ObjectiveTo construct a multifunctional liposomal delivery system by replacing cholesterol（Chol） in conventional liposomes with saikosaponin D（SSD） and modifying with poloxamer 407（P407） for co-delivery of curcumin（Cur）. The system was evaluated for in vivo tumor targeting and inhibitory effects on mouse subcutaneous solid tumors. MethodsSingle-factor and orthogonal tests combined with information entropy weighting were used to optimize the formulation process of the liposome with encapsulation efficiency and absolute Zeta potential as indexes， and validation studies and liposomal characterization were performed. A subcutaneous solid tumor model was established by injecting H22 hepatocellular carcinoma cells subcutaneously into the dorsal surface of the right forelimb of mice. DiR-loaded traditional Chol liposomes（P407-DiR-Chol-LPs， PDCL） and novel SSD-based liposomes（P407-DiR-SSD-LPs， PDSL） were prepared by the optimized formulation process， and tail vein injection was performed to investigate the impact of SSD on liposome tumor targeting with small animal in vivo imaging. Mice were randomly divided into eight groups， including blank group， model group， free doxorubicin（DOX） group（2 mg·kg^-1）， free Cur group（8 mg·kg^-1）， free SSD group（10 mg·kg^-1）， P407-Cur-Chol-LPs（PCCL） group， P407-SSD-LPs（PSL） group， and P407-Cur-SSD-Lps（PCSL） group. Treatments were administered intraperitoneally every other day for seven doses. Antitumor efficacy and biocompatibility were evaluated by monitoring body weight change， organ indices， tumor volume and mass， relative tumor proliferation rate（T/C）， and tumor growth inhibition rate（TGI）. Histopathological analysis of liver， kidney， and tumor tissues was performed using hematoxylin-eosin（HE） staining. Serum levels of aspartate aminotransferase（AST）， alanine aminotransferase （ALT）， blood urea nitrogen（BUN）， and creatinine（Crea）in mice were quantified by fully automated biochemical analyzer. ResultsOrthogonal test yielded optimal ratios of Cur， SSD， and P407 to soybean phosphatidylcholine（SPC） as 1∶25， 1∶20， and 1∶4. The optimized PCSL exhibited spherical morphology with a particle size of 179.15 nm， a Zeta potential of -47.25 mV， and an encapsulation efficiency of 96.40%. Its in vitro release profile conformed to first-order kinetics， demonstrating excellent storage stability and hemocompatibility. In vivo imaging revealed that the fluorescence signal in tumor tissues and the fluorescence intensity ratio between tumors and organs were significantly higher in the PDSL group than in the PDCL group（P<0.05， P<0.01）. Among the treatment groups， PCSL group showed superior efficacy over free Cur group， free SSD group， PCCL group， and PSL group， with TGI>40% and T/C<60%， indicating pronounced anti-hepatocellular carcinoma effects（P<0.05， P<0.01）. Histopathology and serum biochemistry indicated minimal hepatorenal toxicity and improved hepatic and renal function in PCSL-treated mice. ConclusionReplacing Chol with SSD in preparing multifunctional drug delivery systems not only stabilizes liposomes but also yields superior anti-hepatocellular carcinoma efficacy， achieving the effect of drug-excipient integration. Co-delivery of Cur via this system can be used for treating subcutaneous solid tumors in hepatocellular carcinoma， providing new insights and technical approaches for anti-hepatocellular carcinoma research and the meridian-guiding and messenger-directing theory in traditional Chinese medicine.

