ObjectiveTo investigate the protective effect of α-ketoglutarate （α-KG） on hepatic lipid deposition in offspring caused by arsenic exposure during pregnancy. Methods8-week-old institute of cancer research （ICR） mice were mated in a ratio of 2∶1 between females and males， and the detection of vaginal plugs confirmed pregnant. A total of 32 pregnant mice were randomly divided into four groups： control group， arsenic group， α-KG group， arsenic+α-KG group. On gestational day 0-16 （GD0-GD16）， the arsenic and arsenic+α-KG groups were exposed to sodium arsenite （NaAsO₂ ，15 mg/L） in drinking water everyday， and the α-KG and arsenic+α-KG groups were gavaged with α-KG （2 g/kg） everyday. On GD16， pregnant mice were euthanized to collect fetal liver， and fetal body weight and crown-rump length were measured. Gene expression differences between the control group and the arsenic group were analyzed by transcriptome. The total triglycerides （TGs） and subtypes in fetal liver were detected by liquid chromatography tandem mass spectrometry （LC-MS/MS）. Oil red O staining was used to observe the histopathological changes in the liver. Quantitative polymerase chain reaction （qPCR） was used to detect the expression level of genes related to lipid synthesis， transport， and degradation， and phosphatidylinositol 3' -kinase/ protein kinase B （PI3K/AKT） in the liver of fetus. ResultsTranscriptomics analysis showed that 2 144 genes were downregulated and 1 675 genes were upregulated in the arsenic exposed fetal liver； body weight and crown-rump length were reduced （P_TuKey<0.05）； the level of hepatic TGs was elevated in arsenic group （P_TuKey<0.05）； oil-red O staining showed a significant increase in lipid droplets in arsenic group （P_TuKey<0.01）； the expression of lipid synthesis-related genes were significantly upregulated （P_TuKey<0.05）； the expression of β-oxidation-related genes and lipid degradation-related genes were downregulated （P_TuKey<0.05）； the expression of PI3K， AKT decreased（P_TuKey<0.05）. Compared with the arsenic group， the body weight and crown-rump length of fetus increased in the arsenic+α-KG group （P_TuKey<0.05）； the level of hepatic TGs decreased in the arsenic+α-KG group （P_TuKey<0.05）； oil red O staining showed lipid droplets significantly decreased （P_TuKey<0.01）； the expression of lipid synthesis-related genes were downregulated （P_TuKey<0.05）， the expression of β-oxidation-related genes and lipid degradation-related genes were upregulated （P_TuKey<0.05）； the expression levels of PI3K and AKT increased （P_TuKey<0.05）. Conclusionα-KG alleviated hepatic lipid deposition in offspring exposed to arsenic during pregnancy through activating PI3K/AKT signaling pathway.

Objective:To explore the relationship between autistic trait and pain empathy among college students, as well as the mediating role of personal pain perception.Methods:From October to December 2023, a cross-sectional survey was conducted among 1 195 college students using the autism spectrum quotient, pain sensitivity questionnaire, fear of pain questionnaire, pain catastrophizing scale and empathy for pain scale.SPSS 27.0 software was used for descriptive statistics and correlation analysis.A structural equation model was constructed using Mplus 8.3 to examine the mediating effect of personal pain perception, which was composed of pain sensitivity, fear and catastrophizing cognition.Results:Autistic trait(22.00(18.00, 26.00))was significantly positively correlated with pain sensitivity (55.00(43.00, 70.00)), fair of pain (69.00(60.00, 78.00)), and pain catastrophizing cognition (16.00(8.00, 23.00)) ( r=0.112, 0.154, 0.204, all P<0.001).Autistic trait was also significantly positively correlated with affective distress(62.00(46.00, 80.00), r=0.162, P<0.001) and vicarious pain (14.00(8.00, 20.00), r=0.096, P<0.001) of pain empathy.Pain sensitivity, fear of pain and pain catastrophizing cognition were significantly positively correlated with affective distress( r=0.244, 0.332, 0.375, all P<0.001) and vicarious pain ( r=0.210, 0.232, 0.285, all P<0.001) of pain empathy.The effects of autistic trait on affective distress and vicarious pain dimensions of pain empathy were fully mediated by personal pain perception, with the mediating effects of 0.115( P<0.001, 95% CI=0.073-0.165) and 0.085( P<0.001, 95% CI=0.053-0.124). Conclusions:The autistic trait of college students can predict the affective distress and vicarious pain of pain empathy indirectly through personal pain perception.

