BACKGROUND:Apoptosis plays an important role in secondary brain injury.Therefore,to explore the pathophysiological mechanism of promoting nerve cell survival after traumatic brain injury provides a new direction and theoretical basis for the prevention and treatment of traumatic brain injury. OBJECTIVE:To explore the expression changes of Lnx1 molecule in mammalian cortical neurons after brain injury and the possible mechanism involved in secondary brain injury. METHODS:Eighty adult SD rats were divided into 20 male and 20 female mice in sham operation group and 20 male and 20 female mice in traumatic brain injury group.The traumatic brain injury rat model was established by heavy falling method.At 6,12,24,48,and 72 hours after brain injury,the expression of related molecules in damaged cortical neurons was analyzed by RT-qPCR,western blot assay,and immunofluorescence staining. RESULTS AND CONCLUSION:(1)The brain tissue of traumatic brain injury group was bleeding and obvious tissue injury could be observed.Water content of brain tissue increased after traumatic brain injury.(2)Compared with the sham operation group,the expression of Lnx1 in cortical neurons after traumatic brain injury increased significantly at 24 hours after injury.(3)After traumatic brain injury,the expression of PBK and BCR protein decreased,and the pro-survival factor ctgf increased.(4)These findings suggest that after traumatic brain injury,the expression of Lnx1 is up-regulated in neurons,which may be due to the decrease of the expression of its target molecules PBK and BCR,and further promote the expression of living factor ctgf,which has a protective effect on the damaged neurons.

BackgroundMigrant children face many challenges in the process of social change and adaptation to a new environment， especially in school adaptation. Studies have shown that peer attachment plays a vital role in the social adaptation of children and adolescents， while psychological resilience and sense of security， as important psychological resources， also play a moderating and mediating role in individuals' coping with environmental changes. However， there is a lack of systematic research on how peer attachment affects the school adaptation of migrant children through psychological resilience and whether this process is moderated by sense of security. ObjectiveTo explore the relationship between peer attachment and school adaptation of migrant children and to examine the path of psychological resilience and sense of security in it， so as to provide references for improving the school adaptation of migrant children. MethodsUsing cluster sampling method， 695 migrant children in grades 4 to 6 of a primary school in an urban-rural fringe area of Sichuan Province were selected from April 1 to 30， 2022. Assessments were conducted using Revised Inventory for Parent and Peer Attachment （IPPA-R）， Resilience Scale for Chinese Adolescents （RSCA）， Scale of Sense of Security of Children Left Behind （SSSCLB） and Scale of School Adjustment of Student （SSAS）. Process 4.1 was used to examine the role of psychological resilience and sense of security. ResultsA total of 631 （90.79%） valid questionnaires were gathered. There were significant positive correlations among IPPA-R peer attachment subscale score， RSCA score， SSSCLB score and SSAS score （r=0.160~0.600， P<0.01）. Peer attachment had a significant positive predictive effect on the school adaptation （β=0.178， P<0.01） and psychological resilience （β=0.518， P<0.01） of migrant children. Psychological resilience had positive predictive effect on the school adaptation （β=0.467， P<0.01）. Psychological resilience played a partial mediating role in the relationship between peer attachment and school adaptation， with the mediating effect value was 0.242 （95% CI： 0.184~0.302）， accounting for 57.62% of the total effect. Moreover， the interaction term between psychological resilience and sense of security had a significant predictive effect on school adaptation （β=0.103， P<0.01）. ConclusionThe psychological resilience of migrant children plays a partial mediating role in the relationship between peer attachment and school adaptation， and the status of sense of security can moderate the relationship between psychological resilience and school adaptation of migrant children.

