OBJECTIVE To screen and quantitatively analyze the quality marker （Q-Marker） associated with anti-renal fibrosis in Shenqi shenshuai mixture （SQSS）， so as to provide references for the analysis of pharmacodynamic substances and new drug transformation of SQSS. METHODS The chemical components of SQSS were characterized by untargeted metabolomics. Combined with network pharmacology， gene expression omnibus （GEO） and connectivity map （CMAP） databases， the anti-renal fibrosis Q-Markers of SQSS were screened. HPLC-MS/MS was applied to determine the contents of Q-Markers in 10 batches of SQSS. RESULTS A total of 1 319 compounds were identified from SQSS via untargeted metabolomics，and 84 active ingredients with anti-renal fibrosis activity were further screened out， such as formononetin. Nine anti-renal fibrosis Q-Markers were obtained by network pharmacology and GEO database， including berberine， quercetin， honokiol， nicotinamide， daidzein， coumarin， kaempferol， formononetin and amygdalin. The quantitative results showed that the average contents of the above components （excluding amygdalin） in 10 batches of SQSS were 2.523， 1.942， 26.848， 1.415， 0.692， 0.171， 0.374， 7.401 μg/mL， respectively. CONCLUSIONS Nine anti-renal fibrosis Q-Markers of SQSS were screened in this study， and the contents of eight among them were determined. The results can provide a basis for elucidating the pharmacodynamic material basis and promoting the new drug transformation of SQSS.

OBJECTIVE To screen and quantitatively analyze the quality marker （Q-Marker） associated with anti-renal fibrosis in Shenqi shenshuai mixture （SQSS）， so as to provide references for the analysis of pharmacodynamic substances and new drug transformation of SQSS. METHODS The chemical components of SQSS were characterized by untargeted metabolomics. Combined with network pharmacology， gene expression omnibus （GEO） and connectivity map （CMAP） databases， the anti-renal fibrosis Q-Markers of SQSS were screened. HPLC-MS/MS was applied to determine the contents of Q-Markers in 10 batches of SQSS. RESULTS A total of 1 319 compounds were identified from SQSS via untargeted metabolomics，and 84 active ingredients with anti-renal fibrosis activity were further screened out， such as formononetin. Nine anti-renal fibrosis Q-Markers were obtained by network pharmacology and GEO database， including berberine， quercetin， honokiol， nicotinamide， daidzein， coumarin， kaempferol， formononetin and amygdalin. The quantitative results showed that the average contents of the above components （excluding amygdalin） in 10 batches of SQSS were 2.523， 1.942， 26.848， 1.415， 0.692， 0.171， 0.374， 7.401 μg/mL， respectively. CONCLUSIONS Nine anti-renal fibrosis Q-Markers of SQSS were screened in this study， and the contents of eight among them were determined. The results can provide a basis for elucidating the pharmacodynamic material basis and promoting the new drug transformation of SQSS.

