This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

ObjectiveTo investigate the application value of a machine learning model based on preoperative clinical indicators in predicting the risk of hypoalbuminemia after partial hepatectomy. MethodsA retrospective analysis was performed for the clinical data of 700 patients who underwent partial hepatectomy in Nanfang Hospital， Southern Medical University， from January 2018 to January 2023， including demographic data， history of underlying diseases， tumor characteristics， preoperative laboratory markers， and perioperative indicators. The research data were divided into a training set and a test set at a ratio of 7∶3. The two-independent-samples t test was used for comparison of normally distributed continuous data between two groups； the two-independent-samples Wilcoxon rank-sum test was used for comparison of continuous data with skewed distribution between two groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. The least absolute shrinkage and selection operator （LASSO） regression analysis was used to identify characteristic variables， and 7 machine learning algorithms were used to construct predictive models， i.e.， logistic regression， decision tree， artificial neural network， K-nearest neighbors （KNN）， support vector machine， eXtreme gradient boosting， and light gradient boosting machine. The receiver operating characteristic （ROC） curve and the area under the ROC curve （AUC） were used to assess the discriminatory ability of models， and the DeLong test was used for comparison of AUC. The calibration curve and decision curve analysis were used to assess the calibration and clinical practicability of models， and the models were compared with albumin-bilirubin （ALBI） score and Model for End-Stage Liver Disease （MELD） score. SHapley Additive exPlanations （SHAP） were used to interpret the key influencing factors for the optimal model. ResultsA total of 700 patients were finally enrolled， 283 （40.42%） developed hypoalbuminemia after surgery. The LASSO regression analysis identified 8 predictive factors of age， hepatitis B， fatty liver， blockade time， preoperative albumin （Alb）， time of operation， intraoperative blood loss， and preoperative aspartate aminotransferase （AST）. Among the 7 machine learning models， the KNN model showed the best overall predictive performance， with an AUC of 0.835 （95% confidence interval： 0.781 — 0.889）， a sensitivity of 84.0%， and a specificity of 65.5% in the test set. ALBI and MELD scores had an AUC of 0.652 and 0.524， respectively， and the KNN model had a better predictive performance than these two scores （Z=5.309 and 8.945， both P <0.001）. The calibration curve showed good consistency between predicted probabilities and actual incidence rates， and the decision curve analysis showed that the KNN model had net clinical benefit across a wide threshold range. The SHAP analysis showed that preoperative Alb， hepatitis B， time of operation， and age were the most significant influencing factors， and a synergistic effect was observed between hepatitis B and age/time of operation. ConclusionThe KNN machine learning model constructed based on preoperative clinical indicators can effectively predict the risk of hypoalbuminemia after partial hepatectomy and has a better performance than traditional scoring models， which provides a reference for the early identification of high-risk patients in clinical practice.

Objective: To examine the prevalence of e-cigarette use and associated factors among primary and secondary school students in Pudong New Area, Shanghai, and to explore the pathways linking harm perception of e-cigarettes, interpersonal social influence, and attitudes toward e-cigarette use with experimentation behavior, in order to provide scientific basis for further optimizing the prevention and control strategies of e-cigarette among adolescents. Methods: From September to October 2025, a multi stage cluster random sampling method was used to select 5 144 primary and secondary school students aged 8-19 years from 47 primary and secondary schools in Pudong New Area, Shanghai, to conduct an anonymous questionnaire survey. The questionnaire collected information on e-cigarette use, harm perception of e-cigarette, interpersonal social influence, and attitudes toward e-cigarette use. The Chi-square test was applied to analyze the differences in cigarette and e-cigarette use behavior among primary and secondary school students with different demographic characteristics. Structural equation modeling (SEM) was constructed using Mplus 8.3 software, and the bootstrap method was utilized to test the mediating effects. Results: The reported rates of cigarette experimentation, e-cigarette experimentation, and current e-cigarette use among primary and secondary school students were 1.85%, 2.10%, and 0.70%, respectively. Higher reporting rates of e-cigarette experimentation were observed among boys (2.82%), secondary school students aged 16-19 (3.39%), senior high school students (3.05%), and those with weekly pocket money >100 yuan ( 6.11% ) ( χ 2=11.67, 8.61, 8.00, 54.18, all P <0.05). Structural pathway analysis results demonstrated that e-cigarette harm perception positively predicted interpersonal social influence ( β =0.61) and e-cigarette use attitude ( β = 0.53 ), and interpersonal social influence ( β =0.65) and e-cigarette use attitude ( β =0.25) further promoted e-cigarette experimentation behavior among primary and secondary school students (all P <0.01), with interpersonal social influence playing a major mediating role (indirect effect=0.40). Conclusions E-cigarette experimentation behavior among primary and secondary school students in Pudong New Area is jointly influenced by multiple psychosocial factors. Intervention strategies should strengthen interpersonal social factors such as family and peers on the basis of health education, thereby constructing a comprehensive prevention and control strategy for e-cigarette use among primary and secondary school students.