Objective: To analyze the association and dose response relationship between physical activity and inflammatory markers in college students, so as to provide a reference for promoting cardiometabolic health in college students. Methods: A cluster random sampling method was used to select 747 college students from two universities in Hefei, Anhui Province and Shangrao, Jiangxi Province from April to May 2019. Physical activity was assessed by using the International Physical Activity Questionnaire-Short Form (IPAQ-SF), and peripheral blood was collected to detect plasma inflammatory factor levels [including hypersensitive C reactive protein (hsCRP), interleukin-10 (IL-10), interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α)]. The differences between the groups were compared by using the χ 2 test and the Kruskal-Wallis rank sum test, and the association between physical activity and inflammatory markers was analyzed by using the Generalized Linear Model. The dose response relationship between physical activity and inflammatory markers was analyzed using the Restricted Cubic Spline Model. Results: The proportions of low physical activity, moderate physical activity, and high physical activity groups of college students were 15.9%, 53.7% and 30.4%, respectively. The levels of hsCRP, IL-10, IL-1β, IL-6 and TNF-α in the high physical activity group were 0.38(0.21, 1.10)mg/L, 70.74(47.90, 116.43)pg/mL, 1.75(1.21, 2.64)pg/mL, 4.33(2.93, 6.82) pg/mL , 5.27(3.89, 7.30)pg/mL,the levels in the low physical activity group were 0.80(0.31, 1.30)mg/L, 73.88 (47.90, 124.24)pg/mL, 1.88(1.42, 2.81) pg/mL, 4.82 (3.64, 6.67) pg/mL, 5.63 (4.34, 7.62)pg/mL, the levels in the moderate physical activity group were 0.63(0.25, 1.30)mg/L, 89.78(58.21, 127.65)pg/mL, 2.21(1.59, 3.27)pg/mL, 5.15( 3.72 , 7.72)pg/mL, 5.87( 4.63 , 8.00)g/mL, and the differences were statistically significant ( H=10.66, 11.38, 27.79, 14.13, 9.44, P <0.05). After adjusting for variables such as gender, body mass index, smoking, alcohol consumption and health status, the results of Generalized Linear Model showed that compared with the high physical activity group, the low physical activity group ( OR=2.20, 95%CI = 1.46- 3.31) and the moderate physical activity group ( OR=1.65, 95%CI =1.22-2.25) were more likely to have high levels of hsCRP, and the moderate physical activity group was more likely to have high levels of IL-1β ( OR=1.85, 95%CI =1.36-2.51), IL-6 ( OR=1.44, 95%CI =1.06-1.96), and TNF-α ( OR=1.43, 95%CI =1.05-1.94) ( P <0.05). The Restricted Cubic Spline Model showed that there was no linear dose response relationship between the time of moderate to vigorous physical activity weekly and IL-10, IL-6, II-1β, and TNF-α ( P <0.05). Conclusion There is an association between physical activity and inflammation in college students, and moderate to high intensity per week could reduce inflammation levels to promote cardiometabolic health in college students.

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

Objective To construct a model combining with traditional Chinese medicine(TCM)syndrome for predicting the risk of disease progression in patients with idiopathic membranous nephropathy(IMN)by machine learning methods,thus to quantitatively evaluating the value of TCM syndrome in the prediction of the risk of disease progression in IMN.Methods Monofactor analysis,recursive feature elimination(RFE)and multivariate binary Logistic regression analysis were used to screen the independent related factors affecting the risk of disease progression of IMN,and then a risk prediction model was constructed.A total of 102 patients with IMN were randomly assigned to the training set and the test set in a ratio of 65∶35,and then the comparison was conducted in the performance indicators of accuracy,sensitivity,specificity,F1 value,and area under the receiver operating characteristic(ROC)area under the curve(AUC)of the risk prediction model with or without the inclusion of the TCM syndrome information.Results Before the inclusion of TCM syndrome information,12 clinical characteristic variables for patients with MN were obtained after monofactor analysis combined with RFE screening,and they were age,hemoglobin quantification,urinary occult blood,24-hour urine protein quantification,urine protein-creatinine ratio,estimated glomerular filtration rate(eGFR),creatinine,uric acid,alanine transaminase,anti-phospholipase A2 receptor antibody(PLA2R-Ab),total cholesterol,and low-density lipoprotein cholesterd.A risk cholesterol prediction model containing the above variables was constructed.The multivariate binary Logistic regression analysis showed that the differences of the clinical variables mentioned above between the training-set group and test-set group were statistically significant,and the risk prediction model presented good sensitivity and predictability.Monofactor analysis combined with RFE screening was performed again after the inclusion of TCM syndrome information,and then 14 variables were obtained,which included blood stasis syndrome and dampness obstruction syndrome.The sensitivity and specificity of the model with the inclusion of the TCM syndrome information were significantly improved when compared with those without the inclusion of TCM syndrome information.Conclusion The results of the study initially indicate that TCM syndrome can be used as an important supplementary variable for predicting the risk of disease progression in IMN,and will provide a reference for intelligent diagnosis through the integration of traditional Chinese and western medicine information,and will supply the guidance for the treatment of IMN with TCM.

