ObjectiveUltra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） was used to identify the metabolites of harmine in rats， in order to explore the differences in distribution of metabolites in rats after single dose（40 mg·kg^-1） intragastric administration of harmine， as well to speculate the metabolic pathways. MethodSD rats were given a single dose of harmine by intragastric administration. Plasma， bile， urine and feces samples were collected after administration， and the samples were processed for determination by UPLC-Q-TOF-MS. The separation was performed on an ACQUITY UPLC™ HSS T3 columu（2.1 mm×100 mm， 1.8 μm） with acetonitrile（A）-0.1% formic acid aqueous solution（B） as mobile phase for gradient elution（0-2 min， 5%A； 2-9 min， 5%-35%A； 9-9.5 min， 35%-100%A； 9.5-12 min， 100%A； 12-12.5 min， 100%-5%A； 12.5-14 min， 5%A）， the mass spectra were obtained in positive ion mode with electrospray ionization（ESI）， the scanning range was m/z 50-1 200. The metabolites of harmine were identified based on the information of the obtained compounds and the literature data， and the metabolic pathways were hypothesized. ResultA total of 42 compounds（harmine and its metabolites） were identified in rats， including 27 in plasma， 17 in bile， 26 in urine and 13 in feces. The metabolic pathways involved in these 42 metabolites included monohydroxylation， dihydroxylation， demethylation， glucuronidation and sulfation. ConclusionHarmine can undergo phase Ⅰ and phase Ⅱ metabolic reactions in rats， and the prototype drug is metabolized rapidly in vivo， and the metabolites are mainly excreted by the kidneys， which can provide a reference basis for the pharmacodynamics and material basis of harmine.

China/epidemiology* ; Humans ; Pemphigoid, Bullous/epidemiology* ; Retrospective Studies

Objective　In this study,glial cell-derived neurotrophic factor (GDNF) were used to induce neural stem cells (NSCs) derived from brain tissue of rat embryo to directional differentiation at a low oxygen environment.Thereby,exploring the affects of low oxygen on differentiation of NSCs into dopaminergic neurons.In this condition.We got quite a lot of dopaminergic cells,which will lay the foundation for the next step of cell transplantation.Methods　NSCs were isolated and cultured from cortex of 14~16 days Wistar rat embryo.Then,at a series of different oxygen concentration with adding of GDNF,the TH positive cells differentiated from NSCs were detected by immunocytochemistry and immunofluorescence methods.Results　Low oxygen obviously increased TH expression with significant differences compared to the normal oxygen control group（P<0.01）.What’s more,at 3% low oxygen concentration,there was a highest differentiation rate for NSCs to TH positive neurons.Conclusion　Low oxygen concentration promoted the differentiation from NSCs to TH positive neurons.3% oxygen concentration was the optimum low oxygen concentration.There was no dependence relationship between differentiation rate promoted by low oxygen concentration for NSCs to TH positive neurons and oxygen concentration gradient.There was a more significant increase in induction efficiency for combined use of low oxygen and GDNF on induction of differentiation of NSCs into TH positive neurons.

Objective: To evaluate the effect of height (HT), total body weight (TBW), body mass index (BMI), lean body weight (LBW), body surface area (BSA) and blood volume (BV) on aortic and liver contrast enhancement during upper abdominal contrast-enhanced CT scans. Methods: One hundred and thirteen enrolled patients underwent upper abdominal multiphase contrast-enhanced CT scans. The enhancement (ΔHU) of aorta in hepatic arterial phase and liver parenchyma in portal venous phase were measured and calculated. The ΔHU values difference of aorta and liver parenchyma in subgroups between males and females, TBW<60 kg and TBW≥60 kg, BMI<25 kg/m² and BMI≥25 kg/m² were compared. To evaluate the effect of the patient′s body parameters on aortic and hepatic enhancement, we performed simple linear regression analyses between the change in CT numbers per gram of iodine (ΔHU/gI) at aorta and liver and each of the following: HT, TBW, BMI, LBW, BSA, and BV. Pearson and t test were used. Results: The mean ΔHU values of aorta and liver were significantly lower at males than that of at females (P<0.05). They were higher at TBW<60 kg patients than at TBW≥60 kg patients(P<0.05), and the mean ΔHU values of the liver at BMI<25 kg/m² patients were significantly higher than at BMI≥25 kg/m² patients(P<0.05). The proportion of the ΔHU values at liver less than 50 HU was higher at males (18.3%, 11/60) than at females (7.5%, 4/53). The most obvious negative correlation coefficients were found between the ΔHU/gI of aorta and LBW at hepatic arterial phase (r=-0.559, P<0.01), and between the ΔHU/gI of liver and BSA at portal venous phase (r=-0.680, P<0.01). Conclusion LBW or BSA could be the alternative body index to TBW for the calculation of personalized iodine dose protocol at aortic and liver enhanced CT scans.