Objective:To investigate the patterns of mutation evolution in patients with acute myeloid leukemia (AML) during treatment and the possible clinical significances.Methods:A retrospective case series study was conducted. A total of 103 AML patients who were hospitalized at the Affiliated Yuebei People's Hospital of Medical College of Shantou University from November 2019 to August 2021 and underwent high-throughput next-generation sequencing (NGS) technology to detect the mutations of 128 AML-related genes in bone marrow samples were selected. Based on the NGS results, the somatic gene mutations in samples of patients collected at initial diagnosis (73 cases), complete remission (CR) (30 cases), non-remission (NR) (23 cases), and recurrence (12 cases) were analyzed, and the targeted drugs involved in the gene mutations detected in NR and recurrence samples were summarized.Results:The median age [ M ( Q1, Q3)] of onset for 103 patients was 58 (48, 66) years, including 64 males (61%) and 39 females (39%); 86 cases (83%) were primary AML, and 17 cases (17%) were secondary AML; at the initial diagnosis, 51 cases (50%) had normal karyotypes, 34 cases (33%) had abnormalities, and 18 cases (17.5%) were unknown. Compared with the CR samples, the mutation frequencies of FLT3 [29% (21/73) vs. 3% (1/30)], NPM1 [27% (20/73) vs. 3% (1/30)], NRAS [22% (16/73) vs. 3% (1/30)], and IDH2 [14% (10/73) vs. 0 (0/30)] were all higher in the initial diagnosis samples, and the differences were statistically significant (all P < 0.05); compared with the initial diagnosis sample, the median number of gene mutations in each CR sample was lower [4 (2, 5) vs. 7 (5, 9)], and the difference was statistically significant ( P < 0.001). However, there was no statistically significant difference in the median number of gene mutations in each patient between the initial diagnosis samples and the NR samples, the initial diagnosis samples and the recurrence samples, and the NR samples and the recurrence samples (all P > 0.05). Analysis of 14 patients with NGS data at initial diagnosis and CR showed that the same gene mutations could be detected at initial diagnosis and CR, such as DNAH23 (3 cases), USH2A (3 cases), etc; partial gene mutations were detected at initial diagnosis but were not detected at CR, including NRAS (5 cases), FLT3 (3 cases), ANKRD26 (3 cases), NPM1 (3 cases), ETV6 (3 cases), etc; ARID1B (1 case) and DNMT3A (1 case) were negative for mutations at initial diagnosis but positive upon reaching CR. Analysis of 14 patients with NGS data at initial diagnosis and NR showed that most gene mutations persisted at initial diagnosis and NR, such as DNMT3A (5 cases), NRAS (5 cases), KRAS (3 cases), RUNX1 (3 cases), etc; the mutant genes detected at initial diagnosis but not detected at NR included USH2A (2 cases), PCLO (2 cases), ATM (2 cases), FAT1 (2 cases), etc; partial gene mutations were not detected at initial diagnosis but were detected at NR, such as FAT1 (2 cases), TCF3 (2 cases), etc. Analysis of 5 patients with NGS data at CR and recurrence showed that some gene mutations were detected at both CR and recurrence, such as BCORL1 (1 case), ARID2 (1 case), SETD2 (1 case), VEGFC (1 case), etc; FLT1 (1 case) and GNAS (1 case) gene mutations were detected at CR but not detected at recurrence; at recurrence, some gene mutations that were not detected at CR were also detected, such as ANKRD26 (1 case), WT1 (1 case), etc. Among the 23 NR samples and 12 recurrence samples, the targets of drugs approved by US Food and Drug Administration or in clinical trials were detected in 14 (61%) and 5 (42%) samples respectively, including IDH1, IDH2, FLT3, KIT, KRAS, NRAS, SF3B1, U2AF1, and SRSF2. Conclusions:The number of gene mutations in AML patients during CR is significantly less than that at initial diagnosis, some gene mutations disappear when CR is achieved through treatment, but the majority of gene mutations persist during the treatment period, including NR and recurrence, suggesting that monitoring through NGS technology can help understand the evolution of gene mutations during AML treatment and discover the potential therapeutic targets.

Objective To explore the quality markers of Puerariae Lobatue Radix;To predict its"efficacy component group"with alcohol detoxification and liver protection effects.Methods Fingerprints of 26 batches of Puerariae Lobatue Radix samples from different origins in China was established.Multivariate statistical analysis was employed to identify quality markers,while network pharmacology and molecular docking were used to predict the potential"efficacy component group".Results UPLC fingerprint analysis calibrated 11 common peaks.Clustering analysis classified 26 batches of samples into 3 categories,and 7 quality markers were ultimately screened through multivariate statistical analysis,including mirificin,puerarin,puerarin-6''-O-xyloside,3'-methoxypuerarin,ononin,genistin and daidzin.Network pharmacology revealed that all 7 markers interacted with targets related to alcohol-associated liver disease,identifying 19 core targets such as TNF,CASP3,BCL2,MMP9,IL2,and 93 signaling pathways involving IL-17 and PI3K-Akt signaling pathways.Molecular docking demonstrated strong binding affinity between the 7 markers and target proteins,with binding energies<-5 kcal/mol.Conclusion The"efficacy component group",main targets and signaling pathways predicted in this study can provide support for the research on the mechanism,material basis and quality control of the alcohol detoxification and liver protection effects of Puerariae Lobatue Radix.

