OBJECTIVE To analyze the prototype components absorbed into blood and brain of Lithocarpus litseifolius leaves， so as to provide a reference for clarifying the pharmacological material basis of its prevention and treatment of central nervous system dis eases. METHODS The ethanol extract of L. litseifolius leaves， as well as the gastric lavage fluid and perfusion solution were prepared. Using rats as subjects， plasma samples of intestinal wall metabolism， intestinal flora metabolism and hepatic metabolism were prepared via in situ intestinal perfusion and closed intestinal loop method； while comprehensive metabolic plasma samples， brain tissue samples， and cerebrospinal fluid samples were collected after intragastric administration. UPLC-HRMS technology was utilized to analyze and identify chemical components and prototype components absorbed into blood and brain of L. litseifolius leaves. RESULTS A total of 66 chemical constituents were identified in L. litseifolius leaves， primarily consisting of flavonoids， organic acids， and others. A total of 16， 13， 11， and 5 prototype components were identified in intestinal wall metabolism， intestinal flora metabolism， hepatic metabolism， and comprehensive metabolic plasma samples， respectively. Additionally， 4 prototype components were detected in brain tissue and 9 in cerebrospinal fluid. Phloridzin， trilobatin， phloretin-2- O -malonyl hexoside， and phloretin were identified as common components across all sample types. CONCLUSIONS Prototype components absorbed into blood and brain of L. litseifolius leaves， such as phloridzin， trilobatin， phloretin， and other components may serve as the pharmacological material basis for their therapeutic effects on central nervous system diseases.

Objective:To analyze the changes in the prevalence characteristics of multimorbidity among adolescents aged 13-18 in Inner Mongolia Autonomous Region from 2019 to 2022 and to explore the association between multimorbidity and moderate to high-intensity physical activity among them.Methods:A stratified random cluster sampling method was used to select students aged 13-18 in Inner Mongolia Autonomous Region every September from 2019 to 2022. Physical examinations, demographic characteristics, and depression-related surveys were conducted to analyze the multimorbidity of overweight, obesity, high blood pressure, myopia, spinal curvature abnormality, and depression. A logistic regression model was used to analyze the association between multimorbidity and moderate to high-intensity physical activity.Results:From 2019 to 2022, 70 972, 62 923, 80 254, and 78 288 study subjects were included, with the rates of multimorbidity being 56.4%, 55.4%, 57.2%, and 55.8%, respectively. The rates of multimorbidity remained relatively stable from 2019 to 2022 ( χ2=0.06, P=0.950). The incidence of multimorbidity among girls was significantly higher than that among boys ( P<0.001). The incidence of multimorbidity among urban students was significantly higher than that among suburban students ( P<0.001). The incidence of multimorbidity among high school students was higher than that among middle school students ( P<0.001). The top three multimorbidity combinations were myopia and overweight/obesity (26.4%), myopia and high blood pressure (24.4%), and myopia and depression (19.8%), while the least common combination was depression and spinal curvature abnormality (1.1%). The multimorbidity patterns showed no significant differences between years ( χ2=0.03, P=0.999). The multimorbidity status was significantly associated with the status of meeting the standard of moderate to high-intensity physical activity ( OR=0.83, 95% CI: 0.80-0.86). The association was stronger in boys ( OR=0.77, 95% CI: 0.73-0.81) compared with girls ( OR=0.90, 95% CI: 0.85-0.96), with a significant interaction term ( P<0.001). Conclusion:From 2019 to 2022, the incidence of multimorbidity among adolescents aged 13 to 18 in Inner Mongolia Autonomous Region is relatively high, mainly due to the co-occurrence of myopia and other health problems. Adequate physical activity is an important factor in reducing multimorbidity.