Diarrhea-predominant irritable bowel syndrome （IBS-D） exhibits typical characteristics of psychosomatic comorbidity. Its core pathogenesis is considered to involve simultaneous disorders of both the body and the spirit， for which the former is attributed to liver constraint and spleen deficiency， and dysfunction of large intestine conduction， whereas the latter is induced by spirit restlessness of zang （脏） organs， and gate insecurity of the corporeal soul. Based on this understanding， the therapeutic principle of "simultaneous regulation of body and spirit" is established. For regulating the body， the methods include soothing the liver， fortifying the spleen， consolidating the intestines， and stopping diarrhea， with emphasis on the front-mu （募） points of the related zang-fu （脏腑） organs and acupoints of the foot yangming （阳明） stomach channel and foot taiyin （太阴） spleen channel. For regulating the spirit， the methods include calming the brain spirit， tranquilizing the zang organs spirit， and securing the corporeal soul gate， mainly selecting acupoints of Governer Vessel （督脉） and the back-shu （背俞） points of the corresponding zang-fu organs. Needle manipulation techniques for supplementation and drainage are flexibly applied according to the deficiency or excess nature of the syndrome. In addition， comprehensive application of moxibustion， electroacupuncture， and auricular therapy is emphasized， with the aim of providing clinical insights for diagnosis and treatment.

Objective:To analyze the changes in the prevalence characteristics of multimorbidity among adolescents aged 13-18 in Inner Mongolia Autonomous Region from 2019 to 2022 and to explore the association between multimorbidity and moderate to high-intensity physical activity among them.Methods:A stratified random cluster sampling method was used to select students aged 13-18 in Inner Mongolia Autonomous Region every September from 2019 to 2022. Physical examinations, demographic characteristics, and depression-related surveys were conducted to analyze the multimorbidity of overweight, obesity, high blood pressure, myopia, spinal curvature abnormality, and depression. A logistic regression model was used to analyze the association between multimorbidity and moderate to high-intensity physical activity.Results:From 2019 to 2022, 70 972, 62 923, 80 254, and 78 288 study subjects were included, with the rates of multimorbidity being 56.4%, 55.4%, 57.2%, and 55.8%, respectively. The rates of multimorbidity remained relatively stable from 2019 to 2022 ( χ2=0.06, P=0.950). The incidence of multimorbidity among girls was significantly higher than that among boys ( P<0.001). The incidence of multimorbidity among urban students was significantly higher than that among suburban students ( P<0.001). The incidence of multimorbidity among high school students was higher than that among middle school students ( P<0.001). The top three multimorbidity combinations were myopia and overweight/obesity (26.4%), myopia and high blood pressure (24.4%), and myopia and depression (19.8%), while the least common combination was depression and spinal curvature abnormality (1.1%). The multimorbidity patterns showed no significant differences between years ( χ2=0.03, P=0.999). The multimorbidity status was significantly associated with the status of meeting the standard of moderate to high-intensity physical activity ( OR=0.83, 95% CI: 0.80-0.86). The association was stronger in boys ( OR=0.77, 95% CI: 0.73-0.81) compared with girls ( OR=0.90, 95% CI: 0.85-0.96), with a significant interaction term ( P<0.001). Conclusion:From 2019 to 2022, the incidence of multimorbidity among adolescents aged 13 to 18 in Inner Mongolia Autonomous Region is relatively high, mainly due to the co-occurrence of myopia and other health problems. Adequate physical activity is an important factor in reducing multimorbidity.

Objective:To investigate the relationship between different types of tea intake and COVID-19 infection.Methods:Data were retrieved from a genome-wide association study(GWAS),involving 447 485,and 64 949 people for single nucleotide polymorphisms(SNPs).Two-sample Mendelian randomization(MR)analysis was used to investigate the relationship of different types of tea intake with four subgroups of COVID-19 infected population,including COVID-19 infected population versus general population,COVID-19 hospitalized population versus general population,COVID-19 hospitalized population versus non-hospitalized population,and very severe respiratory confirmed population versus general population.Inverse-variance weighted(IVW)method was used as the main method of causal analysis.MR Egger intercept was used for pleiotropy test,and Cochran's Q-statistic was used for heterogeneity test.Results:Compared to the general population,tea intake decreased the incidence of COVID-19 in the infection population(IVW method,OR=0.806,95%CI:0.651-0.999),and the hospitalized population(IVW method,OR=0.533,95%CI:0.369-0.770).Additionally,the underlying pleiotropy was not found following the MR-Egger regression intercept(MR intercept=-0.002,P=0.667),and the Cochran's Q-statistic showed no heterogeneity(Q-statistic=52.712,P=0.057).Compared to the general population,the underlying pleiotropy in the hospitalized patients was not found by MR-Egger regression intercept(MR intercept=-0.001,P=0.909),and the Cochran's Q-statistic showed no heterogeneity(Q-statistic=25.214,P=0.945).However,green tea and herbal tea had no effect on COVID-19 infection.Conclusions:Overall tea intake reduces the risk of COVID-19 infection in the general population compared to COVID-19 infected and hospitalized populations,while green tea and herbal tea have no protective effect against COVID-19 infection.

