1.Spatial Heterogeneity and Risk Factors of Dental Caries in 12-Year-Old Children in Shanxi Province,China
Hou RUXIA ; Yang TINGTING ; Liu JIAJIA ; Chen HAO ; Kang WEN ; Li JUNMING ; Shi XIAOTONG ; Liang YI ; Liu JUNYU ; Zhao BIN ; Wang XIANGYU
Biomedical and Environmental Sciences 2024;37(10):1173-1183
Objective This study aimed to explore the spatial heterogeneity and risk factors for dental caries in 12-year-old children in Shanxi province,China. Methods The data encompassed 3,721 participants from the two most recent oral health surveys conducted across 16 districts in Shanxi Province in 2015 and 2018.Eighteen specific variables were analyzed to examine the interplay between socioeconomic factors,medical resources and environmental conditions.The Geo-detector model was employed to assess the impacts and interactions of these ecological factors. Results Socioeconomic factors(Q=0.30,P<0.05)exhibited a more substantial impact compared to environmental(Q=0.19,P<0.05)and medical resource factors(Q=0.25,P<0.05).Notably,the urban population percentage(UPP)demonstrated the most significant explanatory power for the spatial heterogeneity in caries prevalence,as denoted by its highest q-value(q=0.51,P<0.05).Additionally,the spatial distribution's heterogeneity of caries was significantly affected by SO2 concentration(q=0.39,P<0.05)and water fluoride levels(q=0.27,P<0.05)among environmental factors. Conclusion The prevalence of caries exhibited spatial heterogeneity,escalating from North to South in Shanxi Province,China,influenced by socioeconomic factors,medical resources,and environmental conditions to varying extents.
2.BMP7 overexpression lentiviral vector construction and its effect on calcification of mouse aortic smooth muscle cells
Shi-Lin FU ; Xue-Jiao YI ; Wen-Xu PAN ; Chun YIN ; Hua-Li KANG ; De-Hui QIAN
Journal of Regional Anatomy and Operative Surgery 2024;33(2):95-99
Objective To construct a lentiviral vector for overexpression of bone morphogenetic protein 7(BMP7)in mice,and the effect of BMP7 overexpression on the expression of Jagged1 in mouse aortic endothelial cells and the calcification of the co-cultured vascular smooth muscle cells(VSMCs)were analyzed.Methods According to the target gene information Mouse-BMP7(NM_007557.3)and plasmid information pLVX-zsGreen-C1,gene sequence synthesis was carried out to construct BMP7 overexpression lentivirus.The efficiency of BMP7 overexpression lentivirus infection was detected by qPCR;the expression of Jagged1 protein in aortic endothelial cells from infected mice was detected by Western blot.The endothelial cells with lentivirus overexpressing BMP7 were co-cultured with VSMCs,and the calcification of VSMCs was observed by alizarin red staining.Results BMP7 overexpression lentiviral vector was successfully constructed and transfected into aortic endothelial cells.qPCR test results showed that the expression level of BMP7 mRNA was significantly increased in the BMP7 overexpression group than that in the normal control group(P<0.01),while there was no significant difference in the expression of BMP7 mRNA between the empty vector control group and the normal control group(P>0.05).Western blot results showed that the expression level of Jagged1 protein in endothelial cells of mouse in the BMP7 overexpression group was significantly lower than that in the normal control group(P<0.01),while there was no significant difference in the expression level of Jagged1 protein in endothelial cells between the empty vector control group and the normal control group(P>0.05).The results of alizarin red staining showed that the calcification of VSMCs was significantly increased after co-cultured with endothelial cells infected with BMP7 lentivirus.Conclusion Mouse BMP7 overexpression lentiviral vector was successfully constructed,and overexpression of BMP7 can reduce the expression of Jagged1 in mouse aortic endothelial cells and promote the calcification of co-cultured VSMCs.
3.Artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures
Kang-En HAN ; Hong-Wei WANG ; Hong-Wen GU ; Yin HU ; Shi-Lei TANG ; Zhi-Hao ZHANG ; Hai-Long YU
Journal of Regional Anatomy and Operative Surgery 2024;33(7):579-583
Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.
