Publications by authors named "Weijun Peng"

158 Publications

Facile preparation of sulfhydryl modified montmorillonite nanosheets hydrogel and its enhancement for Pb(II) adsorption.

Chemosphere 2021 Apr 30;280:130727. Epub 2021 Apr 30.

Evaluation and Utilization of Strategic Rare Metals and Rare Earth Resource Key Laboratory of Sichuan Province, Chengdu Analytical & Testing Center, Sichuan Bureau of Geology & Mineral Resources, Chengdu, 610081, PR China.

In the work, sulfhydryl functionalized montmorillonite nanosheets based hydrogel balls were firstly synthesized for Pb(II) adsorption, and then characterized by scanning electron microscope (SEM), fourier transform infrared spectroscopy (FTIR), surface area analyzer (BET), thermogravimetry (TG), and zeta potential. Effects of initial solution pH, adsorbent dosage, contact time, temperature on Pb(II) adsorption of the resulting hydrogel balls were investigated systematically. The experimental results showed that the increase amount of sulfhydryl functionalized montmorillonite nanosheets (MMTNs-SH) maintained the hydrogel balls a better porous structure and bigger specific surface area, endowing it a bigger adsorption capacity. The adsorption process was fitted well with pseudo-second-order kinetics model and Freundlich model, and more than 97% of Pb(II) could be removed under the optimum conditions. Moreover, hydrogel spheres have a certain cycle performance. In addition, the interactions between Pb(Ⅱ) ions and the oxygen atoms in the hydroxyl groups and the sulfur atoms in the sulfhydryl groups, and the ion exchange in MMTNs-SH dominated the adsorption.
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http://dx.doi.org/10.1016/j.chemosphere.2021.130727DOI Listing
April 2021

Radiomics of Tumor Heterogeneity in Longitudinal Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer.

Front Mol Biosci 2021 22;8:622219. Epub 2021 Mar 22.

Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China.

Breast tumor morphological and vascular characteristics can be changed during neoadjuvant chemotherapy (NACT). The early changes in tumor heterogeneity can be quantitatively modeled by longitudinal dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is useful in predicting responses to NACT in breast cancer. In this retrospective analysis, 114 female patients with unilateral unifocal primary breast cancer who received NACT were included in a development ( = 61) dataset and a testing dataset ( = 53). DCE-MRI was performed for each patient before and after treatment (two cycles of NACT) to generate baseline and early follow-up images, respectively. Feature-level changes (delta) of the entire tumor were evaluated by calculating the relative net feature change (deltaRAD) between baseline and follow-up images. The voxel-level change inside the tumor was evaluated, which yielded a Jacobian map by registering the follow-up image to the baseline image. Clinical information and the radiomic features were fused to enhance the predictive performance. The area under the curve (AUC) values were assessed to evaluate the prediction performance. Predictive models using radiomics based on pre- and post-treatment images, Jacobian maps and deltaRAD showed AUC values of 0.568, 0.767, 0.630 and 0.726, respectively. When features from these images were fused, the predictive model generated an AUC value of 0.771. After adding the molecular subtype information in the fused model, the performance was increased to an AUC of 0.809 (sensitivity of 0.826 and specificity of 0.800), which is significantly higher than that of the baseline imaging- and Jacobian map-based predictive models ( = 0.028 and 0.019, respectively). The level of tumor heterogeneity reduction (evaluated by texture feature) is higher in the NACT responders than in the nonresponders. The results suggested that changes in DCE-MRI features that reflect a reduction in tumor heterogeneity following NACT could provide early prediction of breast tumor response. The prediction was improved when the molecular subtype information was combined into the model.
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http://dx.doi.org/10.3389/fmolb.2021.622219DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044916PMC
March 2021

Noninvasive prediction of residual disease for advanced high-grade serous ovarian carcinoma by MRI-based radiomic-clinical nomogram.

Eur Radiol 2021 Apr 16. Epub 2021 Apr 16.

Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.

Objectives: To develop a preoperative MRI-based radiomic-clinical nomogram for prediction of residual disease (RD) in patients with advanced high-grade serous ovarian carcinoma (HGSOC).

Methods: In total, 217 patients with advanced HGSOC were enrolled from January 2014 to June 2019 and randomly divided into a training set (n = 160) and a validation set (n = 57). Finally, 841 radiomic features were extracted from each tumor on T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) sequence, respectively. We used two fusion methods, the maximal volume of interest (MV) and the maximal feature value (MF), to fuse the radiomic features of bilateral tumors, so that patients with bilateral tumors have the same kind of radiomic features as patients with unilateral tumors. The radiomic signatures were constructed by using mRMR method and LASSO classifier. Multivariable logistic regression analysis was used to develop a radiomic-clinical nomogram incorporating radiomic signature and conventional clinico-radiological features. The performance of the nomogram was evaluated on the validation set.

Results: In total, 342 tumors from 217 patients were analyzed in this study. The MF-based radiomic signature showed significantly better prediction performance than the MV-based radiomic signature (AUC = 0.744 vs. 0.650, p = 0.047). By incorporating clinico-radiological features and MF-based radiomic signature, radiomic-clinical nomogram showed favorable prediction ability with an AUC of 0.803 in the validation set, which was significantly higher than that of clinico-radiological signature and MF-based radiomic signature (AUC = 0.623, 0.744, respectively).

Conclusions: The proposed MRI-based radiomic-clinical nomogram provides a promising way to noninvasively predict the RD status.

Key Points: • MRI-based radiomic-clinical nomogram is feasible to noninvasively predict residual disease in patients with advanced HGSOC. • The radiomic signature based on MF showed significantly better prediction performance than that based on MV. • The radiomic-clinical nomogram showed a favorable prediction ability with an AUC of 0.803.
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http://dx.doi.org/10.1007/s00330-021-07902-0DOI Listing
April 2021

Antioxidant Effect of Polysaccharides in D-Galactose-Induced Heart Aging Mice.

Biomed Res Int 2021 29;2021:6688855. Epub 2021 Mar 29.

Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.

polysaccharides (PSP), the extract of , are demonstrated to exhibit a wide range of pharmacological activities. A recent study reported that PSP alleviated the aging of the kidney and meninges. However, the effect of PSP on heart aging remains unclear. The present study is aimed at investigating the protection of PSP on D-galactose- (D-gal-) induced heart aging. Results showed that irregularly arranged cardiac muscle fibers were observed in heart tissues of D-gal-treated mice, and the levels of cardiac troponin T (cTnT), creatine kinase (CK), p21, and p53 were increased after D-gal treatment. D-gal-induced heart aging and injury can be attenuated by oral administration of PSP. Moreover, PSP also decreased reactive oxygen species (ROS) and malondialdehyde (MDA) and increased the level of superoxide dismutase (SOD) in the hearts of D-gal-treated mice. DNA damages and lipid peroxidation induced by oxidative stress were also inhibited by PSP as indicated by reduced levels of 8-hydroxydeoxyguanosine (8-OHdG) and 4-hydroxy-2-nonenal (4-HNE). Collectively, PSP attenuated D-gal-induced heart aging via inhibiting oxidative stress, suggesting that PSP might serve as a potential effective Chinese herbal active constituent for antiaging therapy.
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http://dx.doi.org/10.1155/2021/6688855DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8024086PMC
March 2021

Identification of the protective effect of polysaccharide on d-galactose-induced brain ageing in mice by the systematic characterization of a circular RNA-associated ceRNA network.

