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Yin X, Archbold T, Burello N, Scolaro M, Li M, Wang W, Zhou K, Fan M. 363 Increased Intestinal Alkaline Phosphatase Maximal Activities Mediate Improvements in Growth and Gut Health Status in Weanling Pigs Fed the Antibiotic-Supplemented Diet. J Anim Sci 2018. [DOI: 10.1093/jas/sky404.393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- X Yin
- University of Guelph,Guelph, ON, Canada
| | | | - N Burello
- University of Guelph,Guelph, ON, Canada
| | - M Scolaro
- University of Guelph,Guelph, ON, Canada
| | - M Li
- Henan University of Animal Husbandry and Economy,China, Zhengshou, Henen, China
| | - W Wang
- University of Guelph,Guelph, ON, Canada
| | - K Zhou
- University of Guelph,Guelph, ON, Canada
| | - M Fan
- University of Guelph,Guelph, ON, Canada
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152
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Yin X, Wang W, Archbold T, Burello N, Scolaro M, Zhou K, Fan M. PSI-28 Genomic determinants of alkaline phosphatase catalytic affinity along the intestinal longitudinal axis of weanling pigs. J Anim Sci 2018. [DOI: 10.1093/jas/sky404.405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- X Yin
- University of Guelph,Guelph, ON, Canada
| | - W Wang
- University of Guelph,Guelph, ON, Canada
| | | | - N Burello
- University of Guelph,Guelph, ON, Canada
| | - M Scolaro
- University of Guelph,Guelph, ON, Canada
| | - K Zhou
- University of Guelph,Guelph, ON, Canada
| | - M Fan
- University of Guelph,Guelph, ON, Canada
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Chen Y, Zhou L, Liao N, Gao P, Chen L, Li X, Fan M. Specific computed tomography imaging characteristics of congenital mesoblastic nephroma and correlation with ultrasound and pathology. J Pediatr Urol 2018; 14:571.e1-571.e6. [PMID: 30145031 DOI: 10.1016/j.jpurol.2018.07.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2018] [Accepted: 07/24/2018] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Congenital mesoblastic nephroma (CMN) is a common solid renal tumor in the neonate. Congenital mesoblastic nephroma can be divided into classic, cellular, and mixed types. The prognosis of CMN is very optimistic. But CMN can easily be misdiagnosed as the other malignant renal tumors by radiology. However, no studies have described the computed tomography (CT) imaging appearance of CNM in detail. The objective of this study is retrospective analyses of the multislice CT characteristics of CMN and their corresponding ultrasound findings and pathology. METHODS This retrospective study reviewed the enhanced CT images of the CMNs and other renal tumors in children younger than 1 year in the past 10 years from the First Affiliated Hospital of Sun Yat-sen University. Two radiologists had noted the CT imaging characteristics of these images. t-test and Fisher's exact test were used in the comparison of imaging characteristics between the CMNs and other renal tumors. RESULTS AND DISCUSSION Compared with other malignant renal tumors, the CMNs tend to appear as smaller round masses without clear coverage or clear boundary with the kidney in CT images (P < 0.01). The intratumor pelvis and the double-layer sign are the specific characteristics of CMNs (P < 0.01). The gender, quality of tumor (solid or solid-cystic), character of enhancement (homogeneous or heterogeneous enhancement), peri-renal hemorrhage, or peripheral lymph node enlargement showed no statistical significance (P > 0.05) between CMNs and other renal tumors. The appearances of CMN with classic components in the CT images are relevant to the pathological findings. The intratumor pelvis is caused by the classic components of CMN growing to encapsulate the pelvis. The double-layer sign in CT image correlates with the specific hypoechoic ring in ultrasound, which is caused by the slow blood flow and delay contrast agent filling in the blood sinus located in the peripheral part of the tumor. The differential diagnosis of CMN should include the other solitary renal tumors such as Wilms' tumor, clear-cell sarcoma of the kidney, and rhabdoid tumor of the kidney. CONCLUSION The unclear coverage and unclear boundary with the kidney, the intratumor pelvis, and double-layer sign after contrast were specific CT imaging characteristics of CMN.
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Affiliation(s)
- Y Chen
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58th, The Second Zhongshan Road, Guanzhou, China
| | - L Zhou
- Department of Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, 58th, The Second Zhongshan Road, Guanzhou, China
| | - N Liao
- Department of Pathology, The First Affiliated Hospital, Sun Yat-sen University, 58th, The Second Zhongshan Road, Guanzhou, China
| | - P Gao
- Department of Pediatric Surgery, The First Affiliated Hospital, Sun Yat-sen University, 58th, The Second Zhongshan Road, Guanzhou, China
| | - L Chen
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58th, The Second Zhongshan Road, Guanzhou, China
| | - X Li
- School of Public Health, Sun Yat-sen University, 58th, The Second Zhongshan Road, Guanzhou, China
| | - M Fan
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58th, The Second Zhongshan Road, Guanzhou, China.
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154
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Alazmi M, Abbas A, Guo X, Fan M, Li L, Gao X. A Slice-based 13C-detected NMR Spin System Forming and Resonance Assignment Method. IEEE/ACM Trans Comput Biol Bioinform 2018; 15:1999-2008. [PMID: 29994483 DOI: 10.1109/tcbb.2018.2849728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Nuclear magnetic resonance (NMR) spectroscopy is attracting more attention in the field of computational structural biology. Till recently, 1H-detected experiments are the dominant NMR technique used due to the high sensitivity of 1H nuclei. However, the current availability of high magnetic fields and cryogenically cooled probe heads allow researchers to overcome the low sensitivity of 13C nuclei. Consequently, 13C-detected experiments have become a popular technique in different NMR applications especially resonance assignment and structure determination of large proteins. In this paper, we propose the first spin system forming method for 13C-detected NMR spectra. Our method is able to accurately form spin systems based on as few as two 13C-detected spectra, CBCACON, and CBCANCO. Our method picks slices from the more trusted spectrum and uses them as feedback to direct the slice picking in the less trusted one. This feedback leads to picking the accurate slices that consequently helps to form better spin systems. We tested our method on a real dataset of 'Ubiquitin' and a benchmark simulated dataset consisting of 12 proteins. We fed our spin systems as inputs to a genetic algorithm to generate the chemical shift assignment, and obtained 92 percent correct chemical shift assignment for Ubiquitin. For the simulated dataset, we obtained an average recall of 86 percent and an average precision of 88 percent. Finally, our chemical shift assignment of Ubiquitin was given as an input to CS-ROSETTA server that generated structures close to the experimentally determined structure.
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155
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Yang J, Fan M, Chen M, Pan L, Ma J, Lang J. Using Circulating Tumor DNA (ctDNA) As Screening and Predictive Marker in Cervical Carcinoma Patients Receiving Radiation Therapy. Int J Radiat Oncol Biol Phys 2018. [DOI: 10.1016/j.ijrobp.2018.07.140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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156
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Xu X, Huang L, Chen J, Wang J, Wen J, Xie L, Liu D, Zhang J, Fan M. Application of Radiomics Signature Captured from Pretreatment CT to Predict Brain Metastases in Stage III/IV Non-small Cell Lung Cancer Patients with ALK Mutation. Int J Radiat Oncol Biol Phys 2018. [DOI: 10.1016/j.ijrobp.2018.07.1920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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157
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Chen Y, Ye J, Zhu Z, Zhao W, Li L, Fan M, WU C, Tang H, Xu G, Lin Q, LI J, Xia Y, Yunhai L, Zhou J, Zhao K. Final Results of a Phase 3 Study of Comparing Paclitaxel Plus 5-Fluorouracil versus Cisplatin Plus 5-Fluorouracil in Chemoradiotherapy for Locally Advanced Esophageal Carcinoma. Int J Radiat Oncol Biol Phys 2018. [DOI: 10.1016/j.ijrobp.2018.06.054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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158
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Li Y, Wang S, Umarov R, Xie B, Fan M, Li L, Gao X. DEEPre: sequence-based enzyme EC number prediction by deep learning. Bioinformatics 2018; 34:760-769. [PMID: 29069344 PMCID: PMC6030869 DOI: 10.1093/bioinformatics/btx680] [Citation(s) in RCA: 123] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Accepted: 10/20/2017] [Indexed: 11/15/2022] Open
Abstract
Motivation Annotation of enzyme function has a broad range of applications, such as metagenomics, industrial biotechnology, and diagnosis of enzyme deficiency-caused diseases. However, the time and resource required make it prohibitively expensive to experimentally determine the function of every enzyme. Therefore, computational enzyme function prediction has become increasingly important. In this paper, we develop such an approach, determining the enzyme function by predicting the Enzyme Commission number. Results We propose an end-to-end feature selection and classification model training approach, as well as an automatic and robust feature dimensionality uniformization method, DEEPre, in the field of enzyme function prediction. Instead of extracting manually crafted features from enzyme sequences, our model takes the raw sequence encoding as inputs, extracting convolutional and sequential features from the raw encoding based on the classification result to directly improve the prediction performance. The thorough cross-fold validation experiments conducted on two large-scale datasets show that DEEPre improves the prediction performance over the previous state-of-the-art methods. In addition, our server outperforms five other servers in determining the main class of enzymes on a separate low-homology dataset. Two case studies demonstrate DEEPre’s ability to capture the functional difference of enzyme isoforms. Availability and implementation The server could be accessed freely at http://www.cbrc.kaust.edu.sa/DEEPre. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Yu Li
- Electrical and Mathematical Sciences and Engineering Division (CEMSE), Computational Bioscience Research Center (CBRC), Computer, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Sheng Wang
- Electrical and Mathematical Sciences and Engineering Division (CEMSE), Computational Bioscience Research Center (CBRC), Computer, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Ramzan Umarov
- Electrical and Mathematical Sciences and Engineering Division (CEMSE), Computational Bioscience Research Center (CBRC), Computer, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Bingqing Xie
- Computer Science Department, Illinois Institute of Technology, Chicago, IL 60616, USA
| | - Ming Fan
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Lihua Li
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Xin Gao
- Electrical and Mathematical Sciences and Engineering Division (CEMSE), Computational Bioscience Research Center (CBRC), Computer, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
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159
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Wen J, Fan M, Chen J, Liu D, Xu X, Zhang J, Gu Y, Huang L. MA22.07 Prognostic Value of Distant Organ-Specific Metastases in Newly Diagnosed Lung Neuroendocrine Tumors: A Population-Based Study. J Thorac Oncol 2018. [DOI: 10.1016/j.jtho.2018.08.506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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160
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Han Y, Zhao T, Cheng X, Zhao M, Gong SH, Zhao YQ, Wu HT, Fan M, Zhu LL. Cortical Inflammation is Increased in a DSS-Induced Colitis Mouse Model. Neurosci Bull 2018; 34:1058-1066. [PMID: 30225764 DOI: 10.1007/s12264-018-0288-5] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 05/22/2018] [Indexed: 12/16/2022] Open
Abstract
While inflammatory bowel disease (IBD) might be a risk factor in the development of brain dysfunctions, the underlying mechanisms are largely unknown. Here, mice were treated with 5% dextran sodium sulfate (DSS) in drinking water and sacrificed on day 7. The serum level of IL-6 increased, accompanied by elevation of the IL-6 and TNF-α levels in cortical tissue. However, the endotoxin concentration in plasma and brain of mice with DSS-induced colitis showed a rising trend, but with no significant difference. We also found significant activation of microglial cells and reduction in occludin and claudin-5 expression in the brain tissue after DSS-induced colitis. These results suggested that DSS-induced colitis increases systemic inflammation which then results in cortical inflammation via up-regulation of serum cytokines. Here, we provide new information on the impact of colitis on the outcomes of cortical inflammation.