The aim of this study is to explore a new path of empowering ideological and political educa-tion in courses with digital intelligence technology,therefore to improve the teaching quality of biology courses in universities,promote the comprehensive implementation of the fundamental task of cultivating morality and talents,and continuously improve the level of"three pronged education".By using the biol-ogy course"Immunology"as a practical carrier,we have constructed a dual-driven framework of"ideo-logical and political guidance+digital intelligence empowerment"utilizing digital tools to further highlight pedagogical feature enhancement,curricular optimization,innovative teaching models,multidimensional assessment,and enhanced teaching refinement.The empowerment of digital intelligence in the ideological and political construction of the course"Immunology"has achieved notable progress.Students' profes-sional abilities and ideological and political literacy have significantly improved,and the proportion of students with excellent grades has been increasing year by year(81.93％of students with good grades or above in 2024),demonstrating outstanding performance in various social practice activities;The course exhibits excellent demonstration and radiation effects on campus,and the teaching results have been sup-ported by the Ministry of Education and provincial-level education reform projects.This study serves as a practical example for the digital transformation of ideological and political education in higher education courses,providing reference and innovative insights for implementing ideological and political elements in other courses of biology majors.

Objective:To analyze the safety and short-term efficacy of thoracic radiotherapy combined with anlotinib in the treatment of inoperable non-small cell lung cancer (NSCLC).Methods:A prospective study was conducted on patients with unresectable locally advanced NSCLC who were intolerant to concurrent chemoradiotherapy and treated at the Department of Radiation Oncology, Cancer Hospital, Chinese Academy of Medical Sciences, from October 2020 to September 2023. Anlotinib was administered orally concurrently with radiotherapy (days 1-14, 21 days per cycle, for 3 cycles). Adverse effects and short-term tumor recurrence were observed from the beginning of radiotherapy to the 3-month post-radiotherapy. Kaplan-Meier method was used to calculate progression-free survival (PFS) and overall survival (OS) rates from the date of initial treatment (induction therapy), and intergroup comparisons were performed using the log-rank test.Results:The median age was 62 years (range:42-76 years), with a male predominance ( n=36, 88%) of the included 41 patients. The incidence of grade 3-4 acute hematologic adverse events was 20% (8 cases); the incidence of grade 3 hemoptysis was 2% (1 case), with no grade 4 hemoptysis; the incidence of grade 3-4 radiation pneumonitis was 10% (4 cases). No grade 5 adverse events were observed in the entire cohort. With a median follow-up of 19.7 months (range: 7.1-50.1 months), 19 patients (46%) experienced recurrence, including 4 patients (10%) with local recurrence, 6 patients (15%) with regional lymph node recurrence, and 11 patients (27%) with distant metastases. The 1-year PFS rate was 78.3%. 8 patients (20%) died, including 3 patients died from COVID-19 infection during the follow-up period, 1 patient who died from hypostatic pneumonia due to prolonged bed rest after cerebral infarction, and 4 patients died from tumor-related causes. The 1-year OS rate was 78.0%. Conclusions:Thoracic radiotherapy combined with anlotinib demonstrates good safety, manageable adverse events, and favorable short-term efficacy in NSCNC patients intolerant to concurrent chemoradiotherapy.

