Objective: To explore the latent profile characteristics of regulatory emotional self-efficacy and its relationship with non-suicidal self-injurious (NSSI) behavior among junior and senior high school students, so as to provide a basis for effectively reducing NSSI behaviors. Methods: From April to October 2023, a total of 1 217 junior and senior high school students were selected from Tongren City, Zunyi City and Qiannan Prefecture of Guizhou Province by stratified cluster random sampling method. The Scale of Regulatory Emotional Self-efficacy and the Adolescent Self-injury Scale were administered. Latent profile analysis (LPA) was employed to explore distinct profiles of regulatory emotional self-efficacy, and the Lanza, Tan, and Bray s method (LTB) was used to analyze the relationship between these profiles and NSSI behavior. Results: The prevalence rate of NSSI behavior among junior and senior high school students was 28.6%. Among males, regulatory emotional self-efficacy was categorized into two types: moderate positive expression-low negative management group (59.1%, n =353) and high efficacy group (40.9%, n =244); among females, regulatory emotional self-efficacy was classified into three categories: low efficacy group (18.4%, n =114), high positive expression-low negative management group (56.3%, n =349), and high efficacy group (25.3%, n =157). There were statistically significant differences in total NSSI scores across different potential categories of regulatory emotional self-efficacy within both males and females ( Z/H = -5.75 , 57.58, both P <0.01). The differences in NSSI prevalence rates across the potential categories of regulatory emotional self-efficacy were statistically significant for both males and females ( χ 2=38.00, 69.14, both P <0.01), and among females, the differences in NSSI prevalence rates between the high efficacy group and the low efficacy group ( χ 2=60.01) and between the high efficacy group and the high positive expression-low negative management group ( χ 2=31.34) were also statistically significant (both P < 0.016 7 ). Binary Logistic regression analysis revealed that, compared with the high efficacy group within each gender, the moderate positive expression-low negative management group among males ( OR =2.36), and both the low efficacy group and the high positive expression-low negative management group among females ( OR =6.19, 2.97), were at an increased risk of engaging in NSSI (all P <0.01). Conclusion Different latent profiles of regulatory emotional self efficacy among junior and senior high school students are associated with NSSI behavior.

Background: Salvia miltiorrhiza Bunge, commonly known as “Danshen” in China due to the distinctive red color of its roots, is one of the most widely used traditional Chinese medicines. It is cultivated in various regions across China, and environmental differences among these regions can affect the secondary metabolites of plants, thereby influencing the quality of S. miltiorrhiza. In recent years, increasing demand for S. miltiorrhiza has exacerbated the problem of origin fraud. Therefore, ensuring the authenticity of its geographical origin is crucial for the sustainable development of the industry. Objective: The red coloration of S. miltiorrhiza is closely associated with the content of its primary active compounds, particularly tanshinones. Therefore, both its internal chemical composition and external color characteristics serve as key indicators for quality assessment. This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S. miltiorrhiza. Methods: Spectral data reflecting the internal chemical properties of S. miltiorrhiza were integrated with color information representing its external features through 3 levels of data fusion. These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification. Results: The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72% by integrating image color and short-wave infrared spectral data. Conclusion: This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S. miltiorrhiza.

Objective:To explore the effects of different titanium(Ti)surfaces on mitochondria metabolism and polarization of mac-rophages.Methods:The anodic oxidation method prepared nanotubes with distinct morphologies(NT5 and NT20 groups)on smooth titanium surfaces(P group)were characterized by scanning electron microscopy(SEM).After 24 hours of culturing RAW264.7 cells on the samples,SEM was employed to observe the morphology of the cells of all groups.Levels of mitochondria ATP and ROS,as well as the activity of hexokinase(HK),were measured by fluorescence probes and luciferase assays.The expression of iNOS,Arg-1,TNF-α and CD206 mRNA was evaluated by RT-qPCR.Changes in mitochondria metabolism and macrophage polarization were studied following inhibition of cellular glycolysis by using 2-deoxy-D-glucose(2-DG)in groups P*and NT20*.Results:Compared with the P group,the NT5 group showed no significant changes in mitochondria ATP,ROS levels and HK activity,but an upregula-tion in M2-associated gene expression was observed.In the NT20 group,mitochondria ATP and ROS levels were increased,HK ac-tivity was elevated,and M1-associated gene expression was upregulated.After glycolysis inhibition,there was no significant differ-ence in mitochondria ATP,ROS levels,HK activity and polarization-related gene expression levels between the P*and NT20*groups compared with the P group.Conclusion:Large-diameter nanotubes may promote macrophage M1 polarization by regulating the metabolic reprogramming that occurs in macrophage mitochondria.

