CHIRAL CARBON NANOTUBES AND CARBON NANOTUBE CHIRAL COMPOSITES:PREPARATION AND APPLICATIONS

XIAOQING CHEN,XIAO-YUN LIAO,JIN-GANG YU,FEI-PENG JIAO,XINYU JIANG 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2013 NANO Vol.8 No.4

A review of preparation of chiral carbon nanotubes (CNTs) and carbon nanotube chiral composites is presented. Novel chiral separation science and technology based on CNTs is analyzed and discussed, with the emphasis in two topics. The first topic concerns the possibility of application of chiral CNTs in resolution and chiral sensing. The second topic centers on the subject of enantioseparation based on CNT chiral composites. Despite the crucial functionalization of CNTs using chiral selectors, better resolution could also be achieved by using a mixture of CNTs and optical pure substances as chiral selectors. Due to their ability of improving the degree of enantioseparation, CNTs could find their potential applications in the resolution in the future.

Synthesis, Antibacterial Activity, and Structure–Activity Relationship of Fusaric Acid Analogs

Qing-Yan Zhang,Yang Fei‐Yu,Liao Shang‐Gao,Wang Bing,Li Rui,Dong Yong‐Xi,Zhou Meng,Yang Yuan‐Yong,Xu Guo‐Bo 대한화학회 2021 Bulletin of the Korean Chemical Society Vol.42 No.4

Forty-one fusaric acid analogs possessing a pyridine carboxylic acid scaffold have been synthesized. The antibacterial activity results demonstrated that compounds 5b, 7b, 8c, and 8d displayed strong antibacterial activities against Staphylococcus aureus ATCC25923 with minimum inhibitory concentrations (MICs) of 4–16 μg/mL. Molecular docking study indicated that these compounds have strong hydrogen-bonding interactions with TyrRS. Meanwhile, 8c and 8d showed promising antibacterial activities against Pseudomonas aeruginosa ATCC9027. Compound 4 exhibited pronounced antibacterial activities against a clinically isolated multidrug-resistant strain of Escherichia coli (MIC: 64 μg/mL as compared 64 μg/mL of levofloxacin and 1024 μg/mL of ceftriaxone sodium). Moreover, compound 17e displayed strong synergistic antibacterial effect with levofloxacin against the multidrug-resistant strain, decreasing the MIC value of levofloxacin to 1/16 of its original MIC. No obvious cytotoxic activities against LO2 was observed for compounds 4, 5b, 8c, 8d, 17d, and 17e at 50 μM. The preliminary structure–activity relationship of fusaric acid analogs was also discussed.

Muscle-derived Stem Cells Differentiate into Functional Smooth Muscle Cells for Ureter Tissue Engineering: An Experimental Study

Zhan-Kui Zhao,Hong-Lian Yu,Fei Xiao,Shi-Wen Li,Wen-Biao Liao,Kai-Liang Zhao 한국생물공학회 2012 Biotechnology and Bioprocess Engineering Vol.17 No.3

We assessed the ability of muscle-derived stem cells (MDSC) to differentiate into smooth muscle cells (SMC) and their potential to promote the regeneration of smooth muscle with a vessel extracellular matrix (VECM)for tissue engineering of the ureter. MDSC were isolated,proliferated, and identified by flow cytometry. SMC phenotype differentiation was induced with a smooth muscle induction medium. Gene expression was evaluated by real-time quantitative polymerase chain reaction (PCR)and Western blot studies. The VECM was obtained by a decellularization process, and cytotoxic effects were evaluated by exposing the induced cells to a VECM extract. The induced cells were seeded onto VECM in vitro for 1 week, and then the compound grafts were used for ureter reconstitution in vivo. The grafts were obtained for histological studies at 2, 4, 8, and 16 weeks post-operation. Intravenous urography was used to evaluate renal function and ureteral patency. Flow cytometry demonstrated that the MDSC expressed Sca-1 and desmin, but did not express CD45. After induction, SMC phenotype gene expression was confirmed in the induced cells by real-time quantitative PCR and Western blot studies. VECM exhibited a nontoxic effect on the induced cells in vitro. At 16 weeks postoperation,a histological evaluation showed that multilayered urothelium and organized muscle fiber bundles had formed in the grafts. Intravenous urography demonstrated no evidence of ureteral stricture or hydroureteronephrosis. These results demonstrate that MDSC can be induced into SMC and that this was useful for promoting regeneration of smooth muscles for ureter tissue engineering. We assessed the ability of muscle-derived stem cells (MDSC) to differentiate into smooth muscle cells (SMC) and their potential to promote the regeneration of smooth muscle with a vessel extracellular matrix (VECM)for tissue engineering of the ureter. MDSC were isolated,proliferated, and identified by flow cytometry. SMC phenotype differentiation was induced with a smooth muscle induction medium. Gene expression was evaluated by real-time quantitative polymerase chain reaction (PCR)and Western blot studies. The VECM was obtained by a decellularization process, and cytotoxic effects were evaluated by exposing the induced cells to a VECM extract. The induced cells were seeded onto VECM in vitro for 1 week, and then the compound grafts were used for ureter reconstitution in vivo. The grafts were obtained for histological studies at 2, 4, 8, and 16 weeks post-operation. Intravenous urography was used to evaluate renal function and ureteral patency. Flow cytometry demonstrated that the MDSC expressed Sca-1 and desmin, but did not express CD45. After induction, SMC phenotype gene expression was confirmed in the induced cells by real-time quantitative PCR and Western blot studies. VECM exhibited a nontoxic effect on the induced cells in vitro. At 16 weeks postoperation,a histological evaluation showed that multilayered urothelium and organized muscle fiber bundles had formed in the grafts. Intravenous urography demonstrated no evidence of ureteral stricture or hydroureteronephrosis. These results demonstrate that MDSC can be induced into SMC and that this was useful for promoting regeneration of smooth muscles for ureter tissue engineering.

