Objective: To analyze the occurrence of unintentional injuries among college students and their association with sexual orientation and gender identity, so as to provide a targeted scientific basis for injury prevention measures and intervention strategies. Methods: From October 24 to November 18, 2023, a sample of 1 629 college students from two general universities in Beijing was selected using convenience sampling method. A questionnaire survey was conducted to collect information on the gender identity, sexual orientation and occurrence of unintentional injuries among college students in the past year. The Symptom Checklist-90 (SCL-90), Pittsburgh Sleep Quality Index (PSQI), Childhood Trauma Questionnaire (CTQ), and Delaware Bullying Victimization Scale-Student (DBVS-S) were used to assess mental health, sleep quality, childhood trauma, and dysfunctional impulsivity status. Analyses of sexual orientation and gender identity were conducted. The t-test and Chi square test were used for intergroup comparison,and multivariate Logistic regression analysis was used to examine risk factors for unintentional injuries among college students of different gender identities. Results: The incidence rate of unintentional injuries among college students was 16.94%, with boys (17.08%) being higher than girls (16.90%). Compared with those who did not experience unintentional injuries (5.28± 3.60 , 118.68±41.38), college students who experienced unintentional injuries had poorer sleep quality and mental health status ( 6.38 ±3.93, 135.59±50.96)( t =-3.92, -4.26); the differences in the incidence of unintentional injury among college students with non suicidal self injury, interpersonal violence, childhood trauma, and different sexual orientations and gender identities were all statistically significant ( χ 2=28.75, 75.18, 9.83, 16.20, 4.13) (all P <0.05). Multivariate Logistic regression analysis showed that after adjusting for age, gender and body mass index, non heterosexual orientation increased the risk of unintentional injuries ( OR=1.61, 95%CI =1.09-2.38), whereas existing non suicidal self injury behaviors ( OR=2.10, 95%CI =1.02-4.37) and poorer mental health status ( OR=1.54, 95%CI =1.05-2.27) increased the risk of unintentional injuries among non heterosexual college students (all P <0.05). Conclusions The incidence rate of unintentional injuries among college students is relatively high, with non heterosexual groups having increased risk of unintentional injuries. Mental health status and non suicidal self injury behaviors are important factors related to unintentional injuries among non heterosexual college students.

Objective:To explore the relationship between life events, anxiety, depression, and behavior problems in adolescents.Methods:From September to October 2022, the cluster sampling method was used to select 5 341 adolescents from 4 middle schools in Xinxiang urban area.The subjects and their parents were investigated by the adolescent self-rating life events check list (ASLEC), generalized anxiety disorder scale (GAD-7), patient health questionnaire (PHQ-9), and child behavior checklist (CBCL). SPSS 27.0 software was used for Spearman correlation analysis, and AMOS 28.0 software was used to construct the structural equation model.Results:The scores of anxiety, depression, and behavioral problems were 1 (0, 4), 1 (0, 4), and 3 (0, 10). The total score of life events was 5 (1, 13), and the dimensions scored as follows: interpersonal conflict 1 (0, 4), academic pressure 2 (0, 5), punishment 0 (0, 2), loss 0 (0, 0), health and adaptation problem 0 (0, 1), and others 0 (0, 2). There were positive correlations between life events and its dimensions, depression, anxiety and behavioral problems ( r=0.28-0.69, all P<0.01). In the overall population, anxiety and depression played parallel mediating roles in the impact of life events on behavior problems. Life events could positively predict anxiety ( β=0.68, P<0.01), and anxiety could positively predict behavior problems ( β=0.04, P=0.02). Life events could positively predict depression ( β=0.77, P<0.01), and depression could positively predict behavior problems ( β=0.18, P<0.01). The standardized total effect size of the impact of life events on behavioral problems was 0.622 (95% CI=0.564-0.675). The standardized direct effect size and indirect effect size were 0.460 (95% CI=0.374-0.539) and 0.162 (95% CI=0.108-0.218), accounting for 74.0% and 26.0%of the total effect, respectively. After stratification by gender, the results for male adolescents were consistent with the overall population, while the mediating effect of anxiety was not significant in the female adolescents. Conclusion:Life events can lead to anxiety and depression in adolescents, thereby increasing the risk of behavior problems.

