OBJECTIVE To develope a predictive model for medication deviation risks during the hospital-to-home transition period in coronary heart disease （CHD） patients with initial treatment， aiming to assist medical staff in rapidly identifying high-risk groups for medication deviation. METHODS A total of 462 CHD patients with initial treatment from the Affiliated Hospital of North China University of Science and Technology （hereinafter referred to as “our hospital”） between January and July 2024 were enrolled. The patients were randomly divided into a modeling group and an internal validation group. The modeling group was further categorized into a medication deviation group and a non-medication deviation group based on whether medication deviations occurred. Similarly， 57 CHD patients with initial treatment from the cardiology department of our hospital between June and September 2025 were collected as an external validation group. Univariate analysis was used to screen predictive factors， followed by multivariate Logistic regression to construct the predictive model. Internal validation methods were employed to evaluate model performance， while external validation methods were used to test the model’s generalizability. RESULTS The 462 patients were divided into a modeling group （319 cases） and an internal validation group （143 cases）. In the modeling group， the medication deviation group （192 cases， 60.19%） and the non-medication deviation group （127 cases， 39.81%） were identified. Multivariate Logistic regression analysis revealed that age， medication type， medication adherence， and self-efficacy in rational medication use were predictive factors for medication deviations in CHD patients with initial treatment （ P ＜0.05）. The predictive model equation was logit P ＝ln[ P /（1－ P ） ] ＝1.321+1.732×age+4.091×medication type －4.360×medication adherence －3.081×self-efficacy in rational medication use. The model demonstrated good discrimination， with a Hosmer-Lemeshow goodness-of-fit test P -value of 0.439， an area under the receiver operating characteristic curve （AUC） of 0.870， sensitivity of 0.970， and specificity of 0.607. A risk nomogram with a total score of 350 points and a cutoff value of 110 points was plotted. The internal validation group showed an AUC o f 0.787 and a prediction accuracy of 77.6%， while the external validation group exhibited an AUC of 0.802 and a prediction accuracy of 73.7%. CONCLUSIONS This study successfully developed a predictive model for medication deviation risks during the hospital-to-home transition period in CHD patients with initial treatment. The model demonstrates excellent discrimination and predictive accuracy， effectively identifying high-risk populations for medication deviations. Age （＞70 years）， number of drug types≥5， poor medication adherence， and poor self-efficacy in rational medication use are independent risk factors for medication deviations.

BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

This study aims to explore the synergistic effects of the main components in salvianolic acids for Injection(SAFI) on key pathological events in cerebral ischemia, elucidating the pharmacological characteristics of SAFI in neuroprotection. Two major pathological gene modules related to endothelial injury and neuroinflammation in cerebral ischemia were mined from single-cell data. According to the topological distance calculated in network medicine, potential synergistic component combinations of SAFI were screened out. The results showed that the combination of caffeic acid and salvianolic acid B scored the highest in addressing both endothelial injury and neuroinflammation, demonstrating potential synergistic effects. The cell experiments confirmed that the combination of these two components at a ratio of 1∶1 significantly protected brain microvascular endothelial cells(bEnd.3) from oxygen-glucose deprivation/reoxygenation(OGD/R)-induced reperfusion injury and effectively suppressed lipopolysaccharide(LPS)-induced neuroinflammatory responses in microglial cells(BV-2). This study provides a new method for uncovering synergistic effects among active components in traditional Chinese medicine(TCM) and offers novel insights into the multi-component, multi-target acting mechanisms of TCM.
Brain Ischemia/metabolism* ; Neuroprotective Agents/pharmacology* ; Animals ; Drugs, Chinese Herbal/administration & dosage* ; Benzofurans/pharmacology* ; Mice ; Drug Synergism ; Caffeic Acids/pharmacology* ; Polyphenols/pharmacology* ; Humans ; Alkenes/pharmacology* ; Endothelial Cells/drug effects* ; Depsides

As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

Real-time acquisition of pulmonary ventilation and perfusion information through thoracic electrical impedance tomography (EIT) holds significant clinical value. This study proposes a novel method based on the rime (RIME) algorithm-optimized variational mode decomposition (VMD) to separate lung ventilation and perfusion signals directly from raw voltage data prior to EIT image reconstruction, enabling independent imaging of both parameters. To validate this approach, EIT data were collected from 16 healthy volunteers under normal breathing and inspiratory breath-holding conditions. The RIME algorithm was employed to optimize VMD parameters by minimizing envelope entropy as the fitness function. The optimized VMD was then applied to separate raw data across all measurement channels in EIT, with spectral analysis identifying relevant components to reconstruct ventilation and perfusion signals. Results demonstrated that the structural similarity index (SSIM) between perfusion images derived from normal breathing and breath-holding states averaged approximately 84% across all 16 subjects, significantly outperforming traditional frequency-domain filtering methods in perfusion imaging accuracy. This method offers a promising technical advancement for real-time monitoring of pulmonary ventilation and perfusion, holding significant value for advancing the clinical application of EIT in the diagnosis and treatment of respiratory diseases.
Humans ; Electric Impedance ; Algorithms ; Tomography/methods* ; Pulmonary Ventilation/physiology* ; Lung/diagnostic imaging* ; Image Processing, Computer-Assisted/methods* ; Adult