Pharm Biol 2021 Dec;59(1):347-366

Department of Integrated Traditional Chinese and Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.

Context: polysaccharide (PSP), derived from Delar. ex Redoute (Liliaceae), is known to be able to delay the ageing process. However, the specific mechanisms underlying these effects are not clear.

Objective: To investigate the mechanisms underlying the effects of PSP treatment on brain ageing by the application of transcriptomic analysis.

Materials And Methods: Forty Kunming mice were randomly divided into four groups (control, d-galactose, low-dose PSP, high-dose PSP). Mice were administered d-galactose (50 mg/kg, hypodermic injection) and PSP (200 or 400 mg/kg, intragastric administration) daily for 60 days. Behavioural responses were evaluated with the Morris water maze and the profiles of circRNA, miRNA, and mRNA, in the brains of experimental mice were investigated during the ageing process with and without PSP treatment.

Results: PSP improved cognitive function during brain ageing, as evidenced by a reduced escape latency time ( < 0.05) and an increase in the number of times mice crossed the platform ( < 0.05). A total of 37, 13, and 679, circRNAs, miRNAs, and mRNAs, respectively, were significantly altered by PSP treatment (as evidenced by a fold change ≥2 and  < 0.05). These dysregulated RNAs were closely associated with synaptic activity. PSP regulated regulate nine mRNAs (, , , , , , , , ), three miRNAs (, , ), and two circRNAs ( and ) in the competing endogenous RNA (ceRNA) network.

Discussion And Conclusions: Our analyses showed that multiple circRNAs, miRNAs, and mRNAs responded to PSP treatment in mice experiencing brain ageing.
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http://dx.doi.org/10.1080/13880209.2021.1893347DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8018556PMC
December 2021

Emerging Hexagonal MoC Nanosheet with (002) Facet Exposure and Cu Incorporation for Peroxymonosulfate Activation Toward Antibiotic Degradation.

ACS Appl Mater Interfaces 2021 Mar 18;13(12):14342-14354. Epub 2021 Mar 18.

Doctorado Institucional de Ingeniería y Ciencia de Materiales, Universidad Autonoma de San Luis Potosi, Avenue Sierra Leona 530, San Luis Potosi 78210, Mexico.

The catalyst with a special exposed active facet and multivalent element synergism is much desired for advanced oxidation progress (AOP) reaction. Herein, an emerging substrate, Cu-incorporated MoC, with an active (002) facet exposed was developed by one-step calcination to activate peroxymonosulfate (PMS) toward antibiotic degradation. Combining the multivalent Cu-Mo synergistic effect and Cu complexing interaction, Cu was incorporated onto the MoC surface to further enhance its antibiotic removal through PMS activation. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) measurements indicated the 5% Cu-MoC exhibited in the hexagonal nanosheet with Cu uniformly dispersed on the surface. Moreover, 5% Cu-MoC displayed excellent PMS activation which could fully degrade the tetracycline (TC) within 20 min, and the degradation rate was found to be at least 20 times higher than those of pure MoC, classical FeO and CoO, and Fenton reaction of 5% Cu-MoC. The results were found to be ascribed to enhanced electrical conductivity, multivalent Cu-Mo synergism, and increased generation of active radicals which contributed in the sequence SO• > •OH > O. Surface chemical analysis combined with density functional theory (DFT) calculations confirmed that both Cu/Cu and Mo/Mo/Mo redox cycles occurred on the (002) plane of MoC, which dominated more free electrons and mainly accounted for facilitating PMS activation. Meanwhile, systematically conditional experiments uncovered that the 5% Cu-MoC exhibited superb catalysis even under a wide pH and temperature, various natural polluted waters and coexisting ions, and long-time recycle. In addition, the as-prepared catalyst presented excellent adaptability for the degradation of different organic effluents originated from medical, dyeing, and beneficiation wastewaters. Considering its great performance, stability, and applicability, 5% Cu-MoC would be a capable candidate for PMS activation toward large-scale practical application in environmental remediation.
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http://dx.doi.org/10.1021/acsami.1c03601DOI Listing
March 2021

Systematic Pan-Cancer Analysis Identifies TREM2 as an Immunological and Prognostic Biomarker.

Front Immunol 2021 17;12:646523. Epub 2021 Feb 17.

Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.

Triggering receptor expressed on myeloid cells-2 (TREM2) is a transmembrane receptor of the immunoglobulin superfamily and a crucial signaling hub for multiple pathological pathways that mediate immunity. Although increasing evidence supports a vital role for TREM2 in tumorigenesis of some cancers, no systematic pan-cancer analysis of TREM2 is available. Thus, we aimed to explore the prognostic value, and investigate the potential immunological functions, of TREM2 across 33 cancer types. Based on datasets from The Cancer Genome Atlas, and the Cancer Cell Line Encyclopedia, Genotype Tissue-Expression, cBioPortal, and Human Protein Atlas, we employed an array of bioinformatics methods to explore the potential oncogenic roles of TREM2, including analyzing the relationship between TREM2 and prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and immune cell infiltration of different tumors. The results show that TREM2 is highly expressed in most cancers, but present at low levels in lung cancer. Further, TREM2 is positively or negatively associated with prognosis in different cancers. Additionally, TREM2 expression was associated with TMB and MSI in 12 cancer types, while in 20 types of cancer, there was a correlation between TREM2 expression and DNA methylation. Six tumors, including breast invasive carcinoma, cervical squamous cell carcinoma and endocervical adenocarcinoma, kidney renal clear cell carcinoma, lung squamous cell carcinoma, skin cutaneous melanoma, and stomach adenocarcinoma, were screened out for further study, which demonstrated that TREM2 gene expression was negatively correlated with infiltration levels of most immune cells, but positively correlated with infiltration levels of M1 and M2 macrophages. Moreover, correlation with TREM2 expression differed according to T cell subtype. Our study reveals that TREM2 can function as a prognostic marker in various malignant tumors because of its role in tumorigenesis and tumor immunity.
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http://dx.doi.org/10.3389/fimmu.2021.646523DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7925850PMC
February 2021

Computer-aided diagnosis of ground glass pulmonary nodule by fusing deep learning and radiomics features.

Phys Med Biol 2021 Mar 4;66(6):065015. Epub 2021 Mar 4.

Department of Radiology, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, 1558 Sanhuan North Road, Huzhou, Zhejiang, 313000, People's Republic of China.

Objectives: This study aims to develop a computer-aided diagnosis (CADx) scheme to classify between benign and malignant ground glass nodules (GGNs), and fuse deep leaning and radiomics imaging features to improve the classification performance.

