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 explore the longitudinal correlation between smartphone multitasking and depressive symptoms, so as to provide an evidence based basis for promoting the mental health of college students. Methods: A total of 967 college students were recruited from one university in Taiyuan, Chongqing, and Shenzhen cities, China, by using multi stage randomized cluster sampling from October to December 2021 at baseline, and a follow up survey was conducted in May 2022. Smartphone multitasking behaviors were assessed by means of the Assessment of Smartphone Multitasking for Adolescents (ASMA), and depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9) among college students. Chi square tests were performed to compare the differences in depressive symptoms between different groups of demographic characteristics, and binary Logistic regression models were employed to analyze the associations between smartphone multitasking and depressive symptoms among college students. Results: The rates of depressive symptoms among college students at baseline and follow up were 35.2% and 42.3%, respectively. Compared to the low level smartphone multitasking index group at baseline, the moderate and high level groups were more likely to experience depressive symptoms at baseline (moderate level group: OR=1.74, 95%CI =1.22-2.50, high level group: OR=2.77, 95%CI =1.94-3.95) and followup (moderate level group: OR=1.41, 95%CI =1.01-1.95, high level group: OR=1.64, 95%CI =1.17-2.29) ( P <0.05). In addition, compared to the persistently low smartphone multitasking index, increased risk of depressive symptoms was associated with maintaining a moderate to high ( OR=2.94, 95%CI =1.83-4.71), and a higher ( OR=2.07, 95%CI =1.31-3.27) or lower smartphone multitasking index ( OR=2.02, 95%CI =1.27-3.19) ( P <0.05). Moreover, higher smartphone multitasking index scores were positively associated with the risk of new-onset depressive symptoms at follow up ( OR=1.87, 95%CI=1.07-3.27, P <0.05). Conclusions Smartphone multitasking behaviors are find to be associated with an increased risk of depressive symptoms in college students. There is a need to reduce smartphone multitasking in order to decrease depressive symptoms and promote students mental health.

Objective To explore the roles of iron overload in pro-atherogenic activation of foam cells.Methods RAW264.7 and MOVAS cells were stimulated by oxLDL,ferrimine citrate and deferoxamine respectively.Prussian Blue and Oil Red O staining were used to detect iron deposition and foam cell.CCK-8 test,DHE probe,ELISA,RT-qPCR were performed to detect the cell death rate,reactive oxygen species(ROS)generation,lipid peroxidation molecules[glutathione peroxidase(GSH),glutathione peroxidase 4(GPX4),malondialdehyde(MDA)content]and the mRNA level of ATP binding cassette transporter A1(ABCA1),ATP binding cassette transporter G1(ABCG1),inductible nitris oxide synthase(iNOS),arginase-1(Arg-1),α-smooth muscle actin(α-SMA),smooth muscle 22 alpha(SM22a),osteopontin(OPN),Interleukin-1β(IL-1β),tumor necrosis factor-α(TNF-α).Results Iron overload could reduced reverse cholesterol transporters(ABCA1 and ABCG1),promote foam cells generation,increased cell death rate,induced the expression of lipid peroxidation molecules(GSH,GPX4,MDA),and promoted pro-inflammatory M1 marker of macrophage and synthetic marker expression of vascular smooth muscle cell(VSMC)and inflammatory cytokines(IL-1β,TNF-α).Conclusion Iron overload promotes the generation of foam cells derived from macrophages and smooth muscle cells and transform them into pro-atherosclerotic phenotype,aggravates cell lipid peroxidation and inflammatory reaction,which contributes to the progress of atherosclerosis.

Objective: To describe the association of different sleep characteristics and cardiometabolic risk among college students, so as to provide reference for health promotion of college students. Methods: By random cluster sampling method, a questionnaire survey and physical examination including blood pressure, waist circumference and blood lipid indicators, which were conducted in April and May of 2019 among a total of 1 179 college students from the first grade in two universities in Hefei City of Anhui Province and Shangrao City of Jiangxi Province. A total of 729 college students with valid questionnaires were included into analysis. The Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) were used to investigate sleep behavior, and the Morning And Evening Questionnaire-5 (MEQ-5) was used to investigate sleep characteristics. The cardiometabolic risk score was derived using the sum of the standardized sex specific Z scores of waist circumference, mean arterial pressure, HDL cholesterol (multiplied by -1), triglycerides, and insulin resistance index. The rank sum tests were used to compare differences in cardiometabolic risk scores across demographic characteristics. Generalized linear models were used to compare the association of different sleep characteristics with cardiometabolic risk scores among college students. Results: The average cardiovascular metabolic risk score of college students was -0.32(-2.03, 1.58). There were statistically significant differences in cardiovascular metabolic risk scores among college students in variables such as smoking, health status, and physical activity levels ( t/F=-3.41, 12.88, 51.07, P <0.01). The results of the generalized linear model showed that nighttime preference ( B=1.89, 95%CI =1.02-3.49), insomnia symptoms ( B=3.25, 95%CI =1.79-5.90), and short or long sleep duration ( B=1.92, 95%CI =1.21-3.05) were positively correlated with the cardiovascular metabolic risk score of college students ( P <0.05). Conclusions Poor sleep patterns among college students are positively correlated with the risk of cardiovascular metabolism. The sleep behavior of college students should be actively changed to reduce the risk of cardiovascular disease.

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.