BackgroundNon-suicidal self-injury （NSSI） behaviors are prevalent among adolescents， significantly affecting their physical and mental well-being. Understanding the risk factors associated with adolescent NSSI is crucial for prevention. Previous studies have identified mobile phone dependence as a risk factor for NSSI in adolescents. However， as a key form of mobile phone dependence， the evidence regarding the impact of mobile phone social media dependence on adolescent NSSI behavior remains insufficient. ObjectiveTo explore the impact of mobile phone social media dependence and its associated factors on adolescent NSSI behavior， so as to provide references for intervention strategies targeting NSSI in adolescents. MethodsA total of 100 adolescents diagnosed with NSSI according to the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5）， and receiving treatment at Tongde Hospital of Zhejiang Province from January 2022 to December 2023 were included in the study group. Concurrently， 100 age- and sex-matched students from Hangzhou were recruited as the control group. Assessments were conducted using Ottawa Self-injury Inventory（OSI） Function Subscale and Addiction Features Subscale， Adolescents Self-Harm Scale（ASHS）， and Mobile Phone Social Media Dependence Questionnaire. Multiple linear regression was used to analyze the factors influencing NSSI behaviors. ResultsThe research group had a total of 99 patients （99.00%） who completed the study， while the control group consisted of 97 （97.00%） adolescents who finished this research.The study group had statistically significantly higher total scores on the Mobile Phone Social Media Dependence Questionnaire， as well as higher scores on the conflict and withdrawal dimensions， compared with control group（t=-3.061， -2.874， -2.368， P<0.05 or 0.01）. The study group also scored significantly higher on the OSI Function Subscale for internal emotion regulation， social influence， external emotion regulation， and sensation-seeking factors， as well as on the OSI Addiction Features Subscale scores， compared to the control group（t=-22.249， -8.854， -17.968， -10.591， -20.157， P<0.01）. OSI Function Subscale scores were positively correlated with Mobile Phone Social Media Dependence Questionnaire scores （r=0.321， P<0.01）， and OSI Addiction Features Subscale scores were positively correlated with Mobile Phone Social Media Dependence Questionnaire scores （r=0.282， P<0.01）. ASHS scores were positively correlated with Mobile Phone Social Media Dependence Questionnaire scores （r=0.145， P<0.05）. Multiple linear regression analysis showed that compulsivity （β=0.416， P<0.01） and conflict （β=0.256， P<0.05） were significant predictors for adolescent NSSI behaviors. ConclusionAdolescent NSSI behaviors are associated with mobile phone social media dependence. The compulsivity and conflict dimension of mobile phone social media dependence are influencing factors for adolescent NSSI behaviors. The higher level of the compulsivity and conflict are associated with an increased risk of the NSSI behaviors in adolescents. ［Funde by Zhejiang Medical and Health Science and Technology Plan Project in 2022 （number， 2022KY704］

