin signaling pathway inhibits β-catenin degradation by blocking the formation of Axin/glycogen synthase kinase 3β/adenomatous polyposis coli complex， thus promoting β-catenin nuclear metastasis， and it binds to T cell transcription factor/lymphoenhancer factor-1 to initiate downstream target genes and further interfere with the proliferation， migration， and invasion of tumor cells to affect the tumor process. Previous studies have shown that TCM monomers and compounds can mediate the Wnt/β-catenin signaling pathway to inhibit the malignant phenotype of breast cancer cells， thus playing an anti-breast cancer role， and the biochemical process involved in the regulation of therapeutic drugs has not been systematically combed. By analyzing and collating Chinese and foreign literature at the present stage， this paper discussed the association mechanism between Wnt/β-catenin signaling pathway and breast cancer and analyzed the internal mechanism of TCM monomers and compounds in mediating Wnt/β-catenin signaling pathway to exert anti-breast cancer effect. The statistical results showed that the flavonoids， alkaloids， and terpenoids in TCM monomers could target the Wnt/β-catenin signaling pathway and block the further development of malignant phenotype of breast cancer cells. TCM compounds with functions of clearing heat and detoxifying， promoting blood circulation and removing blood stasis， and tonifying kidney and liver were commonly used to intervene in the Wnt/β-catenin signaling pathway to prevent breast cancer. Compared with the current inhibitors of Wnt/β-catenin signaling pathway， the application of TCM monomers and compounds is expected to bring low-toxicity and high-efficiency breast cancer treatment drugs to the clinical practice， and the existing results provide a reference for the subsequent screening， research， and development of TCM small-molecule compounds and TCM compounds against breast cancer.

Objective To understand the driver gene mutation status in patients with non-small cell lung cancer (NSCLC) in Xi'an City, and to analyze the association with environmental exposure factors. Methods A total of 305 NSCLC patients admitted to the First Affiliated Hospital of the Air Force Medical University from January 2019 to December 2023 were included. The driver gene mutation status was observed, and the relationship with environmental exposure factors was analyzed. Results The driver gene mutation rate of 305 patients was 46.89%, with EGFR gene mutation accounting for the highest proportion, and 4 cases of gene co-mutations were detected. There was a difference in gender among patients with different single drive gene mutations (P<0.05), and the proportion of EGFR in women was significantly higher (P<0.05). Univariate analysis showed that there were statistical differences in family history, smoking history, long-term cooking history, and fried smoked food intake between patients with driver gene mutation and patients without driver gene mutation (P<0.05). Logistic regression analysis suggested that long-term cooking history (OR=2.392), and fried smoked food intake (OR=2.849) were the environmental exposure factors affecting EGFR gene mutation (P<0.05), and smoking history (OR=1.377) was an environmental exposure factor of KRAS gene mutation (P<0.05). Conclusion EGFR gene mutation accounts for the highest proportion of NSCLC patients in Xi'an City, and is mainly female. Long-term cooking history, and fried smoked food intake are related to EGFR gene mutation. There is a certain association between smoking history and KRAS gene mutation.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

BACKGROUND:The development of artificial intelligence in the medical field is rapidly advancing,with increasing research on its applications in the field of bone trauma.Through bibliometric analysis,this paper analyzed the research hotspots of artificial intelligence in the field of bone trauma in recent years,and predicted the future research trend. OBJECTIVE:To summarize the development history,research status,hot spots,and future development trends of artificial intelligence technology in the field of bone trauma to provide new insights for future research. METHODS:This study selected relevant literature from the Web of Science core database,covering the period from the inception to August 2023,and retrieved 420 articles related to the application of artificial intelligence,machine learning,and deep learning in the field of bone trauma.After manual screening,202 articles related to this article were exported,and Citespace software was used for visual analysis of cooperation of countries,institutions,cited journals,citation analysis,keyword co-occurrence,and other aspects. RESULTS AND CONCLUSION:(1)The overall number of publications from the 202 selected articles showed an upward trend,indicating significant research potential for future studies.The country with the highest centrality and the highest publication volume was the United States.The University of California(USA)was the most prolific research institution.(2)The top five most commonly used keywords in bone trauma research using artificial intelligence were deep learning,artificial intelligence,bone density,machine learning,and diagnosis.The keyword with the highest centrality was bone density,and the keyword with the highest frequency was deep learning.(3)The top 10 most cited reference papers provided comprehensive insights into the feasibility of applying artificial intelligence techniques to the diagnosis of bone trauma from various perspectives.Among them,eight papers focused on bone and joint injuries and deep convolutional neural networks.One paper discussed the use of deep learning in detecting osteoporosis in CT scans to prevent fragility fractures,while another paper explored the correlation between the application of artificial intelligence in identifying changes in skin texture and the recognition of bone characteristics.(4)In the future,the research hotspots of artificial intelligence will mainly focus on the specific study of fractures caused by bone and joint trauma and osteoporosis.The research trend mainly focuses on improving the performance of artificial intelligence algorithms,using new artificial intelligence technologies to accurately classify and quickly and efficiently diagnose bone injuries,especially for the diagnosis of complex and hidden fractures.By establishing finite element analysis models,more standardized evaluations of bone injuries can be achieved.