Objective To develop and validate a risk prediction model for social dysfunction in middle-aged and elderly patients with ischemic stroke.Methods A non-matched case-control study was conducted among ischemic stroke patients admitted to the neurology department of a tertiary hospital in Tangshan between August 2022 and March 2023.Patients who developed social dysfunction within 3 months after discharge were assigned to a case group,while those without it were assigned to a control group.Multivariate logistic regression was used to identify significant predictors and construct a nomogram-based prediction model.The model's discrimination and calibration were assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Internal validation was performed via bootstrap resampling,and clinical utility was evaluated using decision curve analysis.Results Logistic regression identified the following as significant risk factors for social dysfunction(P＜0.05):male gender,age≥60 years,primary education or below,rural residence,income＜3 000,cognitive impairment,low disability acceptance,poor self-management ability,suboptimal utilization of chronic disease resources,low future-oriented coping,and high cumulative ecological risk.The nomogram achieved an AUC of 0.874,with a sensitivity of 79.4％and specificity of 80.7％.The Hosmer-Lemeshow test indicated good calibration(x2=3.631,P=0.88).Conclusion The developed nomogram provides an effective tool for predicting the risk of social dysfunction in middle-aged and elderly ischemic stroke patients,facilitating early identification of high-risk individuals.

Background:Salvia miltiorrhiza Bunge,commonly known as"Danshen"in China due to the distinctive red color of its roots,is one of the most widely used traditional Chinese medicines.It is cultivated in various regions across China,and environmental differences among these regions can affect the secondary metabolites of plants,thereby influencing the quality of S.miltiorrhiza.In recent years,increasing demand for S.miltiorrhiza has exacerbated the problem of origin fraud.Therefore,ensuring the authenticity of its geo-graphical origin is crucial for the sustainable development of the industry.Objective:The red coloration of S.miltiorrhiza is closely associated with the content of its primary active compounds,particularly tanshinones.Therefore,both its internal chemical composition and external color characteristics serve as key indicators for quality assessment.This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S.miltiorrhiza.Methods:Spectral data reflecting the internal chemical properties of S.miltiorrhiza were integrated with color information represent-ing its external features through 3 levels of data fusion.These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification.Results:The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72％by integrating image color and short-wave infrared spectral data.Conclusion:This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S.miltiorrhiza.

Objective To develop and validate a risk prediction model for social dysfunction in middle-aged and elderly patients with ischemic stroke.Methods A non-matched case-control study was conducted among ischemic stroke patients admitted to the neurology department of a tertiary hospital in Tangshan between August 2022 and March 2023.Patients who developed social dysfunction within 3 months after discharge were assigned to a case group,while those without it were assigned to a control group.Multivariate logistic regression was used to identify significant predictors and construct a nomogram-based prediction model.The model's discrimination and calibration were assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Internal validation was performed via bootstrap resampling,and clinical utility was evaluated using decision curve analysis.Results Logistic regression identified the following as significant risk factors for social dysfunction(P＜0.05):male gender,age≥60 years,primary education or below,rural residence,income＜3 000,cognitive impairment,low disability acceptance,poor self-management ability,suboptimal utilization of chronic disease resources,low future-oriented coping,and high cumulative ecological risk.The nomogram achieved an AUC of 0.874,with a sensitivity of 79.4％and specificity of 80.7％.The Hosmer-Lemeshow test indicated good calibration(x2=3.631,P=0.88).Conclusion The developed nomogram provides an effective tool for predicting the risk of social dysfunction in middle-aged and elderly ischemic stroke patients,facilitating early identification of high-risk individuals.

Background:Salvia miltiorrhiza Bunge,commonly known as"Danshen"in China due to the distinctive red color of its roots,is one of the most widely used traditional Chinese medicines.It is cultivated in various regions across China,and environmental differences among these regions can affect the secondary metabolites of plants,thereby influencing the quality of S.miltiorrhiza.In recent years,increasing demand for S.miltiorrhiza has exacerbated the problem of origin fraud.Therefore,ensuring the authenticity of its geo-graphical origin is crucial for the sustainable development of the industry.Objective:The red coloration of S.miltiorrhiza is closely associated with the content of its primary active compounds,particularly tanshinones.Therefore,both its internal chemical composition and external color characteristics serve as key indicators for quality assessment.This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S.miltiorrhiza.Methods:Spectral data reflecting the internal chemical properties of S.miltiorrhiza were integrated with color information represent-ing its external features through 3 levels of data fusion.These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification.Results:The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72％by integrating image color and short-wave infrared spectral data.Conclusion:This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S.miltiorrhiza.

