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 review the application scope of risk communication based on eHealth technology in the primary prevention of cardiovascular diseases,so as to provide references for future research and application.Methods A systematic search was conducted in PubMed,Cochrane Library,Embase,Web of Science,CINAHL,PsycINFO,CNKI,Wanfang database,and SinoMed.The search time limit was from the establishment of databases to March 1,2024.The included literature was summarized and analyzed.Results A total of 24 articles were included.The forms of eHealth technology applied in risk communication for primary prevention of cardiovascular include online websites,computerized decision support systems,electronic health records,mobile applications,email,telephone,and text messages.The functions include risk assessment,risk notification,personalized advice,risk tracking and reminders.The outcome indicators include risk perception,physiological indicators,lifestyle and behavior,psychological indicators,feasibility evaluation,decision correlation,doctor-patient communication,intention,risk score,and physician drug prescription.Conclusion The use of eHealth technology in risk communication of cardiovascular diseases has potential value in improving patients'risk perception and promoting healthy behaviors.It is necessary to continuously improve the functions of eHealth technology and enhance its precision and intelligence,so as to better meet the needs of medical staff and patients and promote the efficient implementation of primary prevention of cardiovascular diseases.

Hot melt extrusion(HME)technology employs thermodynamic and kinetic principles to mix pharmaceutical polymers with crystalline drugs at high temperatures and extrude them,embedding drug molecules within the polymer matrix to form solid dispersions.Due to its solvent-free nature,capability for one-step processing,and support for continuous operation,HME has garnered significant attention in the pharmaceutical industry in recent years.This article introduced the basic principles and development history of HME technology and its marketed drugs.It reviewed the research progress of HME technology in improving drug solubility,masking taste,controlled release,targeted release,oral dispersible films,implant formulations,semi-solid formulations,and 3D printed formulations.Additionally,the article summarized the advantages and limitations of HME technology and provided an outlook on its future development.

Objective To investigate and compare the effects of electroacupuncture and dexamethasone on lung function and histomorphology and behavior in the offspring of perinatal nicotine exposure(PNE)rats.Methods Twenty-four pregnant Sprague-Dawley rats were randomly divided into control,model,electroacupuncture shallow needling,and dexamethasone groups using the random number table method(n=6 rats per group).A pulmonary dysplasia model in offspring rats with PNE was prepared by cervicodorsal subcutaneous injection with nicotine,and successful establishment of the model was confirmed by demonstrating statistically significant differences in growth parameters,lung function,and lung morphology compared to the control group.From the sixth day of maternal conception,the control group received cervicodorsal subcutaneous injection with 0.9%sodium chloride solution(1 mg/kg once per day),and the remaining groups were similarly injected with nicotine(1 mg/kg once per day).Concurrent with the nicotine injections,the electroacupuncture shallow needling group received electroacupuncture interventions at the"Zusanli"(ST 36)acupoint on both sides once a day for 20 min.In contrast,the offspring rats in the dexamethasone group received intraperitoneal dexamethasone injections from postnatal day 8(1.5 mg/kg once per day for 3 days),with a later dose of 0.75 mg/kg once per day for 4 days.Following successful model establishment,four offspring per rat were retained in each group using the random number table method.Until the 21st day after the birth of the offspring,using the random number table method,one offspring randomly selected from the four retained offspring per rat in each group was assigned to growth parameter assessment including body weight,lung weight,and lung index;simultaneously,one offspring was randomly selected for pulmonary function which was detected by a small animal pulmonary function machine,with the parameters of forced vital capacity(FVC),functional residual capacity(FRC),dynamic lung compliance(Cdyn),peak expiratory flow(PEF),peak inspiratory flow(PIF),and airway resistance(RL);concurrently,one offspring was randomly selected for hematoxylin and eosin staining to observe the histomorphology of the lung tissue,alveolar numbers,and mean alveolar septal thickness;additionally,one offspring was randomly selected for Morris water maze testing to evaluate the effects of the two intervention methods on learning and memory capabilities in offspring rats with PNE.Results Compared with the control group,the body weight,lung weight,lung index,FVC,PEF,FRC,Cdyn,alveolar number,platform crossing times,target quadrant time percentage,and target quadrant path percentage in the Morris water maze experiment were significantly decreased in the offspring rats of the model group(P<0.01).In contrast,PIF,RL,average thickness of alveolar septa,and latency of the Morris water maze experiment were significantly increased in the offspring rats of the model group(P<0.01).Compared with the model group,both electroacupuncture shallow needling group and dexamethasone group exhibited significant increases in body weight,lung weight,lung index,FVC,PEF,FRC,Cdyn,and alveolar numbers(P<0.05,P<0.01),along with significant decreases in PIF,RL values,and mean alveolar septal thickness(P<0.01).However,in the Morris water maze experiment,compared with the model group,the electroacupuncture shallow needling group demonstrated significantly more platform crossing times and a higher target quadrant time percentage and target quadrant path percentage(P<0.01),coupled with reduced latency period(P<0.01),whereas the dexamethasone group showed no significant differences compared to the model group.Compared to the electroacupuncture shallow needling group,the dexamethasone group showed significantly less platform crossing times and a lower target quadrant time percentage and target quadrant path percentage,coupled with increased latency period(P<0.01).Conclusion Both electroacupuncture and dexamethasone demonstrated protective effects on lung development in PNE offspring rats by ameliorating lung histomorphology and pulmonary function.However,offspring receiving late,small-dose,short-course dexamethasone exhibited inferior learning and memory capabilities,whereas the electroacupuncture group showed significantly superior cognitive performance compared to the dexamethasone group.

