Objective: To explore the influencing factors of anxiety symptoms and to construct a predictive model based on machine learning algorithms, so as to provide support for the prevention and management of anxiety symptoms among junior high school students. Methods: From April to May 2023, a stratified random cluster sampling method was adopted to select 8 176 junior high school students from Zhengzhou and Shangqiu citys. All participants completed the Adolescent Self rating Life Events Checklist, the 10item Connor-Davidson Resilience Scale, the School Connectedness Scale, the Parent-Child Cohesion Questionnaire, and the 7 item Generalized Anxiety Disorder Scale. Logistic regression analysis identified the associated factors of anxiety symptoms among junior high school students. Predictive models were constructed using Logistic regression, Random Forest, and eXtreme Gradient Boosting (XGBoost) algorithms, with SHapley Additive exPlanations analysis explaining the optimal model. Results: The detection rate of anxiety symptoms among junior high school students was 16.3%. Logistic regression analysis showed that junior high school students who were female ( OR =1.22), in the ninth grade ( OR =1.27), living in urban areas ( OR =1.37), having a father with a college education or above ( OR =1.26), having a mother with a senior high school education ( OR =1.26), and experiencing higher levels of negative life events ( OR =1.05) reported a higher risk of anxiety symptoms(all P <0.05). In contrast, those with moderate family economic status ( OR =0.71), moderate academic burden ( OR =0.59), low academic burden ( OR =0.54), moderate sleep quality ( OR =0.46), good sleep quality ( OR =0.26), excellent sleep quality ( OR =0.15), higher levels of psychological resilience ( OR =0.96), higher levels of school connectedness ( OR =0.96), and higher levels of parent-child cohesion ( OR =0.98) reported a lower risk of anxiety symptoms (all P <0.05). Three machine learning models demonstrated good predictive performance for anxiety symptoms among junior high school students (all AUC>0.8), with the XGBoost model achieving the best predictive performance. SHAP analysis revealed that negative life events, sleep quality, school connectedness, psychological resilience and parent-child cohesion were the top five relevant factors for predicting anxiety symptoms. Conclusions The detection rate of anxiety symptoms among junior high school students is relatively high. The XGBoost model is the optimal predictive model for anxiety symptoms in the population. Negative life events, sleep quality, school connectedness, psychological resilience, and parent-child cohesion are significant correlates of anxiety symptoms among junior high school students.

Objective To evaluate the transition rules of normal body mass index(BMI),overweight and metabolic syndrome(MetS)in patients with major depressive disorder(MDD).Methods Patients with MDD who had multiple admission records between Jan 2016 and Nov 2021 in Beijing Anding Hospital,Capital Medical University were included.Based on the overweight and metabolic syndrome status assessed at each admission,the patients were categorized into three states:normal BMI,overweight and metabolic syndrome.A multi-state Markov model was used to analyze the transition intensity and transition frequency between three states and the influence of covariates on transitions.Results A total of 892 records of 398 subjects were included,with a median age of 56 years old and 31.4% males.The median follow-up period was 40 months.The multi-state model showed that there were 494 transitions between the three states,of which 5.1% moved from normal BMI to overweight and 5.5% moved from overweight to MetS.The intensity of transition was the highest from overweight to MetS,9.52 times greater than overweight to normal BMI.After 48.53 months,MDD patients with normal BMI began to transition to MetS.For overweight MDD patients,the transition to MetS started after 8.77 months.MDD patients with normal BMI or overweight had 31.4% and 50.4% probabilities of developing Mets after 36 months.For MDD patients comorbid with MetS,the probability of staying at MetS was 51.2% after 36 months.Multivariate analysis showed that being unmarried was a risk factor against developing overweight in normal BMI MDD patients,while a higher level of education was a protective factor against developing MetS in overweight MDD patients.Conclusion MDD patients exhibited a higher intensity and risk of developing MetS,and it is not easy to reverse MetS,suggesting that BMI management and MetS intervention should be strengthened in MDD patients.