Methods: We first retrospectively collected 513 surgery histopathology confirmed GGNs from two centers. Among these GGNs, 100 were benign and 413 were malignant. All malignant tumors were stage I lung adenocarcinoma. To segment GGNs, we applied a deep convolutional neural network and residual architecture to train and build a 3D U-Net. Then, based on the pre-trained U-Net, we used a transfer learning approach to build a deep neural network (DNN) to classify between benign and malignant GGNs. With the GGN segmentation results generated by 3D U-Net, we also developed a CT radiomics model by adopting a series of image processing techniques, i.e. radiomics feature extraction, feature selection, synthetic minority over-sampling technique, and support vector machine classifier training/testing, etc. Finally, we applied an information fusion method to fuse the prediction scores generated by DNN based CADx model and CT-radiomics based model. To evaluate the proposed model performance, we conducted a comparison experiment by testing on an independent testing dataset.

Results: Comparing with DNN model and radiomics model, our fusion model yielded a significant higher area under a receiver operating characteristic curve (AUC) value of 0.73 ± 0.06 (P < 0.01). The fusion model generated an accuracy of 75.6%, F1 score of 84.6%, weighted average F1 score of 70.3%, and Matthews correlation coefficient of 43.6%, which were higher than the DNN model and radiomics model individually.

Conclusions: Our experimental results demonstrated that (1) applying a CADx scheme was feasible to diagnosis of early-stage lung adenocarcinoma, (2) deep image features and radiomics features provided complementary information in classifying benign and malignant GGNs, and (3) it was an effective way to build DNN model with limited dataset by using transfer learning. Thus, to build a robust image analysis based CADx model, one can combine different types of image features to decode the imaging phenotypes of GGN.
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http://dx.doi.org/10.1088/1361-6560/abe735DOI Listing
March 2021

A combined radiomics and clinical variables model for prediction of malignancy in T2 hyperintense uterine mesenchymal tumors on MRI.

Eur Radiol 2021 Jan 23. Epub 2021 Jan 23.

Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Chongming Branch, No.25, Nanmen Road, Chongming District, 202150, Shanghai, China.

Objective: This study aims to develop a machine learning model for prediction of malignancy in T2 hyperintense mesenchymal uterine tumors based on T2-weighted image (T2WI) features and clinical information.

Methods: This retrospective study included 134 patients with T2 hyperintense uterine mesenchymal tumors (104 patients in training cohort and 30 in testing cohort). A total of 960 radiomics features were initially computed and extracted from each 3D segmented tumor depicting on T2WI. The support vector machine (SVM) classifier was applied to build computer-aided diagnosis (CAD) models by using selected clinical and radiomics features, respectively. Finally, an observer study was conducted by comparing with two radiologists to evaluate the diagnostic performance. The area under the receiver operating characteristic (ROC) curve (AUC) was computed to assess the performance of each model.

Results: Comparing with the T2WI-based radiomics model (AUC: 0.76 ± 0.09) and the clinical model (AUC: 0.79 ± 0.09), the combined model significantly improved the AUC value to 0.91 ± 0.05 (p < 0.05). The clinical-radiomics combined model yielded equivalent or higher performance than two radiologists (AUC: 0.78 vs. 0.91, p = 0.03; 0.90 vs.0.91, p = 0.13). There was a significant difference between the AUC values of two radiologists (p < 0.05).

Conclusions: It is feasible to predict malignancy risk of T2 hyperintense uterine mesenchymal tumors by combining clinical variables and T2WI-based radiomics features. Machine learning-based classification model may be useful to assist radiologists in decision-making.

Key Points: • Radiomics approach has the potential to distinguish between benign and malignant mesenchymal uterine tumors. • T2WI-based radiomics analysis combined with clinical variables performed well in predicting malignancy risk of T2 hyperintense uterine mesenchymal tumors. • Machine learning-based classification model may be useful to assist radiologists in characterization of a T2 hyperintense uterine mesenchymal tumor.
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http://dx.doi.org/10.1007/s00330-020-07678-9DOI Listing
January 2021

Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features.

Cancer Manag Res 2021 12;13:235-245. Epub 2021 Jan 12.

Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, People's Republic of China.

Purpose: To explore the potential factors influencing the malignancy risk of amorphous calcifications and establish a predictive nomogram for malignancy risk stratification.

Patients And Methods: Consecutive mammograms from January 2013 to December 2018 were retrospectively reviewed. Traditional clinical features were recorded, and mammographic features were estimated according to the 5th BI-RADS. Included calcifications were randomly divided into the training and validation cohorts. A nomogram was developed to graphically predict the risk of malignancy (risk) based on stepwise multivariate logistic regression analysis. The discrimination and calibration performance of the model were assessed in both the training and validation cohorts.

Results: Finally, 1018 amorphous calcifications with final pathological results in 907 women were identified with a malignancy rate of 28.4% (95% CI: 25.7%, 31.3%). The malignancy rates of subgroups divided by the distribution of calcifications, quantity of calcifications, age, menopausal status and family history of cancer were significantly different. There were 712 cases and 306 cases in the training and validation cohorts. The prediction nomogram was finally developed based on four risk factors, including age and distribution, maximum diameter and quantity of calcifications. The AUC of the nomogram was 0.799 (95% CI: 0.761, 0.836) in the training cohort and 0.795 (95% CI: 0.738, 0.852) in the validation cohort.

Conclusion: On mammography, the distribution, maximum diameter and quantity of calcifications are independent predictors of malignant amorphous calcifications and can be easily obtained in the clinic. The nomogram developed in this study for individualized malignancy risk stratification of amorphous calcifications shows good discrimination performance.
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http://dx.doi.org/10.2147/CMAR.S286269DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7811441PMC
January 2021

Identification and Validation of Six Autophagy-related Long Non-coding RNAs as Prognostic Signature in Colorectal Cancer.

Int J Med Sci 2021 1;18(1):88-98. Epub 2021 Jan 1.

Department of Integrated Traditional Chinese & Western Medicine, Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, P.R.China.

Colorectal cancer (CRC) is a commonly occurring tumour with poor prognosis. Autophagy-related long non-coding RNAs (lncRNAs) have received much attention as biomarkers for cancer prognosis and diagnosis. However, few studies have focused on their prognostic predictive value specifically in CRC. This research aimed to construct a robust autophagy-related lncRNA prognostic signature for CRC. Autophagy-related lncRNAs from The Cancer Genome Atlas database were screened using univariate Cox, LASSO, and multivariate Cox regression analyses, and the resulting key lncRNAs were used to establish a prognostic risk score model. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) analysis was performed to detect the expression of several lncRNAs in cancer tissues from CRC patients and in normal tissues adjacent to the cancer tissues. A prognostic signature comprising lncRNAs AC125603.2, LINC00909, AC016876.1, MIR210HG, AC009237.14, and LINC01063 was identified in patients with CRC. A graphical nomogram based on the autophagy-related lncRNA signature was developed to predict CRC patients' 1-, 3-, and 5-year survival. Overall survival in patients with low risk scores was significantly better than in those with high risk scores (P < 0.0001); a similar result was obtained in an internal validation sample. The nomogram was shown to be suitable for clinical use and gave correct predictions. The 1- and 3-year values of the area under the receiver operating characteristic curve were 0.797 and 0.771 in the model sample, and 0.656 and 0.642 in the internal validation sample, respectively. The C-index values for the verification samples and training samples were 0.756 (95% CI = 0.668-0.762) and 0.715 (95% CI = 0.683-0.829), respectively. Gene set enrichment analysis showed that the six autophagy-related lncRNAs were greatly enriched in CRC-related signalling pathways, including p53 and VEGF signalling. The qRT-PCR results showed that the expression of lncRNAs in CRC was higher than that in adjacent tissues, consistent with the expression trends of lncRNAs in the CRC data set. In summary, we established a signature of six autophagy-related lncRNAs that could effectively guide clinical prediction of prognosis in patients with CRC. This lncRNA signature has significant clinical implications for improving the prediction of outcomes and, with further prospective validation, could be used to guide tailored therapy for CRC patients.
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http://dx.doi.org/10.7150/ijms.49449DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738973PMC
January 2021

