Objective Exploring the therapeutic mechanism of Yishen Jiangzhuo Granules(YSJZG)on chronic kidney disease(CKD)based on mitochondrial dynamics and apoptosis of renal tubular epithelial cells.Methods The CKD model of rats with 5/6 nephrectomy was adopted and divided into 6 groups according to random number table:sham operation control group,model group,emodin group(500 mg/kg/d),Yishen Jiangzhuo granule low,middle and high dose groups.After 8 weeks of treatment with YSJZG,serum creatinine(SCR)and urea nitrogen(BUN),pathological changes of renal cortex,mitochondrial morphology and ultrastructure were detected,and mitochondrial kinetic protein in renal tubular epithelial cells was detected by immunohistochemistry(Drp1,Fis1)and fusion proteins(Opa1,Mfn1)were detected by Western blot,and apoptotic proteins(CytC,Bax)in cytoplasm and mitochondria were detected by real-time PCR.Results Renal injury:Compared with the model group,YSJZG groups significantly reduced the levels of SCR and BUN,renal tubular degeneration and necrosis,and mitochondrial structural damage in rats.Renal tubule mitochondrial dynamic protein:Compared with the model group,the expression of division proteins Drp1 and Fis1 was downregulated,the expression of fusion proteins Opa1 and Mfn1 was upregulated,and transmission electron microscopy observed that the mitochondrial fragmentation changes were relatively mild.Apoptosis related indicators and mtDNA copy number of renal tubular cells:Compared with the model group,the content of Bax protein in renal tubular epithelial cells of YSJZG groups increased significantly in cytoplasm(P<0.05)and decreased significantly in mitochondria(P<0.05).The content of CytC protein decreased significantly in cytoplasm(P<0.05)and increased significantly in mitochondria(P<0.05).The copy number of mtDNA increased significantly(P<0.05),and the total levels of SMAC,CytC and Bax mRNA decreased significantly(P<0.05).Correlation between mitochondrial dynamic protein and apoptosis in renal tubular cells:Pearson correlation analysis showed that the expression of Drp1 and Fis1 was negatively correlated with the expression of CytC in mitochondria,and positively correlated with the expression of CytC in cytoplasm.The expression levels of fusion proteins Opa1 and Mfn1 showed a significant positive correlation with CytC expression in mitochondria,and a significant negative correlation with CytC expression in cytoplasm.Conclusion YSJZG can significantly delay the progression of CKD,and its mechanism may be achieved by regulating mitochondrial dynamics of renal tubular epithelial cells,thereby inhibiting endogenous cell apoptosis pathway.

Objective To compare the performance of 3 risk prediction models based on machine learning in predicting the risk of compassion fatigue among obstetrics and gynaecology nurses.Methods Using the convenience sampling method,1 323 obstetrics and gynaecology nurses from 11 tertiary hospitals in 9 cities were selected from December 2022 to March 2023,and were randomly divided into a training set and a test set according to 7∶3 ratio.Compassion Fatigue Scale,Five Facet Mindfulness Questionnaire and Emotional Intelligence Scale were used for the survey.A total of 3 types of risk prediction models were constructed for the factors affecting the compassion fatigue of obstetrics and gynaecology nurses,namely,Logistic Regression,Decision Tree,and Random Forest.The accuracy,precision,specificity,sensitivity,Fl score and AUC were used to compare the predictive performance of the 3 models.Results Finally 1 276 maternity nurses completed the survey.All 3 models showed that nature of employment,years of experience,mindfulness and emotional intelligence were independent risk factors for compassion fatigue in obstetrics and gynaecology nurses(P＜0.05).The results of model comparison showed that the accuracy of Logistic regression,decision tree and random forest were 0.804,0.806,0.796;the precision was 0.821,0.827,0.823;the sensitivity was 0.956,0.949,0.939;the Fl score was 0.883,0.884,0.877;the AUC was 0.704(95％CI:0.701～0.713),0.760(95％CI:0.751～0.771),0.742(95％CI:0.723～0.762)respectively.Conclusion The risk prediction model of factors affecting compassion fatigue among obstetrics and gynaecology nurses constructed by decision tree performed the best,and the predictive performance was better than that of the random forest and logistic regression models.The multi-model effectively predicts the risk of compassion fatigue in obstetrics and gynecology nurses,explores the interaction of influencing factors in multiple dimensions,and it can inform the early identification and prevention of compassion fatigue and the development of related interventions.