Objective:To investigate the application value of baseline MRI multi-parametric imaging radiomics in prediction of neoadjuvant chemoradiotherapy (NCR) efficacy of rectal mucinous adenocarcinoma (RMAC).Methods:Retrospective analysis was performed in the Sixth Affiliated Hospital of Sun Yat-sen University from August 2012 to October 2018. A total of 79 patients were included in this study, including 52 males and 27 females, aged 20-78 years (median age 52 years). According to the classification criteria of pathological regression, all patients were divided into NCR responsiveness group ( n=31) and nonresponsiveness group ( n=48). And 701 imaging features of T 2WI, diffusion weighted imaging (DWI) and enhanced T 1WI images of baseline MRI were extracted, and feature subsets were selected by repeatability analysis and feature dimensionality reduction to construct the radiomics prediction model. The tumor features from baseline MRI between the NCR responsiveness group and the nonresponsiveness group were compared, and the features of P<0.05 were combined with the radiomics to construct a model. Using pathology as the gold standard, the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficiency of the prediction model, and the area under the curve (AUC), 95% confidence interval, sensitivity and specificity were calculated, and the DeLong test was used to compare the diagnostic efficacy of different prediction models. Results:By comparing the conventional tumor imaging characteristics of the NCR responsiveness group and the nonresponsiveness group, the differences in lymph node stage and mucinous nodule status between the two groups were statistically significant (χ2 =6.040, 5.870, P<0.05). The AUC of ROC curves based on T 2WI, DWI, and enhanced T 1WI radiomics were 0.816, 0.821, and 0.819, respectively, which were higher than those of conventional tumor characteristics (lymph node staging, mucinous nodule status) (AUC=0.607), and the differences were statistically significant ( Z=-2.391, -2.580 and -2.717, P<0.05). Among the joint prediction models of T 2WI, DWI and contrast-enhanced T 1WI radiomics and conventional tumor features, the DWI combined model had the largest AUC (0.843), and there was no statistically significant difference between the three combined models (all P>0.05). Conclusion:The baseline T 2WI, DWI, and contrast-enhanced T 1WI radiomics model can be used to predict the NCR efficacy of RMAC, which is better than the predictive efficacy of conventional features, and the combination with conventional features can further improve the predictive efficacy.

Objective To explore the optimal body size index for the calculation of iodine contrast agent dose required for multiphase liver enhanced CT scans based on the total body weight (TBW),lean body weight (LBW)and body surface area (BSA).Methods Two hundred and twenty enrolled patients were randomly divided into three groups,TBW-group (n＝75),LBW-group (n＝72)and BSA-group (n＝73),and administrated iodine doses were 600 mg I/TBW(kg),780 mg I/LBW(kg)and 22 g I/BSA(m2 ),respectively.All patients had taken upper abdominal plain scans and triple-phase enhanced CT scans.The enhanced values (ΔHU)of the aorta at hepatic arterial phase (HAP),the portal vein and liver parenchyma at portal venous phase (PVP)were compared.The correlation coefficients of adjusted maximal hepatic enhancement(aMHE)with TBW,LBW and BSA in three groups were evaluated,respectively.Results There were no statistical differences in the ΔHU values of the aorta at HAP and the portal vein and liver parenchyma at PVP in the three groups respectively.The smallest variances of the aorta at HAP,the portal vein and liver parenchyma at PVP were found in the LBW group. The aMHE showed mildly positive correlation with TBW (r＝0.230)with a P value of 0.047,but it was consistent with LBW (r＝0.158)and BSA (r＝－0.1 54)with corresponding P values of 0.1 85 and 0.1 9 2 ,respectively.Conclusion Compared with TBW and BSA,iodine contrast agent dose calculated based on the patient’s LBW can improve the patient-to-patient uniformities on aorta,portal vein and liver enhancement during the liver multiphase enhanced CT scans.The LBW is the best body index for the calculation of iodine dose on liver enhanced CT scans.

Objective To evaluate endoscopic surgical treatment of synchronous esophageal squamous cell carcinoma and adenocarcinonm at the esophagogastric junction.Methods The clinical data of 17 patients with synchronous esophageal squamous cell carcinoma associated with adenocarcinoma of esophagogatric junction between Jan 2010 and Jan 2017 were analyzed retrospectively.Results Among these 17 patients,9 patients underwent thoracoscopy and laparoscopy with partial resection of esophagus and proximal stomach,and gastroesophageal and neck anastomosis.3 patients underwent thoracoscopy and laparoscopy with partial resection of esophagus and proximal stomach,gastroesophageal intrathoracic anastomosis.Laparoscopic radical total gastrectomy combined with radiotherapy for esophageal cancer was performed in 5 cases.There was not perioperative death or serious complications.The cumulative survival rates of 1,3 and 5 years after surgery were 100％,42％ and 24％,respectively.Conclusion Thoracolaparscopic surgery combined with local radiation therapy is a safe and effective treatment for patients with synchronous esophageal squamous cell carcinoma and adenocarcinoma at esophagogastric junction.