Objective To analyze the current status and hotspots of domestic research on traditional Chinese medicine(TCM)in treating chronic refractory wounds(CRW)over the past 10 years using bibliometric and visualized analysis methods.Methods Articles about TCM therapy for CRW issued by the core periodicals in recent 10 years were retrieved from CNKI,Wanfang and VIP databases.The parameters of annual issued papers,authors,institutions and keywords of the articles were counted with the bibliometric methods.And then the statistical results were presented as visualized graphs by using VOSviewer and CiteSpace software.Results A total of 404 articles were included in the study,and 313 institutions and 1 340 scholars participated in the research on the treatment of CRW with TCM.However,there was limited collaboration between the authors and institutions.Research hotspots mainly focused on the efficacy of TCM external therapies for diabetic foot and pressure ulcers,and discussions on syndrome differentiation,treatment principles and methods about internal treatment by various medical experts.The development and application of Chinese patent medicines,exploration of TCM medication patterns,and the evidence-based medical research on TCM are future research trends in the treatment of CRW with TCM.Conclusion Research on TCM treatment of CRW has attracted significant attention in recent years,but academic barriers exist between the authors and institutions.In the future,it is necessary to promote multicenter research collaboration,strengthen the exploration of experiences in acupoint selection,and conduct higher-level research,thus to provide more compelling evidence and enhance the efficacy of TCM in treating CRW.

ObjectiveTo explore the effectiveness of health information dissemination and its influencing factors using the "Shanghai CDC" WeChat public account as a case study, providing references for public health institutions to optimize the use of official new media platforms for effective publicity. MethodsA total of 1 030 headline articles published on the "Shanghai CDC" WeChat public account between 2016 and 2019 were analyzed using content analysis and non-parametric tests to examine the impact of factors such as titles and content categories. ResultsFrom 2016 to 2019, the number of WeChat public account followers increased by 280 000, with the articles accumulating over 8.8 million views. The median (P₂₅, P₇₅) open rate of articles was 5.90% (3.69%, 10.31%), and the median (P₂₅, P₇₅) sharing and forwarding rate was 6.60% (4.25%, 9.17%). Factors such as the use of first- and second-person pronouns, degree adverbs, negative adverbs, explicit viewpoints, and title length all significantly affected the open rate of articles, with OR (95%CI) values of 0.175 (0.041‒0.756), 32.606 (2.350‒452.432), 4.079 (1.093‒15.230), 0.106 (0.028‒0.409), and 1.184 (1.063‒1.319),respectively (all P<0.05). In terms of content, statistical significant differences in dissemination effectiveness were observed across article categories and themes (P<0.05). In terms of article categories, articles related to news hotspots and service information had higher open rates of 9.58% and 14.00%, respectively. These two types of articles also obtained higher sharing and forwarding rates of 7.65% and 9.16%, respectively. In terms of article topics, compared with healthy life and health products, among the top four topics in terms of publication volume, the open rates of articles about infectious diseases and disease-causing biology and immunization programs were higher, accounting for 7.88% and 6.88%, respectively, with no significant difference in sharing and forwarding rates. ConclusionThe "Shanghai CDC" WeChat public account demonstrated good dissemination effectiveness. Enhancing article titles by increasing informational content and degree adverbs (e.g., "highly," "most," and "extremely") and negative adverbs (e.g., "no") can improve dissemination reach. Public health WeChat accounts should incorporate news hotspots or service information in their articles. While maintaining their strengths in disseminating knowledge on infectious diseases and immunization programs, they should also enhance public education in other professional fields within their scope of responsibility to improve the overall dissemination impact of health information.

Objective:To assess the fall risk of hospitalized patients with cardiovascular diseases, analyze the related influencing factors, and construct a prediction model based on machine learning technology, so as to provide a basis for the fall management of hospitalized patients with cardiovascular diseases.Methods:This study was a retrospective cohort study. A total of 450 patients admitted to the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University from June 2017 to June 2024 were selected as the research objects by convenience sampling method. By reviewing electronic medical records, trained nurses extracted the patients' general information and Activities of Daily Living Scale (ADL) scores during hospitalization. Lasso regression was used to screen risk factors, and machine learning libraries were used to construct support vector machine (SVM), decision tree, XGBoost, and neural network models. Bootstrap resampling method and area under the curve (AUC) were used to verify the model performance.Results:Among the 450 patients, there were 261 males and 189 females, with a mean age of (66.0 ± 8.4) years. Among them, 90 patients fell during hospitalization and 360 patients did not fall. The results of Lasso regression showed that ADL score ≤60 points, use of hypnotics, hypokalemia, nighttime toilet visits≥2 times, use of antihypertensive drugs, no caregiver, and history of atrial fibrillation were all risk factors for falls in hospitalized patients with cardiovascular diseases (regression coefficients ranging from 0.61 to 1.20, all P<0.01). Among the machine learning models, XGBoost had the best comprehensive performance (AUC=0.98), which was better than decision tree (AUC=0.66), SVM (AUC=0.95), and neural network (AUC=0.87). Conclusions:The fall risk of hospitalized patients with cardiovascular diseases is jointly affected by physiological, medication and behavioral factors, and the XGBoost model can effectively identify high-risk groups. In actual clinical work, nursing strategies can be optimized in combination with risk factors, and the application of intelligent fall prediction and assessment tools can be promoted.