ObjectiveTo investigate the effect of Danggui Shaoyaosan on ferroptosis in the rat model of non-alcoholic fatty liver disease （NAFLD） and explore the underlying mechanism based on the nuclear factor E₂-related factor 2 （Nrf2）/solute carrier family 7 member 11 （SLC7A11）/glutathione peroxidase 4 （GPX4） signaling pathway. MethodsThe sixty SD rats were randomly grouped as follows： control， model， Yishanfu （0.144 g·kg^-1）， and low-， medium-， and high-dose （2.44， 4.88， and 9.76 g·kg^-1， respectively） Danggui Shaoyaosan. A high-fat diet was used to establish the rat model of NAFLD. After 12 weeks of modeling， rats were treated with corresponding agents for 4 weeks. Then， the body weight and liver weight were measured， and the liver index was calculated. At the same time， serum and liver samples were collected. The levels or activities of total cholesterol （TC）， triglycerides （TG）， alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， and Fe²⁺ in the serum and TC， TG， free fatty acids （FFA）， malondialdehyde （MDA）， superoxide dismutase （SOD）， glutathione peroxidase （GPX）， and Fe²⁺ in the liver were measured. Hematoxylin-eosin staining and oil red O staining were employed to observe the pathological changes in the liver. Immunofluorescence was used to assess the reactive oxygen species （ROS） content in the liver. Mitochondrial morphology was observed by transmission electron microscopy. The protein levels of Nrf2， SLC7A11， GPX4， transferrin receptor 1 （TFR1）， and divalent metal transporter 1 （DMT1） in the liver were determined by Western blot. ResultsCompared with the control group， the model group showed increases in the body weight， liver weight， liver index， levels or activities of TC， TG， ALT， AST， and Fe²⁺ in the serum， levels of TC， TG， FFA， MDA， Fe²⁺， and ROS in the liver， and protein levels of TFR1 and DMT1 in the liver （P<0.01）， and decreases in the activities of SOD， GPX and the protein levels of Nrf2， SLC7A11， and GPX4 in the liver （P<0.05， P<0.01）. Meanwhile， the liver tissue in the model group presented steatosis， iron deposition， mitochondrial shrinkage， and blurred or swollen mitochondrial cristae. Compared with the model group， all doses of Danggui Shaoyaosan reduced the body weight， liver weight， liver index， levels or activities of TC， TG， ALT， AST， and Fe²⁺ in the serum， levels of TC， TG， FFA， MDA， Fe²⁺， and ROS in the liver， and protein levels of TFR1 and DMT1 in the liver （P<0.01）， while increasing the activities of SOD and GPX and the protein levels of Nrf2， SLC7A11， and GPX4 in the liver （P<0.01）. Furthermore， Danggui Shaoyaosan alleviated steatosis， iron deposition， and mitochondrial damage in the liver. ConclusionDanggui Shaoyaosan may inhibit lipid peroxidation and ferroptosis by activating the Nrf2/SLC7A11/GPX4 signaling pathway to treat NAFLD.

The Solomon four-group design， a critical method for improving internal validity in clinical research， can reduce bias and control the interference of Hawthorne effects and pretest sensitization on research results， which offers unique advantages in evaluating complex intervention outcomes. This paper systematically outlined the core framework and key points of statistical analysis of the Solomon four-group design， summarized its applications in clinical research at home and abroad， explored its advantages and limitations， and discussed the potential value in traditional Chinese medicine （TCM） clinical trials. It is believed that the Solomon four-group design can help distinguish between testing effects and intervention effects in TCM clinical studies， and reduce the bias in the evaluation of subjective indicators. Meanwhile， given the complexity of the Solomon four-group design and the particularity of TCM clinical research， it is proposed that future TCM clinical studies should focus on using psychological scales， know-ledge， attitude， and behavior measurements， and other similat evaluations as endpoints. It also advocates strengthening interdisciplinary collaboration to provide new methodological paths for TCM clinical research.

Objective To compare the cost-effectiveness between sodium valproate and levetiracetam in the treatment of childhood epilepsy and provide an economic basis for clinical medication choices. Methods A cost-effectiveness analysis was conducted using a decision tree model to compare the effectiveness and drug costs of sodium valproate and levetiracetam in treating childhood epilepsy. Single-factor sensitivity analysis and probabilistic sensitivity analysis were used to assess the impact of parameter variations on the study results. Results The treatment cost of levetiracetam was significantly higher than that of sodium valproate. The incremental cost-effectiveness ratio （ICER） of levetiracetam compared to sodium valproate was ¥8 628.43. Sensitivity analysis results were consistent with the base-case analysis. The probabilistic sensitivity analysis showed that, over a 6-month treatment period, levetiracetam became a more cost-effective option when the willingness-to-pay （WTP） threshold was ¥9,000 or higher. One-way sensitivity analysis revealed that the price of levetiracetam was the most influential factor affecting the ICER. Conclusion When the WTP per effective pediatric epilepsy case is ¥9,000 or higher, levetiracetam demonstrates a cost-effectiveness advantage.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

