Objective: To evaluate the incremental vaccine effectiveness (VE) of two dose of the mumps containing vaccine (MuCV) in chidren, so as to provide a basis for optimizing mumps immunization strategies. Methods: A 1∶2 frequency matched case-control study was conducted by using reported mumps cases in childcare centers or schools from Lu an, Hefei, Ma anshan and Huainan cities of Anhui Province from September 1, 2023 to June 30, 2024, as a case group(383 cases). And healthy children in the same classroom were selected as a control group(766 cases). The MuCV immunization histories of participants were collected to estimate the incremental VE of the second dose of MuCV against mumps. Group comparisons were performed using the Chi square test or t-test. For matched case-control pairs, the Cox regression model was employed to calculate the odds ratio (OR) with 95% confidence interval (CI) for two dose MuCV vaccination and to estimate the incremental vaccine effectiveness (VE). Results: There were no statistically significant differences between the case and control groups regarding gender, age, dosage of MuCV vaccination and the time interval since the last dose vaccination( χ 2/t=0.05, 0.20, 0.94, -0.02, P >0.05). The proportions of the case and control groups vaccinated with two doses of MuCV were 26.63% and 29.37%, respectively, and the overall incremental VE of the second dose of MuCV was 40.73% (95% CI=3.03%-63.77%, P <0.05). Subgroup analyses revealed that the incremental VE for children with a period of ≥1 year between the two doses of MuCV was 54.13% (95% CI=1.90%-78.56%, P <0.05), while for children with a period of <1 year, it was 30.63% (95% CI=-28.59%-62.58%, P >0.05). The incremental VE of the second dose of MuCV was 30.36% (95% CI=-25.95%-61.50%, P >0.05) in kindergarten children and 66.73% (95% CI=14.92%-86.99%, P <0.05) in elementary and secondary school students. The incremental VE was 28.78% (95% CI=-27.46%-60.21%, P >0.05) within five years of the last dose of MuCV vaccination and 66.07% (95% CI=-41.56%-91.87%, P >0.05) for vaccinations administered beyond five years. Conclusions The second dose of MuCV may offer additional protection for children; however, extending the interval between two dose of MuCV (<1 year) has shown limited incremental protective effects. Therefore, it is crucial to consider optimizing current immunization strategies for mumps.

Objective To explore the preoperative non-invasive prediction of early postoperative glioma recurrence using multi-modal conventional MRI radiomics.Methods A retrospective analysis of the clinical and MRI data of 83 glioma patients who met the inclusion criteria was conducted.The Kruskal-Wallis test was used to compare clinical factors between recurrent and non-recurrent groups.The automated segmentation of the entire tumor lesion for glioma patients was accomplished with VB-Net algorithm,a deep learning approach developed by United Imaging Healthcare;and the extraction of radiomics features from preoperative T1CE and T2WI images was carried out on URP platform.The optimal feature combination was determined using the maximum relevance and minimum redundancy and least absolute shrinkage and selection operator methods.Logistic regression and five-fold cross-validation were employed to analyze radiomics features and construct 4 prediction models,namely T2WI model,T1CE model,T2WI+T1CE model,and imaging-clinical fusion model.The diagnostic performances of these models were evaluated and compared using the area under the receiver operating characteristic curve(AUC)and the Delong test.In addition,the model sensitivity and specificity were calculated.Results Postoperatively,there were 40 recurrent cases and 43 non-recurrent cases.The clinical factors such as glioma grade showed statistical significance between two groups(P<0.05),while gender and age did not show significant statistical differences(P>0.05).For the single-sequence radiomics models,T1CE model(AUC:0.804)outperformed T2WI model(AUC:0.702).The multi-modal combined model exhibited a higher AUC than the single-sequence prediction models,with an AUC of 0.849,a sensitivity of 72.5%,and a specificity of 79.1%.The imaging-clinical fusion model whose predictive efficiency was close to that of multi-modal combined model(P=0.303)also performed well in forecasting postoperative glioma recurrence,with an AUC of 0.839,a sensitivity of 72.5%,and a specificity of 79.1%.Conclusion The multi-modal conventional MRI radiomics model can better predict early postoperative glioma recurrence.The imaging-clinical fusion model that includes glioma grade does not have the diagnostic performance superior to that of radiomics model.