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Affiliation(s)
- Ying Han
- Center for Brain Disorders Research, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, 100069, China.,Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, 100850, China
| | - Tong Zhao
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, 100850, China
| | - Xiang Cheng
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, 100850, China
| | - Ming Zhao
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, 100850, China
| | - Sheng-Hui Gong
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, 100850, China
| | - Yong-Qi Zhao
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, 100850, China
| | - Hai-Tao Wu
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, 100850, China
| | - Ming Fan
- Center for Brain Disorders Research, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, 100069, China. .,Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, 100850, China. .,Co-innovation Center of Neuroregeneration, Nantong University, Nantong, 226001, China.
| | - Ling-Ling Zhu
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, 100850, China. .,Co-innovation Center of Neuroregeneration, Nantong University, Nantong, 226001, China.
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161
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Quinn SE, Dyer SD, Fan M, Keller VDJ, Johnson AC, Williams RJ. Predicting risks from down-the-drain chemicals in a developing country: Mexico and linear alkylbenzene sulfonate as a case study. Environ Toxicol Chem 2018; 37:2475-2486. [PMID: 29878446 DOI: 10.1002/etc.4181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 04/21/2018] [Accepted: 05/30/2018] [Indexed: 06/08/2023]
Abstract
It is recognized that the amount of natural dilution available can make a significant difference in the exposure and risk assessment of chemicals that emanate from wastewater treatment plants (WWTPs). However, data availability is a common limiting factor in exposure assessments for emerging markets. In the present study, we used a novel approach to derive dilution factors for the receiving waters within 5 km of wastewater discharge points in Mexico by combining locally measured river volumes, ecoregion categorization, data on WWTP capacity, and global river network models. Distributions of wastewater effluent into receiving stream dilution factors were developed for the entire country and organized by ecoregion type to explore spatial differences. The distribution of dilution factors in Mexico ranged from >1000 in tropical and temperate ecoregions to 1 in desert ecoregions. To demonstrate its utility, dilution factors were used to develop a probabilistic model to explore the potential ecological risks of the high-volume surfactant linear alkylbenzene sulfonate (LAS), commonly used in down-the-drain cleaning products. The predicted LAS river exposure values were below the predicted no-effect concentration in all regions. The methodology developed for Mexico can be used to derive refined exposure assessments in other countries with emerging markets throughout the world, resulting in more realistic risk assessments. Environ Toxicol Chem 2018;37:2475-2486. © 2018 SETAC.
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Affiliation(s)
| | | | - Ming Fan
- Procter & Gamble, Cincinnati, Ohio, USA
| | | | - Andrew C Johnson
- Centre for Ecology and Hydrology, Wallingford, Oxfordshire, United Kingdom
| | - Richard J Williams
- Centre for Ecology and Hydrology, Wallingford, Oxfordshire, United Kingdom
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Alexandrou A, Fan M, Juma S, Perks J, Vaughan A, Tepper C, Fu L, Woloschak G, Grdina D. Abstract LB-184: Core circadian clock component, PERIOD2, regulates adaptive radioprotection via PER2-β-Catenin controlled mitochondrial bioenergetics. Cancer Res 2018. [DOI: 10.1158/1538-7445.am2018-lb-184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Circadian clocks are intimately involved in the homeostatic maintenance of metabolic and physiological processes that may have increasingly important roles to enhance bone marrow transplantation success in cancer patients; to protect normal tissue surrounding tumors from the harmful effects of radio/chemotherapy; and to enhance the quality of diet and sleep for astronauts during space exploration. Herein, we report that expression of PERIOD2 (PER2; a core circadian clock component and “the inherent driver” of radioprotection) is required for adaptive protection against environmental radiation stress. PER2 expression is induced by exposure to low dose radiation (LDR; 10cGy) and siRNA blockade of PER2 ablates LDR-induced adaptive radioprotection. In addition, melatonin (N-acetyl-5-methoxytryptamine), a natural anti-oxidant and hypothalamic circadian synchronizer, stimulates PER2 expression and confers mice radioprotection through weight maintenance and increased survival. LDR-induced PER2 transcription is regulated by NF-κB and β-catenin and is released from phospho-glycogen synthase kinase-3ß (p-GSK3ß) in the WNT/β-catenin pathway. Unbound β-catenin interacts with the TCF/LEF domain on the Per2 promoter to promote feed-forward PER2-pGSK3β complex formation. Mitochondrial bioenergetics measured by oxygen consumption and ATP generation was attenuated in bone marrow isolated from PER2 mutant (Per2m/m) mice. Furthermore, RNA-seq profiling of bone marrow-derive progenitor hematopoietic stem cells (BM-pHSCs; Lin-/Sca1+/cKit+; LSK) cells isolated form LDR-treated wild-type (WT) versus Per2m/m mice showed a cluster of genes involved in mitochondrial bioenergetics and DNA repair capacity. These results demonstrate that a core circadian regulator plays an indispensable role in defending mammalian cells against environmental genotoxic stress through the PER2/β-catenin pathway, a potential therapeutic target to enhance cell survival under radiation.
Citation Format: Aris Alexandrou, Ming Fan, Shuaib Juma, Julian Perks, Andrew Vaughan, Clifford Tepper, Loning Fu, Gayle Woloschak, David Grdina. Core circadian clock component, PERIOD2, regulates adaptive radioprotection via PER2-β-Catenin controlled mitochondrial bioenergetics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-184.
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Affiliation(s)
| | - Ming Fan
- 2University of California at Davis, Sacramento, CA
| | - Shuaib Juma
- 2University of California at Davis, Sacramento, CA
| | - Julian Perks
- 2University of California at Davis, Sacramento, CA
| | | | | | - Loning Fu
- 3Baylor College of Medicine, Houston, TX
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163
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Cai WW, Mo DS, Fan M, Cai HC, Zhang GW, Wang WP, Shang XJ. [Fosfomycin tromethamine inhibits the expressions of TNF-α, IL-8 and IL-6 in the prostate tissue of rats with chronic bacterial prostatitis]. Zhonghua Nan Ke Xue 2018; 24:491-498. [PMID: 30173452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
OBJECTIVE To investigate the effects of fosfomycin tromethamine (FT) on the expressions of tumor necrosis factor-α (TNF-α), interleukin-8 (IL-8), and interleukin-6 (IL-6) in the prostate tissue of the rats with chronic bacterial prostatitis (CBP). METHODS We randomly divided 70 male SD rats into 7 groups of equal number: blank control, CBP model control, positive control, 14 d low-dose FT, 7 d low-dose FT, 14 d high-dose FT, and 7 d high-dose FT. The CBP model rats in the latter five groups were treated intragastrically with levofloxacin at 100 mg/kg/d for 30 days and FT at 200 mg/kg/d for 14 and 7 days and at 300 mg/kg/d for 14 and 7 days, respectively. Then we collected the prostate tissue from the animals for determination of the levels of TNF-α, IL-8 and IL-6 by ELISA. RESULTS Compared with the blank controls, the CBP model rats showed significantly increased levels of TNF-α ([19.83 ± 6.1] vs [32.93 ± 6.21] ng/g prot, P <0.01), IL-8 ([8.26 ± 0.52] vs [16.2 ± 2.84] ng/g prot, P <0.01) and IL-6 ([1.55 ± 0.11] vs [2.51 ± 1.06] ng/g prot, P <0.05) in the prostate tissue. In comparison with the CBP model controls, the levels of TNF-α and IL-8 were remarkably decreased in the groups of positive control ([20.54 ± 5.78] ng/g prot, P <0.01; [12.43 ± 4.02] ng/g prot, P <0.05), 14 d low-dose FT ([21.95 ± 6.48] ng/g prot, P <0.01; [11.11 ± 2.86] ng/g prot, P <0.01), 7 d low-dose FT ([23.8 ± 6.93] ng/g prot, P <0.05; [12.43 ± 4.02] ng/g prot, P <0.05), 14 d high-dose FT ([19.97 ± 2.58] ng/g prot, P <0.01; [8.83 ± 1.32] ng/g prot, P <0.01), and 7 d high-dose FT ([21.97 ± 3.38] ng/g prot, P <0.01; [12.68±1.97] ng/g prot, P <0.05). No statistically significant differences were observed between the positive control and FT groups in the contents of TNF-α, IL-8 or IL-6 (P >0.05). The expression of IL-6 was markedly reduced in the 14 d high-dose FT group as compared with the model controls ([1.76 ± 0.46] vs [2.51 ± 1.06] ng/g prot, P<0.05) but exhibited no significant difference between the CBP model control and the other groups (P >0.05). CONCLUSIONS Fosfomycin tromethamine inhibits the expressions of TNF-α, IL-8 and IL-6 in the prostate tissue, suppresses its inflammatory reaction, promotes the repair of damaged prostatic structure, and thus contributes to the treatment of chronic bacterial prostatitis in rats.