Objective To compare the performance of 3 risk prediction models based on machine learning in predicting the risk of compassion fatigue among obstetrics and gynaecology nurses.Methods Using the convenience sampling method,1 323 obstetrics and gynaecology nurses from 11 tertiary hospitals in 9 cities were selected from December 2022 to March 2023,and were randomly divided into a training set and a test set according to 7∶3 ratio.Compassion Fatigue Scale,Five Facet Mindfulness Questionnaire and Emotional Intelligence Scale were used for the survey.A total of 3 types of risk prediction models were constructed for the factors affecting the compassion fatigue of obstetrics and gynaecology nurses,namely,Logistic Regression,Decision Tree,and Random Forest.The accuracy,precision,specificity,sensitivity,Fl score and AUC were used to compare the predictive performance of the 3 models.Results Finally 1 276 maternity nurses completed the survey.All 3 models showed that nature of employment,years of experience,mindfulness and emotional intelligence were independent risk factors for compassion fatigue in obstetrics and gynaecology nurses(P＜0.05).The results of model comparison showed that the accuracy of Logistic regression,decision tree and random forest were 0.804,0.806,0.796;the precision was 0.821,0.827,0.823;the sensitivity was 0.956,0.949,0.939;the Fl score was 0.883,0.884,0.877;the AUC was 0.704(95％CI:0.701～0.713),0.760(95％CI:0.751～0.771),0.742(95％CI:0.723～0.762)respectively.Conclusion The risk prediction model of factors affecting compassion fatigue among obstetrics and gynaecology nurses constructed by decision tree performed the best,and the predictive performance was better than that of the random forest and logistic regression models.The multi-model effectively predicts the risk of compassion fatigue in obstetrics and gynecology nurses,explores the interaction of influencing factors in multiple dimensions,and it can inform the early identification and prevention of compassion fatigue and the development of related interventions.

Objective To investigate the effect of the rs3765467 polymorphism of glucagon-like peptide-1 receptor(GLP-1R)gene on the efficacy of Liraglutide(Lir)in patients with type 2 diabetes mellitus(T2DM)and metabolic associated fatty liver disease(MAFLD).Methods A total of 281 patients with T2DM from May 2022 to May 2023 were selected,including 125 patients with simple T2DM(T2DM group)and 156 patients with T2DM combined with MAFLD(T2DM+MAFLD group).120 healthy individuals during the same period were selected as the control(NC)group.The related indexes of glucose and lipid metabolism were detected.The polymorphism of GLP-1R gene rs3765467 was detected.Results BMI,FPG,HbA1c,HOMA-IR and TG in each group increased in turn(P<0.05),while the distribution frequency of genotype GG and allele G decreased in turn(P<0.05).TC and LDL-C in T2DM and T2DM+MAFLD groups were higher than those in NC group(P<0.05).TC and TG levels in genotype GA/AA patients were significantly higher than those in genotype GG patients(P<0.05).Compared with before treatment,the levels of BMI,FPG,HbA1c,HOMA-IR,TC,TG and LDL-C in T2DM patients with MAFLD were significantly decreased after Lir treatment(P<0.05).There was no significant difference in BMI and related indexes of glucose and lipid metabolism in GG and GA/AA patients before and after Lir treatment(P>0.05).Conclusions The distribution frequency of GG and G allele at rs3765467 of GLP-1R gene is reduced in T2DM patients with MAFLD.The carrying of allele A was associated with increased TC and TG levels,but did not affect the efficacy of Lir in reducing weight and improving glycolipid metabolism.