Objective To analyze the prevalence of dengue fever in Guangzhou based on circuit-qi theory.Methods Data on dengue fever cases in Guangzhou from January 21,2012,to January 19,2024 were collected.And then the incidence of dengue fever was analyzed under the circuit-qi conditions of dominant qi,guest qi,celestial qi,joining of guest qi with dominant qi,and dissimilation of circuit and qi.Results Higher incidence of dengue fever in Guangzhou was presented under the circuit-qi conditions of the fifth qi of the dominant qi in each year,shaoyang minister fire of the guest qi,shaoyin monarch fire of the celestial qi,guest qi restricting dominant qi in the joining of guest qi with dominant qi,shaoyang minister fire(guest qi)joining with yangming dry-metal(dominant qi)in the pattern of guest qi restricting dominant qi.The outbreak of dengue fever under the circuit-qi conditions of dissimilation of circuit and qi showed no statistically significant difference.Conclusion Over the 12-year period from 2012 to 2024,the prevalence of dengue fever in Guangzhou exhibited a 4-5-year cyclical pattern,often with consecutive outbreaks over two years.The prevalence of dengue fever in Guangzhou is associated with the factors of dampness and heat in the theory of five circuits and six qi,while has less relation with dissimilation of circuit and qi.

Objective:To explore the relationship between autistic trait and pain empathy among college students, as well as the mediating role of personal pain perception.Methods:From October to December 2023, a cross-sectional survey was conducted among 1 195 college students using the autism spectrum quotient, pain sensitivity questionnaire, fear of pain questionnaire, pain catastrophizing scale and empathy for pain scale.SPSS 27.0 software was used for descriptive statistics and correlation analysis.A structural equation model was constructed using Mplus 8.3 to examine the mediating effect of personal pain perception, which was composed of pain sensitivity, fear and catastrophizing cognition.Results:Autistic trait(22.00(18.00, 26.00))was significantly positively correlated with pain sensitivity (55.00(43.00, 70.00)), fair of pain (69.00(60.00, 78.00)), and pain catastrophizing cognition (16.00(8.00, 23.00)) ( r=0.112, 0.154, 0.204, all P<0.001).Autistic trait was also significantly positively correlated with affective distress(62.00(46.00, 80.00), r=0.162, P<0.001) and vicarious pain (14.00(8.00, 20.00), r=0.096, P<0.001) of pain empathy.Pain sensitivity, fear of pain and pain catastrophizing cognition were significantly positively correlated with affective distress( r=0.244, 0.332, 0.375, all P<0.001) and vicarious pain ( r=0.210, 0.232, 0.285, all P<0.001) of pain empathy.The effects of autistic trait on affective distress and vicarious pain dimensions of pain empathy were fully mediated by personal pain perception, with the mediating effects of 0.115( P<0.001, 95% CI=0.073-0.165) and 0.085( P<0.001, 95% CI=0.053-0.124). Conclusions:The autistic trait of college students can predict the affective distress and vicarious pain of pain empathy indirectly through personal pain perception.

Objective To establish a machine learning radiomics model that can accurately predict MRI enhancement patterns of glioma based on T2 fluid attenuated inversion recovery(T2-FLAIR)images for optimizing the workflow of magnetic resonance imaging(MRI)examinations of glioma patients.Methods We retrospectively collected preoperative MR T2-FLAIR images from 385 patients with pathologically confirmed glioma,who were divided into enhancing and non-enhancing groups according to the enhancement pattern.Predictive radiomics models were established using Gaussian Process,Linear Regression,Linear Regression-Least absolute shrinkage and selection operator,Support Vector Machine,Linear Discriminant Analysis or Naive Bayes as the classifiers in the training cohort(n=201)and tested both in the internal(n=85)and external validation cohorts(n=99).The receiver-operating characteristic curve was used to assess the predictive performance of the models.Results The predictive model constructed based on 15 radiomics features using Gaussian Process as the classifier had the best predictive performance in both the training cohort and the internal validation cohort,with areas under the curve(AUC)of 0.88(95%CI:0.81-0.94)and 0.80(95%CI:0.71-0.88),respectively.In the external validation cohort,the model showed an AUC of 0.81(95%CI:0.71-0.90)with sensitivity,specificity,positive predictive value and negative predictive value of 0.98,0.61,0.76 and 0.96,respectively.Conclusion The T2-FLAIR-based machine learning radiomics model can accurately predict the enhancement pattern of gliomas on MRI.