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Affiliation(s)
- Wen-Wei Cai
- Center of Reproductive Medicine, Jiaxing Women and Children's Hospital, Jiaxing, Zhejiang 314000, China
| | - Dun-Sheng Mo
- Department of Urology, Liuzhou Workers' Hospital / The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi 545005, China
| | | | - Hong-Cai Cai
- Family Planning Research Institute / Center of Reproductive Medicine, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Guo-Wei Zhang
- Department of Andrology, Jinling Hospital Affiliated to Southern Medical University / Nanjing General Hospital of Nanjing Military Region, Nanjing, Jiangsu 210002, China
| | - Wei-Piong Wang
- Institute of Medical Laboratory, Jinling Hospital Affiliated to Southern Medical University / Nanjing General Hospital of Nanjing Military Region, Nanjing, Jiangsu 210002, China
| | - Xue-Jun Shang
- Department of Andrology, Jinling Hospital Affiliated to Southern Medical University / Nanjing General Hospital of Nanjing Military Region, Nanjing, Jiangsu 210002, China
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164
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Chen M, Wang J, Fan M, Lang JY, Yang J. Prognostic and functional characterization of AQP1 and AQP4 in patients with glioma. J Clin Oncol 2018. [DOI: 10.1200/jco.2018.36.15_suppl.e14063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
- Meihua Chen
- Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jichuan Wang
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Ming Fan
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jin Yi Lang
- Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jialin Yang
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
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Yang J, Chen M, Wang J, Lang JY, Fan M, Pan L, Wang J. Identification of potential oncogenic LncRNA RP11-474D1.3 in colorectal cancer. J Clin Oncol 2018. [DOI: 10.1200/jco.2018.36.15_suppl.e15611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
- Jialin Yang
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Meihua Chen
- Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jie Wang
- Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jin Yi Lang
- Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Ming Fan
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Li Pan
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jichuan Wang
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
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166
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Luo L, Chen T, Li Z, Zhang Z, Zhao W, Fan M. Heteroatom self-doped activated biocarbons from fir bark and their excellent performance for carbon dioxide adsorption. J CO2 UTIL 2018. [DOI: 10.1016/j.jcou.2018.03.014] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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167
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Sun M, Xu N, Li C, Wu D, Zou J, Wang Y, Luo L, Yu M, Zhang Y, Wang H, Shi P, Chen Z, Wang J, Lu Y, Li Q, Wang X, Bi Z, Fan M, Fu L, Yu J, Hao M. The public health emergency management system in China: trends from 2002 to 2012. BMC Public Health 2018; 18:474. [PMID: 29642902 PMCID: PMC5896068 DOI: 10.1186/s12889-018-5284-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Accepted: 03/08/2018] [Indexed: 11/10/2022] Open
Abstract
Background Public health emergencies have challenged the public health emergency management systems (PHEMSs) of many countries critically and frequently since this century. As the world’s most populated country and the second biggest economy in the world, China used to have a fragile PHEMS; however, the government took forceful actions to build PHEMS after the 2003 SARS outbreak. After more than one decade’s efforts, we tried to assess the improvements and problems of China’s PHEMS between 2002 and 2012. Methods We conducted two rounds of national surveys and collected the data of the year 2002 and 2012, including all 32 provincial, 139 municipal, and 489 county CDCs. The municipal and county CDCs were selected by systematic random sampling. Twenty-one indicators of four stages (preparation, readiness, response and recovery) from the National Assessment Criteria for CDC Performance were chosen to assess the ten-year trends. Results At the preparation stage, organization, mechanisms, workforce, and stockpile across all levels and regions were significantly improved after one decade’s efforts. At the readiness stage, the capability for formulating an emergency plan was also significantly improved during the same period. At the response stage, internet-based direct reporting was 98.8%, and coping scores were nearly full points of ten in 2012. At the recovery stage, the capabilities were generally lower than expected. Conclusions Due to forceful leadership, sounder regulations, and intensive resources, China’s PHEMS has been improved at the preparation, readiness, and response stages; however, the recovery stage was still weak and could not meet the requirements of crisis management and preventive governance. In addition, CDCs in the Western region and counties lagged behind in performance on most indicators. Future priorities should include developing the recovery stage, establishing a closed feedback loop, and strengthening the capabilities of CDCs in Western region and counties.
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Affiliation(s)
- Mei Sun
- Research Institute of Health Development Strategies & Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, 177 box, 130 Dong'an Road, Shanghai, 200032, China.,Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China (Fudan University), School of Public Health, Fudan University, Shanghai, China
| | - Ningze Xu
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China (Fudan University), School of Public Health, Fudan University, Shanghai, China
| | - Chengyue Li
- Research Institute of Health Development Strategies & Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, 177 box, 130 Dong'an Road, Shanghai, 200032, China
| | - Dan Wu
- Shanghai Health Education Institution, Shanghai, China
| | - Jiatong Zou
- Research Institute of Health Development Strategies & Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, 177 box, 130 Dong'an Road, Shanghai, 200032, China
| | - Ying Wang
- Research Institute of Health Development Strategies & Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, 177 box, 130 Dong'an Road, Shanghai, 200032, China
| | - Li Luo
- Research Institute of Health Development Strategies & Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, 177 box, 130 Dong'an Road, Shanghai, 200032, China
| | - Mingzhu Yu
- Bureau of Disease Control and Prevention of National Health Commission of the People's Republic of China, Beijing, China
| | - Yu Zhang
- Health and Family Planning Commission of Hubei Province, Wuhan, China
| | - Hua Wang
- Health and Family Planning Commission of Jiangsu Province, Nanjing, China
| | - Peiwu Shi
- Zhejiang Academy of Medical Sciences, Hangzhou, China
| | - Zheng Chen
- National Grassroots Health Prevention Group, Shanghai, China
| | - Jian Wang
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yueliang Lu
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Qi Li
- Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, China
| | - Xinhua Wang
- Gansu Provincial Center for Disease Control and Prevention, Lanzhou, China
| | - Zhenqiang Bi
- Shandong Provincial Center for Disease Control and Prevention, Jinan, China
| | - Ming Fan
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China
| | - Liping Fu
- Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, China
| | - Jingjin Yu
- Bureau of Disease Control and Prevention of National Health Commission of the People's Republic of China, Beijing, China
| | - Mo Hao
- Research Institute of Health Development Strategies & Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, 177 box, 130 Dong'an Road, Shanghai, 200032, China.
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168
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Abstract
Quinacrine, widely used to treat parasitic diseases, binds to cell membranes. We previously found that quinacrine pretreatment reduced microwave radiation damage in rat hippocampal neurons, but the molecular mechanism remains poorly understood. Considering the thermal effects of microwave radiation and the protective effects of quinacrine on heat damage in cells, we hypothesized that quinacrine would prevent microwave radiation damage to cells in a mechanism associated with cell membrane stability. To test this, we used retinoic acid to induce PC12 cells to differentiate into neuron-like cells. We then pretreated the neurons with quinacrine (20 and 40 mM) and irradiated them with 50 mW/cm2 microwaves for 3 or 6 hours. Flow cytometry, atomic force microscopy and western blot assays revealed that irradiated cells pretreated with quinacrine showed markedly less apoptosis, necrosis, and membrane damage, and greater expression of heat shock protein 70, than cells exposed to microwave irradiation alone. These results suggest that quinacrine stabilizes the neuronal membrane structure by upregulating the expression of heat shock protein 70, thus reducing neuronal injury caused by microwave radiation.
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Affiliation(s)
- Xue-Feng Ding
- Department of Cognitive Sciences, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Yan Wu
- Department of Cognitive Sciences, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Wen-Rui Qu
- Hand & Foot Surgery and Reparative & Reconstructive Surgery Center, Orthopedic Hospital of the Second Hospital of Jilin University, Changchun, Jilin Province, China
| | - Ming Fan
- Department of Cognitive Sciences, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Yong-Qi Zhao
- Department of Cognitive Sciences, Beijing Institute of Basic Medical Sciences, Beijing, China
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169
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Xi D, Li L, Zhang J, Shan Y, Dai G, Fan M, Zheng B. Improvement of Mammographic Mass Classification Performance Using an Intelligent Data Fusion Method. j med imaging hlth inform 2018. [DOI: 10.1166/jmihi.2018.2297] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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170
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Fan M, He T, Zhang P, Cheng H, Zhang J, Gao X, Li L. Diffusion-weighted imaging features of breast tumours and the surrounding stroma reflect intrinsic heterogeneous characteristics of molecular subtypes in breast cancer. NMR Biomed 2018; 31:e3869. [PMID: 29244222 DOI: 10.1002/nbm.3869] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Revised: 10/28/2017] [Accepted: 10/30/2017] [Indexed: 06/07/2023]
Abstract
Breast cancer heterogeneity is the main obstacle preventing the identification of patients with breast cancer with poor prognoses and treatment responses; however, such heterogeneity has not been well characterized. The purpose of this retrospective study was to reveal heterogeneous patterns in the apparent diffusion coefficient (ADC) signals in tumours and the surrounding stroma to predict molecular subtypes of breast cancer. A dataset of 126 patients with breast cancer, who underwent preoperative diffusion-weighted imaging (DWI) on a 3.0-T image system, was collected. Breast images were segmented into regions comprising the tumour and surrounding stromal shells in which features that reflect heterogeneous ADC signal distribution were extracted. For each region, imaging features were computed, including the mean, minimum, variance, interquartile range (IQR), range, skewness, kurtosis and entropy of ADC values. Univariate and stepwise multivariate logistic regression modelling was performed to identify the magnetic resonance imaging features that optimally discriminate luminal A, luminal B, human epidermal growth factor 2 (HER2)-enriched and basal-like molecular subtypes. The performance of the predictive models was evaluated using the area under the receiver operating characteristic curve (AUC). Univariate logistic regression analysis showed that the skewness in the tumour boundary achieved an AUC of 0.718 for discrimination between luminal A and non-luminal A tumours, whereas the IQR of the ADC value in the tumour boundary had an AUC of 0.703 for classification of the HER2-enriched subtype. Imaging features in the tumour boundary and the proximal peritumoral stroma corresponded to a higher overall prediction performance than those in other regions. A multivariate logistic regression model combining features in all the regions achieved an overall AUC of 0.800 for the classification of the four tumour subtypes. These findings suggest that features in the tumour boundary and stroma around the tumour may be further assessed as potential predictors of molecular subtypes of breast cancer.