Objective To investigate the value of predicting microsatellite instability(MSI)status in endometrial cancer based on whole-tumor apparent diffusion coefficient(ADC)histogram.Methods The data of 131 endometrial cancer patients who underwent preoperative MRI examination and were confirmed by pathology were retrospectively analyzed.According to the pathological immu-nohistochemical results,they were divided into microsatellite stability(MSS)group(103 cases)and MSI group(28 cases).The whole-tumor volume of interest(VOI)was outlined using ITK-SNAP software,and ADC histogram analysis was performed using uAI Research Portal software.The t-test or Mann-Whitney U-test were used to compare the differences between the two groups,and multifactorial logistic regression analysis was used to screen independent predictors for the above parameters with differences.The area under the curve(AUC),sensitivity and specificity were calculated using the receiver operating characteristic(ROC)curve.Results The ADC histogram parameters that were statistically significant between groups were ADC10th,ADC90th,ADCmaximum,ADCmedian,ADCmean,ADCrange,ADCinterquartile range,ADCuniformity,ADCvariance,ADCenergy,ADCentropy,ADCtotal energy,ADCroot mean square,ADCmean absolute deviation,ADCrobust mean absolute deviation,all the above parameters were significantly smaller in the MSI group than in the MSS group.Further multifactorial logistic regression analysis results showed that ADCmedian[odds ratio(OR)=1.019,P=0.020]and ADCroot mean square(OR=0.977,P=0.005)were independent predictors of the MSI status in endometrial cancer.The results of ROC curve showed that the AUC of ADCmedian and ADCroot mean square for predicting MSI status were 0.699 and 0.731,respectively,and the AUC of combining the two parameters to predict MSI status was 0.760,with a sensitivity of 57.14%and a specificity of 86.41%.Conclusion The parameters of ADCmedian and ADCroot mean square based on whole-tumor ADC histogram can be used to predict the MSI status of endometrial cancer,and the combined use of these two parameters helps to improve the efficacy of predicting MSI.

Objective To explore the preoperative non-invasive prediction of early postoperative glioma recurrence using multi-modal conventional MRI radiomics.Methods A retrospective analysis of the clinical and MRI data of 83 glioma patients who met the inclusion criteria was conducted.The Kruskal-Wallis test was used to compare clinical factors between recurrent and non-recurrent groups.The automated segmentation of the entire tumor lesion for glioma patients was accomplished with VB-Net algorithm,a deep learning approach developed by United Imaging Healthcare;and the extraction of radiomics features from preoperative T1CE and T2WI images was carried out on URP platform.The optimal feature combination was determined using the maximum relevance and minimum redundancy and least absolute shrinkage and selection operator methods.Logistic regression and five-fold cross-validation were employed to analyze radiomics features and construct 4 prediction models,namely T2WI model,T1CE model,T2WI+T1CE model,and imaging-clinical fusion model.The diagnostic performances of these models were evaluated and compared using the area under the receiver operating characteristic curve(AUC)and the Delong test.In addition,the model sensitivity and specificity were calculated.Results Postoperatively,there were 40 recurrent cases and 43 non-recurrent cases.The clinical factors such as glioma grade showed statistical significance between two groups(P<0.05),while gender and age did not show significant statistical differences(P>0.05).For the single-sequence radiomics models,T1CE model(AUC:0.804)outperformed T2WI model(AUC:0.702).The multi-modal combined model exhibited a higher AUC than the single-sequence prediction models,with an AUC of 0.849,a sensitivity of 72.5%,and a specificity of 79.1%.The imaging-clinical fusion model whose predictive efficiency was close to that of multi-modal combined model(P=0.303)also performed well in forecasting postoperative glioma recurrence,with an AUC of 0.839,a sensitivity of 72.5%,and a specificity of 79.1%.Conclusion The multi-modal conventional MRI radiomics model can better predict early postoperative glioma recurrence.The imaging-clinical fusion model that includes glioma grade does not have the diagnostic performance superior to that of radiomics model.