A generalized adaptive variational mode decomposition method for nonstationary signals with mode overlapped components

Jing-Liang Liu,Fu-Lian Qiu,Zhi-Ping Lin,Yu-Zu Li,Fei-Yu Liao 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.30 No.1

Engineering structures in operation essentially belong to time-varying or nonlinear structures and the resultant response signals are usually non-stationary. For such time-varying structures, it is of great importance to extract time-dependent dynamic parameters from non-stationary response signals, which benefits structural health monitoring, safety assessment and vibration control. However, various traditional signal processing methods are unable to extract the embedded meaningful information. As a newly developed technique, variational mode decomposition (VMD) shows its superiority on signal decomposition, however, it still suffers two main problems. The foremost problem is that the number of modal components is required to be defined in advance. Another problem needs to be addressed is that VMD cannot effectively separate nonstationary signals composed of closely spaced or overlapped modes. As such, a new method named generalized adaptive variational modal decomposition (GAVMD) is proposed. In this new method, the number of component signals is adaptively estimated by an index of mean frequency, while the generalized demodulation algorithm is introduced to yield a generalized VMD that can decompose mode overlapped signals successfully. After that, synchrosqueezing wavelet transform (SWT) is applied to extract instantaneous frequencies (IFs) of the decomposed mono-component signals. To verify the validity and accuracy of the proposed method, three numerical examples and a steel cable with time-varying tension force are investigated. The results demonstrate that the proposed GAVMD method can decompose the multi-component signal with overlapped modes well and its combination with SWT enables a successful IF extraction of each individual component.

Structural Damage Identification Based on Convolutional Neural Network Group Considering the Sensor Fault

Yong-Peng Luo,Linkun Wang,Xu Guo,Jinlin Zheng,Fei-Yu Liao,Zixiong Guo 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.8

This article proposes a structural damage identification method based on one-dimensional convolutional neural network group considering sensor faults. The method aims to reduce the damage misjudgment caused by sensor faults. In the proposed method, according to the sensor layout, some convolutional neural network sub-models are established to extract the features from raw vibration data for sensor fault diagnosis and structural damage identification; then two convolutional neural networks groups, namely the sensor fault diagnosis group and the damage identification group are designed on the basis of the functions of each sub-model. The sensor fault diagnosis group determines whether the sensor data is abnormal and truncates the abnormal signal. The remaining normal signal are entered into the damage identification group and the final damage identification results are calculated according to the statistical decision module. The effectiveness of the devised method is verified by the IASC–ASCE benchmark structure and laboratory experiments. The results demonstrate that the sensor fault diagnosis and damage identification accuracy of each sub-model ranges from 98.54% to 99.77% and from 87.21% to 91.74% respectively at different noise levels; the damage identification group can reduce the impact of sub-model misjudgment on the structural damage identification. The accuracy of the final damage identification results is 100%. The identification time of all samples in the test set is 53.09 s and 22.93 s, respectively, for SHM benchmark and Laboratory experiment cases. And the average judgment time of each submodel in the sensor fault diagnosis group was 278 and 94 ms, and that of each submodel in the damage identification group was 294 and 105 ms, respectively, for a single test sample, which fulfills the requirements of online damage identification for structural health monitoring.