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Affiliation(s)
- Ming Fan
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Ting He
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Peng Zhang
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Hu Cheng
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Juan Zhang
- Zhejiang Cancer Hospital, Zhejiang, Hangzhou, China
| | - Xin Gao
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal, Saudi Arabia
| | - Lihua Li
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
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171
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Yang HH, Liu FJ, Wu Y, Zhu Q, Cheng JX, Fan M, Wu HT. Notch1 gain of function in skeletal muscles leads to neuromuscular junction formation defects and neonatal death. CNS Neurosci Ther 2018; 24:456-459. [PMID: 29345116 DOI: 10.1111/cns.12808] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Revised: 12/30/2017] [Accepted: 12/31/2017] [Indexed: 12/14/2022] Open
Affiliation(s)
- Hai-Hong Yang
- Department of Neurobiology, Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing, China
| | - Feng-Jiao Liu
- Department of Neurobiology, Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing, China
| | - Yan Wu
- Department of Neurobiology, Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing, China
| | - Qian Zhu
- Department of Neurobiology, Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing, China
| | - Juan-Xian Cheng
- Department of Neurobiology, Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing, China
| | - Ming Fan
- Department of Cognitive Sciences, Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing, China.,Key Laboratory of Neuroregeneration, Co-innovation Center of Neuroregeneration, Nantong University, Nantong, China
| | - Hai-Tao Wu
- Department of Neurobiology, Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing, China.,Key Laboratory of Neuroregeneration, Co-innovation Center of Neuroregeneration, Nantong University, Nantong, China
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172
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Li Y, Fan M, Cheng H, Zhang P, Zheng B, Li L. Assessment of global and local region-based bilateral mammographic feature asymmetry to predict short-term breast cancer risk. Phys Med Biol 2018; 63:025004. [PMID: 29226849 DOI: 10.1088/1361-6560/aaa096] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
This study aims to develop and test a new imaging marker-based short-term breast cancer risk prediction model. An age-matched dataset of 566 screening mammography cases was used. All 'prior' images acquired in the two screening series were negative, while in the 'current' screening images, 283 cases were positive for cancer and 283 cases remained negative. For each case, two bilateral cranio-caudal view mammograms acquired from the 'prior' negative screenings were selected and processed by a computer-aided image processing scheme, which segmented the entire breast area into nine strip-based local regions, extracted the element regions using difference of Gaussian filters, and computed both global- and local-based bilateral asymmetrical image features. An initial feature pool included 190 features related to the spatial distribution and structural similarity of grayscale values, as well as of the magnitude and phase responses of multidirectional Gabor filters. Next, a short-term breast cancer risk prediction model based on a generalized linear model was built using an embedded stepwise regression analysis method to select features and a leave-one-case-out cross-validation method to predict the likelihood of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) values significantly increased from 0.5863 ± 0.0237 to 0.6870 ± 0.0220 when the model trained by the image features extracted from the global regions and by the features extracted from both the global and the matched local regions (p = 0.0001). The odds ratio values monotonically increased from 1.00-8.11 with a significantly increasing trend in slope (p = 0.0028) as the model-generated risk score increased. In addition, the AUC values were 0.6555 ± 0.0437, 0.6958 ± 0.0290, and 0.7054 ± 0.0529 for the three age groups of 37-49, 50-65, and 66-87 years old, respectively. AUC values of 0.6529 ± 0.1100, 0.6820 ± 0.0353, 0.6836 ± 0.0302 and 0.8043 ± 0.1067 were yielded for the four mammography density sub-groups (BIRADS from 1-4), respectively. This study demonstrated that bilateral asymmetry features extracted from local regions combined with the global region in bilateral negative mammograms could be used as a new imaging marker to assist in the prediction of short-term breast cancer risk.
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Affiliation(s)
- Yane Li
- College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, People's Republic of China
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173
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Hua J, Zang L, Zhao H, Liu T, Fan M, Chen T, Cao Z, Tian Y, Zhang Z. Studying the origin of fluorescence emissions of neodymium porphyrin based on the analysis of energy level structure. J PORPHYR PHTHALOCYA 2017. [DOI: 10.1142/s1088424617500651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
This paper studies the origin of fluorescence emissions of metalloporphyrins. The absorption spectrum of neodymium-coordinated hematoporphyrin monomethyl ether (Nd-HMME) was found to have four Q bands, which is different from the accepted knowledge (two Q bands). The absorbance of Nd-HMME was comparable to the corresponding absorbance of HMME at wavelengths of 538 nm and 572 nm, but the absorbance of Nd-HMME at wavelengths of 502 nm and 622 nm was approximately 1/30 of that at 572 nm. The doping of Nd[Formula: see text] enhanced the symmetry of HMME, and led to changes in energy level properties. Moreover, Nd-HMME still exhibited two fluorescence peaks at 624 nm and 686 nm, similar to HMME, which can be explained by the observation of a weak absorption peak of Nd-HMME at 622 nm.
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Affiliation(s)
- Jianyu Hua
- Condensed Matter Science and Technology Institute, Harbin Institute of Technology, Harbin 150080, China
| | - Lixin Zang
- Condensed Matter Science and Technology Institute, Harbin Institute of Technology, Harbin 150080, China
| | - Huimin Zhao
- School of Physics and Electronics, Shandong Normal University, Ji’nan 250014, China
| | - Ting Liu
- Condensed Matter Science and Technology Institute, Harbin Institute of Technology, Harbin 150080, China
| | - Ming Fan
- Shenzhen Micromed Tech. Co., Ltd., Shenzhen, 518109, China
| | - Tong Chen
- Shenzhen Micromed Tech. Co., Ltd., Shenzhen, 518109, China
| | - Zhengyu Cao
- Division of Cardiology, The First Affiliated Hospital, Harbin Medical University, Harbin 150001, China
| | - Ye Tian
- Division of Cardiology, The First Affiliated Hospital, Harbin Medical University, Harbin 150001, China
| | - Zhiguo Zhang
- Condensed Matter Science and Technology Institute, Harbin Institute of Technology, Harbin 150080, China
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174
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Zhang YY, Liu SH, Fang T, Fan M, Zhu LL, Zhao YQ. [Change of intracellular Ca 2+ concentration and related signaling pathway in hippocampal cells after high-intensity sound exposure]. Sheng Li Xue Bao 2017; 69:737-742. [PMID: 29270588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
High-intensity sound often leads to the dysfunction and impairment of central nervous system (CNS), but the underlying mechanism is unclear. The present study was aimed to investigate the related mechanisms of CNS lesions in Bama miniature pig model treated with high-intensity sound. The pigs with normal hearing were divided into control and high-intensity sound (900 Hz-142 dB SPL, 15 min) groups. After the treatment, hippocampi were collected immediately. Fluo-4 was used to indicate intracellular Ca2+ concentration ([Ca2+]i) change. Real-time PCR and Western blot were used to detect mRNA and protein expressions of calcium-sensing receptor, L-Ca2+ channel α2/δ1 subunit, PKC and PI3K, respectively. DAPI staining was used to identify nuclear features. The result showed that high-intensity sound exposure resulted in significantly swollen cell nucleus and increased [Ca2+]i in hippocampal cells. Compared with control group, high-intensity sound group showed increased levels of PI3K, PKC and L-Ca2+ channel α2/δ1 subunit mRNA expressions, as well as up-regulated PKC and calcium-sensing receptor protein expressions. These results suggest that the high-intensity sound activates PKC signaling pathway and induces calcium overload, eventually leads to hippocampal injury, which would supply a novel strategy to prevent nervous system from high-intensity sound-induced injury.
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Affiliation(s)
- Yi-Yao Zhang
- The Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing 100850, China
- The Department of Special Clinical Examination, Air Force General Hospital of PLA, Beijing 100042, China
| | - Shu-Hong Liu
- The Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing 100850, China
| | - Tao Fang
- The Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing 100850, China
| | - Ming Fan
- The Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing 100850, China
| | - Ling-Ling Zhu
- The Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing 100850, China.
| | - Yong-Qi Zhao
- The Institute of Basic Medical Sciences, Academy of Military Medical Sciences, Beijing 100850, China.
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175
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Fan M, Cheng H, Zhang P, Gao X, Zhang J, Shao G, Li L. DCE-MRI texture analysis with tumor subregion partitioning for predicting Ki-67 status of estrogen receptor-positive breast cancers. J Magn Reson Imaging 2017; 48:237-247. [PMID: 29219225 DOI: 10.1002/jmri.25921] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2017] [Accepted: 11/22/2017] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Breast tumor heterogeneity is related to risk factors that lead to worse prognosis, yet such heterogeneity has not been well studied. PURPOSE To predict the Ki-67 status of estrogen receptor (ER)-positive breast cancer patients via analysis of tumor heterogeneity with subgroup identification based on patterns of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). STUDY TYPE Retrospective study. POPULATION Seventy-seven breast cancer patients with ER-positive breast cancer were investigated, of whom 51 had low Ki-67 expression. FIELD STRENGTH/SEQUENCE T1 -weighted 3.0T DCE-MR images. ASSESSMENT Each tumor was partitioned into multiple subregions using three methods based on patterns of dynamic enhancement: 1) time to peak (TTP), 2) peak enhancement rate (PER), and 3) kinetic pattern clustering (KPC). In each tumor subregion, 18 texture features were computed. STATISTICAL TESTING Univariate and multivariate logistic regression analyses were performed using a leave-one-out-based cross-validation (LOOCV) method. The partitioning results were compared with the same feature extraction methods across the whole tumor. RESULTS In the univariate analysis, the best-performing feature was the texture statistic of sum variance in the tumor subregion with early TTP for differentiating between patients with high and low Ki-67 expression (area under the receiver operating characteristic curves, AUC = 0.748). Multivariate analysis showed that features from the tumor subregion associated with early TTP yielded the highest performance (AUC = 0.807) among the subregions for predicting the Ki-67 status. Among all regions, the tumor area with high PER at a precontrast MR image achieved the highest performance (AUC = 0.722), while the subregion that exhibited the highest overall enhancement rate based on KPC had an AUC of 0.731. These three models based on intratumoral texture analysis significantly (P < 0.01) outperformed the model using features from the whole tumor (AUC = 0.59). DATA CONCLUSION Texture analysis of intratumoral heterogeneity has the potential to serve as a valuable clinical marker to enhance the prediction of breast cancer prognosis. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017.