Objective:To explore the mediating effect of sense of coherence (SOC) on the utilization of chronic disease resources and symptom distress in liver cancer patients after transarterial chemoembolization (TACE), so as to provide a basis for comprehensive management strategies from a new perspective.Methods:A convenience sampling method was used to select 260 inpatients who underwent TACE in Xinxiang Central Hospital and Henan Provincial People's Hospital from September 2023 to October 2024 as the research objects. The Basic Information Questionnaire, Sense of Coherence Scale-13 (SOC-13), Chronic Illness Resource Survey (CIRS), and the Rotterdam Symptom Checklist (RSCL) were used to investigate the patients. Pearson correlation was used to analyze the relationships among SOC, chronic disease resource utilization, and symptom distress in patients after TACE. Structural equation modeling was established using AMOS 21.0 software to verify the mediating effect.Results:A total of 260 questionnaires were distributed, and 249 valid questionnaires were recovered, with a valid recovery rate of 95.77% (249/260). The SOC-13 score of 249 patients after TACE was (44.30±7.64), the CIRS score was (46.84±7.02), and the RSCL score was (93.61±8.85). The SOC-13 score was positively correlated with the CIRS score ( P<0.01) and negatively correlated with the RSCL score ( P<0.01). The CIRS score was negatively correlated with the RSCL score ( P<0.01). SOC had a direct negative effect on symptom distress (β'=-0.382, P<0.01), chronic disease resource utilization had a direct negative effect on symptom distress (β'=-0.176, P<0.01), and SOC played a partial mediating role between chronic disease resource utilization and symptom distress (β'=-0.148, P<0.01), with the mediating effect accounting for 45.68% of the total effect. Conclusions:There are certain deficiencies in the sense of coherence and chronic disease resource utilization in patients after TACE, and the phenomenon of symptom distress is obvious. SOC plays a partial mediating role between chronic disease resource utilization and symptom distress.

Objective To analyze the factors influencing iodine nutritional status in pregnant women dur-ing pregnancy,based on thyroid function and thyroid autoantibody levels,and to explore the association between iodine nutritional abnormalities and pregnancy outcomes.Methods A total of 838 pregnant women who underwent routine prenatal checkups at Qinghai Provincial People's Hospital between January 2021 and June 2023 were pro-spectively enrolled in this study.All participants were followed until delivery.Seven cases were lost to follow-up,resulting in a final sample size of 831 participants.Among them,276 were in the first trimester,384 in the second trimester,and 171 in the third trimester.Data on urinary iodine concentration(UIC),urinary creatinine(UCr),thyroid function indicators,and thyroid autoantibodies were collected.Based on their iodine nutritional status,the participants were categorized into either the iodine-sufficient group or the iodine-abnormal group(including iodine-deficient,iodine-hyper-sufficient,and iodine-excessive subgroups).This study analyzed the iodine nutritional sta-tus of pregnant women during different gestational periods,compared thyroid function indices,prevalence of thy-roid diseases,and the positivity rates of thyroid peroxidase antibody(TPOAb),thyroglobulin antibody(TGAb),and thyroid-stimulating hormone receptor antibody(TRAb)among different iodine status groups.Additionally,ad-verse pregnancy outcomes were compared across groups.Multivariate logistic regression analysis was conducted to identify risk factors associated with iodine abnormalities during pregnancy,and a predictive model was developed to assess its potential predictive value.Results Among the 831 pregnant women included in the study,373 cases(44.89％)exhibited iodine sufficiency,while 458 cases(55.11％)presented with iodine abnormalities,including 282 cases of iodine deficiency,144 cases of iodine hypersufficiency,and 32 cases of iodine excess.No statistically significant differences were observed in the iodine nutritional status across different trimesters(P>0.05).The se-rum level of thyroid-stimulating hormone(TSH)was significantly higher in the iodine abnormal group compared to the iodine sufficient group(P<0.05).Additionally,the iodine abnormal group demonstrated higher positivity rates of TPOAb alone,TGAb,and TRAb,as well as increased incidence of thyroid dysfunction and total adverse pregnancy outcomes compared to the iodine sufficient group(all P<0.05).These adverse indicators were also sig-nificantly elevated in the iodine-deficient,iodine super-sufficient,and iodine overdose subgroups compared to the iodine sufficient group(P<0.05).Elevated serum TSH levels and the presence of TPOAb,TGAb,and TRAb were identified as risk factors for iodine abnormalities during pregnancy(P<0.05).The predictive model con-structed for identifying iodine abnormalities in pregnant women demonstrated an area under the curve(AUC)of 0.876,with a sensitivity of 72.27％and a specificity of 89.01％.Conclusions The prevalence of iodine nutritional abnormalities among pregnant women during pregnancy was high,with most cases presenting iodine deficiency.These abnormalities were associated with thyroid function,thyroid autoimmunity,and pregnancy outcomes,but showed no significant correlation with gestational age.Furthermore,the prediction model developed based on iden-tified risk factors demonstrated effective performance in predicting iodine nutritional abnormalities during preg-nancy.