Objective:Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions.Methods:Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from the Cancer Hospital of the Chinese Academy of Medical Sciences, Tianjin Central Hospital of Gynecology Obstetrics, Xinmi Maternal and Child Health Hospital of Henan Province, West China Second Affiliated Hospital of Sichuan University, and Heping Hospital Affiliated to Changzhi Medical College collected during April 2014 and March 2015. The hypermethylated gene fragments related to cervical cancer were selected by high-density, high-association, and hypermethylated gene fragment screening and the LASSO regression algorithm. Taking cervical intraepithelial neoplasia grade 2 (CIN2) or more severe lesions as the research outcome, machine learning predictive models based on the random forest (RF), naive Bayes (NB), and support vector machine (SVM) algorithm, respectively, were constructed. A total of 144 outpatient specimens were used as the training set and 80 cervical exfoliated cell specimens from women participating in the cervical cancer screening program were used as the test set to verify the predictive models. Using histological diagnosis results as the gold standard, the detection efficacy for CIN2 or more severe lesions of the three machine learning predictive models were compared with that of the human papilloma virus (HPV) detection and cytological diagnosis.Results:In the training set of 144 cases, there were 34 cases of HPV positivity, with a positive rate of 23.61%. Cytologically, there were 37 cases diagnosed as no intraepithelial lesion or malignancy (NILM), and 107 cases diagnosed as atypical squamous cells of undetermined significance (ASC-US) or above. Histologically, there were 28 cases without cervical intraepithelial neoplasia or benign cervical lesions, 31 cases of CIN1, 18 cases of CIN2, 31 cases of CIN3, and 36 cases of squamous cell carcinoma. Seven hypermethylated gene fragments were selected from 45 genes, and three machine learning prediction models based on the RF, NB, and SVM algorithm, respectively, were constructed. In the validation set of 80 cases, there were 28 cases of HPV positivity, with a positive rate of 35.00%. Cytologically, there were 65 cases diagnosed as NILM and 15 cases as ASC-US or above. Histologically, there were 39 cases without cervical intraepithelial neoplasia or benign cervical lesions, 10 cases of CIN1, 10 cases of CIN2, 11 cases of CIN3, and 10 cases of squamous cell carcinoma. In the validation set, the area under the curve (AUC) values of the RF model, NB model, SVM model, HPV detection, and cytological diagnosis of CIN2 or above were 0.90, 0.88, 0.82, 0.68, and 0.45, respectively. The DeLong test showed that there was no statistically significant difference in the AUC values between the RF, NB, and SVM models (all P＞0.05), and the AUC values of the RF and NB models were higher than that of HPV detection (both P＜0.01), and the AUC values of the RF, NB, and SVM models were higher than that of cytological diagnosis (all P＜0.01). Compared with the NB model, the sensitivity of the RF model was similar (80.65% vs. 77.42%), but the specificity of the NB model was much higher than that of the RF model (93.88% vs. 73.47%). Conclusion:Among the machine learning prediction models for cervical cancer and precancerous lesions constructed based on human DNA methylation, the NB model has good predictive performance for CIN2 and above lesions, and may be used for screening of cervical cancer and precancerous lesions.