Objective The study aimedto investigate the effects and metabolic mechanisms of Gegen Qinlian Decoction(GQD)containing serum on hypoxia-induced glucose metabolism in L02 cells.Methods The effects of five hypoxia durations(6,12,18,24,and 48 hours)on glucose consumption and cell viability of L02 cells were examined under hypoxic conditions to determine the optimal hypoxia time.Normal hepatocytes served as the normal control group.L02 cells with hypoxia-induced reduction in glucose consumption were divided into several groups:hypoxia group,metformin 2 mmol/L group,and 25 g/kg GQD groups treated with 5%,10%,and 15%GQD contain-ing serum.Glucose consumption was used as an indicator of drug efficacy.High-resolution liquid chromatography tandem quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS)was employed to collect metabolite signals from each group.Data were analyzed by using Progenesis QI software,and potential biomarkers were identified through online databases such as HMDB.Finally,metabolic pathways of potential biomarkers were analyzed via the Metabo Analyst 5.0 website.Results An 18 hour hypoxia period was identified as the optimal duration for the replication of the hypoxia-induced L02 cell model.GQD containing serums at 5%and 10%significantly increased glucose consumption in hypoxia-induced L02 cells after 18 hours.14 biomarkers of hypoxia-induced L02 cells were identified,with the levels of 13 biomarkers significantly increased and 1 biomarker significantly decreased.GQD containing serum notably regulated the levels of 3 biomarkers.Conclusion GQD containing serum might improve hypoxia-induced abnormal glucose metabolism in L02 cells and enhance glucose consumption by modulating glycero-phospholipid metabolism,glycosylphosphatidylinositol biosynthesis,and sphingolipid metabolism.

This study was aimed at exploring the epidemic characteristics and spatio-temporal evolution patterns of severe fever with thrombocytopenia syndrome(SFTS)in Henan Province from 2011 to 2022,to provide a reference for prevention and control ef-forts.Data on SFTS in Henan Province from 2011 to 2022 were collected from the Information Management System for Infectious Dis-ease Reporting,and epidemiological characteristics and spatio-temporal evolution patterns were investigated through spatial autocorre-lation analysis,standard deviation ellipse analysis,and spatial-centered transfer curves,on a district-county basis.From 2011 to 2022,a total of 5 471 SFTS cases associated with 81 deaths were reported in Henan Province.The incidence rate showed an increasing trend(χ2trend=23.24,P<0.001),and the average annual incidence was 0.4 677/100 000.The case-fatality rate showed a decreasing trend from 2011 to 2019(χ2trend=8.86,P=0.003),but an increasing trend from 2020 to 2022(χ2trend=12.93,P<0.001).The average an-nual case-fatality rate was 1.48%.The peak incidence period was from May to July;this period accounted for 58.75%of the total cases.Females(59.39%),individuals 60-80 years old(55.40%),and farmers(96.64%)were the high prevalence groups.The disease was distributed primarily in Xinyang City,and Shangcheng County had the highest incidence rate(27.411 8/100 000).Spatial aggregation was observed in the southeastern region(Moran's I>0,P<0.001),and the disease centers were all located in Guangshan County,Xin-yang City,and showed southeast-northwest-southeast-northwest-southeast-northeast-southwest movement during the 12-year pe-riod.In conclusion,from 2011 to 2022,SFTS in Henan Province had a high incidence in May to July,and females,older people,and farmers were the high-risk groups.Spatial aggregation was observed in the southeastern region,along with spread to surrounding areas.Xinyang City is therefore a key area for the prevention and control of SFTS.

Objective To construct the K64 capsule depolymerase recombinant protein,Dep44,and investigate its potential application against carbapenem-resistant Klebsiella pneumoniae(CRKP)infections.Methods The de-polymerase-encoding phage vB_Kpn_HF1013(GenBank:PP803128)was isolated and genomically analyzed to screen for candidate depolymerases.The recombinant protein Dep44 was constructed and functionally verified for depolymerase activity.Dep44 sensitive range was validated and Dep44 antimicrobial activity was assessed by bio-film disruption and serum sterilization assays.Results The tail spike protein of phage vB_Kpn_HF1013 exhibited depolymerase activity and recombinant protein Dep44 specifically degraded K64 CRKP capsule.Biofilm eradication assays demonstrated that recombinant Dep44 at both 2 μg/mL and 10 μg/mL significantly disrupted bacterial bio-films relative to the control.Serum bactericidal assays showed that Dep44 exhibited synergistic activity with serum,dependent on the complement system,as Dep44 alone lacked bactericidal properties.Conclusion Dep44 effec-tively targets and degrades K64 CRKP capsule,disrupts biofilms,and enhances serum bactericidal activity,high-lighting its potential for managing K64 CRKP infections and clearing biofilms from medical devices.

