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 explore the comparative study of constructing prediction models for muscle invasive of bladder cancer based on different machine learning algorithms combined with MRI radiomic.Methods A total of 187 bladder cancer patients who underwent MRI examination and were confirmed by pathology were retrospectively selected.Patients were randomly divided into a training set and a test set in a 7∶3 ratio.The patients were divided into muscle invasive bladder cancer(MIBC)group and non-muscle invasive bladder cancer(NMIBC)group according to the surgical pathology results.Tumor volume of interest(VOI)was outlined on the images of T2 WI,diffusion weighted imaging(DWI),and apparent diffusion coefficient(ADC),and the radiomic features were extracted by A.K software,and dimensionality reduction was performed using the maximum relevance minimum redundancy(mRMR)algorithm combined with least absolute shrinkage and selection operator(LASSO).Six machine learning algorithms,including K-nearest neighbor(KNN),decision tree(DT),support vector machine(SVM),logistic regression(LR),random forest(RF),and explainable boosting machine(EBM)were used to construct the radiomic model and calculate the corresponding area under the curve(AUC),accuracy,sensitivity,and specificity,respectively.Results Six machine learning algorithms,including KNN,DT,SVM,LR,RF,and EBM were used to construct the radiomic model,and the AUC values for predicting MIBC in the training set were 0.863,0.838,0.853,0.866,0.977,0.997,and in the test set were 0.748,0.833,0.860,0.868,0.870,0.900.Among them,the MRI radiomic model constructed based on EBM had the highest predictive efficacy for MIBC,with AUC values,accuracy,sensitivity and specificity of 0.997,0.977,0.957 and 0.981 in the training set,and 0.900,0.877,0.800,and 0.894 in the test set,respectively.Conclusion Multiple machine learning algorithms combined with MRI radiomic to construct models have good predictive efficacy for MIBC,and the model constructed based on EBM shows the highest predictive value.

Objective To investigate the diagnostic efficiency of patients with human epidermal growth factor receptor-2(HER-2)over expressed breast cancer via combining the dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)perfusion parameters,apparent diffusion coefficient(ADC)value and clinical feature model.Methods A total of 197 breast cancer patients who underwent DCE-MRI and diffusion weighted imaging(DWI)scans were analyzed retrospectively,including 47 breast cancer patients with HER-2 over expressed and 150 breast cancer patients with non-HER-2 over expressed.The t-test or chi-square test was used to compare the DCE-MRI perfusion parameters[Ktrans,Kep,Ve,W-in,W-out,and time to peak(TTP)],ADC value,and clinical feature between the two groups.The diagnostic efficiency of the models were analyzed via receiver operating characteristic(ROC)curves.Results There were significant difference in the maximum tumor diameter,minimum tumor diameter,T stage,N stage,Kep,W-in,and ADC value between HER-2 over expressed breast cancer and non-HER-2 over expressed breast cancer groups(P＜0.05).The proposed combined model,which included the combined maximum tumor diameter,minimum tumor diameter,T stage,N stage,Kep,W-in,and ADC value,showed a better diagnostic efficiency with area under the curve(AUC)(AUC=0.763)than the clinical model(AUC=0.634)based on the combined maximum tumor diameter,minimum tumor diameter,T stage,and N stage,and the imaging model(AUC=0.715)based on the combined Kep,W-in and ADC value.Conclusion The maximum tumor diameter,minimum tumor diameter,T stage,N stage,Kep,W-in,and ADC value may be associated with HER-2 over expressed breast cancer.Combining all above parameters can improve the diagnostic ability of breast cancer patients with HER-2 over expressed.

Objective : To investigate the differential expression of mitochondrial microRNAs (mitomiRs) in tongue squamous cell carcinoma (TSCC) and to screen out mitomiRs related to chemotherapy resistance. Methods : Mitochondrial, cytoplasmic, and total cellular RNAs were extracted from the squamous cell carcinoma cell line CAL-27 and the cisplatin-resistant cell line CAL-27-re. High-throughput miRNA microarrays were used to screen for differentially expressed mitomiRs between the drug-resistant and parental cells. The upregulated mitomiRs in the CAL-27 and CAL-27-re cells and in samples from chemoresistant and chemosensitive tongue squamous cell carcinoma patients were verified by qRT-PCR. Results: The microarray detected 263 miRNAs in 6 components of the mitochondrial, cytoplasmic and total cellular RNAs from the CAL-27 and CAL-27-re cells, including 57 mitomiRs and 134 cytoplasmic microRNAs (cytomiRs). Compared with the total miRNAs, 35 mitomiRs were upregulated in the CAL-27-re cells, and 31 mitomiRs were upregulated in the CAL-27 cells (≥ 1.5-fold). Further comparative analysis of mitomiRs that were differentially expressed between the parental and drug-resistant cells identified 11 upregulated mitomiRs (miR-2392, miR-4462, miR-1290, miR-4449, miR-1268a, miR-1246, and miR-371a-5p, miR-3934-5p, miR-4271, miR-513p, and miR-664b-3p) and 5 downregulated mitomiRs (miR-188-5p, miR-1973, miR -3653, miR-4499, and miR-5787); the expression levels of the other 41 mitomiRs were almost identical in both cell lines. The qRT-PCR results were consistent with the miRNA microarray results. The 11 upregulated mitomiRs that were validated between the CAL-27 and CAL-27-re cells included miR-1268a, miR-2392, miR-4462, and miR-1290. Additionally, 5 mitomiRs, including miR-4449, were upregulated in the clinical chemotherapy-resistant tongue squamous cell carcinoma samples. Conclusion Differentially expressed mitomiRs were found between cisplatin-resistant and cisplatin-sensitive tongue squamous cell carcinoma cells. mitomiRs with high expression levels (miR-2392, miR-4462, miR-1290, miR-4449 and miR-1268a) may play important roles in the drug resistance of tongue squamous cell carcinoma.