Objective·To investigate the changes in transcriptome and chromatin accessibility during the differentiation of human embryonic stem cells(hESCs)into neural progenitor cells(NPCs)using in vitro differentiation models and high-throughput multi-omics sequencing technologies.Methods·hESCs were first induced to differentiate into NPCs in vitro using the embryoid body formation method,and cells at both stages were collected.The cell phenotypes were identified by reverse transcription-quantitative real-time PCR(RT-qPCR)and immunofluorescence(IF)staining.Transcriptome sequencing(RNA-seq)was conducted to detect and analyze the differentially expressed genes(DEGs)between hESCs and NPCs.The assay for transposase-accessible chromatin with high-throughput sequencing(ATAC-seq)was employed to assess chromatin accessibility changes between hESCs and NPCs.Motif enrichment analysis was performed on differentially accessible chromatin regions to discover potential regulatory transcription factors.Finally,an integrated analysis of RNA-seq and ATAC-seq data and the protein-protein interaction(PPI)network were performed to identify key genes and regulatory pathways involved in the early stages of neural differentiation in vitro.Results·Both RT-qPCR and IF results indicated that the expression levels of pluripotency markers(NANOG and POU5F1)were high at the hESC stage but significantly decreased at the NPC stage,while early neural differentiation markers(PAX6,SOX1,and NES)were minimally expressed at the hESC stage but markedly upregulated at the NPC stage.RNA-seq analysis revealed that compared to the hESC stage,there were 5 597 genes upregulated and 3 654 genes downregulated at the NPC stage.Gene function enrichment analysis showed that the upregulated genes at the NPC stage were enriched in the functions related to neural development.ATAC-seq analysis demonstrated a total of 27 491 genomic regions had significant changes in chromatin accessibility during the differentiation from hESC to NPC,with 12 381 regions showing increased accessibility and 15 110 regions showing decreased accessibility.Motif enrichment analysis revealed that transcription factor genes such as DLX1 and LHX2 might play an important role in the differentiation process from hESCs into NPCs.Integrated analysis of RNA-seq and ATAC-seq data revealed that overlapping genes with high expression at the NPC stage were mainly enriched in axon guidance,forebrain development,and neuron migration.After neural differentiation,the expression levels of CTNND2 and LHX2 genes increased,and the chromatin accessibility of related genomic regions also increased.PPI network analysis indentified candidate downstream genes including PRKACA,CDH2,and ERBB4.Conclusion·The in vitro differentiation model of hESCs combined with high-throughput multi-omics sequencing technologies can be used to depict the changes in transcriptome and chromatin accessibility during the differentiation of hESCs into NPCs.In this process,the expression levels of genes related to axon guidance,forebrain development,and neuronal migration pathways increase and related chromatin accessibility is enhanced.

Objective:To explore the moderating and mediating roles of psychological resilience in the relationship between job satisfaction and depressive symptoms among petrochemical workers.Methods:In April 2022, a cluster sampling method was used to conduct a questionnaire survey among 1087 in-service employees of a petrochemical enterprise in Henan Province. A total of 861 questionnaires were recovered, including 857 valid ones, with an effective rate of 99.54%. Data on job satisfaction, psychological resilience, and depressive symptoms were collected using the 10-item Connor-Davidson Resilience Scale (CD-RISC-10), Job Satisfaction Questionnaire, and Patient Health Questionnaire-9 (PHQ-9). Spearman rank correlation analysis was applied to analyze the relationships among the scores of job satisfaction, psychological resilience, and depressive symptoms. Hierarchical linear regression analysis was used to test the moderating effect of psychological resilience, and the Bootstrap method was employed to verify the mediating effect of psychological resilience.Results:The scores of job satisfaction, psychological resilience, and depressive symptoms among petrochemical workers were 36.00 (31.00, 36.00) points, 36.00 (30.00, 41.00) points, and 7.00 (3.00, 9.00) points. The detection rate of depressive symptoms was 65.7% (563/857). Results of Spearman rank correlation analysis showed that job satisfaction of petrochemical workers was positively correlated with psychological resilience ( rs=0.270, P<0.01) and negatively correlated with depressive symptoms ( rs=-0.386, P<0.01), psychological resilience was negatively correlated with depressive symptoms ( rs=-0.515, P<0.01). Results of hierarchical linear regression analysis indicated that psychological resilience had no moderating effect on the relationship between job satisfaction and depressive symptoms of petrochemical workers ( b=0.001, P>0.05). Results of the mediating effect test showed that psychological resilience played a partial mediating effect in the relationship between job satisfaction and depressive symptoms ( P<0.01), with a mediating effect value of -0.071 (95% CI: -0.125, -0.045), accounting for 20.16% of the total effect. Conclusion:Psychological resilience exerts a partial mediating effect rather than a moderating effect in the relationship between job satisfaction and depressive symptoms among petrochemical workers.