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Affiliation(s)
- Ming Fan
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Hu Cheng
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Peng Zhang
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Xin Gao
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal, Saudi Arabia
| | - Juan Zhang
- Zhejiang Cancer Hospital, Zhejiang, Hangzhou, China
| | | | - Lihua Li
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
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176
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Ma Y, Xin L, Tan H, Fan M, Li J, Jia Y, Ling Z, Chen Y, Hu X. Chitosan membrane dressings toughened by glycerol to load antibacterial drugs for wound healing. Materials Science and Engineering: C 2017; 81:522-531. [DOI: 10.1016/j.msec.2017.08.052] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 08/06/2017] [Accepted: 08/10/2017] [Indexed: 12/22/2022]
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177
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Fan M, Liu Z, Dyer S, Xia P, Zhang X. Environmental risk assessment of polycyclic musks HHCB and AHTN in consumer product chemicals in China. Sci Total Environ 2017; 599-600:771-779. [PMID: 28499225 DOI: 10.1016/j.scitotenv.2017.05.036] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Revised: 05/02/2017] [Accepted: 05/03/2017] [Indexed: 06/07/2023]
Abstract
An environmental risk assessment (ERA) framework was recently developed for consumer product chemicals in China using a tiered approach, applying an existing Chinese regulatory qualitative method in Tier Zero and, then, utilizing deterministic and probabilistic methods for Tiers One and Two. The exposure assessment methodology in the framework applied conditions specific to China including physical setting, infrastructure, and consumers' habits and practices. Furthermore, two scenarios were identified for quantitatively assessing environmental exposure: (1) Urban with wastewater treatment, and; (2) Rural without wastewater treatment (i.e., direct-discharge of wastewater). Upon a brief discussion on the framework methodology, this paper primarily presented a case study conducted using this new approach for assessing two fragrance chemicals, the polycyclic musks HHCB (Galaxolide, 1,3,4,6,7,8-hexahydro-4,6,6,7,8,8-hexamethylcyclopenta-[gamma]-2-benzopyran) and AHTN (Tonalide, 7-acetyl-1,1,3,4,4,6-hexamethyl-1,2,3,4-tetrahydronaphthalene). Both HHCB and AHTN are widely used as fragrances in a variety of consumer products in China, and occurrences of both compounds have been reported in wastewater influents, effluents, and sludge, in addition to surface water and sediments across several major metropolitan regions throughout China. This case study illustrated the very conservative nature of Tier Zero, which indicated a high risk potential of the fragrances to receiving water aquatic communities due to the fragrance's non-ready biodegradability and eco-toxicity profiles. However, the higher-tiered assessments (including deterministic and site-specific probabilistic) demonstrated greater environmental realism with the conclusion of HHCB and AHTN posing minimal risk, consistent with local monitoring data as well as a recent similar study conducted in the United States.
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Affiliation(s)
- Ming Fan
- Global Product Stewardship, The Procter and Gamble Company, 8700 Mason Montgomery Road, Mason, OH 45040, United States.
| | - Zhengtao Liu
- State Environmental Protection Key Laboratory for Ecological Effect and Risk Assessment of Chemicals (MEP), Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Scott Dyer
- Global Product Stewardship, The Procter and Gamble Company, 8700 Mason Montgomery Road, Mason, OH 45040, United States
| | - Pu Xia
- State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing, Jiangsu 210046, China
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing, Jiangsu 210046, China
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178
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Kang X, Zhou H, Xuan T, Yan W, Gong Y, Dai L, Guan Y, Yang Y, Yang H, Fu H, Fan M, Lin Y, Liang Z, Xiong H, Yang L, Yi X, Chen K. P3.16-053 Genomic Challenges for Lung Cancers with Multiple Pulmonary Sites of Involvement. J Thorac Oncol 2017. [DOI: 10.1016/j.jtho.2017.09.1860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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179
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Liu LL, Li D, He YL, Zhou YZ, Gong SH, Wu LY, Zhao YQ, Huang X, Zhao T, Xu L, Wu KW, Li MG, Zhu LL, Fan M. miR-210 protects renal cell against hypoxia-induced apoptosis by targeting HIF-1 alpha. Mol Med 2017; 23:258-271. [PMID: 29387863 DOI: 10.2119/molmed.2017.00013] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Accepted: 08/21/2017] [Indexed: 01/01/2023] Open
Abstract
The kidney is vulnerable to hypoxia-induced injury. One of the mechanisms underlying this phenomenon is cell apoptosis triggered by hypoxia-inducible factor-1-alpha (HIF-1α) activation. MicroRNA-210 (miR-210) is known to be induced by HIF-1α and can regulate various pathological processes, but its role in hypoxic kidney injury remains unclear. Here, in both kinds of rat systemic hypoxia and local kidney hypoxia models, we found miR-210 levels were upregulated significantly in injured kidney, especially in renal tubular cells. A similar increase was observed in hypoxia-treated human renal tubular HK-2 cells. We also verified that miR-210 can directly suppress HIF-1α expression by targeting the 3' untranslated region (UTR) of HIF-1α mRNA in HK-2 cells in severe hypoxia. Accordingly, miR-210 overexpression caused significant inhibition of the HIF-1α pathway and attenuated apoptosis caused by hypoxia, while miR-210 knockdown exerted the opposite effect. Taken together, our findings verify that miR-210 is involved in the molecular response in hypoxic kidney lesions in vivo and attenuates hypoxia-induced renal tubular cell apoptosis by targeting HIF-1α directly and suppressing HIF-1α pathway activation in vitro.
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Affiliation(s)
- Li-Li Liu
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China.,Navy Aviation and Diving Medical Center, Navy General Hospital of PLA, Beijing, China
| | - Dahu Li
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China
| | - Yun-Ling He
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China
| | - Yan-Zhao Zhou
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China
| | - Sheng-Hui Gong
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China
| | - Li-Ying Wu
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China
| | - Yong-Qi Zhao
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China
| | - Xin Huang
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China
| | - Tong Zhao
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China
| | - Lun Xu
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China
| | - Kui-Wu Wu
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China
| | - Ming-Gao Li
- Navy Aviation and Diving Medical Center, Navy General Hospital of PLA, Beijing, China
| | - Ling-Ling Zhu
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China.,Co-innovation Center of Neuroregeneration, Nantong University, Nantong, China
| | - Ming Fan
- Department of Cognitive Science, Institute of Basic Medical Sciences, Beijing, China.,Co-innovation Center of Neuroregeneration, Nantong University, Nantong, China.,Beijing Institute for Brain Disorders, Beijing, China
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180
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Fan M, Yang J, Wang J, Wang J. The Optimal Management of Postoperative Radiation Therapy in Elderly Patients With Stage I Endometrial Cancer—A National Database Retrospective Analysis. Int J Radiat Oncol Biol Phys 2017. [DOI: 10.1016/j.ijrobp.2017.06.1295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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181
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Nicholson S, Fan M, Hodges R, Higgins M. Learning From Experience: Development of a Cognitive Task List to Perform a Caesarean Section in the Obese Parturient. Journal of Obstetrics and Gynaecology Canada 2017; 39:724-725. [DOI: 10.1016/j.jogc.2017.03.125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Revised: 03/27/2017] [Accepted: 03/28/2017] [Indexed: 10/19/2022]
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182
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Fan M, Wu G, Cheng H, Zhang J, Shao G, Li L. Radiomic analysis of DCE-MRI for prediction of response to neoadjuvant chemotherapy in breast cancer patients. Eur J Radiol 2017; 94:140-147. [DOI: 10.1016/j.ejrad.2017.06.019] [Citation(s) in RCA: 83] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 04/29/2017] [Accepted: 06/26/2017] [Indexed: 01/31/2023]
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183
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He J, Tang Z, Zhao Y, Fan M, Dyer SD, Belanger SE, Wu F. The Combined QSAR-ICE Models: Practical Application in Ecological Risk Assessment and Water Quality Criteria. Environ Sci Technol 2017; 51:8877-8878. [PMID: 28737934 DOI: 10.1021/acs.est.7b02736] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Affiliation(s)
- Jia He
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences , Beijing 100012, China
| | - Zhi Tang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences , Beijing 100012, China
| | - Yuanhui Zhao
- School of Environment, Northeast Normal University , Changchun, 130027, China
| | - Ming Fan
- Global Product Stewardship, Procter and Gamble Company, 8700 Mason Montgomery Road, Mason, Ohio 45040, United States
| | - Scott D Dyer
- Global Product Stewardship, Procter and Gamble Company, 8700 Mason Montgomery Road, Mason, Ohio 45040, United States
| | - Scott E Belanger
- Global Product Stewardship, Procter and Gamble Company, 8700 Mason Montgomery Road, Mason, Ohio 45040, United States
| | - Fengchang Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences , Beijing 100012, China
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184
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Chen X, Liu Y, Fan M, Wang Z, Wu W, Wang J. Thermal and chemical inactivation of Lactobacillus virulent bacteriophage. J Dairy Sci 2017; 100:7041-7050. [PMID: 28668532 DOI: 10.3168/jds.2016-12451] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 05/12/2017] [Indexed: 11/19/2022]
Abstract
The effect of thermal treatments and several biocides on the viability of Lactobacillus virulent phage P1 was evaluated. Times to achieve 99% inactivation (T99) of phage at different treatment conditions were calculated. The thermal treatments applied were 63, 72, and 90°C in 3 suspension media (de Man, Rogosa, Sharpe broth, reconstituted skim milk, and Tris magnesium gelatin buffer). Phage P1 was completely inactivated in 5 and 10 min at 90 and 72°C, respectively; however, reconstituted skim milk provided better thermal protection at 63°C. When phage P1 was treated with various biocides, 800 mg/L of sodium hypochlorite was required for total inactivation (∼7.3 log reduction) within 60 min, whereas treatment with 100% ethanol resulted in only a ∼4.7 log reduction, and 100% isopropanol resulted in a 5.2-log reduction. Peracetic acid (peroxyacetic acid) at the highest concentration used (0.45%) resulted in only a ∼4.-log reduction of phage within 60 min. The results of this study provide additional information on effective treatments for the eradication of potential phage infections in dairy plants.
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Affiliation(s)
- X Chen
- Key Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, Inner Mongolia Agricultural University, Hohhot, 010018, P. R. China
| | - Y Liu
- Key Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, Inner Mongolia Agricultural University, Hohhot, 010018, P. R. China
| | - M Fan
- Key Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, Inner Mongolia Agricultural University, Hohhot, 010018, P. R. China
| | - Z Wang
- Key Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, Inner Mongolia Agricultural University, Hohhot, 010018, P. R. China
| | - W Wu
- Key Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, Inner Mongolia Agricultural University, Hohhot, 010018, P. R. China
| | - J Wang
- Key Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, Inner Mongolia Agricultural University, Hohhot, 010018, P. R. China.