Protective Effect of Quercetin against HO-Induced Oxidative Damage in PC-12 Cells: Comprehensive Analysis of a lncRNA-Associated ceRNA Network.

Oxid Med Cell Longev 2020 1;2020:6038919. Epub 2020 Dec 1.

Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.

Quercetin is a bioflavonoid with potential antioxidant properties. However, the mechanisms underlying its effects remain unclear. Herein, we focused on integrating long noncoding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) sequencing of PC-12 cells treated with quercetin. We treated PC-12 cells with hydrogen peroxide to generate a validated oxidative damage model. We evaluated the effects of quercetin on PC-12 cells and established the lncRNA, miRNA, and mRNA profiles of these cells. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of these RNAs were conducted to identify the key pathways. Quercetin significantly protected PC-12 neuronal cells from hydrogen peroxide-induced death. We identified 297, 194, and 14 significantly dysregulated lncRNAs, miRNAs, and mRNAs, respectively, associated with the antioxidant effect of quercetin. Furthermore, the phosphatidylinositol-3-kinase/protein kinase B pathway was identified as the crucial signalling pathway. Finally, we constructed a lncRNA-associated competing endogenous RNA (ceRNA) network by utilizing oxidative damage mechanism-matched miRNA, lncRNA, and mRNA expression profiles and those changed by quercetin. In conclusion, quercetin exerted a protective effect against oxidative stress-induced damage in PC-12 cells. Our study provides novel insight into ceRNA-mediated gene regulation in the progression of oxidative damage and the action mechanisms of quercetin.
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http://dx.doi.org/10.1155/2020/6038919DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725564PMC
December 2020

Mass Detection and Segmentation in Digital Breast Tomosynthesis Using 3D-Mask Region-Based Convolutional Neural Network: A Comparative Analysis.

Front Mol Biosci 2020 11;7:599333. Epub 2020 Nov 11.

Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China.

Digital breast tomosynthesis (DBT) is an emerging breast cancer screening and diagnostic modality that uses quasi-three-dimensional breast images to provide detailed assessments of the dense tissue within the breast. In this study, a framework of a 3D-Mask region-based convolutional neural network (3D-Mask RCNN) computer-aided diagnosis (CAD) system was developed for mass detection and segmentation with a comparative analysis of performance on patient subgroups with different clinicopathological characteristics. To this end, 364 samples of DBT data were used and separated into a training dataset ( = 201) and a testing dataset ( = 163). The detection and segmentation results were evaluated on the testing set and on subgroups of patients with different characteristics, including different age ranges, lesion sizes, histological types, lesion shapes and breast densities. The results of our 3D-Mask RCNN framework were compared with those of the 2D-Mask RCNN and Faster RCNN methods. For lesion-based mass detection, the sensitivity of 3D-Mask RCNN-based CAD was 90% with 0.8 false positives (FPs) per lesion, whereas the sensitivity of the 2D-Mask RCNN- and Faster RCNN-based CAD was 90% at 1.3 and 2.37 FPs/lesion, respectively. For breast-based mass detection, the 3D-Mask RCNN generated a sensitivity of 90% at 0.83 FPs/breast, and this framework is better than the 2D-Mask RCNN and Faster RCNN, which generated a sensitivity of 90% with 1.24 and 2.38 FPs/breast, respectively. Additionally, the 3D-Mask RCNN achieved significantly ( < 0.05) better performance than the 2D methods on subgroups of samples with characteristics of ages ranged from 40 to 49 years, malignant tumors, spiculate and irregular masses and dense breast, respectively. Lesion segmentation using the 3D-Mask RCNN achieved an average precision (AP) of 0.934 and a false negative rate (FNR) of 0.053, which are better than those achieved by the 2D methods. The results suggest that the 3D-Mask RCNN CAD framework has advantages over 2D-based mass detection on both the whole data and subgroups with different characteristics.
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http://dx.doi.org/10.3389/fmolb.2020.599333DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7686533PMC
November 2020

Application of MRI Radiomics-Based Machine Learning Model to Improve Contralateral BI-RADS 4 Lesion Assessment.

Front Oncol 2020 29;10:531476. Epub 2020 Oct 29.

Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.

Objective: This study aimed to explore the potential of magnetic resonance imaging (MRI) radiomics-based machine learning to improve assessment and diagnosis of contralateral Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions in women with primary breast cancer.

Materials And Methods: A total of 178 contralateral BI-RADS 4 lesions (97 malignant and 81 benign) collected from 178 breast cancer patients were involved in our retrospective dataset. T1 + C and T2 weighted images were used for radiomics analysis. These lesions were randomly assigned to the training (n = 124) dataset and an independent testing dataset (n = 54). A three-dimensional semi-automatic segmentation method was performed to segment lesions depicted on T2 and T1 + C images, 1,046 radiomic features were extracted from each segmented region, and a least absolute shrinkage and operator feature selection method reduced feature dimensionality. Three support vector machine (SVM) classifiers were trained to build classification models based on the T2, T1 + C, and fusion image features, respectively. The diagnostic performance of each model was evaluated and tested using the independent testing dataset. The area under the receiver operating characteristic curve (AUC) was used as a performance metric.

Results: The T1+C image feature-based model and T2 image feature-based model yielded AUCs of 0.71 ± 0.07 and 0.69 ± 0.07 respectively, and the difference between them was not significant (P > 0.05). After fusing T1 + C and T2 imaging features, the proposed model's AUC significantly improved to 0.77 ± 0.06 (P < 0.001). The fusion model yielded an accuracy of 74.1%, which was higher than that of the T1 + C (66.7%) and T2 (59.3%) image feature-based models.

Conclusion: The MRI radiomics-based machine learning model is a feasible method to assess contralateral BI-RADS 4 lesions. T2 and T1 + C image features provide complementary information in discriminating benign and malignant contralateral BI-RADS 4 lesions.
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http://dx.doi.org/10.3389/fonc.2020.531476DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660748PMC
October 2020

Bushen-Tiansui Formula Improves Cognitive Functions in an A Fibril-Infused Rat Model of Alzheimer's Disease.