Objective:To evaluate potentially inappropriate medication (PIM) in hospitalized elderly patients with bacterial pneumonia, and explore its influencing factors.Methods:It was a single-center cross-sectional study. The study focused on elderly patients with bacterial pneumonia who were admitted to Xuanwu Hospital, Capital Medical University from January 2018 to November 2022. Patients′ gender, age, weight, length of hospital stay, diagnosis at admission, physical examination, diagnosis at discharge, comorbidities, medications, and laboratory test results were extracted from hospital information system and electronic medical records. Medication use of patients included in the analysis during their hospitalization were evaluated according to the classification of PIMs in the 5 lists of the Beer′s criteria of American Geriatrics Society. Based on whether PIM occurred, the patients were divided into with PIM group and without PIM group. The clinical features between the 2 groups were compared and the influencing factors of PIM were analyzed using multivariable logistic regression.Results:A total of 2 720 patients were included, in which 1 734 (63.75%) were male. The median age was 78 (70, 85) years and their ages ranged from 65 to 103 years. The number of drugs used per patient was 14 (10, 18) kinds, ranging from 1 to 57 kinds. The length of hospital stay was 12 (9, 17) days, ranging from 1 to 162 days. Charlson comorbidity index (CCI) was 6 (5, 8) points. Among the 2 720 patients, 1 894 (69.63%) experienced PIM, with a total of 6 166 cases of PIM. The top 3 drugs ranked by the number of PIM occurrence were antiplatelet agents (1 357 cases), benzodiazapine receptor agonists (956 cases), and antipsychotics (884 cases). The comparison of clinical characteristics between the 2 groups showed that differences in age, CCI, length of hospital stay, and number of medications between with PIM and without PIM patients were statistically significant (all P<0.001). Multivariable logistic regression results showed that CCI, length of hospital stay, and number of medications were independent influencing factors for PIM. The risk increased by 8% and 1% with one point increase in CCI and one day extension in length of hospital stay [odds ratio ( OR)=1.08, 95% confidence interval ( CI): 1.04-1.13, P<0.001; OR=1.01, 95% CI: 1.00-1.03, P=0.03]. PIM risk of patients with more than 15 concurrent medications had a 22.16 times higher PIM risk than those with less than 5 concurrent medications ( OR=22.16, 95% CI: 14.15-34.72, P<0.001). Conclusions:Hospitalized eldery patients with bacterial pneumonia who have more severe comorbidities, longer hospital stay, and multiple concomitant medications are at a higher risk of PIM occurrence. Rational medication use among these patients should be paid attention to in clinical practice.

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.