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185
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Fan M, Wong T. ERRORLESS TRAINING CHANGES VISUOMOTOR CONTROL IN REACHING UNDER VISUAL DEFICIENCY AMONG OLD ADULTS. Innov Aging 2017. [DOI: 10.1093/geroni/igx004.898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- M. Fan
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - T. Wong
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
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186
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Ding X, Wang H, Zhao Y, Peng W, Zhang Q, Fan M, Suo WZ. [P2–085]: THE USE OF A FULL SPECTRUM OF FEARFUL CHALLENGE INCREASES THE SENSITIVITY FOR ASSESSING RODENT FEAR AND ANXIETY. Alzheimers Dement 2017. [DOI: 10.1016/j.jalz.2017.06.734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Xue‐Feng Ding
- Beijing Institute of Basic Medical SciencesBeijingChina
- Veterans Affairs Medical CenterKansas CityMOUSA
| | - He‐Jun Wang
- The Third People's Hospital of ShizuishanShizuishanChina
| | - Yong‐Qi Zhao
- Beijing Institute of Basic Medical SciencesBeijingChina
| | - Wei Peng
- Veterans Affairs Medical CenterKansas CityMOUSA
| | - Qiang Zhang
- Veterans Affairs Medical CenterKansas CityMOUSA
| | - Ming Fan
- Beijing Institute of Basic Medical SciencesBeijingChina
| | - William Z. Suo
- Veterans Affairs Medical CenterKansas CityMOUSA
- University of Kansas Medical CenterKansas CityKSUSA
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187
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Navas-Moreno M, Mehrpouyan M, Chernenko T, Candas D, Fan M, Li JJ, Yan M, Chan JW. Nanoparticles for live cell microscopy: A surface-enhanced Raman scattering perspective. Sci Rep 2017; 7:4471. [PMID: 28667313 PMCID: PMC5493633 DOI: 10.1038/s41598-017-04066-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Accepted: 05/11/2017] [Indexed: 11/09/2022] Open
Abstract
Surface enhanced Raman scattering (SERS) nanoparticles are an attractive alternative to fluorescent probes for biological labeling because of their photostability and multiplexing capabilities. However, nanoparticle size, shape, and surface properties are known to affect nanoparticle-cell interactions. Other issues such as the formation of a protein corona and antibody multivalency interfere with the labeling properties of nanoparticle-antibody conjugates. Hence, it is important to consider these aspects in order to validate such conjugates for live cell imaging applications. Using SERS nanoparticles that target HER2 and CD44 in breast cancer cells, we demonstrate labeling of fixed cells with high specificity that correlates well with fluorescent labels. However, when labeling live cells to monitor surface biomarker expression and dynamics, the nanoparticles are rapidly uptaken by the cells and become compartmentalized into different cellular regions. This behavior is in stark contrast to that of fluorescent antibody conjugates. This study highlights the impact of nanoparticle internalization and trafficking on the ability to use SERS nanoparticle-antibody conjugates to monitor cell dynamics.
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Affiliation(s)
- Maria Navas-Moreno
- University of California-Davis, Center for Biophotonics, Sacramento, 95817, USA
| | | | | | - Demet Candas
- University of California-Davis, Dept. of Radiation Oncology, Sacramento, 95817, USA
| | - Ming Fan
- University of California-Davis, Dept. of Radiation Oncology, Sacramento, 95817, USA
| | - Jian Jian Li
- University of California-Davis, Dept. of Radiation Oncology, Sacramento, 95817, USA
| | - Ming Yan
- BD Biosciences, San Jose, 95131, USA
| | - James W Chan
- University of California-Davis, Center for Biophotonics, Sacramento, 95817, USA.
- University of California-Davis, Dept. of Pathology and Laboratory Medicine, Sacramento, 95817, USA.
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188
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Li C, Sun M, Wang Y, Luo L, Yu M, Zhang Y, Wang H, Shi P, Chen Z, Wang J, Lu Y, Li Q, Wang X, Bi Z, Fan M, Fu L, Yu J, Hao M. The Centers for Disease Control and Prevention System in China: Trends From 2002-2012. Am J Public Health 2017; 106:2093-2102. [PMID: 27831781 DOI: 10.2105/ajph.2016.303508] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To assess the improvements of the Chinese Centers for Disease Control and Prevention (CDCs) system between 2002 and 2012, and problems the system has encountered. METHODS We obtained data from 2 national cross-sectional surveys in 2006 and 2013, including 32 provincial, 139 municipal, and 489 county-level CDCs throughout China. We performed a pre-post comparative analysis to determine trends in resource allocation and service delivery. RESULTS The overall completeness of public health services significantly increased from 47.4% to 76.6%. Furthermore, the proportion of CDC staff with bachelor's or higher degrees increased from 14.6% to 32.6%, and governmental funding per CDC increased 5.3-fold (1.283-8.098 million yuan). The working area per CDC staff increased from 37.9 square meters to 63.3 square meters, and configuration rate of type A devices increased from 28.1% to 65.0%. Remaining problems included an 11.9% reduction in staff and the fact that financial investments covered only 71.1% of actual expenditures. CONCLUSIONS China's CDC system has progressed remarkably, enabling quicker responses to emergent epidemics. Future challenges include establishing a sustainable financing mechanism and retaining a well-educated, adequately sized public health workforce.
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Affiliation(s)
- Chengyue Li
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Mei Sun
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Ying Wang
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Li Luo
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Mingzhu Yu
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Yu Zhang
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Hua Wang
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Peiwu Shi
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Zheng Chen
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Jian Wang
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Yueliang Lu
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Qi Li
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Xinhua Wang
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Zhenqiang Bi
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Ming Fan
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Liping Fu
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Jingjin Yu
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
| | - Mo Hao
- Chengyue Li, Mei Sun, Ying Wang, Li Luo, and Mo Hao are with the Research Institute of Health Development Strategies and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. Mingzhu Yu and Jingjin Yu are with the Department of the Bureau of Disease Control and Prevention of National Health and Family Planning Commission, Beijing, China. Yu Zhang is with the Department of Health and Family Planning Commission of Hubei Province, Wuhan, Hubei, China. Hua Wang is with the Department of Health and Family Planning Commission of Jiangsu Province, Nanjing, Jiangsu, China. Peiwu Shi is with Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, China. Zheng Chen is with the Department of National Grassroots Health Prevention Group, Shanghai. Jian Wang is with Chinese Center for Disease Control and Prevention, Beijing. Yueliang Lu is with Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu. Qi Li is with Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hubei. Xinhua Wang is with Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China. Zhenqiang Bi is with Shandong Provincial Center for Disease Control and Prevention, Jinan, Shandong, China. Ming Fan is with Jilin Provincial Center for Disease Control and Prevention, Changchun, Jilin, China. Liping Fu is with Xinjiang Provincial Center for Disease Control and Prevention, Urumqi, Xinjiang, China
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Zang L, Zhao H, Fang Q, Fan M, Chen T, Tian Y, Yao J, Zheng Y, Zhang Z, Cao W. Photophysical properties of sinoporphyrin sodium and explanation of its high photo-activity. J PORPHYR PHTHALOCYA 2017. [DOI: 10.1142/s1088424617500055] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Sinoporphyrin sodium (DVDMS) is a novel photosensitizer with high photodynamic therapy (PDT) effect. Reasons for its high photo-activity were investigated according to the study of photophysical characteristics of DVDMS. Extinction coefficients ([Formula: see text] of DVDMS at 405 nm and 630 nm are 4.36 × 105 and 1.84 × 104 M[Formula: see text].cm[Formula: see text]; fluorescence quantum yield ([Formula: see text] is 0.026; quantum yield of lowest triplet state formation is 0.94 and singlet oxygen quantum yield ([Formula: see text] is 0.92. Although [Formula: see text] of DVDMS is only 10% higher than that of Photofrin[Formula: see text] (0.83), the extinction coefficient of DVDMS at 630 nm is 10-fold greater than that of Photofrin[Formula: see text]. This leads to its higher singlet oxygen generation efficiency ([Formula: see text]. The higher [Formula: see text] of DVDMS can result in an effective reduction of dosage (1/10 of Photofrin[Formula: see text] reaching the same cytotoxic effect as Photofrin[Formula: see text]. Even though [Formula: see text] is approximately equal to that of Photofrin[Formula: see text], brightness ([Formula: see text] of DVDMS is 10-fold greater than that of Photofrin[Formula: see text] because of the 10-fold greater extinction coefficient. Thus, fluorescence diagnosis ability of 0.2 mg/kg DVDMS is comparable to that of 2 mg/kg Photofrin[Formula: see text] used in PDT. Overall, the 10-fold greater extinction coefficients are responsible for the high brightness and singlet oxygen generation efficiency of DVDMS.
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Affiliation(s)
- Lixin Zang
- Condensed Matter Science and Technology Institute, Harbin Institute of Technology, Harbin, 150080, China
| | - Huimin Zhao
- School of Physics and Electronics, Shandong Normal University, Ji’nan, 250014, China
| | - Qicheng Fang
- Institute of Materia Medica, Chinese Academy of Medical Science, Beijing, 100050, China
| | - Ming Fan
- Shenzhen Micromed Tech. Co., Ltd., Shenzhen, 518109, China
| | - Tong Chen
- Shenzhen Micromed Tech. Co., Ltd., Shenzhen, 518109, China
| | - Ye Tian
- Division of Cardiology, the First Affiliated Hospital, Cardiovascular Institute, Harbin Medical University, Harbin, 150001, China
| | - Jianting Yao
- Division of Cardiology, the First Affiliated Hospital, Cardiovascular Institute, Harbin Medical University, Harbin, 150001, China
| | - Yangdong Zheng
- Department of Physics, Harbin Institute of Technology, Harbin, 150001, China
| | - Zhiguo Zhang
- Condensed Matter Science and Technology Institute, Harbin Institute of Technology, Harbin, 150080, China
| | - Wenwu Cao
- Department of Mathematics and Materials Research Institute, The Pennsylvania State University, Pennsylvania, 16802, USA
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190
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Zhang J, Chen J, Fan C, Li J, Lin J, Yang T, Fan M. Alteration of Spontaneous Brain Activity After Hypoxia-Reoxygenation: A Resting-State fMRI Study. High Alt Med Biol 2017; 18:20-26. [PMID: 28266873 DOI: 10.1089/ham.2016.0083] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Zhang, Jiaxing, Ji Chen, Cunxiu Fan, Jinqiang Li, Jianzhong Lin, Tianhe Yang, and Ming Fan. Alteration of spontaneous brain activity after hypoxia-reoxygenation: A resting-state fMRI study. High Alt Med Biol. 18:20-26, 2017.-The present study was designed to investigate the effect of hypoxia-reoxygenation on the spontaneous neuronal activity in brain. Sixteen sea-level (SL) soldiers (20.5 ± 0.7 years), who garrisoned the frontiers in high altitude (HA) (2300-4400 m) for two years and subsequently descended to sea level for one to seven days, were recruited. Control group consisted of 16 matched SL natives. The amplitude of low-frequency fluctuations (ALFF) of regional brain functional magnetic resonance imaging signal in resting state and functional connectivity (FC) between brain regions was analyzed. HA subjects showed significant increases of ALFF at several sites within the bilateral occipital cortices and significant decreases of ALFF in the right anterior insula and extending to the caudate, putamen, inferior frontal orbital cortex, temporal pole, and superior temporal gyrus; lower ALFF values in the right insula were positively correlated with low respiratory measurements. The right insula in HA subjects had increases of FC with the right superior temporal gyrus, postcentral gyrus, rolandic operculum, supramarginal gyrus, and inferior frontal triangular area. We thus demonstrated that hypoxia-reoxygenation had influence on the spontaneous neuronal activity in brain. The decrease of insular neuronal activity may be related to the reduction of ventilatory drive, while the increase of FC with insula may indicate a central compensation.
