Southeast University

About: Southeast University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Computer science & MIMO. The organization has 66363 authors who have published 79434 publications receiving 1170576 citations. The organization is also known as: SEU.

Aldehyde Dehydrogenase 1 A1–Positive Cell Population Is Enriched in Tumor-Initiating Cells and Associated with Progression of Bladder Cancer

Abstract: Aldehyde dehydrogenase 1 A1 (ALDH1A1) has recently been suggested as a marker for cancer stem or stem-like cancer cells of some human malignancies. The purpose of this study was to investigate the stem cell-related function and clinical significance of the ALDH1A1 in bladder urothelial cell carcinoma. Aldefluor assay was used to isolate ALDH1A1+ cells from bladder cancer cells. Stem cell characteristics of the ALDH1A1+ cells were then investigated by in vitro and in vivo approaches. Immunohistochemistry was done for evaluating ALDH1A1 expression on 22 normal bladder tissues and 216 bladder tumor specimens of different stage and grade. The ALDH1A1+ cancer cells displayed higher in vitro tumorigenicity compared with isogenic ALDH1A1- cells. The ALDH1A1+ cancer cells could generate xenograft tumors that resembled the histopathologic characteristics and heterogeneity of the parental cells. High ALDH1A1 expression was found in 26% (56 of 216) of human bladder tumor specimens and significantly related to advanced pathologic stage, high histologic grade, recurrence and progression, and metastasis of bladder urothelial cell carcinomas (all P < 0.05). Furthermore, ALDH1A1 expression was inversely associated with cancer-specific and overall survivals of the patients (P = 0.027 and 0.030, respectively). Therefore, ALDH1A1+ cell population could be enriched in tumor-initiating cells. ALDH1A1 may serve as a useful marker for monitoring the progression of bladder tumor and identifying bladder cancer patients with poor prognosis who might benefit from adjuvant and effective treatments.

Fluorescence Modified Chitosan-Coated Magnetic Nanoparticles for High-Efficient Cellular Imaging

Abstract: Labeling of cells with nanoparticles for living detection is of interest to various biomedical applications. In this study, novel fluorescent/magnetic nanoparticles were prepared and used in high-efficient cellular imaging. The nanoparticles coated with the modified chitosan possessed a magnetic oxide core and a covalently attached fluorescent dye. We evaluated the feasibility and efficiency in labeling cancer cells (SMMC-7721) with the nanoparticles. The nanoparticles exhibited a high affinity to cells, which was demonstrated by flow cytometry and magnetic resonance imaging. The results showed that cell-labeling efficiency of the nanoparticles was dependent on the incubation time and nanoparticles’ concentration. The minimum detected number of labeled cells was around 104by using a clinical 1.5-T MRI imager. Fluorescence and transmission electron microscopy instruments were used to monitor the localization patterns of the magnetic nanoparticles in cells. These new magneto-fluorescent nanoagents have demonstrated the potential for future medical use.

Fuzzy Adaptive Internal Model Control Schemes for PMSM Speed-Regulation System

Abstract: In this paper, the speed regulation problem for permanent magnet synchronous motor (PMSM) system under vector control framework is studied. First, a speed regulation scheme based on standard internal model control (IMC) method is designed. For the speed loop, a standard internal model controller is first designed based on a first-order model of PMSM by analyzing the relationship between reference quadrature axis current and speed. For the two current loops, PI algorithms are employed respectively. Second, considering the disadvantages that the standard IMC method is sensitive to control input saturation and may lead to poor speed tracking and load disturbance rejection performances, a modified IMC scheme is developed based on a two-port IMC method, where a feedback control term is added to form a composite control structure. Third, considering the case of large variations of load inertia, two adaptive IMC schemes with two different adaptive laws are proposed. A method based on disturbance observer is adopted to identify the inertia of PMSM and its load. Then a linear adaptive law is developed by analyzing the relationship between the internal model and identified inertia. Considering the control input saturation in practical applications, a fuzzy adaptive law based IMC scheme is developed based on apriori experimental tests and experiences, where a fuzzy inferencer based supervisor is designed to automatically tune the parameter of speed controller according to the identified inertia. The effectiveness of the proposed methods have been verified by Matlab simulation and TMS320F2808 DSP experimental results.

A set of stability criteria for delayed cellular neural networks

Abstract: This work presents a set of criteria on the global asymptotic stability of delayed cellular neural networks (DCNN) by constructing suitable Lyapunov functionals, introducing ingeniously real parameters w/sub i/>0, /spl alpha//sup *//sub ij/, /spl beta//sup *//sub ij/, /spl eta//sup *//sub ij/, /spl zeta//sup *//sub ij/, /spl alpha//sub ij/, /spl beta//sub ij/, /spl eta//sub ij/, /spl zeta//sub ij//spl isin/R with /spl alpha//sup *//sub ij/+/spl beta//sup *//sub ij/=1, /spl alpha//sub ij/+/spl beta//sub ij/=1, /spl eta//sup *//sub ij/+/spl zeta//sup *//sub ij/=1, /spl eta//sub ij/+/spl zeta//sub ij/=1(i, j=1, 2, ..., n) and combining with elementary inequality technique 2ab/spl les/a/sup 2/+b/sup 2/. These criteria are of theoretical and applicable important significance in signal processing, especially in speed detection of moving objects, processing of moving images and the design of networks since they possess infinitely adjustable real parameters. This result is also discussed from the point of view of its relationship to earlier results.