Macrophages are closely related to tumor progression,and can promote tumor growth and pro-liferation by promoting inflammation,angiogenesis and immunosuppression and so on,as well as killing tumors by directly killing tumor cells and triggering specific immune responses.Iron death,as an iron-depend-ent cell death caused by lipid peroxidation,can effectively kill tumor cells when regulated from the perspective of iron homeostasis,and can also release pro-inflammatory factors,trigger inflammatory reactions,change the survival environment of tumors as well as reduce the immune susceptibility of tumor cells.In recent years,more and more studies have shown that macrophages and iron death are closely related.In this paper,the rela-tionship between macrophages and iron death in terms of their functional properties and targeting of tumors are mainly introduced,and an overview of the functional properties of the two differentiated phenotypes of macrophages for the treatment of iron death in tumors is provided.

Objective To establish a classification tree model for non-alcoholic fatty liver disease(NAFLD)among aircrews,screen for influencing factors of NAFLD,so as to provide scientific basis for prevention and intervention decisions for NAFLD.Methods Aircrews who underwent recuperation at a sanatorium from January 2019 to December 2023 were selected as the research objects.Their annual physical examination data were collected and the NAFLD detection rate was calculated.Age,body mass index(BMI),blood pressure,waist circumference,blood routine,biochemistry indexes,and thyroid function were incorporated,and a NAFLD risk model was constructed using classification regression tree method.The predictive performance of the NAFLD classification tree model was evaluated through model misclassification matrix,risk statistics,and receiver operating characteristic curve.Results A total of 4088 aircrews were included in the study,and NAFLD was detected in 380 persons(380/4088,9.30%).The NAFLD model consisted of three layers,and five explanatory variables affecting the onset of NAFLD were extracted,including BMI,triglycerides(TG),high-density lipoprotein cholesterol(HDL-C),alanine aminotransferase(ALT),and total bilirubin(TBIL).BMI was located at the top of the classification tree and was the most important risk factor for NAFLD in aircrews.The area under the curve(AUC)of the model was 0.853.The predictive accuracy of NAFLD was 90.9%,indicating that the model has good accuracy and fitting effect.Conclusion In this study,the detection rate of NAFLD in aircrews was 9.30%.BMI,TG,HDL-C,ALT,and TBIL are risk factors for the onset of NAFLD.NAFLD is mainly related to weight gain and lipid metabolism disorders caused by unhealthy lifestyles.