Objective ToinvestigatethecorrelationandthediagnosticefficiencyofquantitativeDCE-MRIparametersandADC valueinhistopathologicalgradeinpatients withinvasiveductalbreastcancer.Methods The DCE-MRIquantitativeparameters (Ktrans,KepandVe),semiquantitativeparameters(W-in,W-outandTTP)andtheADCvaluewereanalyzedandcomparedaccording bydifferenthistopathologicalgradein90invasiveductalbreastcancerpatients.Results ThemeanvalueofKtrans washigheringradeⅢgroupthanthatingradeⅡgroup,andthemeanvalueofADCwasloweringradeⅢgroupthanthatingradeⅡgroup.Thedifferenceswere statisticallysignificant(P<0.05),butthecorrelationswereweak(|r|<0.30).TherewerenostatisticallysignificantdifferencesamongKep, Ve,W-in,W-out,TTPingradeⅡandgradeⅢ (P>0.05).TheAUCofKtrans,ADCandKtranscombinedwithADCwere0.647,0.685 and0.749,respectively.Conclusion TheDCE-MRIquantitativeparametersKtransandADCvaluehavecorrelationswithhistopathologicalgradeof invasiveductalbreastcancer.HigherKtransandlowerADCvalueindicatehigherhistologicalgrade,andKtranscombinedwithADCcould improvethediagnosticefficiency.

Objective: To explore the value of dynamic contrast-enhanced MRI (DCE-MRI) based radiomics model in predicting the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) of breast cancer. Methods: In this retrospective study, 91 patients who had received NAC and had pathological response results were collected in Meizhou people′s hospital from January 2016 to August 2018. A primary cohort consisted of 63 patients and an independent validation cohort consisted of 28 patients. The patients were divided into pCR group of 23 cases and non-pathological complete response (Non-pCR) group of 68 cases. All the patients underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) before NAC. A list of radiomics features were extracted using the A.K software and the corresponding radiomics signature was constructed. Logistic regression was used to develop the prediction model. The predictive ability of the model was tested by using the area under the curve (AUC) of ROC analysis. Results: The discrimination performance of radiomics signature yielded a AUC of 0.750 in the primary dataset and a AUC of 0.789 in the validation dataset. The model that incorporated estrogen receptor (ER), progesterone receptor (PR) and radiomics features was developed, and had an AUC of 0.859 in the primary dataset and an AUC of 0.905 in the validation dataset. Conclusion The radiomics predictive model, which integrated with the DCE-MRI based radiomics signature, ER and PR, can be used as a promising and applicable adjunct approach for predicting the pCR to NAC of breast cancer.

Objective: A new ion exchange column technology was used to establish an efficient and sensitive method for the detection of inorganic arsenic. Methods: Based on the new As Specia Fast Column, the pretreatment methods, liquid phase separation and mass spectrometry determination conditions of inorganic arsenic in rice were optimized. Finally, arsenic compounds were separated by As Specia Fast Column and detected by liquid chromatography inductively coupled plasma mass spectrometry. The external standard method was used for quantitative analysis. The detection limit, precision and accuracy of the method were determined by measuring the content of arsenic compounds in rice samples and rice standard samples. At the same time, three Guangdong rice samples were selected as the experimental samples of this study, and 1 g of each sample was weighed and measured in parallel three times. The method was compared with the method of liquid chromatography-atomic fluorescence spectrometry (LC-AFS) and liquid chromatography-inductively coupled plasma mass spectrometry (LC-ICP-MS) in the national standard. Results: The inorganic arsenic in rice was extracted with 0.5% nitric acid solution at 65 ℃ for 15 h, and the pH was adjusted to alkaline. The mobile phase A (8 mmol/L HNO₃, 50 mmol/L NH₃·H₂O) and mobile phase B (40 mmol/L HNO₃, 80 mmol/L NH₃·H₂O) were used as the mobile phase gradient elution (93%) . Five arsenic compounds can reach baseline separation under the conditions of RF power of 1 500 W and atomization gas flow of 0.97 L/min. The detection limits ranged from 0.114 to 0.331 μg/L, and the inorganic arsenic content in rice samples ranged from 0.063 to 0.232 mg/kg. The results of determination of arsenic compounds in rice flour reference materials were all within the uncertainty range indicated by the standard. The recoveries were 86.7%~106.7%, and the precision was 1.9%-12.5%. Compared with national standards, the results of determination of arsenate in rice were relatively close (using this method, LC-AFS, LC-ICP-MS to detect the content of arsenate in rice samples 1 was 0.231, 0.226, 0.236 mg/kg, respectively). However, due to insufficient sensitivity, the national standard method is difficult to detect low levels of arsenic compounds (Arsenobetaine was not detected in rice sample 1). The method can detect the content of arsenobetaine in rice sample 1 was 0.023 mg/kg. Conclusion The established method can meet the requirements of inorganic arsenic determination in rice, and it is more rapid and accurate than the current national standard. It can better monitor and evaluate the content of i-As in rice, and provide accurate data for comprehensively grasping and evaluating the safety of rice consumption of residents.