4.Establishment and validation of a prediction model to evaluate the prolonged hospital stay after anterior cervical discectomy and fusion
Hong-Wen GU ; Hong-Wei WANG ; Shi-Lei TANG ; Kang-En HAN ; Zhi-Hao ZHANG ; Yin HU ; Hai-Long YU
Journal of Regional Anatomy and Operative Surgery 2024;33(7):604-609
Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.
5.Risk factors for surgical site infection after transforaminal lumbar interbody fusion in treatment of lumbar degenerative diseases
Kang-En HAN ; Hong-Wei WANG ; Hong-Wen GU ; Yin HU ; Shi-Lei TANG ; Zhi-Hao ZHANG ; Hai-Long YU
Journal of Regional Anatomy and Operative Surgery 2024;33(9):810-814
Objective To explore the risk factors for surgical site infection(SSI)after transforaminal lumbar interbody fusion(TLIF)for the treatment of lumbar degenerative diseases.Methods A total of 1 000 patients who underwent TLIF for lumbar degenerative diseases in our hospital were included and divided into the infection group(n=23)and the non-infection group(n=977)according to whether the surgical incision was infected.General data,surgical and laboratory indicators of patients were collected,and potential risk factors of SSI were screened by univariate analysis and multivariate regression analysis,a nomogram model was established,and its predictive efficiency was validated by the receive operating characteristic(ROC)curve.Results The incidence of SSI in patients after TLIF was 2.3%.The results of univariate analysis showed that age,operative time,intraoperative blood loss,preoperative C-reactive protein(CRP),smoking,and diabetes mellitus were the significant risk factors for the occurrence of SSI.Multivariate regression analysis showed that older age,longer operation time,more intraoperative blood loss,smoking and diabetes mellitus were the independent risk factors for postoperative SSI.ROC curve showed that the nomogram model established in this study has good predictive efficiency.Conclusion Older age,longer operation time,more intraoperative blood loss,smoking,and diabetes mellitus were independent risk factors for postoperative SSI.For patients with these high risk factors,corresponding intervention measures should be taken before operation to reduce the incidence of SSI.
6.Application of Clinical and Ultrasound-Based Model in Secondary Hyperparathyroidism
Jinmei MA ; Xinhui SHI ; Yanfei KANG ; Chunli CAO ; Wen LIU ; Jing CHENG ; Jun LI
Chinese Journal of Medical Imaging 2024;32(5):447-453
Purpose To explore the application value of clinical-ultrasound parameter model in secondary hyperparathyroidism(SHPT).Materials and Methods A total of 86 patients(134 lesions)with renal insufficiency who underwent maintenance hemodialysis in the First Affiliated Hospital of Shihezi University from October 2020 to August 2022 were included and divided into group 1 according to the level of parathyroid hormone(iPTH)(iPTH<300 pg/ml),group 2(iPTH 300-800 pg/ml)and group 3(iPTH≥800 pg/ml),all patients underwent gray-scale parathyroid ultrasound and acoustic palpation tissue quantitative imaging examinations.The characteristics of glandular gray-scale ultrasound and virtual touch tissue imaging quantification parameters between different groups,combined with relevant clinical indicators,established a clinical-ultrasound parameter model,used multiple linear regression to analyze the correlation between the model and iPTH,explored the independent risk factors of iPTH,and evaluated this model to evaluate SHPT the value of.Results There were significant differences in dialysis age,phosphorus,alkaline phosphatase,serum creatinine,corrected calcium and phosphorus product,lesion size,number,echo,shear wave velocity(SWV)max,SWVcen,and SWVmean among the three groups(F/x2/H=6.396-53.524,all P<0.05).Dialysis age,phosphorus,alkaline phosphatase,and SWVratio were independent influencing factors of iPTH level(β=0.514,0.422,0.226,-0.368,all P<0.005).The area under the curve,sensitivity,specificity and accuracy of the model for diagnosing SHPT and predicting surgical treatment with iPTH levels of 300 pg/ml and 800 pg/ml were 0.967,95.00%,100.00%,97.73%and 0.824,77.42%,71.43%and 90.00%,respectively.Conclusion Dialysis age,phosphorus,alkaline phosphatase and SWVratio are independent influencing factors of iPTH level,and the clinical-ultrasound parameter model is of great value in accurately assessing the severity of SHPT.