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Affiliation(s)
- Jiaxing Zhang
- 1 Department of Physiology, Medical College of Xiamen University , Xiamen, China
| | - Ji Chen
- 1 Department of Physiology, Medical College of Xiamen University , Xiamen, China
| | - Cunxiu Fan
- 1 Department of Physiology, Medical College of Xiamen University , Xiamen, China
| | - Jinqiang Li
- 2 Department of Clinical Psychology, Gulangyu Sanatorium of PLA , Xiamen, China
| | - Jianzhong Lin
- 3 Magnetic Resonance Center, Zhongshan Hospital Xiamen University , Xiamen, China
| | - Tianhe Yang
- 3 Magnetic Resonance Center, Zhongshan Hospital Xiamen University , Xiamen, China
| | - Ming Fan
- 4 Department of Cognitive Sciences, Institute of Basic Medical Sciences , Beijing, China
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Narayanan R, Ponnusamy S, Fan M, Yang CH, Grimes BL, Fleming MD, Pritchard EF, Berry MP, Oswaks RM, Fine RE, Loiseau JC, Schwartzberg LS, Pfeffer LM. Abstract P6-12-06: Nonsteroidal, tissue selective androgen receptor modulator (SARM), enobosarm, reduces growth of androgen receptor-positive breast cancer in patient-derived preclinical models. Cancer Res 2017. [DOI: 10.1158/1538-7445.sabcs16-p6-12-06] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Introduction: In breast cancer the androgen receptor (AR) is the most abundantly expressed steroid receptor with 75-95% of estrogen receptor (ER)-positive and 40-70% of ER-negative breast cancers expressing the AR. Historically, advanced breast cancer has been treated with androgens, resulting in significant clinical response. However, the use of steroidal androgens fell from favor as a result of their virilizing side effects. Nonsteroidal, tissue selective androgen receptor modulators (SARMs) will provide a novel targeted approach to exploit the therapeutic benefits of androgens in breast cancer.
Aims: To test the effects of enobosarm (a first-in-class SARM) and enzalutamide (AR antagonist) on the growth of patient-derived breast cancer xenografts (PDX) and to discern the mechanism of action of AR-targeted therapies in AR-positive breast cancer.
Materials and Methods: AR-positive PDXs with varying receptor expression (ER, progesterone receptor (PR), and HER2) were implanted in immunecompromised mice. Mice carrying PDXs were treated with vehicle, 10 mg/kg/day (mpk) enobosarm (GTx, Inc., Memphis, TN), or 20 mpk enzalutamide (Medivation Inc.), orally. Tumor volume was measured twice or thrice weekly. Tumors that received enobosarm were further analyzed to determine the mechanism of action.
Results: Enobosarm significantly (p<0.01) inhibited the growth of ER-, PR-, and HER2- positive HCI-7 and ER- and PR- negative and HER2-positive HCI-12 PDX. While enobosarm inhibited the growth of HCI-12 by ~80% and HCI-7 by ~60%, enzalutamide failed to inhibit the growth of the HCI-7 PDX. In contrast, neither enobosarm nor enzalutamide inhibited the growth of ER- and PR-negative and HER2-positive HCI-9 PDX, consistent with the heterogeneity of AR-positive breast cancers. Growth of two triple-negative breast cancer (TNBC) PDXs were inhibited by 30-40% by enobosarm, but not by enzalutamide. These results were reproduced in xenografts developed with breast cancer cell lines, MCF-7 and MDA-MB-231 expressing the AR. Gene expression studies conducted with the HCI-12 tumors indicated that enobosarm inhibited the expression of various proliferative genes (MUC2, IL10RA, IGSF1, SLC6A4, and others) and increased the expression of growth inhibitory genes (CYP4F8, MYBPC1, and others). Ingenuity pathway analysis demonstrated that enobosarm inhibited genes that are downstream of HER2 signaling. Interestingly, miR-21-3p, which has been implicated in chemo-resistance, was consistently expressed at approximately 10-50-fold higher than miR-21-5p in PDXs. This imbalance was partially reversed by enobosarm.
Conclusion: These results indicate that AR-positive breast cancers are highly heterogeneous and that enobosarm has promise as novel targeted therapy to treat AR-positive breast cancer. Enobosarm is currently in phase II clinical trial in both ER-positive breast cancer and in TNBC patients.
Citation Format: Narayanan R, Ponnusamy S, Fan M, Yang CH, Grimes BL, Fleming MD, Pritchard EF, Berry MP, Oswaks RM, Fine RE, Loiseau J-C, Schwartzberg LS, Pfeffer LM. Nonsteroidal, tissue selective androgen receptor modulator (SARM), enobosarm, reduces growth of androgen receptor-positive breast cancer in patient-derived preclinical models [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-12-06.
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Affiliation(s)
- R Narayanan
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - S Ponnusamy
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - M Fan
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - CH Yang
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - BL Grimes
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - MD Fleming
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - EF Pritchard
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - MP Berry
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - RM Oswaks
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - RE Fine
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - J-C Loiseau
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - LS Schwartzberg
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
| | - LM Pfeffer
- University of Tennessee Health Science Center, Memphis, TN; West Cancer Center, Memphis, TN
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192
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Liu S, Yin F, Zhao M, Zhou C, Ren J, Huang Q, Zhao Z, Mitra R, Fan W, Fan M. The homing and inhibiting effects of hNSCs-BMP4 on human glioma stem cells. Oncotarget 2017; 7:17920-31. [PMID: 26908439 PMCID: PMC4951260 DOI: 10.18632/oncotarget.7472] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Accepted: 02/11/2016] [Indexed: 02/06/2023] Open
Abstract
Malignant gliomas patients have a poor survival rate, partially due to the inability in delivering therapeutic agents to the tumors, especially to the metastasis of human glioma stem cells (hGSCs). To explore whether the human neural stem cells (hNSCs) with an over-expression of BMP4 (hNSCs-BMP4) can trace and inhibit hGSCs, in this study, we examined the migration of hNSCs to hGSCs using transwell assay in vitro and performed the fluorescent tracer experiment in vivo. We examined the proliferation, differentiation, apoptosis and migration of hGSCs after co-culturing with hNSCs-BMP4 in vitro and tested the tropism and antitumor effects of hNSCs-BMP4 in the established brain xenograft models of hGSCs. We found that hNSCs-BMP4 could secrete BMP4 and trace hGSCs both in vitro and in vivo. When compared to the normal human astrocytes (NHAs) and hNSCs, hNSCs-BMP4 could significantly inhibit the invasive growth of hGSCs, promote their differentiation and apoptosis by activating Smad1/5/8 signaling, and prolong the survival time of the tumor-bearing nude mice. Collectively, this study suggested that hNSCs-BMP4 may help in developing therapeutic approaches for the treatment of human malignant gliomas.
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Affiliation(s)
- Shuang Liu
- Department of Neurosurgery, Navy General Hospital, PLA, Beijing 100048, China
| | - Feng Yin
- Department of Neurosurgery, Navy General Hospital, PLA, Beijing 100048, China
| | - Mingming Zhao
- Department of Neurosurgery, Navy General Hospital, PLA, Beijing 100048, China
| | - Chunhui Zhou
- Department of Neurosurgery, Navy General Hospital, PLA, Beijing 100048, China
| | - Junlin Ren
- Department of Neurosurgery, Navy General Hospital, PLA, Beijing 100048, China
| | - Qiming Huang
- Department of Brain Protection & Plasticity Research, Beijing Institute of Basic Medical Sciences, Beijing 100850, China
| | - Zhongming Zhao
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, USA.,Departments of Psychiatry and Cancer Biology, Vanderbilt University Medical Center, Nashville, TN 37232, USA.,Center for Precision Health, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Ramkrishna Mitra
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Wenhong Fan
- National Institutes for Food and Drug Control, Beijing 100050, China
| | - Ming Fan
- Department of Brain Protection & Plasticity Research, Beijing Institute of Basic Medical Sciences, Beijing 100850, China
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193
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Ding XF, Wang HJ, Qian L, Hu ZY, Feng SF, Wu Y, Yang HH, Wu HT, Fan WH, Fan M. Cpne5 is Involved in Regulating Rodent Anxiety Level. CNS Neurosci Ther 2017; 23:266-268. [PMID: 28168849 DOI: 10.1111/cns.12674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Revised: 12/16/2016] [Accepted: 12/19/2016] [Indexed: 11/28/2022] Open
Affiliation(s)
- Xue-Feng Ding
- Department of Neurobiology, Beijing Institute of Basic Medical Sciences, Beijing, China.,Department of Cognitive Sciences, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - He-Jun Wang
- Department of Neurosurgery, The Third People's Hospital of Shizuishan, Shizuishan, China
| | - Lu Qian
- Department of Neurobiology, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Zeng-Yao Hu
- Beijing Institute of Pharmacology and Toxicology, Beijing, China
| | - Shu-Fang Feng
- Department of Neurobiology, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Yan Wu
- Department of Cognitive Sciences, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Hai-Hong Yang
- Department of Neurobiology, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Hai-Tao Wu
- Department of Neurobiology, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Wen-Hong Fan
- National Institutes for Food and Drug Control, Beijing, China
| | - Ming Fan
- Department of Cognitive Sciences, Beijing Institute of Basic Medical Sciences, Beijing, China
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194
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Li D, Zhang L, Xu L, Liu L, He Y, Zhang Y, Huang X, Zhao T, Wu L, Zhao Y, Wu K, Li H, Yu X, Zhao T, Gong S, Fan M, Zhu L. WIP1 phosphatase is a critical regulator of adipogenesis through dephosphorylating PPARγ serine 112. Cell Mol Life Sci 2017; 74:2067-2079. [DOI: 10.1007/s00018-016-2450-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Revised: 12/07/2016] [Accepted: 12/29/2016] [Indexed: 12/19/2022]
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195
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Fan M, Li H, Wang S, Zheng B, Zhang J, Li L. Radiomic analysis reveals DCE-MRI features for prediction of molecular subtypes of breast cancer. PLoS One 2017; 12:e0171683. [PMID: 28166261 PMCID: PMC5293281 DOI: 10.1371/journal.pone.0171683] [Citation(s) in RCA: 98] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2016] [Accepted: 01/24/2017] [Indexed: 12/15/2022] Open
Abstract
The purpose of this study was to investigate the role of features derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and to incorporated clinical information to predict the molecular subtypes of breast cancer. In particular, 60 breast cancers with the following four molecular subtypes were analyzed: luminal A, luminal B, human epidermal growth factor receptor-2 (HER2)-over-expressing and basal-like. The breast region was segmented and the suspicious tumor was depicted on sequentially scanned MR images from each case. In total, 90 features were obtained, including 88 imaging features related to morphology and texture as well as dynamic features from tumor and background parenchymal enhancement (BPE) and 2 clinical information-based parameters, namely, age and menopausal status. An evolutionary algorithm was used to select an optimal subset of features for classification. Using these features, we trained a multi-class logistic regression classifier that calculated the area under the receiver operating characteristic curve (AUC). The results of a prediction model using 24 selected features showed high overall classification performance, with an AUC value of 0.869. The predictive model discriminated among the luminal A, luminal B, HER2 and basal-like subtypes, with AUC values of 0.867, 0.786, 0.888 and 0.923, respectively. An additional independent dataset with 36 patients was utilized to validate the results. A similar classification analysis of the validation dataset showed an AUC of 0.872 using 15 image features, 10 of which were identical to those from the first cohort. We identified clinical information and 3D imaging features from DCE-MRI as candidate biomarkers for discriminating among four molecular subtypes of breast cancer.