Objective:To explore the relationship between life events, anxiety, depression, and behavior problems in adolescents.Methods:From September to October 2022, the cluster sampling method was used to select 5 341 adolescents from 4 middle schools in Xinxiang urban area.The subjects and their parents were investigated by the adolescent self-rating life events check list (ASLEC), generalized anxiety disorder scale (GAD-7), patient health questionnaire (PHQ-9), and child behavior checklist (CBCL). SPSS 27.0 software was used for Spearman correlation analysis, and AMOS 28.0 software was used to construct the structural equation model.Results:The scores of anxiety, depression, and behavioral problems were 1 (0, 4), 1 (0, 4), and 3 (0, 10). The total score of life events was 5 (1, 13), and the dimensions scored as follows: interpersonal conflict 1 (0, 4), academic pressure 2 (0, 5), punishment 0 (0, 2), loss 0 (0, 0), health and adaptation problem 0 (0, 1), and others 0 (0, 2). There were positive correlations between life events and its dimensions, depression, anxiety and behavioral problems ( r=0.28-0.69, all P<0.01). In the overall population, anxiety and depression played parallel mediating roles in the impact of life events on behavior problems. Life events could positively predict anxiety ( β=0.68, P<0.01), and anxiety could positively predict behavior problems ( β=0.04, P=0.02). Life events could positively predict depression ( β=0.77, P<0.01), and depression could positively predict behavior problems ( β=0.18, P<0.01). The standardized total effect size of the impact of life events on behavioral problems was 0.622 (95% CI=0.564-0.675). The standardized direct effect size and indirect effect size were 0.460 (95% CI=0.374-0.539) and 0.162 (95% CI=0.108-0.218), accounting for 74.0% and 26.0%of the total effect, respectively. After stratification by gender, the results for male adolescents were consistent with the overall population, while the mediating effect of anxiety was not significant in the female adolescents. Conclusion:Life events can lead to anxiety and depression in adolescents, thereby increasing the risk of behavior problems.

Objective:To examine the spatial and temporal distribution characteristics of first-time callers with suicidal ideation and risk factors related to suicidal ideation in a psychological assistance hotline in Henan Province.Methods:The computerised counselling operating system of the Henan Provincial Psychological Assis-tance Hotline was used to extract data from 31 401 callers who called the hotline between January 2020 and October 2023.A circular distribution and kernel density analysis were employed to investigate the spatial and temporal distri-bution of first-time callers with suicidal ideation.Binary logistic regression analysis was employed to investigate the risk factors for suicidal ideation.Results:A total of 5 494 first-time callers were included in the study,of whom 1 697(30.9％)reported suicidal ideation in the previous two weeks.The temporal distribution of suicidal ideation calls indicated a peak between 12:36 and 01:08.The weekly distribution further revealed that the majority of calls occurred on Fridays.In terms of spatial distribution,the primary hotspots for callers with suicidal ideation were clus-tered around Zhengzhou and Xinxiang.Meanwhile,the secondary hotspots exhibited a dispersed distribution across multiple centers within the province.Logistic regression analysis revealed that being under 20 years old(OR=11.85),being unemployed(OR=1.78),having psychological issues(OR=5.03),experiencing family relation-ship problems(OR=3.67),and facing economic hardships(OR=7.08)were risk factors for suicidal ideation.Conclusion:The time distribution of calls from individuals with suicidal ideation to the psychological as-sistance hotline in Henan Province exhibits a centralized trend,while the spatial distribution of calls demonstrates an imbalance.When receiving initial calls from individuals with suicidal ideation,particular attention should be paid to those aged 20 years old or younger,those who are unemployed,and those experiencing psychiatric,psychological,familial,and economic difficulties.