Objective To explore the m ain perform ance of personality change in people w ith m ild psy-chiatric im pairm ents w hich due to the brain traum a caused by traffic accidents and its value in assess-m ent of psychiatric im pairm ent. Methods The condition of personality change of patients w ith traum atic brain injury caused by traffic accident w as evaluated by the Scale of Personality Change Post-traum atic Brain Injury (SPCPTBI). Furtherm ore, the correlation betw een the personality change and the degrees of traum atic brain injury and psychiatric im pairm ent w ere explored. Results In 271 sam ples, 239 (88.2% ) w ith personality changes. A m ong these 239 sam ples, 178 (65.7% ), 46 (17.0% ), 15 (5.5% ) w ith m ild, m oderate and severe personality changes, respectively. The ratio based on the extent of personality changes to the degree of brain traum a w as not significant (P>0.05), but the total score difference betw een the groups w as significant (P<0.05). There w as no statistical significance betw een the m edium and high severity brain traum a groups. The higher degree of personality changes, the higher rank of m ental disabilities. The total score difference of the scale of personality change am ong the different m ild psychiatric im pair-m ent group w as significant (P<0.05). The difference betw een other psychiatric im pairm ent levels had statistical significance (P<0.05) except level 7 and 8. Conclusion The occurrence of personality change due to traum atic brain injury caused by traffic accident w as high. Correlations exist betw een the personality change and the degree of psychiatric im pairm ent. Personality change due to brain traum a caused by traffic accident can be assessed effectively by m eans of SPCPTBI, and the correlation betw een the total score and the extent of traum atic brain injury can be found.

Objective To analyze the chromosome karyotypes,prenatal diagnosis indications and pregnancy outcomes of high-risk pregnant women in Guangzhou.Methods 2 475 cases pregnant women with screening high risk were operated amniocen-tesis or cordocentesis from January 2010 to September 2012,then amniotic fluids and cord bloods were cultured and the cell were collected for chromosome preparation,G banding,karyotype analysis.We completed follow-up works lastly.Results 38 cases were detected chromosomal abnormality(including 12 cases Down′s syndrome,9 cases sex chromosome abnormality,7 cases transloca-tion,5 cases Edwards′syndrome,2 cases inversion,2 cases deletion,1 cases triploid),the abnormal rate was 1.54%.132 cases were detected chromosomal polymorphism(60 cases 1,9,16qh+ ,30 cases inv(9),25 cases D/Gs+ ,17 cases Y polymorphism).Research on prenatal diagnosis indications,there were 449 cases advanced age,668 cases Down′s screening with high risk,158 cases with ab-normal B ultrasound screening,38 cases with adverse pregnancy history.Conclusion The highest percentage abnormal karyotype is Down′s syndrome.Down′s screening high risk is the main reason for prenatal diagnosis.It is very important to do prenatal diagnos-tic and system B ultrasound for the high-risk pregnant women.

Objective To compare the clinical effects in patients treated with anterograde reamed intramedullary nail (IMN) and dynamic compression plate (DCP) for diaphyseal fractures of the humerus.Methods Forty-seven patients with diaphyseal fractures of the humerus,were divided into two groups by random digits table:IMN group (23 cases) and DCP group (24 cases),IMN and DCP were performed fixation,respectively.After the surgery,perioperative,functional outcomes of shoulder and elbow,postoperative complications between two groups were compared.Results The average follow-up time was (22.3 ± 5.7)months,3 cases were lost in 12-month-follow-up,1 case in IMN group and 2 cases in DCP group.The operation time,intraoperative blood loss in IMN group were significantly shorter than those in DCP group [(67.7 ± 15.3) min vs.(87.0 ± 12.5) min,(106.3 ±57.6) ml vs.(226.7 ±60.2) ml,P＜0.05].The incidence rate of subacromial impingement in IMN group was significantly higher than that in DCP group [18.2％ (4/22) vs.0,P ＜ 0.05].The incidence rate of wound infection in IMN group was significantly better than that in DCP group [4.5％(1/22) vs.22.7％(5/22),P ＜ 0.05].There were no statistically significant differences between two groups in other indexes (P ＞ 0.05).Conclusions DCP has some advantage in perioperative period,but they are comparable in the functional outcomes of shoulder and elbow and complications.