As the core force in medical services,healthcare professionals are key stakeholders in implementing the Healthy China strategy,strengthening public health awareness,and improving national health literacy.They must actively shoul-der the social responsibility of science communication.In the face of the rising mortality rate of coronary heart disease(CHD),they are obligated to scientifically disseminate relevant health knowledge to the public.This article takes the Fifth Internal Medi-cine Party Branch of the Second Clinical General Party Branch at Guangdong Provincial Hospital of Traditional Chinese Medicine(Dade Road Main Campus)as a typical case to explore how Party building can create the"Heart-Shaping"science popularization brand for CHD.The Party branch plays a leading and exemplary role by organizing resources and uniting Party members.Through cross-media integration,innovative content formats,and other methods,it fosters a strong atmosphere of science popularization under Party leadership,encouraging medical staff to break away from tradition and pioneer a diversified model of CHD science communication,successfully establishing the"Heart-Shaping"brand.Additionally,it meticulously cultivates a professional sci-ence communication team,achieving synergistic progress in both Party building and CHD science popularization.This provides replicable and practical innovative experience for Party building-driven CHD science communication,highlighting the unique ad-vantages of Party building in enhancing the effectiveness of CHD science popularization and promoting the integration of Party work and professional services.

Objective:To systematically review the progress in the method development and application of distributed learning in the estimation of epidemiological effect and provide methodological reference for multi-center studies.Methods:We conducted a literature retrieval for English papers published up to December 31, 2023 by using keywords of "health/medical big data" and "distributed/federated learning". After consulting experts, we set criteria of paper inclusion and exclusion and created a framework for data extraction. We collected information about basic study details, including method, application, and evaluation. Two researchers independently screened the papers and extracted information. We used EndNote 20 for the management of literatures and EpiData for the management of data.Results:A total of 3 444 papers were collected, and 29 papers were included in the final analysis. Most of the papers (25, 86.2%) were published in or after 2019, and the papers were mainly from the United States (21/29, 72.4%). For the estimation of epidemiological effects, 22 distributed learning methods had been developed, including methods for logistic regression (8), Cox regression (8), Poisson regression (2), and generalized linear mixed model (GLMM) (4), as well as three platforms for distributed analysis (VLP, Vantage6, AusCAT). The 29 papers described 45 applications, with 20 (44.4%) focusing on the establishment of prediction model and 25 (55.6%) on association analysis. Importantly, except for GLMM, current distributed learning methods can estimate effects with little bias in 1-3 rounds of communication. These methods show less bias compared with meta-analysis, especially in the address of data heterogeneity and rare outcomes. However, less studies examined how differences in data structure and sparse data affect results, an area that requires further research.Conclusion:While distributed learning shows promise in epidemiological effect estimation, it is still in early development, requiring further research on data heterogeneity handling and communication efficiency improvement.

Objective:To summarize the best evidence for frailty management in patients undergoing postoperative chemotherapy for gastric cancer, so as to provide reference for alleviating patient frailty.Methods:Guidelines, expert consensus, evidence summaries, systematic reviews, and randomized controlled trials and other articles on the frailty management of patients with postoperative chemotherapy for gastric cancer were electronically searched in computerized decision-making systems such as UpToDate, BMJ Best Practice, and Guidelines International Network, in comprehensive databases such as PubMed, Embase, and Web of Science, and in the websites of professional societies. The search period was from database establishment to September 15, 2024. Two researchers independently screened the literature and evaluated the quality of the included literature, combining professional judgment to extract and summarize the best evidence.Results:A total of 18 papers were included, including two clinical decisions, one evidence summary, eight guidelines, two expert consensus, one systematic review, one randomized controlled trial, two quasi-experimental studies, and one observational study. The best evidence included a total of 34 pieces in seven aspects of comprehensive screening, nursing plan construction, preoperative prehabilitation, nutritional interventions, Chinese medicine interventions, exercise interventions, and psychological interventions for frailty.Conclusions:The summary of the best evidence for frailty management in patients undergoing postoperative chemotherapy for gastric cancer may provide an evidence-based basis for frailty interventions by clinical medical and staff.

Home-based self-management can effectively improve functional status and slow disease progression in patients with stroke. Modern information technology has brought new opportunities for enhancing stroke self-management at home. This review summarizes the current application of modern information technologies-including artificial intelligence, mobile devices, virtual reality, and the Internet of Things-in home-based self-management for stroke patients. Based on this, the review further discusses the challenges and opportunities associated with applying these technologies, aiming to provide a reference for promoting their broader implementation in stroke patient self-management.