Objective To compare the diagnostic value of transabdominal intestinal ultrasound (IUS) and magnetic resonance enterography (MRE) for intestinal stenosis in inflammatory bowel disease (IBD). Methods A retrospective analysis was conducted on the imaging features of 51 IBD patients who underwent both IUS and MRE at Beijing Friendship Hospital,Capital Medical University,between January 2021 and February 2025.With endoscopy as the gold standard,the diagnostic performance of the two methods was compared. Results The sensitivity (84.2% vs. 52.6%,P=0.008) and accuracy (66.7% vs. 45.1%,P=0.035) of IUS for stenosis were higher than those of MRE.In the localization of stenosis,IUS demonstrated higher sensitivity than MRE for detecting stenosis in the terminal ileum (78.6% vs. 35.7%,P=0.070) and colorectum (86.7% vs. 53.3%,P=0.060).Furthermore,IUS showed higher diagnostic accuracy than MRE for terminal ileum stenosis (70.6% vs. 29.4%,P=0.039).The intestinal wall thickness[(8.2±2.7) mm vs. (10.3±3.8) mm;t=3.20,P=0.002)] and stenosis inner diameter[(3.0±1.6) mm vs. (4.3±1.8) mm;t=2.15,P=0.035] measured by IUS were lower than those measured by MRE,with a moderate level of consistency (ICC:0.19-0.53).In addition,IUS demonstrated a higher detection rate for mesenteric fat hypertrophy (70.6% vs. 27.5%,Kappa=0.27,P=0.005),whereas MRE was more sensitive in detecting lymphadenopathy (90.2% vs. 56.9%,Kappa=0.16,P=0.080). Conclusions IUS is superior to MRE in the diagnosis and localization sensitivity for intestinal stenosis in IBD.However,the two methods showcase poor consistency in detecting and quantitating some inflammatory signs.IUS can be used as a first-line screening method for diagnosing intestinal stenosis in IBD patients,while its clinical application should be combined with specific needs to optimize diagnosis.
Humans ; Retrospective Studies ; Constriction, Pathologic/diagnostic imaging* ; Ultrasonography/methods* ; Magnetic Resonance Imaging/methods* ; Inflammatory Bowel Diseases/diagnostic imaging* ; Male ; Female ; Adult ; Middle Aged ; Intestines/diagnostic imaging* ; Sensitivity and Specificity

Objective:To establish a novel method for the early diagnosis of gastric cancer(GC)by screening for the microRNAs within tumor-specific exosomes in peripheral blood.Methods:The gene expression omnibus database was used to download the GSE148334 and GSE130654 datasets of GC exosomes,and differentially expressed RNAs were obtained according to logFC>1 or logFC<-1 and P<0.05.TargetScan and ENCORI databases were used to predict the regulatory relationship between mRNA,miRNA,and ln-cRNA,and Cytoscape software was used to construct a ceRNA network and identify hub genes for validation.A total of 27 patients with early-stage GC,25 healthy controls,and 25 patients with other types of cancer were enrolled,and the ultracentrifugation method was used to isolate exosomes in serum.RT-qPCR was performed for RNA in serum and exosome samples to analyze the expression of hub genes in each group.Results:Three hub genes were identified by the bioinformatics method,namely hsa-miR-105-5p,hsa-miR-219b-3p,and hsa-miR-889-3p,and RT-qPCR showed that the GC group had a significantly higher expression level of hsa-miR-219b-3p in serum and exosome samples than the healthy control group and the other cancer group(serum:4.050±2.697 vs.1.357±0.857/1.934±2.434,P<0.05;exosomes:2.525±1.518 vs.0.774±0.559/1.259±2.127,P<0.05),while there were no significant differences in the expression levels of hsa-miR-889-3p and hsa-miR-105-5p between the GC group and the other two groups(P>0.05).The re-ceiver operating characteristic(ROC)curve showed that hsa-miR-219b-3p in serum-derived exosomes had an area under the ROC curve of 0.896(95%CI=0.800-0.993),which was significantly better than the traditional tumor markers of carcinoembryonic antigen(P=0.015),CA19-9(P=0.021),and CA72-4(P=0.005),and there-fore,exosomal hsa-miR-219b-3p showed a better diagnostic efficacy in GC patients.Conclusion:This study shows that hsa-miR-219b-3p in serum-derived exosomes can be used as a potential marker for the early diagnosis of GC in clinical practice.