BACKGROUND:Rev-erbα is involved in the regulation of inflammation,but pharmacological activation of Rev-erbα increases the risk for cardiovascular diseases.To reduce the relevant risk,an exploration on SR9009,a Rev-erbα agonist,combined with other drugs to relieve inflammation in skeletal myoblasts was conducted,laying the theoretical foundation for the treatment of inflammation-associated skeletal muscle atrophy. OBJECTIVE:To investigate the relationship of SR9009,indolepropionic acid and nuclear factor-κB signaling pathways in lipopolysaccharide-induced C2C12 myoblasts. METHODS:(1)C2C12 myoblasts were induced to differentiate in the presence of lipopolysaccharide(1 μg/mL).RNA-seq and KEGG pathway analysis were used to study signaling pathways.(2)C2C12 myoblast viability was assessed using the cell counting kit-8 assay to determine optimal concentrations of indolepropionic acid.Subsequently,cells were categorized into control group,lipopolysaccharide(1 μg/mL)group,SR9009(10 μmol/L)+lipopolysaccharide group,indolepropionic acid(80μmol/L)+lipopolysaccharide group,and SR9009+indolepropionic acid+lipopolysaccharide group.ELISA was employed to measure protein expression levels of interleukin-6 in the cultured supernatant.Real-time quantitative PCR were employed to measure mRNA expression levels of interleukin-6,tumor necrosis factor α,TLR4 and CD14.Western blot assay were employed to measure protein expression levels of NF-κB p65 and p-NF-κB p65.(3)After Rev-erbα was knocked down by siRNA,knockdown efficiency was assessed by RT-qPCR.And mRNA levels of interleukin-6 and tumor necrosis factor α were also measured. RESULTS AND CONCLUSION:Compared with the blank control group,lipopolysaccharide time-dependently inhibited myofibroblast fusion to form myotubes,the mRNA expression levels of interleukin-6 and tumor necrosis factor α were elevated,and the level of interleukin-6 in the cell supernatant was significantly increased.The results of KEGG pathway showed that the nuclear factor-κB signaling pathway was activated by lipopolysaccharide.Indolepropionic acid exhibited significant suppression of C2C12 myoblasts viability when its concentration exceeded 80 μmol/L.Indolepropionic acid and SR9009 inhibited the activation of NF-κB signaling pathway,thereby played an anti-inflammatory role,and suppressed the mRNA expression levels of interleukin-6,tumor necrosis factor α,TLR4 and CD14.Compared with the lipopolysaccharide group,the ratio of p-NF-κB p65/NF-κB p65 protein expression were downregulated.SR9009 combined with indolepropionic acid notably reduced lipopolysaccharide-induced inflammation,further downregulated the mRNA expression levels of interleukin-6,tumor necrosis factor α,TLR4 and CD14.The ratio of p-NF-κB p65/NF-κB p65 protein expression was significantly lower than that in the SR9009+lipopolysaccharide group or indolepropionic acid+lipopolysaccharide group.Rev-erbα increases time-dependently with lipopolysaccharide induction.The knockdown efficiency of Rev-erbα by siRNA reached over 58%,and lipopolysaccharide was added after Rev-erbα was successfully knocked down.Compared with the lipopolysaccharide group,the mRNA expression levels of interleukin-6 and tumor necrosis factor α were significantly up-regulated.These results conclude that Rev-erbα may act as a promising pharmacological target to reduce inflammation.SR9009 targeted activation of Rev-erbα combined with indolepropionic acid significantly inhibits the nuclear factor-κB signaling pathway and attenuates the inflammatory response of C2C12 myofibroblasts.Moreover,the combined anti-inflammatory effect is superior to that of the intervention alone.

ObjectiveTo establish a risk recognition model for coronary artery stenosis by using a machine learning method and to identify the key causative factors. MethodsPatients aged ≥18 years，diagnosed with coronary heart disease through coronary angiography from January 2013 to May 2020 in two prominent hospitals in Shanxi Province， were continuously enrolled. Logistic regression，back propagation neural network （BPNN）， and random forest（RF）algorithms were used to construct models for detecting the causative factors of coronary artery stenosis. Sensitivity （TPR）， specificity （TNR）， accuracy （ACC）， positive predictive value （PV+）， negative predictive value （PV-）， area under subject operating characteristic curve （AUC）， and calibration curve were used to compare the discrimination and calibration performance of the models. The best model was then employed to predict the main risk variables associated with coronary stenosis. ResultsThe RF model exhibited superior comprehensive performance compared to logistic regression and BPNN models. The TPR values for logistic regression，BPNN，and RF models were 75.76%， 74.30%， and 93.70%， while ACC values were 74.05%， 72.30%， and 79.49%， respectively. The AUC values were：logistic regression 0.739 9； BPNN 0.723 1； RF 0.752 2. Manifestations such as chest pains，abnormal ST segments on ECG，ventricular premature beats with hypertension， atrial fibrillation， regional wall motion abnormalities（RWMA） by color echocardiography， aortic regurgitation（AR）， pulmonary insufficiency （PI）， family history of cardiovascular diseases，and body mass index（BMI）were identified as top ten important variables affecting coronary stenosis according to the RF model. ConclusionsRandom forest model shows the best comprehensive performance in identification and accurate assessment of coronary artery stenosis. The prediction of risk factors affecting coronary artery stenosis can provide a scientific basis for clinical intervention and help to formulate further diagnosis and treatment strategies so as to delay the disease progression.