Objective:To explore the effects of different titanium(Ti)surfaces on mitochondria metabolism and polarization of mac-rophages.Methods:The anodic oxidation method prepared nanotubes with distinct morphologies(NT5 and NT20 groups)on smooth titanium surfaces(P group)were characterized by scanning electron microscopy(SEM).After 24 hours of culturing RAW264.7 cells on the samples,SEM was employed to observe the morphology of the cells of all groups.Levels of mitochondria ATP and ROS,as well as the activity of hexokinase(HK),were measured by fluorescence probes and luciferase assays.The expression of iNOS,Arg-1,TNF-α and CD206 mRNA was evaluated by RT-qPCR.Changes in mitochondria metabolism and macrophage polarization were studied following inhibition of cellular glycolysis by using 2-deoxy-D-glucose(2-DG)in groups P*and NT20*.Results:Compared with the P group,the NT5 group showed no significant changes in mitochondria ATP,ROS levels and HK activity,but an upregula-tion in M2-associated gene expression was observed.In the NT20 group,mitochondria ATP and ROS levels were increased,HK ac-tivity was elevated,and M1-associated gene expression was upregulated.After glycolysis inhibition,there was no significant differ-ence in mitochondria ATP,ROS levels,HK activity and polarization-related gene expression levels between the P*and NT20*groups compared with the P group.Conclusion:Large-diameter nanotubes may promote macrophage M1 polarization by regulating the metabolic reprogramming that occurs in macrophage mitochondria.

Objective To investigate the clinical significance of the expression of antioxidant 1 copper chaperone protein(ATOX1)in hepatocellular carcinoma(HCC)and its relationship with tumor proliferation,migration and invasion.Methods The expression of ATOX1 mRNA in HCC cancer tissue and normal liver tissue was analyzed using the Human Genome Atlas database.Immunohistochemical experiment was used to detect the expression of ATOX1 in 15 cases of HCC cancer tissue and adjacent tissue.Human HCC cell lines Hep3B and HepG2 were divided into the control group(NC),the ATOX1 knockdown group 1(si-ATOX1#1)and the ATOX1 knockdown group 2(si-ATOX1#2).The effects of ATOX1 knockdown on the malignant biological behavior of HCC cells were observed through CCK-8 cell proliferation experiment,scratch experiment and Transwell invasion experiments.A nude mouse xenograft tumor model was constructed to analyze the effect of ATOX1 knockdown on the quality and volume of transplanted tumors.Western blot assay was used to detect the relationship between ATOX1 and JAK2/STAT3 pathway protein expression.Results Bioinformatics analysis showed that expression of ATOX1 mRNA in HCC cancer tissue was higher than that in adjacent normal tissue(P＜0.05).The immunohistochemical staining results showed that the positive rate of ATOX1 protein was higher in HCC cancer tissue than that in adjacent tissue(93.33%vs.13.33%,P＜0.01).In vitro experimental results showed that siRNA knockdown of ATOX1 protein expression in Hep3B and HepG2 cells significantly reduced the proliferation,migration and invasion abilities of cancer cells(P＜0.05).In vivo experiments in mice showed that the volume and weight of subcutaneous xenograft tumors were significantly smaller in the sh-ATOX1 group than those in the sh-con group(P＜0.05).The expression levels of JAK2/STAT3 pathway-related proteins p-JAK2,p-STAT3,CyclinD1 and MMP2 were significantly lower in the subcutaneous transplanted tumor tissue of the sh-ATOX1 group than that of the sh-con group(P＜0.05).Conclusion ATOX1 can promote the proliferation,migration and invasion of HCC through JAK2/STAT3 pathway,which can potentially become a potential tumor marker and therapeutic target.

The impact of prenatal exposure to a mixture of heavy metals on birth weight in newborns has been a topic of ongoing interest. In this study, 258 mothers and infants from the New Hampshire Birth Cohort Study (NHBCS) were selected as the study subjects, and the concentrations of seven heavy metals in the placenta, including Aluminum (Al), Cobalt (Co), Chromium (Cr), Nickel (Ni), Plumbum (Pb), Selenium (Se) and Arsenic (As) were collected. And the birth weight of newborns, the relevant covariates of mothers and newborns were collected. Three analytical methods, Weighted Quantile Sum (WQS) regression, Quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR) were employed. After adjusting for maternal gestational age, pre-pregnancy BMI, smoking status, education level, parity, gestational age and newborn gender, the combined three methods showed that the total effect of mixed exposure of seven heavy metals on birth weight was negative. Specifically, the WQS analysis revealed that Se had the greatest impact on birth weight, followed by Al. The QGC results showed that the heavy metal associated with the reduction of birth weight was mainly Se and Al in female and male infants, respectively. The BKMR analysis demonstrated a negative combined effect of the seven heavy metals on birth weight in both male and female infants, with Se having the highest posterior inclusion probabilities (PIPs) for female infants (0.45), and Al having the highest PIPs for male infants (0.64) after stratification by gender. In summary, mixed exposure to heavy metals during pregnancy was associated with a decrease in newborn birth weight. Furthermore, there are gender effects with Se and Al associated with decreased birth weight in female and male infants, respectively. These findings provide a theoretical basis for the development of public health policies aimed at preventing adverse pregnancy outcomes and improving the health of newborns.