Objective:To examine the spatial and temporal distribution characteristics of first-time callers with suicidal ideation and risk factors related to suicidal ideation in a psychological assistance hotline in Henan Province.Methods:The computerised counselling operating system of the Henan Provincial Psychological Assis-tance Hotline was used to extract data from 31 401 callers who called the hotline between January 2020 and October 2023.A circular distribution and kernel density analysis were employed to investigate the spatial and temporal distri-bution of first-time callers with suicidal ideation.Binary logistic regression analysis was employed to investigate the risk factors for suicidal ideation.Results:A total of 5 494 first-time callers were included in the study,of whom 1 697(30.9％)reported suicidal ideation in the previous two weeks.The temporal distribution of suicidal ideation calls indicated a peak between 12:36 and 01:08.The weekly distribution further revealed that the majority of calls occurred on Fridays.In terms of spatial distribution,the primary hotspots for callers with suicidal ideation were clus-tered around Zhengzhou and Xinxiang.Meanwhile,the secondary hotspots exhibited a dispersed distribution across multiple centers within the province.Logistic regression analysis revealed that being under 20 years old(OR=11.85),being unemployed(OR=1.78),having psychological issues(OR=5.03),experiencing family relation-ship problems(OR=3.67),and facing economic hardships(OR=7.08)were risk factors for suicidal ideation.Conclusion:The time distribution of calls from individuals with suicidal ideation to the psychological as-sistance hotline in Henan Province exhibits a centralized trend,while the spatial distribution of calls demonstrates an imbalance.When receiving initial calls from individuals with suicidal ideation,particular attention should be paid to those aged 20 years old or younger,those who are unemployed,and those experiencing psychiatric,psychological,familial,and economic difficulties.

Objective:To explore the mechanism by which Pien Tze Huang improves liver Kupffer cell damage induced by lipopolysaccharide (LPS) by regulating the expression of miR-155.Methods:LPS induced liver Kupffer cells to establish a cell injury model to simulate septic liver injury. RT-qPCR was used to detect the expression of miR-155 in damaged cells, and RT-qPCR, Western Blot, ELISA and flow cytometry were used to evaluate the inflammatory response and apoptosis of damaged cells. Then we treated LPS-induced Kupffer cells with Pien Tze Huang at different concentrations (0 mg/L, 5 mg/L, 10 mg/L and 15 mg/L), and detected the expression of miR-155 in the cells, the inflammatory response of the cells and Apoptosis rate. MiR-155 was silenced in the cell injury model, and RT-qPCR, Western Blot, ELISA and flow cytometry were used to evaluate the effect of miR-155 on inflammatory response and apoptosis of model cells. Overexpression of miR-155 in damaged cells treated with Pien Tze Huang was used to detect changes in cellular inflammatory response and apoptosis. Data are expressed in the form of mean ± standard deviation, and each group of data is analyzed using t test or one-way analysis of variance.Results:In the LPS-induced liver Kupffer cell injury model, the expression of miR-155 was significantly increased ( P<0.05), the expression levels of pro-inflammatory factors IL-6 and TNF-α were significantly increased, and the anti-inflammatory factor IL-10 was significantly increased. was inhibited ( P<0.05), and the cell apoptosis rate was significantly increased ( P<0.05). After Pien Tze Huang treatment, the expression of miR-155 in damaged liver cells was inhibited ( P<0.05), the levels of cellular inflammatory factors IL-6 and TNF-α were inhibited, and the expression of anti-inflammatory factor IL-10 was promoted ( P<0.05). Inhibit cell apoptosis ( P<0.05). Silencing miR-155 reduced the inflammatory response and apoptosis rate of cells ( P<0.05). Overexpression of miR-155 can reverse the effect of Pien Tze Huang on liver cell injury ( P<0.05). Conclusions:In the model of LPS-induced liver Kupffer cell injury, Pien Tze Huang can inhibite the inflammatory response and apoptosis of cells by inhibiting the expression of miR-155.