Objective:To evaluate the role of a single PET-CT scan in predicting survival and prognosis in patients with non-small cell lung cancer (NSCLC) who did not undergo surgery but received radiotherapy after neoadjuvant chemotherapy combined with immunotherapy.Methods:A retrospective analysis was conducted on the data of 23 NSCLC patients treated at the Cancer Hospital of the Chinese Academy of Medical Sciences from May 2022 to June 2024. All patients were pathologically confirmed, received neoadjuvant chemotherapy combined with immunotherapy, did not undergo surgery for various reasons, and instead received radiotherapy. Each patient underwent only one PET-CT scan after neoadjuvant chemotherapy combined with immunotherapy and before radiotherapy. According to the maximum standardized uptake value (SUV max) on PET-CT, patients were divided into the low-uptake group (SUV max < 8, n=12) and high-uptake group (SUV max ≥ 8, n=11). Survival analysis was performed using the Kaplan-Meier method with survival curves plotted. Univariate analysis of influencing factors of survival was conducted using the Cox proportional hazards regression model. Clinical characteristics and survival outcomes of the two groups were compared, including progression-free survival (PFS) and overall survival (OS). Results:The 1-year PFS rates were 100% in the low-uptake group, 54.5% in the high-uptake group. This difference was statistically significant ( P=0.007). The 1-year and 2-year OS rates were both 100% in the low-uptake group, the 1-year and 2-year OS rates were both 90.9% in the high-uptake group, with no statistically significant difference ( P=0.394). Univariate Cox analysis identified age as an independent factor affecting PFS. Conclusions:For NSCLC patients who did not undergo surgical resection but received radiotherapy after neoadjuvant chemotherapy combined with immunotherapy, a single PET-CT scan before radiotherapy has potential value in predicting PFS. However, clinical studies with larger sample size and longer follow-up are required to evaluate its predictive value for OS.

OBJECTIVE: Baicalein has been reported to have wide therapeutic effects that act through its anti-inflammatory activity. This study examines the effect and mechanism of baicalein on sepsis-induced cardiomyopathy (SIC). METHODS: A thorough screening of a small library of natural products, comprising 100 diverse compounds, was conducted to identify the most effective drug against lipopolysaccharide (LPS)-treated H9C2 cardiomyocytes. The core target proteins and their associated signaling pathways involved in baicalein's efficacy against LPS-induced myocardial injury were predicted by network pharmacology. RESULTS: Baicalein was identified as the most potent protective agent in LPS-exposed H9C2 cardiomyocytes. It exhibited a dose-dependent inhibitory effect on cell injury and inflammation. In the LPS-induced septic mouse model, baicalein demonstrated a significant capacity to mitigate LPS-triggered myocardial deficits, inflammatory responses, and ferroptosis. Network pharmacological analysis and experimental confirmation suggested that hypoxia-inducible factor 1 subunit α (HIF1-α) is likely to be the crucial factor in mediating the impact of baicalein against LPS-induced myocardial ferroptosis and injury. By combining microRNA (miRNA) screening in LPS-treated myocardium with miRNA prediction targeting HIF1-α, we found that miR-299b-5p may serve as a regulator of HIF1-α. The reduction in miR-299b-5p levels in LPS-treated myocardium, compared to the control group, was reversed by baicalein treatment. The reverse transcription quantitative polymerase chain reaction, Western blotting, and dual-luciferase reporter gene analyses together identified HIF1-α as the target of miR-299b-5p in cardiomyocytes. CONCLUSION Baicalein mitigates SIC at the miRNA level, suggesting the therapeutic potential of it in treating SIC through the regulation of miR-299b-5p/HIF1-α/ferroptosis pathway. Please cite this article as: Zhou WY, Du JK, Liu HH, Deng L, Ma K, Xiao J, Zhang S, Wang CN. Baicalein attenuates lipopolysaccharide-induced myocardial injury by inhibiting ferroptosis via miR-299b-5p/HIF1-α pathway. J Integr Med. 2025; 23(5):560-575.
Flavanones/pharmacology* ; Animals ; MicroRNAs/genetics* ; Lipopolysaccharides ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Ferroptosis/drug effects* ; Mice ; Myocytes, Cardiac/metabolism* ; Signal Transduction/drug effects* ; Rats ; Male ; Mice, Inbred C57BL ; Cardiomyopathies/etiology* ; Cell Line ; Sepsis/complications*