ObjectiveTo investigate the effect of video-based educational intervention combined with maternal presence on perioperative adverse outcomes in preschool children undergoing general anesthesia， including cooperation in anesthesia induction， perioperative anxiety， pain and agitation during recovery. MethodsA total of 300 preschool children scheduled for general anesthesia in our hospital from June to December 2023 were randomly assigned to control group （n=150） and intervention group （n=150）. The control group received routine recovery care. For the intervention group， in addition to routine recovery care， a preoperative visit was scheduled one day before surgery. During this visit， mothers were guided to watch anesthesia videos with their children. During the waiting period in the operating room and 30 minutes after awakening， the mothers were guided to accompany the children for more than 30 minutes. Recovery conditions were recorded using the surgical anesthesia information system， and the children’s anesthetic induction compliance， perioperative anxiety， pain， and agitation were evaluated and recorded using the modified Yale Preoperative Anxiety Scale （m-YPAS）， the Induction Compliance Scale （ICC）， the Children’s Pain Behavior Scale （FLACC）， and the Pediatric Agitation and Emergence Delirium Scale （PAED）. ResultsOn the preoperative visit day， there were no statistically significant differences in baseline data between the two groups （P > 0.05）. For perioperative anxiety， the m-YPAS scores of the intervention group were significantly lower than those of the control group， both when entering the operating room waiting area （35.27±6.48 vs. 41.79±6.68， P < 0.05） and 30 minutes after postoperative recovery （20.13±7.05 vs. 35.75±9.51， P < 0.05）. In terms of anesthesia induction cooperation， the ICC scores of the intervention group were significantly lower than those of the control group （1.84±0.95 vs. 3.17±0.62， P < 0.05）， and the proportion of good induction cooperation was significantly higher than that of the control group （24.00% vs. 12.67%， P < 0.05）. There was no significant difference in awakening duration between the two groups， but the intervention group had a significantly shorter length of stay in the post-anesthesia care unit than the control group （0.90±0.29 hours vs. 1.29±0.42 hours， P < 0.001）. For perioperative agitation， the PAED scores of the intervention group were significantly lower than those of the control group （entering in the operating room waiting area： 8.5 vs. 9.2， P < 0.05； 30 minutes after postoperative recovery： 4.2 vs. 7.8， P < 0.05）. In terms of pain scores， the FLACC scores of the intervention group were also significantly lower than those of the control group， both when entering the operating room waiting area （ 5.3 vs. 6.7， P < 0.05； 30 minutes after postoperative recovery： 2.1 vs. 4.9， P < 0.05）. ConclusionsVideo-based educational intervention combined with maternal presence reduces the perioperative anxiety， pain and agitation of preschool children undergoing general anesthesia， and improved the compliance of anesthesia induction. It is recommended to promote this intervention measure in clinical practice.

BACKGROUND: Metabolic-associated fatty liver disease (MAFLD) is the predominant form of chronic liver disease worldwide. This study was designed to investigate the proportion and characteristics of MAFLD within the general Chinese population and to identify the contributory risk factors for liver fibrosis among MAFLD individuals. METHODS: The participants were recruited from a cohort undergoing routine health evaluations at the Third Hospital of Hebei Medical University between May 2019 and March 2023. The diagnosis of MAFLD was based on the established clinical practice guidelines. The fibrosis-4 index score (FIB-4) was employed to evaluate hepatic fibrosis, with a FIB-4 score of ≥1.3 indicating significant fibrosis. Binary logistic regression analyses were used to determine risk factors associated with significant hepatic fibrosis in MAFLD. RESULTS: A total of 22,970 participants who underwent comprehensive medical examinations were included in the analysis. The overall proportion of MAFLD was 28.77% (6608/22,970), with 16.87% (1115/6608) of these patients showing significant fibrosis as assessed using FIB-4. Independent risk factors for significant liver fibrosis in MAFLD patients were male (odds ratio [OR] = 0.676, 95% confidence interval [CI]: 0.558-0.821), hepatitis B surface antigen (HBsAg) positivity (OR = 2.611, 95% CI: 1.557-4.379), body mass index ≥23.00 kg/m 2 (OR = 0.632, 95% CI: 0.470-0.851), blood pressure ≥130/85 mmHg (OR = 1.885, 95% CI: 1.564-2.272), and plasma glucose ≥5.6 mmol/L (OR = 1.815, 95% CI: 1.507-2.186) (all P <0.001). CONCLUSIONS The proportion of MAFLD in an urban Chinese population is 28.77%. About 16.87% of MAFLD patients presented with significant liver fibrosis. Independent risk factors for significant liver fibrosis in MAFLD patients should be noticed.
Humans ; Male ; Female ; Liver Cirrhosis/pathology* ; Middle Aged ; Risk Factors ; Adult ; Fatty Liver/pathology* ; Aged ; China/epidemiology* ; Logistic Models ; Urban Population ; East Asian People