Background and purpose:For patients with human epidermal growth factor receptor 2(HER2)-positive metastatic breast cancer,trastuzumab treatment can prolong the overall survival and significantly improve the prognosis of patients.However,the reference original research trastuzumab(Herceptin?)is more expensive.Biosimilars have comparable efficacy and safety profiles while increasing patient access to treatment.This clinical trial aimed to evaluate the efficacy,pharmacokinetics,safety and immunogenicity of the trastuzumab biosimilar AK-HER2 compared to trastuzumab(Herceptin?)in patients with HER2-positive metastatic breast cancer.Methods:This multi-center,randomised,double-blind phase Ⅲ clinical trial was conducted in 43 subcenters in China.This study complied with the research protocol,the ethical principles stated in the Declaration of Helsinki and the quality management standards for drug clinical trials.It was approved by the hospital's medical ethics committee.The clinical trial registration agency is the State Food and Drug Administration(clinical trial approval number:2015L04224;clinical trial registration number:CTR20170516).Written informed consent was obtained from subjects before enrollment.Enrolled patients were randomly assigned to the AK-HER2 group and the control group,respectively receiving AK-HER2 or trastuzumab(initial loading dose 8 mg/kg,maintenance dose 6 mg/kg,every 3 weeks as a treatment cycle,total treatment time is 16 cycles)in combination with docetaxel(75 mg/m2,treatment duration is at least 9 cycles).The primary endpoint of this clinical trial was the objective response rate(ORR9)between the AK-HER2 group and the control group in the 9th cycle.Secondary efficacy endpoints included ORR16,disease control rate(DCR),clinical benefit rate(CBR),progression-free survival(PFS)and 1-year survival rate.In this study,100 subjects(AK-HER2 group to control group=1:1)were randomly selected for blood sample collection after the 6th cycle of medication,The collection time points were 45 minutes after infusion(the end of administration),4,8,24,72,120,168,336,and 504 hours after the end of administration.After collection,blood samples were analyzed by PK parameter set(PKPS).Other evaluation parameters included safety and immunogenicity assessment.Results:A total of 550 patients with HER2-positive metastatic breast cancer were enrolled in this clinical trial between Sep.2017 and Mar.2021.In the AK-HER2 group(n=237),129 subjects in the experimental group achieved complete response(CR)or partial response(PR),and the ORR9 was 54.4%.There were 134 subjects in the control group(n=241)who achieved CR or PR,and the ORR9 was 55.6%.The ORR9 ratio between the AK-HER2 group and the control group was 97.9%[90%confidence interval(CI):85.4%-112.2%,P=0.784],which was not statistically significant.In all secondary efficacy endpoints,no statistically significant differences were observed between the two groups.We conducted a mean ratio analysis of pharmacokinetics(PK)parameters between the AK-HER2 group and the control group,and the results suggested that the pharmacokinetic characteristics of the two drugs are similar.The incidence of treatment emergent adverse event(TEAE)leading to drug reduction or suspension during trastuzumab treatment was 3.6%(10 cases)in the AK-HER2 group and 8.1%(22 cases)in the control group.There was statistically significant difference between the two groups(P=0.027).The incidence rate was significantly lower in the AK-HER2 group than in the control group,and there was no statistically significant difference among the other groups.The differences in the positive rates of anti-drug antibodies(ADA)and neutralizing antibodies(NAB)between groups were of no statistical significance(P=0.385 and P=0.752).Conclusion:In patients with HER2-positive metastatic breast cancer,AK-HER2 was comparable to the trastuzumab(Herceptin?)in terms of drug efficacy,pharmacokinetics,safety and immunogenicity.