Neural Plast 2020 24;2020:8874885. Epub 2020 Sep 24.

Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha 410011, China.

Bushen-Tiansui Formula (BTF) was empirically updated from a classical prescription named Kong-Sheng-Zhen-Zhong pill. It is based on the traditional Chinese medicine theory of the mutual relationship between the brain and the kidney and is intended to treat neurodegenerative diseases. This formulation has been used for several years to treat patients with Alzheimer's disease- (AD-) like symptoms in our clinical department. However, the medicinal ingredients and the mechanisms by which BTF improves cognition and memory functions have not been characterized. In this study, we used UPLC-MS to generate a chromatographic fingerprinting of BTF and identified five possible active ingredients, including stilbene glycoside; epimedin A1, B, and C; and icariin. We also showed that oral administration of BTF reversed the cognitive defects in an A fibril-infused rat model of AD, protected synaptic ultrastructure in the CA1 region, and restored the expression of BDNF, synaptotagmin (Syt), and PSD95. These effects likely occurred through the BDNF-activated receptor tyrosine kinase B (TrkB)/Akt/CREB signaling pathway. Furthermore, BTF exhibited no short-term or chronic toxicity in rats. Together, these results provided a scientific support for the clinical use of BTF to improve learning and memory in patients with AD.
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http://dx.doi.org/10.1155/2020/8874885DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532368PMC
September 2020

Integrated meta-analysis, network pharmacology, and molecular docking to investigate the efficacy and potential pharmacological mechanism of Kai-Xin-San on Alzheimer's disease.

Pharm Biol 2020 Dec;58(1):932-943

Teaching and Research Section of Clinical Nursing, Xiangya Hospital, Central South University, Changsha, China.

Context: Kai-Xin-San (KXS) has been used to treat Alzheimer's disease (AD) for thousands of years. However, no quantitative data regarding AD treatment using KXS are available. Moreover, its active compounds and mechanism of action for the treatment of AD remain largely unclear.

Objectives: To evaluate the efficacy and the potential pharmacological mechanisms of KXS in AD treatment.

Materials And Methods: A systematic collection of KXS experiments was conducted from PubMed, Web of Science, Embase, CNKI, VIP, and Wanfang Data up to February, 2020. Review Manager 5 software was used for meta-analysis. In network pharmacology, components of KXS were screened, AD-related genes were then identified and the 'component-target-pathway' network constructed. Molecular docking was finally employed for simulation matching between representative KXS compounds and their target genes.

Results: Meta-analysis revealed that KXS improves the cognitive benefits in AD models by reducing the time of escape latency (SMD = -16.84) as well as increasing the number of cross-platform (SMD = 2.56) and proportion of time in the target quadrant (SMD = 7.52). Network pharmacology identified 25 KXS active compounds and 44 genes targets. DRD2, MAOA, ACHE, ADRA2A and CHRM2 were core target proteins. Besides, 22 potential pathways of KXS were identified, like cholinergic synapses, the cGMP/PKG pathway and calcium signalling. Molecular docking showed that stigmasterol, aposcopolamine and inermin can closely bind three targets (ACHE, ADRA2A and CHRM2).

Discussion And Conclusion: These findings suggest that KXS exerts effect on AD through multi-target, multi-component and multi-pathway mechanism. Future studies may explore the active components of KXS.
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http://dx.doi.org/10.1080/13880209.2020.1817103DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7534219PMC
December 2020

A Network Pharmacology Analysis of the Active Components of the Traditional Chinese Medicine Zuojinwan in Patients with Gastric Cancer.

Med Sci Monit 2020 Aug 31;26:e923327. Epub 2020 Aug 31.

Department of Integrated Traditional Chinese and Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China (mainland).

BACKGROUND Zuojinwan (ZJW) is a traditional Chinese prescription normally used for gastritis. Several studies indicated that it could fight against gastric cancer. This study was designed to determine the potential pharmacological mechanism of ZJW in the treatment of gastric cancer. MATERIAL AND METHODS Bioactive compounds and potential targets of ZJW and related genes of gastric cancer were retrieved from public databases. Pharmacological mechanisms including crucial ingredients, potential targets, and signaling pathways were determined using protein-protein interaction (PPI) and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Virtual docking was performed to validate the findings. RESULTS Network analysis identified 47 active ZJW compounds, and 48 potential ZJW target genes linked to gastric cancer. Quercetin, beta-sitosterol, isorhamnetin, wogonin, and baicalein were identified as potential candidate agents. Our PPI analysis results combined with previously published results indicated that matrix metalloproteinases family members MMP9, MMP1, and MMP3 may play key roles in the anti-gastric cancer effect of ZJW. Molecular docking analysis showed that these crucial targets had good affinity for the representative components in ZJW. GO and KEGG enrichment analysis showed that ZJW target genes functioned in multiple pathways for treating gastric cancer, including interleukin-17 signaling and platinum drug resistance. CONCLUSIONS Our results illuminate the active ingredients, associated targets, biological processes, and signaling pathways of ZJW in the treatment of gastric cancer. This study enhances our understanding of the potential effects of ZJW in gastric cancer and demonstrates a feasible method for discovering potential drugs from Chinese medicinal formulas.
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http://dx.doi.org/10.12659/MSM.923327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482508PMC
August 2020

Insight into the effect of oxidation degree of graphene oxides on their removal from wastewater via froth flotation.

Chemosphere 2021 Jan 3;262:127837. Epub 2020 Aug 3.

School of Chemical Engineering, Zhengzhou University, Zhengzhou, Henan, 450001, PR China.

The effect of oxidation degree of graphene oxides (GO) on their removal from wastewater via froth flotation was studied in this work. Four types of GO samples with different oxidation degrees were synthesized and characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), atomic force spectroscopy (AFM) et al. The effects of cetyl trimethyl ammonium bromide (CTAB) concentration, pH, stirring time on the removal of GO by froth flotation had been discussed. It was found that the addition of CTAB could improve surface hydrophobicity of GO, endowing GO to be easily separated by froth flotation. The removal was dependent on CTAB dosage, pH and stirring time. Moreover, the removal first increased and then decreased with the increasing oxidation degree of GO, and less kinetic energy input was needed to overcome the energy barrier between GO flocs with the increase of oxidation degree. The removal mechanism was proven to be electrostatic attraction, and the different contents of oxgenous-containing functional groups in GOs with various oxidation degrees played a vital role in their removal via froth flotation.
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http://dx.doi.org/10.1016/j.chemosphere.2020.127837DOI Listing
January 2021

Network Pharmacology-Based Prediction and Verification of the Active Ingredients and Potential Targets of Zuojinwan for Treating Colorectal Cancer.

Drug Des Devel Ther 2020 14;14:2725-2740. Epub 2020 Jul 14.

Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, People's Republic of China.

Background: Zuojinwan (ZJW), a famous Chinese medicine formula, has been widely used to treat colorectal cancer (CRC). However, its bioactive compounds, potential targets, and molecular mechanism remain largely elusive.