Objective To construct an enhancer-based prognostic risk prediction model for non-small cell lung cancer (NSCLC) by integrating DNA methylome data and transcriptome data. Methods The weighted gene co-expression network analysis (WGCNA) was used to identify NSCLC related genes from the differentially methylated positions (DMPs) of enhancers. Based on the transcriptome data,the prognostic risk prediction model was constructed using LASSO-Cox regression algorithm. Results Through the analysis on DNA methylome data of NSCLC,19784 DMPs were obtained and their distribution patterns were characterized,including 6089 DMPs of enhancers. WGCNA analysis screened 79 highly correlated DMPs of enhancer with NSCLC from the 6089 DMPs. After analyzing the target genes of 79 DMPs with LASSO-Cox regression based on the transcriptome data,10 genes were used to construct a prognostic risk prediction model. The prognostic risk prediction model was evaluated by calculating the areas under the curve (AUC) of 3-,5-,and 10-year time-dependent receiver operating characteristic (ROC) curves in training set and validation set;and the results showed that the 3-,5-,and 10-year AUC in training set and validation set were all higher than 0.7. Finally,a nomogram was constructed to predict the 3-,5-,and 10-year survival probabilities of NSCLC. Conclusion This study provides new insights into the role of enhancers in NSCLC and has the potential to improve the prognosis by guiding personalized treatment decisions.

Objective:To analyze the changes in the prevalence characteristics of multimorbidity among adolescents aged 13-18 in Inner Mongolia Autonomous Region from 2019 to 2022 and to explore the association between multimorbidity and moderate to high-intensity physical activity among them.Methods:A stratified random cluster sampling method was used to select students aged 13-18 in Inner Mongolia Autonomous Region every September from 2019 to 2022. Physical examinations, demographic characteristics, and depression-related surveys were conducted to analyze the multimorbidity of overweight, obesity, high blood pressure, myopia, spinal curvature abnormality, and depression. A logistic regression model was used to analyze the association between multimorbidity and moderate to high-intensity physical activity.Results:From 2019 to 2022, 70 972, 62 923, 80 254, and 78 288 study subjects were included, with the rates of multimorbidity being 56.4%, 55.4%, 57.2%, and 55.8%, respectively. The rates of multimorbidity remained relatively stable from 2019 to 2022 ( χ2=0.06, P=0.950). The incidence of multimorbidity among girls was significantly higher than that among boys ( P<0.001). The incidence of multimorbidity among urban students was significantly higher than that among suburban students ( P<0.001). The incidence of multimorbidity among high school students was higher than that among middle school students ( P<0.001). The top three multimorbidity combinations were myopia and overweight/obesity (26.4%), myopia and high blood pressure (24.4%), and myopia and depression (19.8%), while the least common combination was depression and spinal curvature abnormality (1.1%). The multimorbidity patterns showed no significant differences between years ( χ2=0.03, P=0.999). The multimorbidity status was significantly associated with the status of meeting the standard of moderate to high-intensity physical activity ( OR=0.83, 95% CI: 0.80-0.86). The association was stronger in boys ( OR=0.77, 95% CI: 0.73-0.81) compared with girls ( OR=0.90, 95% CI: 0.85-0.96), with a significant interaction term ( P<0.001). Conclusion:From 2019 to 2022, the incidence of multimorbidity among adolescents aged 13 to 18 in Inner Mongolia Autonomous Region is relatively high, mainly due to the co-occurrence of myopia and other health problems. Adequate physical activity is an important factor in reducing multimorbidity.