OBJECTIVE To investigate the induction of apoptosis in hepatocellular carcinoma cells by polyphyllin 9 （PP9） through the regulation of the Fas/Fas ligand （FasL） signaling pathway， and its inhibitory effect on the growth of transplanted tumor in nude mice. METHODS Based on the screening of cell lines and intervention conditions， HepG2 cells were selected as the experimental subject to investigate the effects of 2 μmol/L and 4 μmol/L PP9 treatment on cell colony formation activity， apoptosis rate， as well as the protein expressions of Fas， FasL， cleaved caspase-8 and cleaved caspase-3. Additionally， Fas inhibitor KR- 33493 was introduced to investigate the underlying mechanism of PP9’s anti-hepatocellular carcinoma activity. Using HepG2 cell tumor-bearing nude mice model as the object， and 5-fluorouracil （20 mg/kg） as the positive control， the effects of 10 mg/kg PP9 on tumor volume， tumor mass， and the protein expressions of the nuclear proliferation-associated antigen Ki-67 and cleaved caspase-3 in tumor-bearing nude mice were investigated. RESULTS Compared with the control group， 2， 4 μmol/L PP9 significantly decreased the number of clones and the clone formation rate of cells， but significantly increased the apoptosis rate， the protein expressions of Fas， FasL， cleaved caspase-8 and cleaved caspase-3 （P＜0.05 or P＜0.01）. However， the combination of Fas inhibitor KR-33493 could significantly reverse the effect of PP9 on the up-regulation of proteins related to the Fas/FasL signaling pathway （P＜0.01）. Compared with the control group， the tumor volume （on day 27）， mass and protein expression of Ki- 67 in nude mice of the PP9 group were significantly decreased， while the protein expression of cleaved caspase-3 was significantly increased （P＜0.01）. CONCLUSIONS PP9 can induce apoptosis of HepG2 cells by activating the Fas/FasL signaling pathway. Meanwhile， PP9 can also effectively inhibit the growth of transplanted tumors in nude mice.

As people’s attention to health continues to increase, the market demand for traditional Chinese medicine (TCM) is growing steadily. The quality and safety of Chinese medicinal materials have attracted unprecedented social attention. In particular, the issue of exogenous harmful residue pollution in TCM has become a hot topic of concern for both regulatory authorities and society. The Chinese Pharmacopoeia 2025 Edition further refines the detection methods and limit standards for exogenous harmful residues in TCM. This not only reflects China’s high-level emphasis on the quality and safety of TCM but also demonstrates the continuous progress made by China in the field of TCM safety supervision. Basis on this study, by systematically reviewing the development history of the detection standards for exogenous harmful residues in TCM and analyzing the revisions and updates of these detection standards in the Chinese Pharmacopoeia 2025 Edition, deeply explores the key points of the changes in the monitoring standards for exogenous harmful residues in TCM in the Chinese Pharmacopoeia 2025 Edition. Moreover, it interprets the future development directions of the detection of exogenous residues in TCM, aiming to provide a reference for the formulation of TCM safety supervision policies.

ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

Objective: To establish a prediction model for high-risk cardiovascular disease (CVD) among residents aged 35 to 75 years, so as to provide the basis for improving CVD prevention and control measures. Methods: Permanent residents aged 35 to 75 years were selected from Dongcheng District, Beijing Municipality using the stratified random sampling method from 2018 to 2023. Demographic information, lifestyle, waist circumference and blood biochemical indicators were collected through questionnaire surveys, physical examinations and laboratory tests. Influencing factors for high-risk CVD among residents aged 35 to 75 years were identified using a multivariable logistic regression model, and a prediction model for high-risk CVD was established. The predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 6 968 individuals were surveyed, including 2 821 males (40.49%) and 4 147 females (59.51%), and had a mean age of (59.92±9.33) years. There were 1 155 high-risk CVD population, with a detection rate of 16.58%. Multivariable logistic regression analysis showed that gender, age, smoking, central obesity, systolic blood pressure, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol were influencing factors for high-risk CVD among residents aged 35 to 75 years (all P<0.05). The area under the ROC curve of the established prediction model was 0.849 (95%CI: 0.834-0.863), with a sensitivity of 0.693 and a specificity of 0.863, indicating good discrimination. Conclusion The model constructed by eight factors including demographic characteristics, lifestyle and blood biochemical indicators has good predictive value for high-risk CVD among residents aged 35 to 75 years.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.