BackgroundNon-suicidal self-injury （NSSI） behavior among adolescents has become a global public health concern. Anxiety and depression are considered key factors influencing NSSI behavior， while social support may play a protective role in alleviating emotional and behavioral issues. However， existing research has primarily focused on the direct impact of individual factors on NSSI behavior， with insufficient exploration of the combined effects of anxiety， depression and social support. ObjectiveTo investigate the direct effect of anxiety on NSSI， the mediating role of depression and the moderating role of social support in relationship between anxiety and NSSI behavior， thus to provide references for the prevention and intervention of NSSI behavior among adolescents. MethodsIn February 2022， a total of 40 820 students in grades 7 to 12 across 10 middle schools in a district of Chengdu were selected as participants， and they were assessed using Generalized Anxiety Disorder Scale-7 item （GAD-7）， Patient's Health Questionnaire Depression Scale-9 item （PHQ-9）， Social Support Scale for Urban Students （SSSUS） and Adolescent Self-Harm Scale （ASHS）. Pearson correlation analysis was conducted to examine the correlations between scale scores among adolescents with NSSI behaviors. Mediation and moderation analyses were performed using Process 3.5 in SPSS， and the significance was tested with bootstrapping. The interaction was visualized by using simple slope analysis. ResultsAmong 34 534 （84.60%） valid respondents， 542 adolescents （1.57%） reported engaging in NSSI behavior. Significant differences in gender， GAD-7 scores， PHQ-9 scores， and SSSUS scores were observed between NSSI behavior group and non-NSSI group （χ²/t=62.889， 71.120， 94.365， -41.464， P<0.01）.Adolesents with NSSI showed positive correlations between GAD-7 scores and both ASHS and PHQ-9 scores （r=0.158， 0.166， P<0.01）. PHQ-9 scores were positively correlated with ASHS scores （r=0.364， P<0.01）， but negatively correlated with SSSUS scores （r=-0.290， P<0.01）. SSSUS scores were negatively correlated with ASHS scores （r=-0.247， P<0.01）. Depression partially mediated the relationship between anxiety and NSSI behavior， with an effect size of 0.544 （95% CI： 0.162~0.944）， accounting for 35.79% of the total effect. Social support moderated the relationship between depression and NSSI bahavior， with an effect value of -0.082 （95% CI： -0.135~-0.029）. ConclusionAnxiety not only directly influences NSSI bahavior among adolescents， also indirectly exacerbates it through depression， while social support mitigates the impact of depression on NSSI behavior. ［Funded by Youth Project of National Natural Science Foundation of China （number， 82401812）； Project of Health Commission of Sichuan Province （number， 24LCYJPT18）］

ObjectiveTo analyze the epidemiological characteristics of long COVID and to investigate its main influencing factors by examining individuals infected with SARS-CoV-2 between March and June 2022 in two communities in Shanghai, to lay the foundation for further research on the mechanism and clinical treatment of long COVID, and to provide the basis for the development of inexpensive, convenient, and feasible prevention and intervention strategies. MethodsA cross-sectional study was conducted, enrolling 6 410 individuals infected with SARS-CoV-2. Data were collected through a questionnaire survey. The incidence and common symptoms of long COVID were analyzed, along with their associations with demographic characteristics, medical history, and behavioral factors. A logistic regression model was used to identify the major factors associated with the development of long COVID symptoms. ResultsThe overall incidence rate of long COVID among the study population was 13.9%. The most commonly reported symptoms included fatigue (65.1%), attention disorders (23.1%), and cough (16.9%). The analysis showed that having underlying chronic diseases (OR=2.580, 95%CI: 2.165‒3.074), a history of allergies (OR=1.418, 95%CI: 1.003‒1.971), current smoking (OR=1.461, 95%CI: 1.013‒2.079), ever smoking (OR=2.462, 95%CI: 1.687‒3.551), a greater number of symptoms during the acute phase [1 symptom (OR=1.778, 95%CI: 1.459‒2.162), 2 symptoms (OR=2.749, 95%CI: 2.209‒3.409), ≥3 symptoms (OR=7.792, 95%CI: 6.333‒9.593)] and aggravated symptoms during the acute phase (OR=1.082, 95%CI: 1.070‒1.094) were factors associated with a higher risk of developing long COVID symptoms. Additionally, individuals who had consumed alcohol in the past year (OR=1.914, 95%CI: 1.344‒2.684) were more prone to objective long COVID symptoms. Among individuals under 50 years of age, females (OR=1.427, 95%CI: 1.052‒1.943) were more likely to develop objective long COVID symptoms. ConclusionThis study has identified the diversity of long COVID symptoms, which involve multiple organs and systems, including fatigue, attention disorders, cough, and joint pain. It has also revealed associations between long COVID and various demographic factors (e.g., age, gender), personal medical history (e.g., underlying chronic diseases, history of allergies), acute-phase characteristics (e.g., number and severity of symptoms), and behavioral factors (e.g., smoking, alcohol consumption). These findings highlight the need for further research and ongoing surveillance of long COVID and may inform the development of more targeted health management strategies for specific populations.