BackgroundCompared with absenteeism， health-related productivity loss has a long-lasting negative effect， and poses a greater harm and loss. The health-related productivity loss is mediated by self-efficacy， and perceived social support has been shown to have an impact on health-related productivity loss， whereas the interaction mechanism among the three remains unclear. ObjectiveTo investigate the status of perceived social support， occupational coping self-efficacy and health-related productivity loss among ICU nurses， and to test the mediation role of perceived social support in the relationship between occupational coping self-efficacy and health-related productivity loss. MethodsFrom September to November， 2021， purposive sampling technique was adopted to select 468 ICU nurses in 8 tertiary hospitals in Sichuan Province. Subjects were assessed using self-made general information questionnaire， Perceived Social Support Scale （PSSS）， Occupational Coping Self Efficacy Scale for Nurses （OCSE-N） and Stanford Presenteeism Scale-6 （SPS-6）. Pearson correlation analysis was used to examine the correlation among variables. Amos 24.0 was utilized to test the mediation role of perceived social support in the relationship between occupational coping self-efficacy and health-related productivity loss. ResultsA total of 415 ICU nurses completed the valid questionnaire survey. ICU nurses scored （63.13±11.62） on PSSS， （22.24±6.15） on OCSE-N， and （16.83±4.24） on SPS-6. Health-related productivity loss was detected in 279 ICU nurses （67.23%）. Correlation analysis denoted that PSSS total score was positively correlated with OCSE-N total score （r=0.348， P<0.05）， and negatively correlated with SPS-6 total score （r=-0.274， P<0.05）. OCSE-N total score was negatively correlated with SPS-6 total score （r=-0.421， P<0.05）. The direct effect value of occupational coping self-efficacy on health-related productivity loss was -0.401， and perceived social support showed a mediation role in the relationship between occupational coping self-efficacy and health-related productivity loss （the indirect effect value was -0.052， accounting for 11.48% of the total effect）. ConclusionThe occupational coping self-efficacy of ICU nurses may affect the health-related productivity loss through the action path of perceived social support.［Funded by Scientific Research Project of Sichuan Provincial Health Commission （number， 19PJ042）］

Objective To establish a machine learning radiomics model that can accurately predict MRI enhancement patterns of glioma based on T2 fluid attenuated inversion recovery(T2-FLAIR)images for optimizing the workflow of magnetic resonance imaging(MRI)examinations of glioma patients.Methods We retrospectively collected preoperative MR T2-FLAIR images from 385 patients with pathologically confirmed glioma,who were divided into enhancing and non-enhancing groups according to the enhancement pattern.Predictive radiomics models were established using Gaussian Process,Linear Regression,Linear Regression-Least absolute shrinkage and selection operator,Support Vector Machine,Linear Discriminant Analysis or Naive Bayes as the classifiers in the training cohort(n=201)and tested both in the internal(n=85)and external validation cohorts(n=99).The receiver-operating characteristic curve was used to assess the predictive performance of the models.Results The predictive model constructed based on 15 radiomics features using Gaussian Process as the classifier had the best predictive performance in both the training cohort and the internal validation cohort,with areas under the curve(AUC)of 0.88(95%CI:0.81-0.94)and 0.80(95%CI:0.71-0.88),respectively.In the external validation cohort,the model showed an AUC of 0.81(95%CI:0.71-0.90)with sensitivity,specificity,positive predictive value and negative predictive value of 0.98,0.61,0.76 and 0.96,respectively.Conclusion The T2-FLAIR-based machine learning radiomics model can accurately predict the enhancement pattern of gliomas on MRI.