With the deepening of the modernization of traditional Chinese medicine(TCM),the analysis of mineralogical features of mineralogical TCM,as an important part of TCM,has received more and more attention.At present,the research of mineral-based traditional Chinese medicine is faced with problems such as confusion of medicinal resources,unclear material basis,and low exclusivity of quality standards,while common analytical techniques have certain limitations in quantitative analysis,sensitivity and comprehensive characterization,which restrict the modernization research of mineral-based medicines and its clinical applications.The advanced mineral identification and characterization system integrates energy spectrum and spectral analysis techniques,combined with efficient data processing algorithms,which can rapidly and accurately analyze mineral components qualitatively and quantitatively,but its application in mineral medicine research is still in its infancy.This article reviews the common analytical techniques for mineral medicine and the potential application of advanced mineral identification and characterization system in the identification of mineral Chinese medicine matrix and quality control.The advanced mineral identification and characterization system can not only accurately distinguish the mineralogical characteristics of mineral medicines,such as the mineral composition,elemental state and embedded characteristics,and provide data support for the research of mineral medicine resources,but also provide scientific basis for the establishment of systematic quality standards,the analysis of the preparation mechanism,the revelation of its potential medicinal effect of the material basis and the control of the risk of heavy metals.

With the deepening of the modernization of traditional Chinese medicine(TCM),the analysis of mineralogical features of mineralogical TCM,as an important part of TCM,has received more and more attention.At present,the research of mineral-based traditional Chinese medicine is faced with problems such as confusion of medicinal resources,unclear material basis,and low exclusivity of quality standards,while common analytical techniques have certain limitations in quantitative analysis,sensitivity and comprehensive characterization,which restrict the modernization research of mineral-based medicines and its clinical applications.The advanced mineral identification and characterization system integrates energy spectrum and spectral analysis techniques,combined with efficient data processing algorithms,which can rapidly and accurately analyze mineral components qualitatively and quantitatively,but its application in mineral medicine research is still in its infancy.This article reviews the common analytical techniques for mineral medicine and the potential application of advanced mineral identification and characterization system in the identification of mineral Chinese medicine matrix and quality control.The advanced mineral identification and characterization system can not only accurately distinguish the mineralogical characteristics of mineral medicines,such as the mineral composition,elemental state and embedded characteristics,and provide data support for the research of mineral medicine resources,but also provide scientific basis for the establishment of systematic quality standards,the analysis of the preparation mechanism,the revelation of its potential medicinal effect of the material basis and the control of the risk of heavy metals.

Objective:To identify different subtypes of patients with preeclampsia(PE)through clinical liver function index data-driven the cluster analysis,to explore the correlation between liver function of different sub-types and pregnancy complications.Methods:From January 2012 to December 2022,the general data of 2230 sin-gleton pregnant women with PE who underwent prenatal examination and delivered in Fujian Maternity and Child Health Hospital were collected.Using 13 liver function indexes before delivery as baseline variables,all included subjects were classified into subtypes by cluster method.The clinical characteristics of different subtypes of PE patients were compared.Single-factor Logistic regression was used to analyze the risk of pregnancy complications among subtypes.Results:PE patients were divided into 3 subgroups that represented different characteristics of patients' liver function.The first subtype(n=1065)exhibited abnormal liver enzymology index characterized by in-creased alkaline phosphatase(ALP)level.The second subtype(n=648)showed abnormal bilirubin metabolism index with the highest levels of total bilirubin(TBIL),direct(DBIL)and indirect bilirubin(IBIL).The third subtype(n=517)had abnormal liver enzymology indexes with elevated alanine aminotransferase(ALT)and aspartate aminotransferase(AST)levels,abnormal bile acid detection indexes with elevated total bile acid(TBA)levels,and abnormal liver synthesis function indexes with decreased total protein(TP),albumin(ALB),and globulin lev-els(GLB).Significant differences were observed among the three subtypes in age,severe PE,anemia,cardiac dysfunction,and renal dysfunction(P＜0.05).Single-factor Logistic regression demonstrated that the third sub-type had significantly higher risks of intrahepatic cholestasis of pregnancy,fetal growth restriction,premature rup-ture of membranes,and preterm birth compared to the first and second subtypes(P＜0.05),as well as a higher risk of placental abruption than the second subtype(P＜0.05).The first subtype had higher risks of placental ab-ruption and fetal growth restriction than the second subtype(P＜0.05).Conclusions:Cluster analysis could be used to subclassify PE patients by liver function characteristics,so as to identify the occurrence of pregnancy complications.The results had significance for understanding the heterogeneity of PE and promoting individualized management.