To develop and validate a fat-suppressed (T2 weighted-magnetic resonance imaging, T2W-MRI) based radiomics signature to preoperatively evaluate the histologic grade (grade I/II VS. grade III) of invasive breast cancer.
 Methods: A total of 202 patients with MRI examination and pathologically confirmed invasive breast cancer from June 2011 to February 2017 were retrospectively enrolled. After retrieving fat-suppressed T2W images and tumor segmentation, radiomics features were extracted and valuable features were selected to build a radiomic signature with the least absolute shrinkage and selection operator (LASSO) method. Mann-Whitney U test was used to explore the correlation between radiomics signature and histologic grade. Receiver operating characteristics (ROC) curve was applied to determine the discriminative performance of the radiomics signature [area under curre (AUC), sensitivity, specificity, and accuracy]. An independent validation dataset was used to confirm the discriminatory power of radiomics signature. 
 Results: Eight radiomics features were selected to build a radiomics signature, which showed good performance for preoperatively evaluating histologic grade of invasive breast cancer, with an AUC of 0.802 (95% CI 0.729 to 0.875), sensitivity of 78.7%, specificity of 70.3% and accuracy of 73.7% in training dataset and AUC of 0.812 (95% CI 0.686 to 0.938), sensitivity of 80.0%, specificity of 73.3% and accuracy of 76.0% in the validation dataset.
 Conclusion: The fat-suppressed T2W-MRI based radiomics signature can be used to preoperatively evaluate the histologic grade of invasive breast cancer, which may assist clinical decision-maker.
Breast Neoplasms ; diagnostic imaging ; Humans ; Magnetic Resonance Imaging ; Preoperative Care ; ROC Curve ; Retrospective Studies

To build a CT-based radiomics predictive mode to evaluate the differentiation degree of the esophageal squamous carcinoma.
 Methods: A total of 160 patients with surgical pathology, complete clinical data and chest CT scanning before operation were retrospectively collected from January 2008 to August 2016. All patients were assigned randomly to a primary data set and an independent validation. Texture analysis was performed on CT images, while the carcinomas were performed by manual segmentation to extract the radiomics features. Radiomics features were extracted and 9 radiomics signatures were finally selected after dimension reduction. Radiomics features were extracted and established via Matlab. Multivariable logistic regression analysis was performed to build the predictive model. A 10-fold cross-validation was used for selecting parameters in the least absolute shrinkage and selection operator (LASSO) model by minimum criteria. The receiver operating characteristic (ROC) curves and areas under ROC curve (AUC) were used to compare the model performance in the primary validation and the independent validation for evaluating the differentiation degree of esophageal squamous carcinoma.
 Results: Radiomics signature showed great effect in discriminating primary data set and independent validation. The predictive model had a good performance in primary data set. The AUC was 0.791, the sensitivity was 81.6%, and specificity was 72.3%. In the independent validation, the AUC was 0.757, the sensitivity was 70.0%, and the specificity was 73.0%.
 Conclusion: The predictive model can be used for evaluating the differentiation degree of esophageal squamous carcinoma efficiently, which can be helpful to clinicians in diagnosis and choice of treatment for esophageal squamous carcinoma.
Carcinoma, Squamous Cell ; Esophageal Neoplasms ; Humans ; ROC Curve ; Retrospective Studies ; Tomography, X-Ray Computed

To investigate the effects of different wavelet filters on correlation and diagnostic performance of radiomics features.
 Methods: A total of 143 colorectal cancer (CRC) patients (64 positive in lymph node metastasis and 79 negative) with contrast-enhanced CT examination were recruited. After labeling the tumor area by experienced radiologists, radiomics wavelets features based on 48 different wavelets were extracted using in-house software coded by Matlab. The correlation coefficients of the features with same names between different wavelets were calculated and got the distribution of high-correlation features between each wavelet. The least absolute shrinkage and selection operator (LASSO) was used to build signatures between lymph node metastasis and wavelet features data set based on different wavelets. The numbers of features in signatures and diagnostic performance were compared using Delong's test.
 Results: With the difference of wavelet order increased, the number of high-correlation features between two wavelets decreased. Some features were prone to high correlation between different wavelets. When building radiomics signature based on single wavelet, signatures built from 'rbio2.2', 'sym7' and 'db7' did well in predicting lymph node metastasis. The signature based on Daubechies wavelet feature set had the highest performance in predicting lymph node metastasis, while the signature from Biorthogonal wavelet features was worst. Improvement was significant in diagnostic performance after excluding the high-correlation features in the whole features set (P=0.004).
 Conclusion: In order to reduce the data redundancy of features, it is recommended to select wavelets with large differences in wavelet orders when calculating radiomics wavelet features. It is necessary to remove high correlation features for improving the diagnostic performance of radiomics signature.
Colorectal Neoplasms ; Humans ; Lymphatic Metastasis ; Retrospective Studies