ObjectiveTo develop and preliminarily validate a prediction model for brace treatment failure risk in patients with adolescent idiopathic scoliosis (AIS), based on information obtained before brace treatment and during initial brace fitting. MethodsA total of 191 patients with AIS who initiated thoracolumbosacral orthosis treatment at Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from March, 2015 to August, 2024 and had determinable outcomes were retrospectively included. Patients were divided according to a prespecified scheme into a training set (n = 133) and a validation set (n = 58). Brace treatment failure was defined as progression of the major-curve Cobb angle by ≥ 5° from baseline during follow-up or at brace weaning, or a final major-curve Cobb angle > 45°. Logistic regression, random forest, support vector machine with radial basis function kernel, and extreme gradient boosting (XGBoost) models were developed using routinely available clinical and radiographic variables before brace treatment and during initial brace fitting. Stratified five-fold cross-validation was used for hyperparameter tuning in the training set. Model performance was evaluated in the validation set using the area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AUPRC), Brier score, calibration curves, and decision curve analysis (DCA). SHapley Additive exPlanations (SHAP) was used to interpret the main explanatory model. ResultsIn cross-validation of the training set, both random forest and XGBoost showed good discriminative performance, with cross-validation-AUC values of 0.871 and 0.880, respectively. In the validation set, the AUC values of random forest and XGBoost were 0.888 and 0.899, the AUPRC values were 0.678 and 0.830, and the Brier scores were 0.086 and 0.076, respectively. Random forest was selected as the primary model for interpretation, with a calibration intercept of 0.091 and a calibration slope of 0.995. SHAP analysis indicated that the in-brace correction rate and the major-curve Cobb angle measured in the brace contributed most to the model predictions. ConclusionThe random forest model developed using routinely available pretreatment and initial-fitting variables shows preliminary predictive value for brace treatment failure risk in AIS, and may provide quantitative support for follow-up scheduling, brace-fit reassessment and early adherence-oriented management.

Objective To investigate the risk factors for ICU-acquired weakness (ICU-AW) in patients with sepsis, and to construct a nomogram prediction model. Methods A total of 360 patients with sepsis admitted from January 2020 to December 2025 were enrolled as study subjects. The risk factors for ICU-AW were identified by logistic regression analysis. A nomogram prediction model was constructed, and the model was validated. Results Multivariate logistic regression analysis indicated that age, APACHE II score, duration of mechanical ventilation, duration of immobilization, duration of sedation, and NLR were risk factors for the occurrence of ICU-AW (P<0.05), while ALB was a protective factor (P<0.05). A nomogram model was constructed based on these seven variables. After validation via Bootstrap resampling, ROC curve showed an AUC of 0.949 (0.929–0.969) and a corrected AUC of 0.942 (0.940–0.948), indicating good discrimination degree of the model. Hosmer-Lemeshow test for calibration curve revealed a chi-square value of 10.188 (P=0.252), suggesting that the predicted value of fitting was generally consistent with the actual value. Decision curve analysis demonstrated that when the threshold was in the range of 0.05–0.9, the model had a good net benefit. Conclusion The nomogram prediction model for sepsis ICU-AW based on seven indicators including age, APACHE II score, NLR, ALB, and the durations of mechanical ventilation, immobilization, and sedation exhibits good predictive efficiency and stability. This nomogram prediction model is helpful for the clinical rapid screening of ICU-AW high-risk groups in patients with sepsis, and meets clinical needs for early warning and precise prevention and control.

OBJECTIVE: Aloin, the main active component in Aloe vera (L.) Burm. f., has shown promising anti-tumor effects. This study investigated the impact of aloin in lung squamous cell carcinoma (LUSC) and explored its functional mechanism. METHODS: We analyzed the viability, migration, invasion, proliferation, and apoptosis of two LUSC cell lines after treatment with aloin. Target molecules of aloin and downstream target transcripts of nuclear receptor subfamily 3 group C member 2 (NR3C2) were predicted by bioinformatics. The biological functions of NR3C2 and metallothionein 1 M (MT1M) in the malignant properties of LUSC cells were determined. A co-culture system of LUSC cells with monocyte-derived macrophages was constructed. Mouse xenograft tumor models were generated to analyze the functions of aloin and NR3C2 in the tumorigenic activity of LUSC cells and macrophage polarization in vivo. RESULTS: Aloin suppressed malignant properties of LUSC cells in vitro. However, these effects were negated by the silencing of NR3C2. NR3C2 was found to activate MT1M transcription by binding to its promoter. Additional upregulation of MT1M suppressed the malignant behavior of LUSC cells augmented by NR3C2 silencing. Analysis of the M1 and M2 markers/cytokines in the macrophages or the culture supernatant revealed that aloin treatment or MT1M overexpression in LUSC cells enhanced M1 polarization while suppressing M2 polarization of macrophages, whereas NR3C2 silencing led to reverse trends. Consistent findings were reproduced in vivo. CONCLUSION This study demonstrated that aloin activates the NR3C2/MT1M axis to suppress the malignant behavior of LUSC cells and M2 macrophage polarization. Please cite this article as: Chen YN, Lu JY, Gao CF, Fang ZR, Zhou Y. Aloin blocks the malignant behavior of lung squamous cell carcinoma cells and M2 macrophage polarization by modulating the NR3C2/MT1M axis. J Integr Med. 2025; 23(2): 195-208.
Lung Neoplasms/metabolism* ; Humans ; Animals ; Cell Line, Tumor ; Carcinoma, Squamous Cell/metabolism* ; Mice ; Macrophages/drug effects* ; Emodin/analogs & derivatives* ; Metallothionein/genetics* ; Cell Proliferation/drug effects* ; Cell Movement/drug effects* ; Apoptosis/drug effects* ; Receptors, Glucocorticoid/genetics*

