In view of the few studies on the influence of Armillaria spp. infection on the content of the chemical components in different parts of Polyporus umbellatus sclerotia, this study determined the biomass of P. umbellatus sclerotia and the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in the separated cavity wall of the sclerotia and the uninfected part of the sclerotia in different harvesting years under the conditions of A. gallica and A. mellea infection respectively. According to the difference of content and dynamic changes of the polysaccharide and the steroid substances, the superior Armillaria sp. was screened to obtain the best harvest years of P. umbellatus. Using HPLC and UV-VIS spectrophotometry methods, the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in P. umbellatus sclerotia infected by the two Armillaria spp. in different years were determined. In addition, the differentially expressed genes related to P. umbellatus polysaccharide synthesis were screened according to the transcriptomic data of different parts of P. umbellatus after A. mellea infection. With the increase of years, the biomass of sclerotia infected by different Armillaria spp. had significant differences, and there were significant differences in the four components of sclerotia. The four components of the separated cavity wall of the sclerotia were significantly higher than those of the uninfected part. The best harvest time was the third year after cultivation. Transcriptomic analysis showed that the infection of Armillaria spp. could significantly promote polysaccharide synthesis, which provided a basis for polysaccharide content determination at the molecular level. The study clarified the influence of different Armillaria spp. infection on the accumulation of chemical components of P. umbellatus sclerotia, laying a foundation for exploring the symbiosis mechanism and provided a scientific clue for screening superior Armillaria sp. and guiding the artificial cultivation of P. umbellatus sclerotia.

Objective:To investigate the risk factors for esophageal varices in patients with liver cirrhosis,to establish a predictive model,and to provide reasonable guidance for the prevention of early esophageal varices in patients with liver cirrhosis.Methods:A retrospective analysis was performed for 1 113 patients with liver cirrhosis who attended the hospitals in Chongqing,China from Decem-ber 2006 to May 2021.Recursive feature elimination(RFE)and four machine learning methods were used for the screening of features,and five machine learning predictive models were established by logistic regression,random forest,support vector machine(SVM),de-cision tree,and eXtreme Gradient Boosting(XGBoost).The receiver operating characteristic(ROC)curve was used to evaluate the per-formance of each model,and the model with the best performance was used to investigate the risk factors for esophageal varices in pa-tients with liver cirrhosis.SHAP plots were used to explain the impact of each risk factor on patients.Results:The XGBoost model showed the best performance in predicting the risk of esophageal varices in patients with liver cirrhosis,with an area under the ROC curve of 0.872(95%CI=0.813-0.918).SHAP plots showed that platelet count,diameter of the portal vein,cholinesterase,albumin,ala-nine aminotransferase,hemoglobin,prothrombin ratio,prothrombin time,and serum total protein were risk factors for esophageal vari-ces in patients with liver cirrhosis.Conclusion:This study shows that the XGBoost predictive model has a relatively high predictive value,and the risk factors obtained by this model have a certain guiding significance for the clinical prevention and treatment of early esophageal varices in patients with liver cirrhosis.

This study analyzed the burden and trends in enteric infections in China from 1990 to 2021 from a One Health perspec-tive.Data on mortality associated with enteric infections were extracted from the 2021 Global Burden of Disease(GBD)database.The analysis focused on assessing the mortality rates of enteric infectious diseases attributed to various etiologies and risk factors,along with the age and sex distribution,from 1990 to 2021.Average annual percentage change(AAPC)was used to assess the total changes in disease burden.The age-standardized mortality rate of intestinal infections in China decreased from 9.642/100 000 in 1990 to 0.439/100 000 in 2021,with an AAPC of-57.103%(95%CI:-57.118%to-57.088%).In 2021,Rotavirus,Norovirus,and Crypto-sporidium were the top three etiologies contributing to disease burden,with mortality rates of 1.020/100 000,0.040/100 000 and 0.079/100 000,respectively.A significant variation in etiology distribution was observed across age groups:Rotavirus,Shigella,and Crypto-sporidium dominated among children under 5 years of age,whereas Cryptosporidium,Norovirus,and Clostridioides difficile were more prevalent in older populations.Risk factor analysis indicated that unsafe water sources and poor sanitation accounted for 73.394%of all enteric disease-related deaths.In conclusion,the burden of enteric infections in China markedly declined from 1990 to 2021,and sig-nificant variations in the etiological spectrum and disease burden were observed across age groups.The persistent effects of unsafe wa-ter sources and poor sanitation underscore the need for targeted interventions to further decrease the burden of these diseases.Our find-ings highlight the success of public health interventions in decreasing the burden of enteric infections in China,while emphasizing the need for targeted measures to address disparities in high-risk populations and improve environmental sanitation.

Objective:To explore the relationship between depressive symptoms and stressors among post-graduates and the role of coping styles and psychological suzhi between them.Methods:A total of 775 postgradu-ates were recruited.They were assessed with the Center for Epidemiological Studies Depression Scale(CES-D),Psychological Stressors Scale of Postgraduates(PSSP),Simplified Coping Style Questionnaire(SCSQ),and Col-lege Students Psychological Suzhi Brief Mental Health Version(CSPS-B-MH).Results:The detection rate of de-pression among postgraduates was 52.0％.Postgraduate stressors were positively associated with depression(β=0.47).Coping styles played a partial mediating role in the relationship between stressors and depression in postgrad-uates,with the mediation effect accounting for 24.76％of the total effect.Psychological suzhi was shown to moder-ate the effect of stressors on depression(β=-0.07)and positive coping on depression(β=-0.05).Conclusion:Postgraduate stressors could affect depression through the mediating role of coping styles and the moderating role of psychological suzhi.