7.Eligibility of C-BIOPRED severe asthma cohort for type-2 biologic therapies.
Zhenan DENG ; Meiling JIN ; Changxing OU ; Wei JIANG ; Jianping ZHAO ; Xiaoxia LIU ; Shenghua SUN ; Huaping TANG ; Bei HE ; Shaoxi CAI ; Ping CHEN ; Penghui WU ; Yujing LIU ; Jian KANG ; Yunhui ZHANG ; Mao HUANG ; Jinfu XU ; Kewu HUANG ; Qiang LI ; Xiangyan ZHANG ; Xiuhua FU ; Changzheng WANG ; Huahao SHEN ; Lei ZHU ; Guochao SHI ; Zhongmin QIU ; Zhongguang WEN ; Xiaoyang WEI ; Wei GU ; Chunhua WEI ; Guangfa WANG ; Ping CHEN ; Lixin XIE ; Jiangtao LIN ; Yuling TANG ; Zhihai HAN ; Kian Fan CHUNG ; Qingling ZHANG ; Nanshan ZHONG
Chinese Medical Journal 2023;136(2):230-232
8.Epidemiological and Clinical Characteristics of Non-neonatal Tetanus Patients in Guangxi, China: An 11-year Retrospective Study (2011-2021).
Yi Wen KANG ; Guo Feng MAI ; Xiao Ling ZHU ; Shang Qin DENG ; Shi Xiong YANG ; Hong Li TENG ; Zong Xiang YUAN ; Chu Ye MO ; Jian Yan LIN ; Li YE ; Hua Min TANG
Biomedical and Environmental Sciences 2023;36(9):880-885
9.A multicenter epidemiological study of acute bacterial meningitis in children.
Cai Yun WANG ; Hong Mei XU ; Jiao TIAN ; Si Qi HONG ; Gang LIU ; Si Xuan WANG ; Feng GAO ; Jing LIU ; Fu Rong LIU ; Hui YU ; Xia WU ; Bi Quan CHEN ; Fang Fang SHEN ; Guo ZHENG ; Jie YU ; Min SHU ; Lu LIU ; Li Jun DU ; Pei LI ; Zhi Wei XU ; Meng Quan ZHU ; Li Su HUANG ; He Yu HUANG ; Hai Bo LI ; Yuan Yuan HUANG ; Dong WANG ; Fang WU ; Song Ting BAI ; Jing Jing TANG ; Qing Wen SHAN ; Lian Cheng LAN ; Chun Hui ZHU ; Yan XIONG ; Jian Mei TIAN ; Jia Hui WU ; Jian Hua HAO ; Hui Ya ZHAO ; Ai Wei LIN ; Shuang Shuang SONG ; Dao Jiong LIN ; Qiong Hua ZHOU ; Yu Ping GUO ; Jin Zhun WU ; Xiao Qing YANG ; Xin Hua ZHANG ; Ying GUO ; Qing CAO ; Li Juan LUO ; Zhong Bin TAO ; Wen Kai YANG ; Yong Kang ZHOU ; Yuan CHEN ; Li Jie FENG ; Guo Long ZHU ; Yan Hong ZHANG ; Ping XUE ; Xiao Qin LI ; Zheng Zhen TANG ; De Hui ZHANG ; Xue Wen SU ; Zheng Hai QU ; Ying ZHANG ; Shi Yong ZHAO ; Zheng Hong QI ; Lin PANG ; Cai Ying WANG ; Hui Ling DENG ; Xing Lou LIU ; Ying Hu CHEN ; Sainan SHU
Chinese Journal of Pediatrics 2022;60(10):1045-1053
Objective: To analyze the clinical epidemiological characteristics including composition of pathogens , clinical characteristics, and disease prognosis acute bacterial meningitis (ABM) in Chinese children. Methods: A retrospective analysis was performed on the clinical and laboratory data of 1 610 children <15 years of age with ABM in 33 tertiary hospitals in China from January 2019 to December 2020. Patients were divided into different groups according to age,<28 days group, 28 days to <3 months group, 3 months to <1 year group, 1-<5 years of age group, 5-<15 years of age group; etiology confirmed group and clinically diagnosed group according to etiology diagnosis. Non-numeric variables were analyzed with the Chi-square test or Fisher's exact test, while non-normal distrituction numeric variables were compared with nonparametric test. Results: Among 1 610 children with ABM, 955 were male and 650 were female (5 cases were not provided with gender information), and the age of onset was 1.5 (0.5, 5.5) months. There were 588 cases age from <28 days, 462 cases age from 28 days to <3 months, 302 cases age from 3 months to <1 year of age group, 156 cases in the 1-<5 years of age and 101 cases in the 5-<15 years of