Aim: A network pharmacology-based strategy combined with molecular docking studies and in vitro validation were employed to investigate bioactive compounds, potential targets, and molecular mechanism of ZJW against CRC.

Materials And Methods: Bioactive compounds and potential targets of ZJW, as well as related genes of CRC, were acquired from public databases. Important ingredients, potential targets, and signaling pathways were determined through bioinformatics analysis, including protein-protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, molecular docking and cell experiments were performed to further verify the findings.

Results: A total of 36 bioactive ingredients of ZJW and 163 gene targets of ZJW were identified. The network analysis revealed that quercetin, baicalein, wogonin, beta-sitosterol, and isorhamnetin may be candidate agents. The AKT1, JUN, CDKN1A, BCL2L1, and NCOA1 could become potential drug targets. The KEGG indicated that PI3K-AKT signaling pathway may play an important role in the effect of ZJW against CRC. Molecular docking suggested that quercetin, baicalein, and wogonin combined well with AKT1 and JUN. The in vitro experiment showed that quercetin, the most important ingredient of ZJW, could induce apoptosis of HCT116 cells through PI3K-Akt signaling pathway. This finding was congruent with the prediction obtained through the network pharmacology approach.

Conclusion: This study comprehensively illuminated the active ingredients, potential targets, and molecular mechanism of ZJW against CRC. It also provided a promising approach to uncover the scientific basis and therapeutic mechanism of traditional Chinese medicine (TCM) formula treating for disease.
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http://dx.doi.org/10.2147/DDDT.S250991DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7369379PMC
July 2020

Air and surface contamination by SARS-CoV-2 virus in a tertiary hospital in Wuhan, China.

Int J Infect Dis 2020 Oct 27;99:3-7. Epub 2020 Jul 27.

School of Medicine and Health Management, Tongji Medical School, Huazhong University of Science and Technology, Wuhan, Hubei, China. Electronic address:

Background: Few studies have explored air and surface contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in healthcare settings.

Methods: Air and surface samples were collected from the isolation wards and intensive care units designated for coronavirus disease 2019 (COVID-19) patients. Clinical data and the results of nasopharyngeal specimen and serum antibody testing were also collected for the patient sample.

Results: A total of 367 air and surface swab samples were collected from the patient care areas of 15 patients with mild COVID-19 and nine patients with severe/critical COVID-19. Only one air sample taken during the intubation procedure tested positive. High-touch surfaces were slightly more likely to be contaminated with SARS-CoV-2 RNA than low-touch surfaces. Contamination rates were slightly higher near severe/critical patients than near mild patients, although this difference was not statistically significant (p > 0.05). Surface contamination was still found near the patients with both positive IgG and IgM.

Conclusions: Air and surface contamination with viral RNA was relatively low in these healthcare settings after the enhancement of infection prevention and control. Environmental contamination could still be found near seroconverted patients, suggesting the need to maintain constant vigilance in healthcare settings to reduce healthcare-associated infection during the COVID-19 pandemic.
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http://dx.doi.org/10.1016/j.ijid.2020.07.027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7384415PMC
October 2020

Integrated Metabolomic and Lipidomic Analysis Reveals the Neuroprotective Mechanisms of Bushen Tiansui Formula in an A1-42-Induced Rat Model of Alzheimer's Disease.

Oxid Med Cell Longev 2020 19;2020:5243453. Epub 2020 Jun 19.

Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.

Bushen Tiansui Formula (BSTSF) is a traditional Chinese medicine prescription. It has been widely applied to treat Alzheimer's disease (AD) in the clinic; however, the mechanisms underlying its effects remain largely unknown. In this study, we used a rat AD model to study the effects of BSTSF on cognitive performance, and UPLC-MS/MS-based metabolomic and lipidomic analysis was further performed to identify significantly altered metabolites in the cerebral cortices of AD rats and determine the effects of BSTSF on the metabolomic and lipidomic profiles in the cerebral cortices of these animals. The results revealed that the levels of 47 metabolites and 30 lipids primarily associated with sphingolipid metabolism, glycerophospholipid metabolism, and linoleic acid metabolism were significantly changed in the cerebral cortices of AD rats. Among the altered lipids, ceramides, phosphatidylethanolamines, lysophosphatidylethanolamines, phosphatidylcholines, lysophosphatidylcholines, phosphatidylserines, sphingomyelins, and phosphatidylglycerols showed robust changes. Moreover, 34 differential endogenous metabolites and 21 lipids, of which the levels were mostly improved in the BSTSF treatment group, were identified as potential therapeutic targets of BSTSF against AD. Our results suggest that lipid metabolism is highly dysregulated in the cerebral cortices of AD rats, and BSTSF may exert its neuroprotective mechanisms by restoring metabolic balance, including that of sphingolipid metabolism, glycerophospholipid metabolism, alanine, aspartate, and glutamate metabolism, and D-glutamine and D-glutamate metabolism. Our data may lead to a deeper understanding of the AD-associated metabolic profile and shed new light on the mechanism underlying the therapeutic effects of BSTSF.
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http://dx.doi.org/10.1155/2020/5243453DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7322593PMC
May 2021

Multimode tumor ablation therapy induced different diffusion and microvasculature related parameters change on functional magnetic resonance imaging compared to radiofrequency ablation in liver tumor: An observational study.

Medicine (Baltimore) 2020 Jun;99(26):e20795

Department of Radiology.

To explore different posttreatment changes between multimode tumor ablation therapy (MTAT) and radiofrequency ablation (RFA) using intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion kurtosis imaging (DKI) in patients with hepatic malignancies.Eighty - seven patients with one hundred and twenty eight hepatic lesions receiving MTAT or RFA underwent IVIM-DWI and DKI before and after treatment. The mean value of apparent diffusion coefficient (ADC), IVIM-DWI parameters, including true diffusion coefficient (D), pseudo-diffusion coefficient (DP), perfusion fraction (f), and DKI parameters including diffusion coefficient (DK), apparent diffusional kurtosis (K) were retrospectively compared prior to and following treatment as well as between treatment groups. The degree of parameters change after ablation was compared between 2 treatment modalities.The mean value of ADC, D, and DK increased while f, and K decreased significantly in MTAT group. In RFA group, just ADC and K showed significantly change following treatment. The ADC and D value were higher in MTAT group than in RFA group 1 month after treatment. While f was lower in MTAT group after treatment compared with RFA group. The ADC, D and DK increased (21.89 ± 24.95% versus 8.76 ± 19.72%, P = .04 for ADC, 33.78 ± 54.01% versus 7.91 ± 25.16%, P = .03 for D, 25.91 ± 36.28% versus 1.75 ± 46.42%, P = .01 for DK) while f declined (-32.62 ± 41.48% versus 6.51 ± 44.16%, P < .001) more in MTAT group.The MTAT induced different posttreatment changes on water molecule diffusion and microvasculature related functional MR parameters compared to RFA in patients with liver tumors.
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http://dx.doi.org/10.1097/MD.0000000000020795DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7329015PMC
June 2020

Image quality of the CAIPIRINHA-Dixon-TWIST-VIBE technique for ultra-fast breast DCE-MRI: Comparison with the conventional GRE technique.