Objective:Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions.Methods:Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from the Cancer Hospital of the Chinese Academy of Medical Sciences, Tianjin Central Hospital of Gynecology Obstetrics, Xinmi Maternal and Child Health Hospital of Henan Province, West China Second Affiliated Hospital of Sichuan University, and Heping Hospital Affiliated to Changzhi Medical College collected during April 2014 and March 2015. The hypermethylated gene fragments related to cervical cancer were selected by high-density, high-association, and hypermethylated gene fragment screening and the LASSO regression algorithm. Taking cervical intraepithelial neoplasia grade 2 (CIN2) or more severe lesions as the research outcome, machine learning predictive models based on the random forest (RF), naive Bayes (NB), and support vector machine (SVM) algorithm, respectively, were constructed. A total of 144 outpatient specimens were used as the training set and 80 cervical exfoliated cell specimens from women participating in the cervical cancer screening program were used as the test set to verify the predictive models. Using histological diagnosis results as the gold standard, the detection efficacy for CIN2 or more severe lesions of the three machine learning predictive models were compared with that of the human papilloma virus (HPV) detection and cytological diagnosis.Results:In the training set of 144 cases, there were 34 cases of HPV positivity, with a positive rate of 23.61%. Cytologically, there were 37 cases diagnosed as no intraepithelial lesion or malignancy (NILM), and 107 cases diagnosed as atypical squamous cells of undetermined significance (ASC-US) or above. Histologically, there were 28 cases without cervical intraepithelial neoplasia or benign cervical lesions, 31 cases of CIN1, 18 cases of CIN2, 31 cases of CIN3, and 36 cases of squamous cell carcinoma. Seven hypermethylated gene fragments were selected from 45 genes, and three machine learning prediction models based on the RF, NB, and SVM algorithm, respectively, were constructed. In the validation set of 80 cases, there were 28 cases of HPV positivity, with a positive rate of 35.00%. Cytologically, there were 65 cases diagnosed as NILM and 15 cases as ASC-US or above. Histologically, there were 39 cases without cervical intraepithelial neoplasia or benign cervical lesions, 10 cases of CIN1, 10 cases of CIN2, 11 cases of CIN3, and 10 cases of squamous cell carcinoma. In the validation set, the area under the curve (AUC) values of the RF model, NB model, SVM model, HPV detection, and cytological diagnosis of CIN2 or above were 0.90, 0.88, 0.82, 0.68, and 0.45, respectively. The DeLong test showed that there was no statistically significant difference in the AUC values between the RF, NB, and SVM models (all P＞0.05), and the AUC values of the RF and NB models were higher than that of HPV detection (both P＜0.01), and the AUC values of the RF, NB, and SVM models were higher than that of cytological diagnosis (all P＜0.01). Compared with the NB model, the sensitivity of the RF model was similar (80.65% vs. 77.42%), but the specificity of the NB model was much higher than that of the RF model (93.88% vs. 73.47%). Conclusion:Among the machine learning prediction models for cervical cancer and precancerous lesions constructed based on human DNA methylation, the NB model has good predictive performance for CIN2 and above lesions, and may be used for screening of cervical cancer and precancerous lesions.