Objective To explore the effects of home-based exercise rehabilitation on cardiac structure, valvular function, and exercise capacity in patients with severe aortic stenosis (AS) after transcatheter aortic valve replacement (TAVR). Methods 49 patients with severe AS who underwent TAVR at Zhongshan Hospital, Fudan University, from January 2024 to February 2025 were enrolled. They were divided into an exercise group (n＝25) or a non-exercise group (n＝24) based on participating or not in home-based rehabilitation after TAVR. The exercise group received 12 weeks of home-based exercise training (aerobic exercise plus resistance training every week); the non-exercise group received routine care. Transthoracic echocardiography (TTE) was used to assess cardiac structural parameters before discharge (T0) and after 12 weeks of exercise (T1). Functional outcomes including the 6-minute walk test (6MWT), Duke Activity Status Index (DASI), and Short Physical Performance Battery (SPPB) were compared between the two groups. A linear mixed-effects model was used to analyze the effect of home-based rehabilitation on echocardiographic parameters. Patients were stratified by baseline 6MWT (＜240 m as low-function subgroup, ≥240 m as high-function subgroup) to compare exercise-related outcomes between subgroups. Results At T1, the exercise group had a longer 6MWT distance than the non-exercise group (P＝0.012). The linear mixed-effects model showed that after 12 weeks of exercise, the left ventricular end-diastolic diameter (LVEDD) decreased in the exercise group but slightly increased in the non-exercise group, with a significant difference in changes over time between the two groups (P_interaction＝0.030). The exercise group also showed greater improvement in effective orifice area index (P_interaction＝0.028) and effective orifice area (P_interaction＝0.042) than the non-exercise group. Subgroup analysis revealed that in the low-function subgroup, the exercise group showed greater improvement in the 6MWT (P_interaction＝0.035) and the effective orifice area index (P_interaction＝0.046) compared to the non-exercise group; in the high-function subgroup, the exercise group showed greater improvement only in LVEDD compared to the non-exercise group (P_interaction＝0.046). Conclusions Home-based exercise rehabilitation improves exercise capacity, optimizes left ventricular remodeling, and enhances valvular function in patients with severe AS after TAVR, with greater benefits observed in patients with lower baseline 6MWT.

The Kirsten rat sarcoma viral oncogene homolog ( KRAS ) mutation is one of the most prevalent activating alterations in cancer. It indicates a poor overall prognosis due to its highly invasive nature. Although several KRAS inhibitors have been developed in recent years, a significant clinical challenge has emerged as a substantial proportion of patients eventually develop resistance to these therapies. Therefore, identifying determinants of drug resistance is critical for guiding treatment strategies. This review provides a comprehensive overview of the mutation landscape and molecular mechanisms of KRAS activity in various cancers. Meanwhile, it summaries the progress and prospects of small molecule KRAS inhibitors undergoing clinical trials. Furthemore, this review explores potential strategies to overcome drug resistance, with the ultimate goal of steering toward patient-centric precision oncology in the foreseeable future.
Humans ; Drug Resistance, Neoplasm/drug effects* ; Proto-Oncogene Proteins p21(ras)/metabolism* ; Mutation/genetics* ; Neoplasms/genetics* ; Antineoplastic Agents/therapeutic use*