Objective To investigate the value of predicting microsatellite instability(MSI)status in endometrial cancer based on whole-tumor apparent diffusion coefficient(ADC)histogram.Methods The data of 131 endometrial cancer patients who underwent preoperative MRI examination and were confirmed by pathology were retrospectively analyzed.According to the pathological immu-nohistochemical results,they were divided into microsatellite stability(MSS)group(103 cases)and MSI group(28 cases).The whole-tumor volume of interest(VOI)was outlined using ITK-SNAP software,and ADC histogram analysis was performed using uAI Research Portal software.The t-test or Mann-Whitney U-test were used to compare the differences between the two groups,and multifactorial logistic regression analysis was used to screen independent predictors for the above parameters with differences.The area under the curve(AUC),sensitivity and specificity were calculated using the receiver operating characteristic(ROC)curve.Results The ADC histogram parameters that were statistically significant between groups were ADC10th,ADC90th,ADCmaximum,ADCmedian,ADCmean,ADCrange,ADCinterquartile range,ADCuniformity,ADCvariance,ADCenergy,ADCentropy,ADCtotal energy,ADCroot mean square,ADCmean absolute deviation,ADCrobust mean absolute deviation,all the above parameters were significantly smaller in the MSI group than in the MSS group.Further multifactorial logistic regression analysis results showed that ADCmedian[odds ratio(OR)=1.019,P=0.020]and ADCroot mean square(OR=0.977,P=0.005)were independent predictors of the MSI status in endometrial cancer.The results of ROC curve showed that the AUC of ADCmedian and ADCroot mean square for predicting MSI status were 0.699 and 0.731,respectively,and the AUC of combining the two parameters to predict MSI status was 0.760,with a sensitivity of 57.14%and a specificity of 86.41%.Conclusion The parameters of ADCmedian and ADCroot mean square based on whole-tumor ADC histogram can be used to predict the MSI status of endometrial cancer,and the combined use of these two parameters helps to improve the efficacy of predicting MSI.

Objective To investigate the value of multimodal MRI radiomics in predicting muscle-invasive bladder cancer.Methods A total of 178 patients with pathology diagnosis of bladder cancer were retrospectively collected,including 31 cases of muscle invasive bladder cancer(MIBC)and 147 cases of non-muscle invasive bladder cancer(NMIBC).Patients were randomly divided into training group and testing group at a ratio of 7︰3.The range of bladder tumors in T2WI,diffusion weighted imaging(DWI)and apparent diffusion coefficient(ADC)images were segmented as volume of interest(VOI)by using ITK-SNAP software.Radiomics features were extracted through A.K software.The optimal radiomics features were obtained through radiomics algorithm and least absolute shrinkage and selection operator(LASSO)method.Finally,the logistic regression analysis method and random forest model method were used to construct prediction models.The performance of prediction models was evaluated by the receiver operating characteristic(ROC)curve.Results This study constructed four groups of models containing T2WI prediction model,DWI prediction model,ADC prediction model,and T2WI+DWI+ADC prediction model.The area under the curve(AUC)of T2WI,DWI,and ADC prediction models for identifying MIBC and NMIBC were separately 0.920,0.914,and 0.954 in the training group while those were respectively 0.881,0.773,and 0.871 in the testing group.There was no statistical significance between T2WI,DWI,and ADC prediction models.In training and testing groups,the AUC of T2WI+DWI+ADC prediction model were respectively 0.959 and 0.909,which were higher than the single sequence prediction model.The sensitivity and specificity of the training group were 0.905 and 0.853 and the sensitivity and specificity of the testing group were 0.778 and 0.795.Conclusion MRI radiomics prediction model can effectively differentiate MIBC and NMIBC.The T2WI+DWI+ADC prediction model shows better prediction efficiency.

Objective:To investigate the effectiveness of the modified Bikini approach in the fixation of acetabular fracture with an integrated wing-shaped anatomical locking plate.Methods:A retrospective study was conducted to analyze the data of 54 patients with acetabular fracture who had been treated at Department of Trauma Orthopedics, Orthopedic Medical Center, The Third Hospital Affiliated to Southern Medical University from May 2017 to June 2021. The patients were divided into 2 groups based on different surgical approaches: an observation group [26 cases, 6 males, 20 females; aged 40.0 (29.8, 46.8) years] treated with fixation with an integrated wing-shaped anatomical locking plate through the modified Bikini approach, and a control group [28 cases, 10 males, 18 females; aged 34.5 (24.0, 43.5) years] treated with fixation with an integrated wing-shaped anatomical locking plate through the lateral-rectus approach. The incision length, operation time, intraoperative bleeding, length of hospital stay, quality of postoperative fracture reduction, visual analog scale (VAS) for pain, hip function, Vancouver Scar Scale (VSS) and Patient and Observer Scar Assessment Scale (POSAS) were compared between the 2 groups.Results:The differences in the preoperative general data between the 2 groups were not statistically significant, indicating comparability ( P>0.05). There were no statistically significant differences between the 2 groups either in terms of incision length, operation time, intraoperative bleeding, or hospital stay ( P>0.05). The 2 groups were not significantly different in the excellent/good rate of fracture reduction [100.0% (26/26) versus 92.9% (26/28)], VAS at 1 month postoperation [2.0(1.0, 3.0) versus 2.0(1.0, 3.0)], or the modified Merle d'Aubigné and Postel hip score at 12 months postoperation [13.5(12.3, 14.8) versus. 14.0(13.0, 15.0)] ( P>0.05). However, the VSS [4.50(4.00, 6.00)] and POSAS (29.85±10.05) at 12 months postoperation in the observation group were significantly lower than those in the control group [6.50(5.00, 8.25) and 37.11±11.75] ( P<0.05). Conclusion:In the fixation of acetabular fracture with an integrated wing-shaped anatomical locking plate, the modified Bikini approach can not only achieve as fine early clinical efficacy as the lateral-rectus approach, but also demonstrate the aesthetic advantages of smaller incision scar and more hidden incision.