BACKGROUND:Studies have found that inhibition of tumor necrosis factor receptor-associated factor 6 improves myocardial function and promotes myocardial autophagy in sepsis,but the specific mechanism is not clear.OBJECTIVE:To explore the effect of inhibiting tumor necrosis factor receptor-associated factor 6-regulated mTORC1/ULK1 autophagy signaling pathway on myocardial injury in sepsis mice.METHODS:Thirty male Kunming mice were randomly divided into sham operation group,cecal ligation and puncture group(model group),model+tumor necrosis factor receptor-associated factor 6 specific inhibitor C25-140(model+C)group,model+C25-140+autophagy inhibitor 3-methyladenine(model+C+3-MA)group,and model+C25-140+mTORC1-specific agonist MHY1485(model+C+M)group.The cecum of mice in the sham operation group was not ligated or punctured.The mice in the other groups underwent cecum ligation and puncture to establish the mouse sepsis model.C25-140,3-methyladenine,and MHY1485 were intraperitoneally injected 0.5 hours after surgery according to the grouping.Myocardial tissue was obtained 24 hours after surgery.Hematoxylin-eosin staining was used to evaluate myocardial inflammatory lesions.Transmission electron microscopy was used to observe the changes in the autophagic bodies and mitochondrial microstructures of myocardial cells.TUNEL assay was used to detect myocardial cell apoptosis.PCR was used to detect the relative expression of tumor necrosis factor receptor-associated factor 6 mRNA.Western blot assay was used to detect the expression of related proteins.RESULTS AND CONCLUSION:(1)Compared with sham operation group,myocardial inflammatory cell infiltration and fibrous edema were observed in the model group.The mitochondria of the cells were obviously swollen,and autophagosomes were occasionally seen;cardiomyocyte apoptosis increased significantly;the expression of tumor necrosis factor receptor-associated factor 6,phosphorylated nuclear factor κB P65/P65,p-mTOR/mTOR,p-ULK1/ULK1,P62 and Bax protein increased,and the expression of Bcl2 protein decreased(P＜0.05).(2)Compared with the model group,myocardial inflammation and fibrous edema were alleviated in the model+C group.Myocardial mitochondrial swelling was reduced and autophagosomes increased;cardiomyocyte apoptosis decreased;the expression of phosphorylated nuclear factor κB P65/nuclear factor-κB P65,p-mTOR/mTOR,p-ULK1/ULK1,P62,and Bax protein decreased,while the Beclin-1 and Bcl2 protein increased(P＜0.05).(3)Compared with the model+C group,myocardial autophagosomes decreased and myocardial mitochondrial swelling was more obvious in the model+C+3-MA group.Myocardial inflammation was aggravated;myocardial cell apoptosis increased;the expression of phosphorylated nuclear factor κB P65/nuclear factor κB P65,P62,and Bax protein increased,and the Beclin-1 and Bcl2 protein decreased(P＜0.05).(4)Compared with the model+C group,the expression of p-mTOR/mTOR and p-ULK1/ULK1 in the model+C+M group increased,and the Beclin-1 and microtubule-associated protein 1 light chain 3 Ⅱ/Ⅰ protein expression decreased(P＜0.05).It is concluded that inhibition of tumor necrosis factor receptor-associated factor 6 regulates mTORC1/ULK1 autophagy signal to promote myocardial autophagy and participate in the protection of myocardial injury in sepsis.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