OBJECTIVE To identify the chemical components of Shenbai Jiedu Decoction(SBJDD),a traditional Chinese medi-cine(TCM)prescription clinically used for the treatment of colorectal adenoma(CRA),and explore the potential mechanism of SBJDD preventing and treating CRA carcinogenesis.METHODS An ultra-high performance liquid chromatography-time of flight-mass spectrometry(UPLC-Q-TOF-MS)method was established to detect the chemical components in the decoction of SBJDD and the plas-ma samples of rats after administration with SBJDD.Based on the network pharmacological method,SBJDD was screened for the poten-tial active ingredients at different stages of CRA carcinogenesis,and the mechanism of the anti-cancer effect of SBJDD was explored.In vitro experiments were also carried out to verify the mechanism of anti-colorectal cancer(CRC)action of SBJDD.RE-SULTS The detection data of UPLC-Q-TOF-MS showed that 152 components were found from SBJDD water extraction.41 chemical compounds were identified in plasma samples from rats administrated with SBJDD.Network pharmacology analysis indicated that during the CREI stage,the potential active ingredients in SBJDD,including epiberberine,and kushenol H,might affect target proteins such as PIK3CA,MAPK3 and PIK3CB.This,in turn,can influence signaling pathways like PI3K-AKT and Ras signaling pathways,and regulate biological processes like protein phosphorylation,and signal transduction.During the CRA stage,the potential active ingredi-ents from SBJDD,such as 3,7-dihydroxycoumarin,palmatine,and kushenol A,might affect target proteins such as AKT and EGFR.This can regulate the negative regulation of apoptotic process,and positive regulation of cell proliferation,and modify HIF-1,and Rap1 signaling pathways.During the progression of CRA carcinogenesis,potential active ingredients such as 3,7-dihydroxycouma-rin may interact with TP53,and impact the PI3K-AKT,and Thyroid hormone signaling pathways to regulate biological processes,in-cluding positive regulation of transcription from RNA polymerase Ⅱ promoter,and negative regulation of apoptotic process.In the CRC stage,core ingredients like p-coumaric acid may bind with proteins such as PRKCB.This binding may impact the signaling pathways that negatively affect EGFR tyrosine kinase inhibitor resistance,and PI3K-AKT signaling pathways.Additionally,it may regulate bio-logical processes,including negative regulation of apoptotic process,signal transduction,and protein phosphorylation.In vitro experi-ment results indicated that SBJDD inhibited the proliferation of HT29 cells and suppressed the expression of EGFR and PKC proteins.CONCLUSION The UPLC-Q-TOF-MS method is established to effectively separate the chemical constituents in SBJDD,which are mainly composed of alkaloids,organic acids and flavonoids components.Components from SBJDD dock with different targets during the carcinogenesis process of CRA and regulate cancer-related signaling pathways to exert therapeutic effects.

There is currently a huge worldwide demand for donor kidneys for organ transplantation. Consequently, numerous marginal donor kidneys, such as kidneys with microthrombi, are used to save patients' lives. While some studies have shown an association between the presence of microthrombi in donor kidneys and an increased risk for delayed graft function (DGF) (McCall et al., 2003; Gao et al., 2019), other studies have demonstrated that microthrombi negatively impact the rate of DGF (Batra et al., 2016; Hansen et al., 2018), but not graft survival rate (McCall et al., 2003; Batra et al., 2016; Gao et al., 2019). In contrast, Hansen et al. (2018) concluded that fibrin thrombi were not only associated with reduced graft function six months post-transplantation but also with increased graft loss within the first year of transplantation. On the other hand, Batra et al. (2016) found no significant differences in the DGF rate or one-year graft function between recipients in diffuse and focal microthrombi groups. To date, however, the overall influence of donor kidney microthrombi and the degree of influence on prognosis remain controversial, necessitating further research.