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Affiliation(s)
- Ming Fan
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Hui Li
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Shijian Wang
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Bin Zheng
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma, United States of America
| | - Juan Zhang
- Zhejiang Cancer Hospital, Zhejiang Hangzhou, China
- * E-mail: (JZ); (LL)
| | - Lihua Li
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
- * E-mail: (JZ); (LL)
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Wei W, Wang X, Gong Q, Fan M, Zhang J. Cortical Thickness of Native Tibetans in the Qinghai-Tibetan Plateau. AJNR Am J Neuroradiol 2017; 38:553-560. [PMID: 28104637 DOI: 10.3174/ajnr.a5050] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Accepted: 10/24/2016] [Indexed: 02/05/2023]
Abstract
BACKGROUND AND PURPOSE High-altitude environmental factors and genetic variants together could have exerted their effects on the human brain. The present study was designed to investigate the cerebral morphology in high-altitude native Tibetans. MATERIALS AND METHODS T1-weighted brain images were obtained from 77 Tibetan adolescents on the Qinghai-Tibetan Plateau (altitude, 2300-5300 m) and 80 matched Han controls living at sea level. Cortical thickness, curvature, and sulcus were analyzed by using FreeSurfer. RESULTS Cortical thickness was significantly decreased in the left posterior cingulate cortex, lingual gyrus, superior parietal cortex, precuneus, and rostral middle frontal cortex and the right medial orbitofrontal cortex, lateral occipital cortex, precuneus, and paracentral lobule. Curvature was significantly decreased in the left superior parietal cortex and right superior marginal gyrus; the depth of the sulcus was significantly increased in the left inferior temporal gyrus and significantly decreased in the right superior marginal gyrus, superior temporal gyrus, and insular cortex. Moreover, cortical thickness was negatively correlated with altitude in the left superior and middle temporal gyri, rostral middle frontal cortex, insular cortex, posterior cingulate cortex, precuneus, lingual gyrus, and the right superior temporal gyrus. Curvature was positively correlated with altitude in the left rostral middle frontal cortex, insular cortex, and middle temporal gyrus. The depth of the sulcus was negatively correlated with altitude in the left lingual gyrus and right medial orbitofrontal cortex. CONCLUSIONS Differences in cortical morphometry in native Tibetans may reflect adaptations related to high altitude.
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Affiliation(s)
- W Wei
- From the MRI Center (W.W.), First Affiliated Hospital of Xiamen University, Xiamen, China.,Institute of Brain Disease and Cognition (W.W., J.Z.), Medical College of Xiamen University, Xiamen, China
| | - X Wang
- Department of Neurology (X.W.), Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Q Gong
- Huaxi Magnetic Resonance Research Center (Q.G.), West China Hospital, Sichuan University, Chengdu, China
| | - M Fan
- Department of Cognitive Sciences (M.F.), Institute of Basic Medical Sciences, Beijing, China
| | - J Zhang
- Institute of Brain Disease and Cognition (W.W., J.Z.), Medical College of Xiamen University, Xiamen, China
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197
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McColgan P, Gregory S, Razi A, Seunarine KK, Gargouri F, Durr A, Roos RAC, Leavitt BR, Scahill RI, Clark CA, Tabrizi SJ, Rees G, Coleman A, Decolongon J, Fan M, Petkau T, Jauffret C, Justo D, Lehericy S, Nigaud K, Valabrègue R, Choonderbeek A, Hart EPT, Hensman Moss DJ, Crawford H, Johnson E, Papoutsi M, Berna C, Reilmann R, Weber N, Stout J, Labuschagne I, Landwehrmeyer B, Orth M, Johnson H. White matter predicts functional connectivity in premanifest Huntington's disease. Ann Clin Transl Neurol 2017; 4:106-118. [PMID: 28168210 PMCID: PMC5288460 DOI: 10.1002/acn3.384] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Revised: 11/22/2016] [Accepted: 11/28/2016] [Indexed: 02/01/2023] Open
Abstract
Objectives The distribution of pathology in neurodegenerative disease can be predicted by the organizational characteristics of white matter in healthy brains. However, we have very little evidence for the impact these pathological changes have on brain function. Understanding any such link between structure and function is critical for understanding how underlying brain pathology influences the progressive behavioral changes associated with neurodegeneration. Here, we demonstrate such a link between structure and function in individuals with premanifest Huntington's. Methods Using diffusion tractography and resting state functional magnetic resonance imaging to characterize white matter organization and functional connectivity, we investigate whether characteristic patterns of white matter organization in the healthy human brain shape the changes in functional coupling between brain regions in premanifest Huntington's disease. Results We find changes in functional connectivity in premanifest Huntington's disease that link directly to underlying patterns of white matter organization in healthy brains. Specifically, brain areas with strong structural connectivity show decreases in functional connectivity in premanifest Huntington's disease relative to controls, while regions with weak structural connectivity show increases in functional connectivity. Furthermore, we identify a pattern of dissociation in the strongest functional connections between anterior and posterior brain regions such that anterior functional connectivity increases in strength in premanifest Huntington's disease, while posterior functional connectivity decreases. Interpretation Our findings demonstrate that organizational principles of white matter underlie changes in functional connectivity in premanifest Huntington's disease. Furthermore, we demonstrate functional antero–posterior dissociation that is in keeping with the caudo–rostral gradient of striatal pathology in HD.
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198
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Affiliation(s)
- Wei Song
- School of Information Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China
- School of Information Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China
| | - Zhiguang Wang
- Deparment of Computer Science, University of Maryland, Baltimore County, MD 21250, USA
- School of Information Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China
| | - Fan Zhang
- School of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, Henan, China
| | - Yangdong Ye
- School of Information Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China
| | - Ming Fan
- School of Information Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China
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199
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Gong W, Xu P, Guo S, Li X, Jin Z, Zhao Y, Fan M, Xue M. Effect of hypoxia on the pharmacokinetics and metabolism of zaleplon as a probe of CYP3A1/2 activity. RSC Adv 2017. [DOI: 10.1039/c7ra03025h] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The objective of this study was to compare the pharmacokinetics and metabolism of zaleplon (ZAL) in rats under hypoxic and normoxic condition and the effect of hypoxia on the protein expression and activities of the main metabolic enzyme CYP3A1/2.
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Affiliation(s)
- Wenwen Gong
- Department of Pharmacology
- Beijing Laboratory for Biomedical Detection Technology and Instrument
- School of Basic Medical Sciences
- Capital Medical University
- Beijing 100069
| | - Pingxiang Xu
- Department of Pharmacology
- Beijing Laboratory for Biomedical Detection Technology and Instrument
- School of Basic Medical Sciences
- Capital Medical University
- Beijing 100069
| | - Shanshan Guo
- Department of Pharmacology
- Beijing Laboratory for Biomedical Detection Technology and Instrument
- School of Basic Medical Sciences
- Capital Medical University
- Beijing 100069
| | - Xiaorong Li
- Department of Pharmacology
- Beijing Laboratory for Biomedical Detection Technology and Instrument
- School of Basic Medical Sciences
- Capital Medical University
- Beijing 100069
| | - Zengliang Jin
- Department of Pharmacology
- Beijing Laboratory for Biomedical Detection Technology and Instrument
- School of Basic Medical Sciences
- Capital Medical University
- Beijing 100069
| | - Yuming Zhao
- Department of Pharmacology
- Beijing Laboratory for Biomedical Detection Technology and Instrument
- School of Basic Medical Sciences
- Capital Medical University
- Beijing 100069
| | - Ming Fan
- Department of Nerobiology
- School of Basic Medical Sciences
- Capital Medical University
- Beijing
- China
| | - Ming Xue
- Department of Pharmacology
- Beijing Laboratory for Biomedical Detection Technology and Instrument
- School of Basic Medical Sciences
- Capital Medical University
- Beijing 100069
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200
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Fan M, Chau CK, Chan EHW, Jia J. A decision support tool for evaluating the air quality and wind comfort induced by different opening configurations for buildings in canyons. Sci Total Environ 2017; 574:569-582. [PMID: 27648534 DOI: 10.1016/j.scitotenv.2016.09.083] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Revised: 08/01/2016] [Accepted: 09/11/2016] [Indexed: 06/06/2023]
Abstract
This study formulated a new index for evaluating both the air quality and wind comfort induced by building openings at the pedestrian level of street canyons. The air pollutant concentrations and wind velocities induced by building openings were predicted by a series of CFD simulations using ANSYS Fluent software based on standard k-ɛ model. The types of opening configurations investigated inside isolated and non-isolated canyons included separations, voids and permeable elements. It was found that openings with permeability values of 10% were adequate for improving the air quality and wind comfort conditions for pedestrians after considering the reduction in development floor areas. Openings were effective in improving the air quality in isolated canyons and different types of opening configurations were suggested for different street aspect ratios. On the contrary, openings were not always found effective for non-isolated canyons if there were pollutant sources in adjacent street canyons. As such, it would also be recommended introducing openings to adjacent canyons along with openings to the target canyons. The formulated index can help city planners and building designers to strike an optimal balance between air quality and wind comfort for pedestrians when designing and planning buildings inside urban streets and thus promoting urban environmental sustainability.
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Affiliation(s)
- M Fan
- School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
| | - C K Chau
- Department of Building Services Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region.
| | - E H W Chan
- Department of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region
| | - J Jia
- Department of Building Services Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region
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