Objective:To explore the moderating and mediating roles of psychological resilience in the relationship between job satisfaction and depressive symptoms among petrochemical workers.Methods:In April 2022, a cluster sampling method was used to conduct a questionnaire survey among 1087 in-service employees of a petrochemical enterprise in Henan Province. A total of 861 questionnaires were recovered, including 857 valid ones, with an effective rate of 99.54%. Data on job satisfaction, psychological resilience, and depressive symptoms were collected using the 10-item Connor-Davidson Resilience Scale (CD-RISC-10), Job Satisfaction Questionnaire, and Patient Health Questionnaire-9 (PHQ-9). Spearman rank correlation analysis was applied to analyze the relationships among the scores of job satisfaction, psychological resilience, and depressive symptoms. Hierarchical linear regression analysis was used to test the moderating effect of psychological resilience, and the Bootstrap method was employed to verify the mediating effect of psychological resilience.Results:The scores of job satisfaction, psychological resilience, and depressive symptoms among petrochemical workers were 36.00 (31.00, 36.00) points, 36.00 (30.00, 41.00) points, and 7.00 (3.00, 9.00) points. The detection rate of depressive symptoms was 65.7% (563/857). Results of Spearman rank correlation analysis showed that job satisfaction of petrochemical workers was positively correlated with psychological resilience ( rs=0.270, P<0.01) and negatively correlated with depressive symptoms ( rs=-0.386, P<0.01), psychological resilience was negatively correlated with depressive symptoms ( rs=-0.515, P<0.01). Results of hierarchical linear regression analysis indicated that psychological resilience had no moderating effect on the relationship between job satisfaction and depressive symptoms of petrochemical workers ( b=0.001, P>0.05). Results of the mediating effect test showed that psychological resilience played a partial mediating effect in the relationship between job satisfaction and depressive symptoms ( P<0.01), with a mediating effect value of -0.071 (95% CI: -0.125, -0.045), accounting for 20.16% of the total effect. Conclusion:Psychological resilience exerts a partial mediating effect rather than a moderating effect in the relationship between job satisfaction and depressive symptoms among petrochemical workers.

Objective·To investigate the changes in transcriptome and chromatin accessibility during the differentiation of human embryonic stem cells(hESCs)into neural progenitor cells(NPCs)using in vitro differentiation models and high-throughput multi-omics sequencing technologies.Methods·hESCs were first induced to differentiate into NPCs in vitro using the embryoid body formation method,and cells at both stages were collected.The cell phenotypes were identified by reverse transcription-quantitative real-time PCR(RT-qPCR)and immunofluorescence(IF)staining.Transcriptome sequencing(RNA-seq)was conducted to detect and analyze the differentially expressed genes(DEGs)between hESCs and NPCs.The assay for transposase-accessible chromatin with high-throughput sequencing(ATAC-seq)was employed to assess chromatin accessibility changes between hESCs and NPCs.Motif enrichment analysis was performed on differentially accessible chromatin regions to discover potential regulatory transcription factors.Finally,an integrated analysis of RNA-seq and ATAC-seq data and the protein-protein interaction(PPI)network were performed to identify key genes and regulatory pathways involved in the early stages of neural differentiation in vitro.Results·Both RT-qPCR and IF results indicated that the expression levels of pluripotency markers(NANOG and POU5F1)were high at the hESC stage but significantly decreased at the NPC stage,while early neural differentiation markers(PAX6,SOX1,and NES)were minimally expressed at the hESC stage but markedly upregulated at the NPC stage.RNA-seq analysis revealed that compared to the hESC stage,there were 5 597 genes upregulated and 3 654 genes downregulated at the NPC stage.Gene function enrichment analysis showed that the upregulated genes at the NPC stage were enriched in the functions related to neural development.ATAC-seq analysis demonstrated a total of 27 491 genomic regions had significant changes in chromatin accessibility during the differentiation from hESC to NPC,with 12 381 regions showing increased accessibility and 15 110 regions showing decreased accessibility.Motif enrichment analysis revealed that transcription factor genes such as DLX1 and LHX2 might play an important role in the differentiation process from hESCs into NPCs.Integrated analysis of RNA-seq and ATAC-seq data revealed that overlapping genes with high expression at the NPC stage were mainly enriched in axon guidance,forebrain development,and neuron migration.After neural differentiation,the expression levels of CTNND2 and LHX2 genes increased,and the chromatin accessibility of related genomic regions also increased.PPI network analysis indentified candidate downstream genes including PRKACA,CDH2,and ERBB4.Conclusion·The in vitro differentiation model of hESCs combined with high-throughput multi-omics sequencing technologies can be used to depict the changes in transcriptome and chromatin accessibility during the differentiation of hESCs into NPCs.In this process,the expression levels of genes related to axon guidance,forebrain development,and neuronal migration pathways increase and related chromatin accessibility is enhanced.