Objective To explore the syndrome differentiation rules of the Yin Dan and Yang Dan method,and summarize Professor Yang Zhimin's valuable experience in the treatment of insomnia.Methods The case data of 11390 insomnia patients treated by Professor Yang Zhimin was retrospectively analyzed,and the distribution of symptoms,signs,pathogenesis and syndrome differentiation rules of insomnia patients was examined based on latent structure analysis.Result A total of 44 symptoms and signs can explain the overall situation of insomnia patients,showing the characteristics of both excess and deficiency,cold and heat.A total of 36 hidden categories(symptom clusters and pathogenesis)was composed.Symptoms and signs such as fear of wind and cold can explain the overall situation of insomnia patients with cold syndrome due to weakness of Wei Qi,symptoms and signs such as pale eyelid can explain the overall situation of insomnia patients with heat syndrome due to weakness of Ying Xve,and established diagnostic criteria for insomnia patients with cold syndrome due to weakness of Wei Qi and heat syndrome due to weakness of Ying Xve.Conclusion Based on the Yang Dan and Yin Dan method to distinguish and treat insomnia from the perspective of disharmony between Ying and Wei,it is in line with the basic understanding of the pathogenesis of insomnia in the classics of traditional Chinese medicine.The pattern differentiation rules obtained through the latent structure analysis method are helpful to summarize valuable clinical experience and provide a certain reference and basis for clinical practice.

Objective To explore the syndrome differentiation rules of the Yin Dan and Yang Dan method,and summarize Professor Yang Zhimin's valuable experience in the treatment of insomnia.Methods The case data of 11390 insomnia patients treated by Professor Yang Zhimin was retrospectively analyzed,and the distribution of symptoms,signs,pathogenesis and syndrome differentiation rules of insomnia patients was examined based on latent structure analysis.Result A total of 44 symptoms and signs can explain the overall situation of insomnia patients,showing the characteristics of both excess and deficiency,cold and heat.A total of 36 hidden categories(symptom clusters and pathogenesis)was composed.Symptoms and signs such as fear of wind and cold can explain the overall situation of insomnia patients with cold syndrome due to weakness of Wei Qi,symptoms and signs such as pale eyelid can explain the overall situation of insomnia patients with heat syndrome due to weakness of Ying Xve,and established diagnostic criteria for insomnia patients with cold syndrome due to weakness of Wei Qi and heat syndrome due to weakness of Ying Xve.Conclusion Based on the Yang Dan and Yin Dan method to distinguish and treat insomnia from the perspective of disharmony between Ying and Wei,it is in line with the basic understanding of the pathogenesis of insomnia in the classics of traditional Chinese medicine.The pattern differentiation rules obtained through the latent structure analysis method are helpful to summarize valuable clinical experience and provide a certain reference and basis for clinical practice.

Acute lung injury (ALI) has been a kind of acute and severe disease that is mainly characterized by systemic uncontrolled inflammatory response to the production of huge amounts of reactive oxygen species (ROS) in the lung tissue. Given the critical role of ROS in ALI, a Fe₃O₄ loaded bovine serum albumin (BSA) nanocluster (BF) was developed to act as a nanomedicine for the treatment of ALI. Combining with NIR irradiation, it exhibited excellent ROS scavenging capacity. Significantly, it also displayed the excellent antioxidant and anti-inflammatory functions for lipopolysaccharides (LPS) induced macrophages (RAW264.7), and Sprague Dawley rats via lowering intracellular ROS levels, reducing inflammatory factors expression levels, inducing macrophage M2 polarization, inhibiting NF-κB signaling pathway, increasing CD4⁺/CD8⁺ T cell ratios, as well as upregulating HSP70 and CD31 expression levels to reprogram redox homeostasis, reduce systemic inflammation, activate immunoregulation, and accelerate lung tissue repair, finally achieving the synergistic enhancement of ALI immunotherapy. It finally provides an effective therapeutic strategy of BF + NIR for the management of inflammation related diseases.