Eur J Radiol 2020 Aug 3;129:109108. Epub 2020 Jun 3.

Department of MR Imaging, Shandong Medical Imaging Research Institute, Shandong University, Jinan, Shandong, China. Electronic address:

Purpose: The aim of this study was to evaluate image quality of the CAIPIRINHA-Dixon-TWIST-Volume-Interpolated Breath-hold Examination (CDT-VIBE) technique for ultra-fast breast dynamic contrast enhanced (DCE) MRI with respect to conventional Gradient-Recalled Echo (GRE) technique.

Methods: A total of 58 patients underwent a DCE-MRI based on CDT-VIBE sequence (temporal resolution: 11.9 s), immediately followed by 1 phase of a conventional T1 weighted GRE sequence (acquisition time: 68 s). The Signal-to-Noise Ratio (SNR) on phantom images, lesion/parenchyma signal ratio (LPSR), image quality, and morphological characterization were compared between the last phase of CDT-VIBE and conventional GRE images. The image quality was assessed by visual grading analysis (VGA). Reader agreement was assessed using Kappa analysis.

Results: There was no significant difference in SNR (phantom) or LPSR (patient) between CDT-VIBE and conventional GRE images (P > 0.05). Significant parallel acquisition technique (PAT) noise and mild blurriness was observed on CDT-VIBE images. Visual grading analysis (VGA) confirmed significantly worse ratings for CDT-VIBE compared to the conventional GRE sequence in terms of PAT noise, lesion's internal feature clarity, and therefore overall image quality (area under contrast curve [AUC] values: 0.578 ‒ 0.764, P < 0.05), but edge sharpness and lesion conspicuity were equivalent (P > 0.05). Kappa analysis revealed good agreement on image quality scores (к = 0.725 ‒ 0.908) and on morphologic terms (к = 0.745-1.000).

Conclusion: The CDT-VIBE sequence provides excellent spatial resolution and adequate image quality in ultra-fast breast DCE-MRI. Further improvement in PAT noise and internal structure blurriness may be necessary.
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http://dx.doi.org/10.1016/j.ejrad.2020.109108DOI Listing
August 2020

Integrated transcriptomic and metabolomic analyses to characterize the anti-cancer effects of (-)-epigallocatechin-3-gallate in human colon cancer cells.

Toxicol Appl Pharmacol 2020 08 6;401:115100. Epub 2020 Jun 6.

Department of Integrated Traditional Chinese &Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China. Electronic address:

(-)-Epigallocatechin-3-gallate (EGCG) is the main bioactive component in tea (Camellia sinensis) catechins, and exhibits potential antitumor activity against colorectal cancer (CRC). However, the underlying mechanisms are largely unclear. We investigated the effects of EGCG on activities of CRC cells and the exact molecular mechanism. We used human colon cancer cells (HT-29) and exposed them to EGCG at various concentrations. The MTT assay, flow cytometry, and TUNEL staining were used to study the underlying mechanisms of EGCG (proliferation, apoptosis, autophagy). Western blotting was used to measure expression of marker proteins of the cell cycle, apoptosis, and autophagy. Using a combined microarray-based transcriptomic and ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight tandem mass spectrometry (UHPLC-QTOF/MS)-based metabolomic approach, we investigated the perturbed pathways induced by EGCG treatment at transcript and metabolite levels. Transcriptomic analyses showed that 486 genes were differentially expressed between untreated and EGCG-treated cells. Also, 88 differentially expressed metabolites were identified between untreated and EGCG-treated cells. The altered metabolites were involved in the metabolism of glutathione, glycerophospholipids, starch, sucrose, amino sugars, and nucleotide sugars. There was substantial agreement between the results of transcriptomics and metabolomics analyses. Our data indicate that the anticancer activity of EGCG against HT-29 cells is mediated by induction of cell-cycle arrest, apoptosis, and autophagy. EGCG modulates cancer-cell metabolic pathways. These results provide a platform for future molecular mechanistic studies of EGCG.
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http://dx.doi.org/10.1016/j.taap.2020.115100DOI Listing
August 2020

Differentiation of renal cell carcinoma subtypes through MRI-based radiomics analysis.

Eur Radiol 2020 Oct 4;30(10):5738-5747. Epub 2020 May 4.

Department of Radiology, Fudan University Shanghai Cancer Center (FUSCC), No. 270, Dongan Rd, Shanghai, 200032, People's Republic of China.

Objectives: To explore whether clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (pRCC), and chromophobe renal cell carcinoma (cRCC) can be distinguished using radiomics features extracted from magnetic resonance (MR) images.

Methods: Seventy-seven patients (ccRCC = 32, pRCC = 23, cRCC = 22) underwent MRI before surgery between May 2013 and August 2018 in this retrospective study. Thirty-nine radiomics features were extracted from tumor volumes on three sequences (T2WI, EN-T1WI CMP, and EN-T1WI NP). The Kruskal-Wallis test with Bonferonni correction and variance threshold were used for feature selection among the three RCC subtypes. ROC curves for the three subtypes were generated based on radiomics features. AUC, accuracy, sensitivity, and specificity for subtype differentiation are reported. Linear discriminant analysis (LDA) was used to assess the discriminative ability of these radiomics features.

Results: Significant radiomics features among the three subtypes were identified, and ROC curves achieved excellent AUCs for T2WI, EN-T1WI CMP, EN-T1WI NP, and combined three MR sequences (0.631, 0.790, 0.959, and 0.959 between ccRCC and cRCC; 0.688, 0.854, 0.909, and 0.955 between pRCC and cRCC; 0.747, 0.810, 0.814, and 0.890 between ccRCC and pRCC). In addition, LDA demonstrated the three RCC subtypes were correctly classified by radiomics analysis (66.2% for EN-T1WI CMP, 71.4% for EN-T1WI NP, 55.8% for T2WI, and 71.4% for the combined three MR sequences).

Conclusions: Radiomics analysis can be used to differentiate among ccRCC, pRCC, and cRCC based on radiomics features extracted from multiple-sequence MRI and may help diagnose and treat RCC patients in the future, while further study is still needed.

Key Points: • Radiomics features on multiple-sequence MRI can help differentiate the three subtypes of renal cell carcinoma (clear cell, papillary renal cell, and chromophobe renal cell carcinoma). • Radiomics features based on MRI indicate greater textural heterogeneity on ccRCCs than pRCCs and cRCCs (the highest AUCs on EN-T1WI NP are 0.814 for ccRCCs vs pRCCs and 0.959 for ccRCCs vs cRCCs, respectively). • There is a significant difference in the textural heterogeneity of radiomics features between pRCCs and cRCCs (the AUC is 0.909, 0.854, and 0.688 on EN-T1WI NP, EN-T1WI CMP, and T2WI, respectively).
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http://dx.doi.org/10.1007/s00330-020-06896-5DOI Listing
October 2020

Comparison and Fusion of Deep Learning and Radiomics Features of Ground-Glass Nodules to Predict the Invasiveness Risk of Stage-I Lung Adenocarcinomas in CT Scan.