Humans ; Thrombotic Microangiopathies ; Transplantation, Homologous ; Tissue Donors ; Kidney ; Allografts

Objective:To construct of a computed tomography (CT) based radiomics model for predicting the prognosis of patients with gastric neuroendocrine neoplasm (GNEN) and inves-tigate its application value.Methods:The retrospective cohort study was conducted. The clinico-pathological data of 182 patients with GNEN who were admitted to 2 medical centers, including the First Affiliated Hospital of Zhengzhou University of 124 cases and the Affiliated Cancer Hospital of Zhengzhou University of 58 cases, from August 2011 to December 2020 were collected. There were 130 males and 52 females, aged 64(range, 56-70)years. Based on random number table, all 182 patients were divided into the training dataset of 128 cases and the validation dataset of 54 cases with a ratio of 7:3. All patients underwent enhanced CT examination. Observation indicators: (1) construction and validation of the radiomics prediction model; (2) analysis of prognostic factors for patients with GNEN in the training dataset; (3) construction and evaluation of the prediction model for prognosis of patients with GNEN. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and the chi-square test, corrected chi-square test or Fisher exact probability were used for comparison between groups. The Kaplan-Meier method was used to calculate survival rate and draw survival curve, and the Log-rank test was used for survival analysis. The COX regression model was used for univariate and multivariate analyses. The R software (version 4.0.3) glmnet software package was used for least absolute shrinkage and selection operator (LASSO)-COX regression analysis. The rms software (version 4.0.3) was used to generate nomogram and calibration curve. The Hmisc software (version 4.0.3) was used to calculate C-index values. The dca.R software (version 4.0.3) was used for decision curve analysis. Results:(1) Construction and valida-tion of the radiomics prediction model. One thousand seven hundred and eighty-one radiomics features were finally extracted from the 182 patients. Based on the feature selection using intra-group correlation coefficient >0.75, and the reduce dimensionality using LASSO-COX regression analysis, 14 non zero coefficient radiomics features were finally selected from the 1 781 radiomics features. The radiomics prediction model was constructed based on the radiomics score (R-score) of these non zero coefficient radiomics features. According to the best cutoff value of the R-score as -0.494, 128 patients in the training dataset were divided into 64 cases with high risk and 64 cases with low risk, 54 patients in the validation dataset were divided into 35 cases with high risk and 19 cases with low risk. The area under curve (AUC) of radiomics prediction model in predicting 18-, 24-, 30-month overall survival rate of patients in the training dataset was 0.83[95% confidence interval ( CI ) as 0.76-0.87, P<0.05], 0.84(95% CI as 0.73-0.91, P<0.05), 0.91(95% CI as 0.78-0.95, P<0.05), respectively. The AUC of radiomics prediction model in predicting 18-, 24-, 30-month overall survival rate of patients in the validation dataset was 0.84(95% CI as 0.75-0.92, P<0.05), 0.84 (95% CI as 0.73-0.91, P<0.05), 0.86(95% CI as 0.82-0.94, P<0.05), respectively. (2) Analysis of prognostic factors for patients with GNEN in the training dataset. Results of multivariate analysis showed gender, age, treatment method, tumor boundary, tumor T staging, tumor N staging, tumor M staging, Ki-67 index, CD56 expression were independent factors influencing prognosis of patients with GNEN in the training dataset ( P<0.05). (3) Construction and evaluation of the prediction model for prognosis of patients with GNEN. The clinical prediction model was constructed based on the independent factors influen-cing prognosis of patients with GNEN including gender, age, treatment method, tumor boundary, tumor T staging, tumor N staging, tumor M staging, Ki-67 index, CD56 expression. The C-index value of clinical prediction model in the training dataset and the validation dataset was 0.86 (95% CI as 0.82-0.90) and 0.80(95% CI as 0.72-0.87), respectively. The C-index value of radiomics prediction model in the training dataset and the validation dataset was 0.80 (95% CI as 0.74-0.86, P<0.05) and 0.75(95% CI as 0.66-0.84, P<0.05), respectively. The C-index value of clinical-radiomics combined prediction model in the training dataset and the validation dataset was 0.88(95% CI as 0.85-0.92) and 0.83 (95% CI as 0.77-0.89), respectively. Results of calibration curve show that clinical prediction model, radiomics prediction model and clinical-radiomics combined prediction model had good predictive ability. Results of decision curve show that the clinical-radiomics combined prediction model is superior to the clinical prediction model, radiomics prediction model in evaluating the prognosis of patients with GNEN. Conclusions:The predection model for predicting the prognosis of patients with GNEN is constructed based on 14 radiomics features after selecting. The prediction model can predict the prognosis of patients with GNEN well, and the clinical-radiomics combined prediction model has a better prediction efficiency.