Complex brain diseases seriously endanger human health, and early diagnostic biomarkers and effective treatments are currently lacking. Due to ethical constraints on human research, establishing monkey models is crucial to address these issues. With the rapid development of technology, transgenic monkey models of a range of brain diseases, especially autism spectrum disorder (ASD), have been successfully established. However, to establish practical and effective brain disease models and subsequently apply them to disease mechanism and treatment studies, there is still a lack of a standard tool, i.e., a system for collecting and analyzing the daily behaviors of brain disease model monkeys. Therefore, with the goal of undertaking a comprehensive and quantitative study of behavioral phenotypes, we established a standard daily behavior collection and analysis system, including behavioral data collection protocols and a monkey daily behavior ethogram (MDBE) for rhesus and cynomolgus monkeys, which are the most commonly used non-human primates in model construction. Then, we used ASD as an application example after referring to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR), which is widely used in clinical disease diagnosis to obtain ASD core clinical symptoms. We then established a sub-ethogram (ASD monkey core behavior ethogram (MCBE-ASD)) specifically for quantitative assessment of the core clinical symptoms of an ASD monkey model based on MDBE. Subsequently, we demonstrated the high reproducibility of the system.
Animals ; Autism Spectrum Disorder ; Macaca mulatta ; Disease Models, Animal ; Behavior, Animal ; Macaca fascicularis ; Male ; Humans

Objective:To explore the relationship between bullying and depressive symptoms in college students,the mediating role of mobile phone addiction and the moderating role of gender.Methods:Totally 1 499 college students in Nantong City were selected to evaluate bullying experience,mobile phone addiction tendency and depressive symptoms with the Revised Adolescent Peer Relations Instrument-Bully and Target(RAPRI-T),Smart-phone Addiction Scale-Short Version(SAS-SV),Patient Health Questionnaire Depression 9-item(PHQ-9).SPSS macro program PROCESS 3.2 was used to examine the mediating role of mobile phone addiction and the modera-ting role of gender.Results:Different forms of bullying,traditional verbal bullying had the highest detection rate.There were positive correlations among bullying and the scores of SAS-SV and PHQ-9(r=0.17-0.42,Ps＜0.001).In the relationship between bullying scores and PHQ-9 scores,SAS-SV scores played a partial mediating role,and the mediating effect accounts for 26.70％of the total effect.The interaction terms between bullying and genders had statistical significance with PHQ-9 scores(β=0.09,P＜0.001),as the bullying scores increased,the PHQ-9 scores were higher in girls than in boys.Conclusion:Mobile phone addiction plays a partial mediating role in the association between bullying and depressive symptomsin college students,and the association between bull-ying and depressive symptoms is moderated by gender factors.

The incidence of osteoporotic thoracolumbar vertebral fracture (OTLVF) in the elderly is gradually increasing. The kyphotic deformity caused by various factors has become an important characteristic of OTLVF and has received increasing attention. Its clinical manifestations include pain, delayed nerve damage, sagittal imbalance, etc. Currently, the definition and diagnosis of OTLVF with kyphotic deformity in the elderly are still unclear. Although there are many treatment options, they are controversial. Existing guidelines or consensuses pay little attention to this type of fracture with kyphotic deformity. To this end, the Lumbar Education Working Group of the Spine Branch of the Chinese Medicine Education Association and Editorial Committee of Chinese Journal of Trauma organized the experts in the relevant fields to jointly develop Clinical guidelines for the diagnosis and treatment of osteoporotic thoracolumbar vertebral fractures with kyphotic deformity in the elderly ( version 2024), based on evidence-based medical advancements and the principles of scientificity, practicality, and advanced nature, which provided 18 recommendations to standardize the clinical diagnosis and treatment.