[摘 要] 目的：探讨内吞作用相关基因FCHO2在各亚型乳腺癌中的表达及其与乳腺癌患者的预后和免疫细胞浸润的相关性。方法：应用免疫组化法和bc-GenExMiner v5.0数据库数据分析FCHO2在各亚型乳腺癌组织中的表达，通过GEO和TIMER数据库数据分析FCHO2与各亚型乳腺癌患者预后和免疫细胞浸润的关系，利用STRING和GEPIA数据库数据分析与FCHO2的互作蛋白网络和其与互作蛋白的相关性，通过UALCAN和DAVID数据库数据对乳腺癌组织中FCHO2表达相关基因进行KEGG和GO分析。结果：免疫组化法结果显示，FCHO2在管腔型和HER2+乳腺癌组织中均呈高表达（均P<0.05），且与HER2和Ki67表达有关联（P=0.03和P=0.007）。FCHO2高表达的管腔型乳腺癌患者总生存期（OS）和无复发生存期（RFS）均明显缩短（均P<0.05）。FCHO2蛋白与EPS15等多种蛋白表达相关且构成蛋白-蛋白互作网络。KEGG和GO分析显示，乳腺癌组织中FCHO2相关表达基因主要与昼夜节律、自噬等生物学过程有关，涉及叉头框蛋白O（FoxO）和TGF-β等信号通路。FCHO2表达与各亚型乳腺癌组织中的免疫细胞浸润相关（均P<0.05）。结论：FCHO2在管腔型、HER2+乳腺癌组织中呈高表达，且与管腔型乳腺癌患者预后及免疫细胞浸润相关，其可能成为乳腺癌治疗的潜在靶点。

[摘 要] 目的：探讨内吞作用相关基因FCHO2在各亚型乳腺癌中的表达及其与乳腺癌患者的预后和免疫细胞浸润的相关性。方法：应用免疫组化法和bc-GenExMiner v5.0数据库数据分析FCHO2在各亚型乳腺癌组织中的表达，通过GEO和TIMER数据库数据分析FCHO2与各亚型乳腺癌患者预后和免疫细胞浸润的关系，利用STRING和GEPIA数据库数据分析与FCHO2的互作蛋白网络和其与互作蛋白的相关性，通过UALCAN和DAVID数据库数据对乳腺癌组织中FCHO2表达相关基因进行KEGG和GO分析。结果：免疫组化法结果显示，FCHO2在管腔型和HER2+乳腺癌组织中均呈高表达（均P<0.05），且与HER2和Ki67表达有关联（P=0.03和P=0.007）。FCHO2高表达的管腔型乳腺癌患者总生存期（OS）和无复发生存期（RFS）均明显缩短（均P<0.05）。FCHO2蛋白与EPS15等多种蛋白表达相关且构成蛋白-蛋白互作网络。KEGG和GO分析显示，乳腺癌组织中FCHO2相关表达基因主要与昼夜节律、自噬等生物学过程有关，涉及叉头框蛋白O（FoxO）和TGF-β等信号通路。FCHO2表达与各亚型乳腺癌组织中的免疫细胞浸润相关（均P<0.05）。结论：FCHO2在管腔型、HER2+乳腺癌组织中呈高表达，且与管腔型乳腺癌患者预后及免疫细胞浸润相关，其可能成为乳腺癌治疗的潜在靶点。

Objective: To describe the prevalence and the association of sleep quality trajectory, social jetlag and comorbid symptoms of anxiety and depression among college students, in order to provide a theoretical basis for improving the comorbid symptoms of anxiety and depression in college students. Methods: A questionnaire survey was conducted among 1 135 college students from two universities in Shangrao, Jiangxi Province and Hefei, Anhui Province from April to May 2019, and were followed up once every one year for a total of three times, with a valid sample size of 1 034 individuals after matching with the baseline survey. A selfassessment questionnaire was used to investigate the social jetlag of college students, the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire 9 (PHQ-9) were used to evaluate anxiety and depression symptoms, respectively, while the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. College students with GAD-7 score ≥5 and PHQ-9 score ≥5 were defined as having comorbid anxiety and depression symptoms. Latent class growth model (LCGM) was employed to analyze the sleep quality trajectory of college students, and binary Logistic regression was used to analyze the relationship between social jetlag, sleep quality trajectory and comorbid symptoms of anxiety and depression. Results: The detection rate of comorbid symptoms of anxiety and depression among college students was 16.9%, and the detection rate of social jetlag ≥2 h was 13.8%. The sleep quality showed an overall improvement trend, and the two trajectories were good sleep quality (81.6%) and poor sleep quality (18.4%). Binary Logistic regression model showed that poor sleep quality and social jetlag ≥2 h were positively correlated with comorbid symptoms of anxiety and depression (OR=5.94, 1.84, P<0.05). Conclusions Poor sleep quality and social jetlag ≥2 h in college students increase the risk of comorbid symptoms of anxiety and depression. Early screening and intervention of sleep quality and reduction of social jetlag are crucial for enhancing the mental health of college students.