Objective To explore the correlation of neutrophil/lymphocyte ratio(NLR),monocyte/high density lipoprotein cholesterol ratio(MHR)and mild cognitive impairment(MCI)in patients with type 2 diabetes mellitus(T2DM).Methods 159 T2DM patients hospitalized in the Department of Endocrinology,Affiliated Hospital of Xuzhou Medical University from February 2023 to April 2023 were selected.The subjects were divided into normal cognitive function(Con,n=72)group and MCI group(n=87)based on score of Montreal cognitive assessment scale(MoCA).NLR and MHR were calculated and compared between the two groups.Spearman correlation analysis was used to analyze the correlation between NLR,MHR and MoCA score.Logistic regression analysis of the factors influencing the association between T2DM with MCI.Receiver operator characteristic(ROC)curve was used to evaluate the predictive value of NLR and MHR for DM complicated with MCI.Results Compared with Con group,MCI group showed a significant increase in hemoglobin A1c(HbA1c),fasting plasma glucose,NLR,MHR,neutrophil count,monocyte count,serum creatinine,cystatin C,while high density lipoprotein cholesterol lymphocytes,visual space and executive function,naming,attention,language ability,abstract thinking,delayed memory,orientation and MoCA score decreased(P＜0.05).Spearman correlation analysis showed that there was a negative correlation between MHR,NLR and MoCA score,visuospatial and executive function,delayed recall and attention.Logistic regression analysis showed that NLR,MHR,HbA1c were all risk factors for MCI in T2DM.ROC curve analysis showed that the area under the curve of NLR combined with MHR for diagnosing T2DM with MCI was 0.872,with corresponding sensitivity of 81.6%and specificity of 87.5%.Conclusions NLR and MHR are closely related to MCI in T2DM patients.The combination of NLR and MHR have certain efficacy in prediction T2DM with MCI.

Objective To explore the effectiveness of drawing-based method in medical courses and their impact on students' learning habits,academic performance,and comprehensive competencies,in order to meet the demand for high-quality,interdisciplinary,and innovative talent,and provide theoretical support for integrating aesthetic education into medical training.Methods A questionnaire survey was conducted among medical students(n=310)at Dalian Medical University,covering the frequency of using drawing method and their effects on learning outcomes,innovation ability,and humanistic qualities.Data were analyzed using the Chi-square test and Fisher's exact test(P＜0.05).Results Totally 93.6％of students approved of using drawing method for learning medical courses,with 70.8％having developed a habit of drawing-based learning.Students with stronger drawing skills were more inclined to use drawing method and supported their application in teaching.The frequency of drawing-based learning was positively correlated with anatomy scores(P＜0.05).Students generally agreed that drawing method enhanced knowledge comprehension,learning interest,long-term memory,innovation ability,critical thinking,and humanistic qualities.However,students with weaker drawing skills perceived drawing method as potentially increasing learning burdens and being less efficient,but this perception significantly decreased with increased drawing frequency(P＜0.05).Conclusion Drawing methods are widely used in medical courses and effectively improve learning outcomes and comprehensive competencies.Drawing proficiency and frequency are key factors influencing students' acceptance and learning effectiveness.Future efforts should focus on promoting drawing method,strengthening students' drawing skills,and optimizing learning processes to deepen the integration of aesthetic education in medical training.

To investigate the effects of Biyan Jiedu Capsules on the proliferation and apoptosis of nasopharyngeal carcinoma cells and their molecular mechanism, nasopharyngeal carcinoma cells CNE1 and CNE2 were used. They were divided into control group(30% blank serum medium), low-(10% drug-containing serum + 20% blank serum medium), medium-(20% drug-containing serum + 10% blank serum medium), and high-(30% drug-containing serum medium) concentration group of Biyan Jiedu Capsules according to in vitro experiment. After 24 h of intervention, the effects of Biyan Jiedu Capsules on the proliferation of CNE1 and CNE2 were detected by CCK-8 assay, clonal formation experiment, and EdU staining. The effect of Biyan Jiedu Capsules on apoptosis of CNE1 and CNE2 was detected by flow cytometry. Western blot was used to detect the effect of Biyan Jiedu Capsules on the expression of X-linked apoptosis inhibitor protein(XIAP), survivin, proliferating cell nuclear antigen(PCNA), and PI3K/Akt pathway-related proteins in CNE1 and CNE2. The results showed that compared with the control group, the survival rate of CNE1 and CNE2 in the medium and high concentration groups of Biyan Jiedu Capsules could be decreased in a concentration-dependent way(P<0.05, P<0.01). At the same time, EdU staining and clonal formation experiments showed that the proliferation of CNE1 and CNE2 was significantly inhibited in the medium and high concentration groups of Biyan Jiedu Capsules(P<0.05, P<0.01). Flow cytometry showed that the apoptosis rate of CNE1 and CNE2 was significantly increased in all concentration groups of Biyan Jiedu Capsules(P<0.01), and the apoptosis rate was concentration-dependent. Western blot showed that the expressions of XIAP, survivin, PCNA, p-PI3K, and p-Akt in all concentration groups of Biyan Jiedu Capsules were significantly down-regulated(P<0.05, P<0.01). In conclusion, Biyan Jiedu Capsules can inhibit the proliferation and induce apoptosis of nasopharyngeal carcinoma cells possibly by down-regulating the PI3K/Akt signaling pathway.
Humans ; Apoptosis/drug effects* ; Cell Proliferation/drug effects* ; Nasopharyngeal Carcinoma ; Nasopharyngeal Neoplasms/physiopathology* ; Proto-Oncogene Proteins c-akt/genetics* ; Cell Line, Tumor ; Drugs, Chinese Herbal/pharmacology* ; Phosphatidylinositol 3-Kinases/genetics* ; Signal Transduction/drug effects* ; Capsules ; Carcinoma/drug therapy*