Objective·To detect immunoglobulin(Ig)expression levels in newly diagnosed multiple myeloma(MM)patients before and after induction therapy,and to explore the clinical significance of Ig expression levels and their dynamic changes in relation to treatment efficacy,infection occurrence,and prognosis.Methods·Clinical data from 142 MM patients treated at the Department of Hematology,The First Affiliated Hospital of Soochow University between August 2018 and September 2020 were analyzed.Baseline Ig expression levels and post-induction changes following bortezomib-lenalidomide-dexamethasone(VRD)regimen were assessed.Immunoparesis was defined as uninvolved Igs below the laboratory lower limit of normal.Patients were stratified by immunoparesis severity(mild,moderate,severe,extremely severe).ANOVA,rank-sum tests,and x2 tests were used to analyze correlations with baseline characteristics.The relationship between the improvement in immunoparesis and the induction efficacy,infection occurrence,and prognosis was analyzed based on the dynamic changes in immunoparesis.Results·Normal Igs were severely reduced in newly diagnosed MM patients.Immunoparesis was present in 128 patients(90.1%),with severe or extremely severe immunoparesis accounting for 76.1%.Patients with extensive immunoparesis(all uninvolved Ig levels below the lower normal limit)were more likely to have severe immunoparesis(P<0.05).There were no statistically significant differences in age,gender,presence of severe renal insufficiency,and high-risk cytogenetics among MM patients with different degrees of immunoparesis(P>0.05),but there were statistically significant differences in MM staging(P=0.008)and typing(P=0.010).Most patients with severe immunoparesis were at stage Ⅱ/Ⅲ based on the Revised International Staging System(R-ISS)and were of the IgG type.At diagnosis,the levels of the involved Ig or light chain were negatively correlated with normal Ig levels(P<0.05).Improvement in immunoparesis after induction therapy was positively correlated with treatment response(P=0.006).The infection rate was high(26.8%),but no significant correlation was found between immunoparesis and infection occurrence(P>0.05).After induction therapy,patients showing improvement in immunoparesis had significantly longer progression-free survival(PFS)(median PFS:not reached vs 38 months,P=0.025),but no significant impact on overall survival(OS)was observed(P=0.450).Conclusion·Immunoparesis is common and severe in newly diagnosed MM patients,with severity correlating with disease stage and subtype.VRD therapy can partially reverse immunoparesis,and improvement is positively associated with treatment response and PFS benefit.Infection risk appears unrelated to immunoparesis severity and warrants comprehensive prevention strategies.Humoral immune deficiency may serve as a prognostic indicator in MM,but its impact on OS requires further investigation.

Objective The study aimedto investigate the effects and metabolic mechanisms of Gegen Qinlian Decoction(GQD)containing serum on hypoxia-induced glucose metabolism in L02 cells.Methods The effects of five hypoxia durations(6,12,18,24,and 48 hours)on glucose consumption and cell viability of L02 cells were examined under hypoxic conditions to determine the optimal hypoxia time.Normal hepatocytes served as the normal control group.L02 cells with hypoxia-induced reduction in glucose consumption were divided into several groups:hypoxia group,metformin 2 mmol/L group,and 25 g/kg GQD groups treated with 5%,10%,and 15%GQD contain-ing serum.Glucose consumption was used as an indicator of drug efficacy.High-resolution liquid chromatography tandem quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS)was employed to collect metabolite signals from each group.Data were analyzed by using Progenesis QI software,and potential biomarkers were identified through online databases such as HMDB.Finally,metabolic pathways of potential biomarkers were analyzed via the Metabo Analyst 5.0 website.Results An 18 hour hypoxia period was identified as the optimal duration for the replication of the hypoxia-induced L02 cell model.GQD containing serums at 5%and 10%significantly increased glucose consumption in hypoxia-induced L02 cells after 18 hours.14 biomarkers of hypoxia-induced L02 cells were identified,with the levels of 13 biomarkers significantly increased and 1 biomarker significantly decreased.GQD containing serum notably regulated the levels of 3 biomarkers.Conclusion GQD containing serum might improve hypoxia-induced abnormal glucose metabolism in L02 cells and enhance glucose consumption by modulating glycero-phospholipid metabolism,glycosylphosphatidylinositol biosynthesis,and sphingolipid metabolism.