Front Oncol 2020 31;10:418. Epub 2020 Mar 31.

Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.

For stage-I lung adenocarcinoma, the 5-years disease-free survival (DFS) rates of non-invasive adenocarcinoma (non-IA) is different with invasive adenocarcinoma (IA). This study aims to develop CT image based artificial intelligence (AI) schemes to classify between non-IA and IA nodules, and incorporate deep learning (DL) and radiomics features to improve the classification performance. We collect 373 surgical pathological confirmed ground-glass nodules (GGNs) from 323 patients in two centers. It involves 205 non-IA (including 107 adenocarcinoma and 98 minimally invasive adenocarcinoma), and 168 IA. We first propose a recurrent residual convolutional neural network based on U-Net to segment the GGNs. Then, we build two schemes to classify between non-IA and IA namely, DL scheme and radiomics scheme, respectively. Third, to improve the classification performance, we fuse the prediction scores of two schemes by applying an information fusion method. Finally, we conduct an observer study to compare our scheme performance with two radiologists by testing on an independent dataset. Comparing with DL scheme and radiomics scheme (the area under a receiver operating characteristic curve (AUC): 0.83 ± 0.05, 0.87 ± 0.04), our new fusion scheme (AUC: 0.90 ± 0.03) significant improves the risk classification performance ( < 0.05). In a comparison with two radiologists, our new model yields higher accuracy of 80.3%. The kappa value for inter-radiologist agreement is 0.6. It demonstrates that applying AI method is an effective way to improve the invasiveness risk prediction performance of GGNs. In future, fusion of DL and radiomics features may have a potential to handle the classification task with limited dataset in medical imaging.
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http://dx.doi.org/10.3389/fonc.2020.00418DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136522PMC
March 2020

Comprehensive Comparison of the Combustion Behavior for Low-Temperature Combustion of -Nonane.

ACS Omega 2020 Mar 5;5(10):4924-4936. Epub 2020 Mar 5.

School of Chemical Engineering, Guizhou Institute of Technology, Guiyang 550003, PR China.

To meet the increasing need for clean combustion, improve the combustion efficiency of fuels, and reduce the pollutants produced in the combustion process, it is necessary to systematically study the combustion of hydrocarbon fuels. An accurate and detailed chemical kinetic model is an important prerequisite for understanding the combustion performance of hydrocarbon fuels and studying complex chemical reaction networks. Therefore, based on ReaxGen, new detailed mechanisms for the low-temperature combustion of -nonane are proposed and verified in detail in this study. Meanwhile, some international mainstream combustion models such as the LLNL model and the JetSurf 2.0 model are compared with ours, showing that the proposed new mechanisms can better predict the ignition delay combustion characteristics of -nonane, and they also hold in a wide range of conditions. In addition, the numerical simulation results of the concentration curve calculated for the new mechanisms, especially Model v2, are in good agreement with the experimental data, and the mechanisms can reproduce the performance of the negative-temperature-coefficient behavior toward -nonane ignition. The numerical simulation results of the laminar flame propagation velocity varying with the equivalence ratio are also in good agreement with the available experimental data. Finally, the ignition delay sensitivity of -nonane is analyzed by the sensitivity analysis method; the key reactions affecting the ignition mechanism are investigated; and the reaction path analysis is conducted to better understand the models' predicted performance. In a word, the new mechanisms are helpful to understand the ignition properties of large hydrocarbon fuels for high-speed aircrafts.
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http://dx.doi.org/10.1021/acsomega.9b03786DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081281PMC
March 2020

Integrated 16S rRNA Sequencing, Metagenomics, and Metabolomics to Characterize Gut Microbial Composition, Function, and Fecal Metabolic Phenotype in Non-obese Type 2 Diabetic Goto-Kakizaki Rats.

Front Microbiol 2019 20;10:3141. Epub 2020 Jan 20.

Hunan Academy of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China.

Type 2 diabetes mellitus (T2DM) is one of the most prevalent endocrine diseases in the world. Recent studies have shown that dysbiosis of the gut microbiota may be an important contributor to T2DM pathogenesis. However, the mechanisms underlying the roles of the gut microbiome and fecal metabolome in T2DM have not been characterized. Recently, the Goto-Kakizaki (GK) rat model of T2DM was developed to study the clinical symptoms and characteristics of human T2DM. To further characterize T2DM pathogenesis, we combined multi-omics techniques, including 16S rRNA gene sequencing, metagenomic sequencing, and metabolomics, to analyze gut microbial compositions and functions, and further characterize fecal metabolomic profiles in GK rats. Our results showed that gut microbial compositions were significantly altered in GK rats, as evidenced by reduced microbial diversity, altered microbial taxa distribution, and alterations in the interaction network of the gut microbiome. Functional analysis based on the cluster of orthologous groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations suggested that 5 functional COG categories belonged to the metabolism cluster and 33 KEGG pathways related to metabolic pathways were significantly enriched in GK rats. Metabolomics profiling identified 53 significantly differentially abundant metabolites in GK rats, including lipids and lipid-like molecules. These lipids were enriched in the glycerophospholipid metabolic pathway. Moreover, functional correlation analysis showed that some altered gut microbiota families, such as and , significantly correlated with alterations in fecal metabolites. Collectively, the results suggested that an altered gut microbiota is associated with T2DM pathogenesis.
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http://dx.doi.org/10.3389/fmicb.2019.03141DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6984327PMC
January 2020

A perspective of stepwise utilization of hazardous zinc plant purification residue based on selective alkaline leaching of zinc.

J Hazard Mater 2020 05 14;389:122090. Epub 2020 Jan 14.

Laboratory of Special Metallurgy and Process Engineering, School of Metallurgy, Northeastern University, Shenyang 110819, China.

A new route for selective recovery of zinc from hazardous zinc plant purification residue was proposed by alkaline leaching process. The thermodynamic analysis revealed that by controlling solution pH in the range from 14.30 to 16.78 at 25 °C, basic zinc sulfate can be converted to ZnO instead of Zn(OH), while Cd will enter into alkaline leaching residue as a hydroxide. It is feasible to leach selectively Zn and to separate it with Cd by alkaline leaching, and the experimental results confirm that. Under the conditions of NaOH concentration of 3 mol/L, L/S of 20 ml/g, temperature of 40 °C, and time of 50 min, LR of Zn reached 96.14% while them of Pb and Cd were only 0.66% and 2.83% respectively. ZnO with hexagonal wurtzite structure and Cd(OH) were the main phases of leaching residue. They crystallized and adhered to the surface of leaching residue particles, which result in the loose and random particle morphology. The findings confirm that alkaline leaching is efficient in separation of Zn and Cd in ZPPR. In addition, nano-ZnO with flowerlike was synthesized with the zinc-rich leaching solution by precipitation method and the its photocatalytic property was similar to that of nano-ZnO purchased.
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http://dx.doi.org/10.1016/j.jhazmat.2020.122090DOI Listing
May 2020