The effect of Radix isatidis polysaccharide(IRPS)on TLR3/TRIF innate immune path-way and type Ⅰ interferon secretion in 3D4/21/CD163 cells infected by porcine reproductive and re-spiratory syndrome virus(PRRSV)was tested by Western blot and ELISA;moreover,the effect of IRPS on the immunosuppression infected by PRRSV was further verified with the TLR3 agonist poly(I∶C).The results showed that the protein levels of TLR3,TRIF,IRF3,IRF7 and type Ⅰ in-terferon secretion were significantly decreased at 18,24 h of PRRSV infection,while IRPS signifi-cantly inhibited this process;poly(I∶C)alleviated the protein levels of TRIF,IRF3 and IRF7 as well as the phosphorylation levels of IRF3 and IRF7 infected by PRRSV;at the same time,IRPS is synergistic with poly(I∶C).The results indicate that IRPS is able to alleviate immunosuppression caused by PRRSV infection via the TLR3/TRIF pathway.

Objective To explore the relationship between androgen level and adverse pregnancy outcome of pregnant women at advanced maternal age.Methods A total of 192 pregnant women who were admitted to Changzhou Maternal and Child Health Care Hospital for delivery from May to October 2022 were selected as the study objects.According to guidelines for diagnosis and treatment of hypertensive disorder complicating pregnancy and maternal age,the study objects were divided into simple pregnant women at advanced maternal age group,pregnant women at advanced maternal age complicated with hypertensive disorder complicating pregnancy,healthy control group and age-appropriate pregnant women complicated with hypertensive disorder complicating pregnancy group.Serum levels of five androgens[total testosterone(TT),sex hormone binding globulin(SHBG),free testosterone index(FTI),dehydroepiandrosterone sulfate(DHEAS)and androstendi-one(A2)]in each group were detected by chemiluminescence method.Results Compared with the healthy control group,TT,A2,FTI were significantly increased and SHBG was significantly decreased in the age-ap-propriate pregnant women complicated with hypertensive disorder complicating pregnancy group,the level of DHEAS was decreased in the simple pregnant women at advanced maternal age group,and the differences were statistically significant(P＜0.05).Pearson correlation analysis showed that TT was negatively correla-ted with age(P＜0.05),positively correlated with systolic blood pressure,diastolic blood pressure and body mass index(P＜0.05),and had no correlation with offspring sex and offspring weight(P＞0.05).Multivari-ate Logistic regression analysis showed that TT and body mass index were independent risk factors for hyper-tensive disorder complicating pregnancy in pregnant women(P＜0.05).Conclusion The level of androgen in pregnant women at advanced maternal age is related to the occurrence of hypertensive disorder complicating pregnancy.

Objective:To evaluate the predictive value of hematological inflammatory markers such as preoperative monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR) and several tumor-related factors in differentiating malignant and benign primary retroperitoneal tumors (PRTs) .Methods:This study retrospectively collected the data of 159 pathologic confirmed PRTs patients who underwent surgery in the First Affiliated Hospital of Wenzhou Medical University and Taizhou Municipal Hospital between Dec. 2009 and Aug. 2020. Univariate analysis of clinic data was performed to identify the differences between the benign and malignant PRTs. Logistic regression analysis was used to determine the independent predictive parameters for malignant PRTs.Results:Among the 159 patients with PRTs, 80 were malignant, 68 were benign, and 11 were borderline. Contrast with benign and borderline tumor, univariate analysis demonstrated that tumor size, preoperative neutrophil count, platelet count, albumin level, MLR, NLR and PLR exhibited significant differences in malignant tumor (all P<0.05). PLR (HR=1.025, P=0.020) and tumor size (HR=1.085, P=0.006) were independent risk factors for predicting malignant PRTs in the multivariate logistic analyses. According to the ROC curve, the optimal cutoff value of tumor size and PLR for predicting malignant PRTs were 194.85 (sensitivity 38.7%, specificity 93.5%), 8.75 cm (sensitivity 69.3%, specificity 72.7%), respectively. Conclusions:Preoperative PLR is useful in differentiating malignant and benign PRTs and it is an independent risk parameter for malignant PRTs. Preoperative PLR could be considered as a new significant predictor for malignant PRTs.