OBJECTIVE: To explore the effect and mechanism of DNA methyltransferase 1 (DNMT1) knockout on the inhibition of acute myeloid leukemia (AML) by natural killer (NK) cells. METHODS: The peripheral blood NK cells of AML patients and controls were collected, and the mRNA and protein level of DNMT1 were measured by PCR and Western blot, respectively. The DNMT1 knockout mice were constructed to obtain NK^DNMT1-/- cells. The NK cells were stimulated with interleukin (IL)-12, IL-15, and IL-18 to construct memory NK cells, and then the interferon-γ (IFN-γ) levels were measured by ELISA. After co-culturing with memory NK cells and HL60 cells, the killing effect of NK^DNMT1-/- cells on HL60 cells was detected by LDH assay. Then, the HL60 cell apoptosis and NK cell NKG2D level were measured by flow cytometry. The perforin and granzyme B protein levels of NK cells were measured by Western blot. The AML model mice were constructed by injecting HL60 cells into the tail vein, meanwhile, memory NK cells were also injected, and then the mouse weights, CD33 positive rates, and survival time were detected. RESULTS: The mRNA and protein levels of DNMT1 in NK cells of AML patients were significantly higher than those in the control group (both P < 0.01), while the IFN-γ level induced by interleukin was significantly lower than that in the control group (P < 0.05). Compared with NK^DNMT1+/+ cells, the ability of NK^DNMT1-/- cells to secrete IFN-γ after interleukin stimulation was significantly increased (P < 0.05). The killing and apoptosis-inducing effects of NK^DNMT1-/- cells on HL60 cells were significantly stronger than those of NK^DNMT1+/+ cells (both P < 0.05). The NKG2D level and expression of perforin and granzyme B of NK^DNMT1-/- cells were significantly increased compared with NK^DNMT1+/+ cells (all P < 0.05). Compared with AML mice injected with NK^DNMT1+/+ cells, AML mice injected with NK^DNMT1-/- cells showed significantly increased body weight, decreased CD33 positive rate, and prolonged survival time (all P < 0.05). CONCLUSION Knocking out DNMT1 can enhance the inhibitory effect of NK cells on AML, which may be related to enhancing NK cell memory function.
Killer Cells, Natural/metabolism* ; Animals ; Leukemia, Myeloid, Acute ; Humans ; DNA (Cytosine-5-)-Methyltransferase 1 ; Mice ; Mice, Knockout ; HL-60 Cells ; Apoptosis ; Interferon-gamma/metabolism* ; Granzymes/metabolism* ; Perforin/metabolism* ; NK Cell Lectin-Like Receptor Subfamily K/metabolism*

OBJECTIVE: To investigate the effect of traditional Chinese Five-body balance exercise on patients with preserved ratio impaired spirometry (PRISm). METHODS: Fifteen patients with PRISm and 15 patients diagnosed with chronic obstructive pulmonary disease (COPD) were recruited from the Outpatient Department of Guang'anmen Hospital and Beijing Niujie Health Service Center from April to December, 2023. Participants in both groups attended supervised Five-body balance exercise training twice a week for 12 weeks. Patients with COPD continued their regular medication regimen during the intervention period. The endpoints were mean changes in the 6-min walk test (6MWT), St. George's Respiratory Questionnaire (SGRQ) score, cardiopulmonary exercise testing (CPET), pulmonary function, and scores of COPD assessment test (CAT), modified British Medical Research Council, Self-Rating Anxiety Scale, and Self-Rating Depression Scale from baseline to 12 weeks. Adverse events were monitored throughout the study. RESULTS: The PRISm group showed a significant improvement from baseline to week 12 in 6MWT, SGRQ symptom score, and forced vital capacity (FVC) compared to the COPD group (P<0.05). No significant between-group changes were observed in other outcome measurements (P>0.05). In addition, compared with baseline, both groups exhibited improvements in 6MWT, SGRQ score, and CPET at week 12 (P<0.05). The PRISm group also showed a significant increase in forced expiratory volume in 1 s and FVC, as well as a significant decrease in CAT score at week 12 (P<0.05). No adverse events were reported. CONCLUSION Patients with PRISm may benefit from Five-body balance exercise training, which can improve the exercise capacity, health-related quality of life, and lung function. (Registration No. ChiCTR2200059290).
Humans ; Spirometry ; Male ; Female ; Pulmonary Disease, Chronic Obstructive/therapy* ; Lung/physiopathology* ; Middle Aged ; Exercise Tolerance/physiology* ; Exercise Therapy ; Aged ; Medicine, Chinese Traditional ; Respiratory Function Tests ; East Asian People