Objective To construct an enhancer-based prognostic risk prediction model for non-small cell lung cancer (NSCLC) by integrating DNA methylome data and transcriptome data. Methods The weighted gene co-expression network analysis (WGCNA) was used to identify NSCLC related genes from the differentially methylated positions (DMPs) of enhancers. Based on the transcriptome data,the prognostic risk prediction model was constructed using LASSO-Cox regression algorithm. Results Through the analysis on DNA methylome data of NSCLC,19784 DMPs were obtained and their distribution patterns were characterized,including 6089 DMPs of enhancers. WGCNA analysis screened 79 highly correlated DMPs of enhancer with NSCLC from the 6089 DMPs. After analyzing the target genes of 79 DMPs with LASSO-Cox regression based on the transcriptome data,10 genes were used to construct a prognostic risk prediction model. The prognostic risk prediction model was evaluated by calculating the areas under the curve (AUC) of 3-,5-,and 10-year time-dependent receiver operating characteristic (ROC) curves in training set and validation set;and the results showed that the 3-,5-,and 10-year AUC in training set and validation set were all higher than 0.7. Finally,a nomogram was constructed to predict the 3-,5-,and 10-year survival probabilities of NSCLC. Conclusion This study provides new insights into the role of enhancers in NSCLC and has the potential to improve the prognosis by guiding personalized treatment decisions.

Objective To summarize the best evidence for perioperative exercise in renal transplant patients and provide evidence-based evidence for clinical staff to perform exercise in renal transplant patients.Methods Evidence-based questions were identified according to the PIPOST model,and computerized searches were conducted on BMJ Best Practice,UpToDate,the World Health Organization,the US National Guidelines,the website of the Chinese Society of Nephrology,the website of the British Renal Association,the website of the American Society of Nephrology,CNKI,the knowledge service platform of Wanfang Data,the Wipo database and other databases for all evidence on perioperative exercise in renal transplant recipients,including clinical guidelines,clinical decision-making,systematic evaluations,evidence summaries,and expert consensus,with a timeframe for searching from the establishment of the database to August 2023.Quality assessment and evidence extraction of the literature were performed independently by 2 nursing graduate students.Results A total of 13 publications were included,including 1 clinical decision,1 guideline,3 expert consensus,and 8 systematic evaluations.A total of 24 pieces of best evidence were summarized in 7 areas:exercise benefits,exercise assessment,preoperative exercise strategies,postoperative exercise strategies,precautions,exercise instruction monitoring,and exercise support.Conclusions This study summarizes the best evidence about perioperative exercise exercise in renal transplantation and provides a reference for standardizing perioperative exercise exercise in renal transplantation.Clinical staff should fully identify the impediments and facilitators of exercise exercise in renal transplant patients,and develop personalized exercise exercise programs based on medical scenarios,patient conditions,and combined with patients'exercise wishes.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective:To investigate the effect and of piperine(PIP)on nerve injury in rats with cerebral infarction.Meth-ods:The rat model of cerebral infarction was prepared by modified thread embolism method.The rats were divided into Sham group,Model group,piperine group(PIP group,20 mg/kg piperine),piperine+PKA inhibitor group(PIP+H-89 group,20 mg/kg PIP+5 mg/kg H-89).The rats were scored for neurological impairment,the volume of cerebral infarction,neuronal damage and neuronal apoptosis were observed,and the levels of cAMP,IL-1β and IL-6 in hippocampus and the protein expressions of GFAP,NSE,AC6,PKA,p-CREB,CREB and BDNF were detected.Results:Compared with Sham group,Model group had large cerebral infarction,cerebral in-farction volume,the neurological deficit score,neuronal apoptosis rate,the levels of IL-6 and IL-1β in hippocampus,and number of GFAP positive cells,the positive expression rates of NSE protein increased,the number of Nissl bodies,and the expressions of cAMP,AC6,PKA,p-CREB and BDNF proteins in hippocampus decreased(P<0.05);compared with Model group,cerebral infarc-tion volume,the neurological deficit score,neuronal apoptosis rate,the levels of IL-6 and IL-1β in hippocampus,and number of GFAP positive cells,the positive expression rates of NSE protein in the PIP group decreased,the number of Nissl bodies,and the ex-pressions of cAMP,AC6,PKA,p-CREB and BDNF proteins in hippocampus increased(P<0.05);the effect of piperine in improving nerve injury in rats with cerebral infarction was able to be reversed by H-89.Conclusion:PIP can inhibit the apoptosis of hippocampal neurons,and improve the neural injury induced by cerebral infarction by activating AC/PKA/CREB signal pathway.