Objective:To explore the relationship between depressive symptoms and stressors among post-graduates and the role of coping styles and psychological suzhi between them.Methods:A total of 775 postgradu-ates were recruited.They were assessed with the Center for Epidemiological Studies Depression Scale(CES-D),Psychological Stressors Scale of Postgraduates(PSSP),Simplified Coping Style Questionnaire(SCSQ),and Col-lege Students Psychological Suzhi Brief Mental Health Version(CSPS-B-MH).Results:The detection rate of de-pression among postgraduates was 52.0％.Postgraduate stressors were positively associated with depression(β=0.47).Coping styles played a partial mediating role in the relationship between stressors and depression in postgrad-uates,with the mediation effect accounting for 24.76％of the total effect.Psychological suzhi was shown to moder-ate the effect of stressors on depression(β=-0.07)and positive coping on depression(β=-0.05).Conclusion:Postgraduate stressors could affect depression through the mediating role of coping styles and the moderating role of psychological suzhi.

This study analyzed the burden and trends in enteric infections in China from 1990 to 2021 from a One Health perspec-tive.Data on mortality associated with enteric infections were extracted from the 2021 Global Burden of Disease(GBD)database.The analysis focused on assessing the mortality rates of enteric infectious diseases attributed to various etiologies and risk factors,along with the age and sex distribution,from 1990 to 2021.Average annual percentage change(AAPC)was used to assess the total changes in disease burden.The age-standardized mortality rate of intestinal infections in China decreased from 9.642/100 000 in 1990 to 0.439/100 000 in 2021,with an AAPC of-57.103%(95%CI:-57.118%to-57.088%).In 2021,Rotavirus,Norovirus,and Crypto-sporidium were the top three etiologies contributing to disease burden,with mortality rates of 1.020/100 000,0.040/100 000 and 0.079/100 000,respectively.A significant variation in etiology distribution was observed across age groups:Rotavirus,Shigella,and Crypto-sporidium dominated among children under 5 years of age,whereas Cryptosporidium,Norovirus,and Clostridioides difficile were more prevalent in older populations.Risk factor analysis indicated that unsafe water sources and poor sanitation accounted for 73.394%of all enteric disease-related deaths.In conclusion,the burden of enteric infections in China markedly declined from 1990 to 2021,and sig-nificant variations in the etiological spectrum and disease burden were observed across age groups.The persistent effects of unsafe wa-ter sources and poor sanitation underscore the need for targeted interventions to further decrease the burden of these diseases.Our find-ings highlight the success of public health interventions in decreasing the burden of enteric infections in China,while emphasizing the need for targeted measures to address disparities in high-risk populations and improve environmental sanitation.

Objective:To explore if miR-133a is involved in the occurrence and development of hepatocellular carcinoma(HCC)via regulating G6PD.Methods:Bioinformatics analysis predicted the binding sites of miR-133a and G6PD;RT-PCR or western blot was used to assess the expres-sion of miR-133a and G6PD in HCC tissues and the adjacent normal tissues;CCK-8 and flow cy-tometry assays were performed to evaluate the effects of miR-133a/G6PD on cell proliferation,apop-tosis;Fluorescent reporter gene and western blot assays were used to assess the effect of miR-133a on G6PD expression.Results:miR-133a expression was decreased in HCC tissues while G6PD was increased(P0.01);Up-regulation of miR-133a significantly reduced G6PD expression(P＜0.01);up-reg-ulation of miR-133a inhibited cell growth and promoted cell apoptosis(P＜0.05),whereas these effects induced by miR-133a over-expression were all abolished when G6PD was up-regulated(P＜0.01).Conclusion:miR-133a represses the occurrence and development of HCC via targeting G6PD.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Aim To investigate the expression level of CBX4 in esophageal squamous cell carcinoma(ESCC)and the effect of CBX4 on ESCC proliferation and un-derlying molecular mechanisms.Methods The ex-pression of CBX4 in different cancers was analyzed in Pan-cancers.The expression level of CBX4 in ESCC was analyzed by t-test based on Gene Expression Omni-bus(GEO)data.The viability of CBX4-overex-pressed/knockdown ESCC cells was detected by MTT assay,colony formation assay and flow cytometry assay.Furthermore,the tumor volumn,tumor weight and Ki67 expression were measured by mouse xenograft assay and immunohistochemistry.The mRNA and protein ex-pression levels of apoptosis-related genes PARP、Bcl-2、Bax were determined by qRT-PCR and Western blot,respectively.In addition,the underlying molecular mechanism of CBX4 in ESCC was revealed by qRT-PCR and Western blot.Results CBX4 was upregulat-ed in various cancers.The expression level of CBX4 in ESCC was higher than that in normal tissues(P＜0.05)based on Gene Expression Omnibus(GEO)da-ta.Compared with the normal group,the proliferation of CBX4 knockdown ESCC cells was significantly in-hibited and the apoptosis was promoted(P＜0.05).Meanwhile,the mRNA and protein expression levels of cleaved PARP and Bax were upregulated while that of Bcl-2 was downregulated.In CBX4 overexpression group,tumor volume in vivo increased(P＜0.05).Immunohistochemical results also showed an increase in Ki67 expression.Furthermore,the results of RNA-seq,bioinformatics analysis and qRT-PCR experiments indicated that CBX4 probably regulated the prolifera-tion and apoptosis of ESCC through p38 MAPK signa-ling pathway.Conclusion CBX4 is highly expressed in ESCC and plays as an oncogene role,which might regulate cell proliferation through the p38 MAPK signa-ling pathway.