age. The detection rates were 38.8% (95/245) and 31.5% (70/222) of Escherichia coli and 27.8% (68/245) and 35.1% (78/222) of Streptococcus agalactiae in infants younger than 28 days of age and 28 days to 3 months of age; the detection rates of Streptococcus pneumonia, Escherichia coli, and Streptococcus agalactiae were 34.3% (61/178), 14.0% (25/178) and 13.5% (24/178) in the 3 months of age to <1 year of age group; the dominant pathogens were Streptococcus pneumoniae and the detection rate were 67.9% (74/109) and 44.4% (16/36) in the 1-<5 years of age and 5-<15 years of age . There were 9.7% (19/195) strains of Escherichia coli producing ultra-broad-spectrum β-lactamases. The positive rates of cerebrospinal fluid (CSF) culture and blood culture were 32.2% (515/1 598) and 25.0% (400/1 598), while 38.2% (126/330)and 25.3% (21/83) in CSF metagenomics next generation sequencing and Streptococcus pneumoniae antigen detection. There were 4.3% (32/790) cases of which CSF white blood cell counts were normal in etiology confirmed group. Among 1 610 children with ABM, main intracranial imaging complications were subdural effusion and (or) empyema in 349 cases (21.7%), hydrocephalus in 233 cases (14.5%), brain abscess in 178 cases (11.1%), and other cerebrovascular diseases, including encephalomalacia, cerebral infarction, and encephalatrophy, in 174 cases (10.8%). Among the 166 cases (10.3%) with unfavorable outcome, 32 cases (2.0%) died among whom 24 cases died before 1 year of age, and 37 cases (2.3%) had recurrence among whom 25 cases had recurrence within 3 weeks. The incidences of subdural effusion and (or) empyema, brain abscess and ependymitis in the etiology confirmed group were significantly higher than those in the clinically diagnosed group (26.2% (207/790) vs. 17.3% (142/820), 13.0% (103/790) vs. 9.1% (75/820), 4.6% (36/790) vs. 2.7% (22/820), χ2=18.71, 6.20, 4.07, all P<0.05), but there was no significant difference in the unfavorable outcomes, mortility, and recurrence between these 2 groups (all P>0.05). Conclusions: The onset age of ABM in children is usually within 1 year of age, especially <3 months. The common pathogens in infants <3 months of age are Escherichia coli and Streptococcus agalactiae, and the dominant pathogen in infant ≥3 months is Streptococcus pneumoniae. Subdural effusion and (or) empyema and hydrocephalus are common complications. ABM should not be excluded even if CSF white blood cell counts is within normal range. Standardized bacteriological examination should be paid more attention to increase the pathogenic detection rate. Non-culture CSF detection methods may facilitate the pathogenic diagnosis.
Adolescent
;
Brain Abscess
;
Child
;
Child, Preschool
;
Escherichia coli
;
Female
;
Humans
;
Hydrocephalus
;
Infant
;
Infant, Newborn
;
Male
;
Meningitis, Bacterial/epidemiology*
;
Retrospective Studies
;
Streptococcus agalactiae
;
Streptococcus pneumoniae
;
Subdural Effusion
;
beta-Lactamases
10.Stopping Transmission of COVID-19 in Public Facilities and Workplaces: Experience from China.
Jiao WANG ; Wen Jing YANG ; Song TANG ; Li Jun PAN ; Jin SHEN ; S Ji JOHN ; Xian Liang WANG ; Li LI ; Bo YING ; Kang Feng ZHAO ; Liu Bo ZHANG ; Lin WANG ; Xiao Ming SHI
Biomedical and Environmental Sciences 2022;35(3):259-262

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