Activating Transcription Factor 1 is a Prognostic Marker of Colorectal Cancer

Huang, Guo-Liang,Guo, Hong-Qiang,Yang, Feng,Liu, Ou-Fei,Li, Bin-Bin,Liu, Xing-Yan,Lu, Yan,He, Zhi-Wei Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.3

Objective: Identifying cancer-related genes or proteins is critical in preventing and controlling colorectal cancer (CRC). This study was to investigate the clinicopathological and prognostic value of activating transcription factor 1 (ATF1) in CRC. Methods: Protein expression of ATF1 was detected using immunohistochemistry in 66 CRC tissues. Clinicopathological association of ATF1 in CRC was analyzed with chi-square test or Fisher's exact test. The prognostic value of ATF1 in CRC is estimated using the Kaplan-Meier analysis and Cox regression models. Results: The ATF1 protein expression was significantly lower in tumor tissues than corresponding normal tissues (51.5% and 71.1%, respectively, P = 0.038). No correlation was found between ATF1 expression and the investigated clinicopathological parameters, including gender, age, depth of invasion, lymph node status, metastasis, pathological stage, vascular tumoral emboli, peritumoral deposits, chemotherapy and original tumor site (all with P > 0.05). Patients with higher ATF1 expression levels have a significantly higher survival rate than that with lower expression (P = 0.026 for overall survival, P = 0.008 for progress free survival). Multivariate Cox regression model revealed that ATF1 expression and depth of invasion were the predictors of the overall survival (P = 0.008 and P = 0.028) and progress free survival (P = 0.002 and P = 0.005) in CRC. Conclusions: Higher ATF1 expression is a predictor of a favorable outcome for the overall survival and progress free survival in CRC.

Mechanical evaluation of polymer microneedles for transdermal drug delivery: In vitro and in vivo

Rui Xuan Liu,Yu Ting He,Ling Liang,Liu Fu Hu,Yue Liu,Rui-xing Yu,Bo Zhi Chen,Yong Cui,Xin Dong Guo 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.114 No.-

In this study, we reported two types of PMNs based on polylactic acid (PLA) and polyvinyl alcohol (PVA),respectively. Parafilm M film, porcine skin, and rats’ models were operated to evaluate the mechanicalproperties in vitro and in vivo to find optimal parameters for efficient insertion. Insertion depth was measuredusing Digital Force Gauge by changing insertion force and speed, respectively. Results showed thatincreasing the insertion force and speed used for PMNs application led to a significant increase in thedepth of insertion. A force of 18 N under a speed of 330 mm/min was the optimal condition for insertingPMNs array into ParafilmM film and porcine skin. In addition, PLA-MNs exhibited higher robustness andenhanced homogeneity in insertion depth compared with PVA-MNs, but PVA-MNs were able to reachmuch deeper insertion depth. Moreover, Sprague Dawley (SD) rat experiments confirmed the effectivenessof optimal insertion parameters for transdermal drug delivery. This study illustrated not only thedevelopment of novel PMNs but also the mechanical evaluation for the design of PMNs.

Performance Analysis of Power Line Communication Network Model Based on Spider Web

Liu Xiao-sheng,Zhang Liang,ZHOU Yan,Xu Dian-guo 전력전자학회 2011 ICPE(ISPE)논문집 Vol.2011 No.5

To enhance the reliability of narrow band PLC (Power Line Communication) in low-voltage network, inspired by the structure and invulnerability of spider web, a new PLC network model is proposed in this paper. The characteristics of the model and the transformational process of low-voltage distribution network from physical topology to artificially spider web logical topology are thoroughly discussed. New networking algorithm and route-reconstruction algorithm are put forward. A two-state Markov model is used to simulate a terminal node and the time-delay characteristic of the new algorithm is analyzed by modeling. Based on Opnet14.5, simulation and comparison are conducted, which prove that the new network model has advantages in improving the communication reliability of PLC network.

Anti-proliferative Effects of Atractylis lancea (Thunb.) DC. via Down-regulation of the c-myc/hTERT/Telomerase Pathway in Hep-G2 Cells

Guo, Wei-Qiang,Li, Liang-Zhi,He, Zhuo-Yang,Zhang, Qi,Liu, Jia,Hu, Cui-Ying,Qin, Fen-Ju,Wang, Tao-Yun Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.11

Atractylis lancea (Thunb.) DC. (AL), an important medicinal herb in Asia, has been shown to have anti-tumor effects on cancer cells, but the involved mechanisms are poorly understood. This study focused on potential effects and molecular mechanisms of AL on the proliferation of the Hep-G2 liver cancer cell line in vitro. Cell viability was assessed by MTT test in Hep-G2 cells incubated with an ethanol extract of AL. Then, the effects of AL on apoptosis and cell cycle progression were determined by flow cytometry. Telomeric repeat amplification protocol (TRAP) assays was performed to investigate telomerase activity. The mRNA and protein expression of human telomerase reverse transcriptase (hTERT) and c-myc were determined by real-time RT-PCR and Western blotting. Our results show that AL effectively inhibits proliferation in Hep-G2 cells in a concentrationand time-dependent manner. When Hep-G2 cells were treated with AL after 48h,the $IC_{50}$ was about 72.1 ${\mu}g/mL$. Apoptosis was induced by AL via arresting the cells in the G1 phase. Furthermore, AL effectively reduced telomerase activity through inhibition of mRNA and protein expression of hTERT and c-myc. Hence, these data demonstrate that AL exerts anti-proliferative effects in Hep-G2 cells via down-regulation of the c-myc/hTERT/telomerase pathway.

Dynamic characteristics and experimental study on a wind turbine gearbox

Liang Xu,Caichao Zhu,Hua iju Liu,Guo Chen,Wei Long 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.1

A gearbox is part of the transmission chain of wind turbine, which can increase rotational speed and reduce torque. Dynamic characteristics of the gearbox directly influence the vibration and the service life of the wind turbine system. In this paper, dynamic behaviors of a megawatt level wind turbine gearbox are studied theoretically and experimentally by dividing the gearbox into a transmission sub-system and a body sub-system. The transmission sub-system, i.e., the gear-shaft-bearing sub-system, is coupled with the gearbox body using bearings which are simulated as mass-less springs. The theoretical study applies a finite element model for the gearbox, where the internal excitations are caused by time-varying stiffness, transmission errors and mesh impacts. The time-varying wind load is considered as the external excitation, collected by a remote real-time online test and transformed into load spectrums through the rain-flow counting method. With boundary conditions and working conditions being defined in the finite element model, the natural characteristic analysis and the dynamic response analysis are conducted. Results show that the operating frequencies of the gearbox are far away from the main natural frequencies of the system, thus avoiding resonances. The main vibration components of the gearbox are with meshing frequencies of the second and third gear stage and their multiplication counterparts. Moreover, the greatest vibration occurs at the bearing housing of the high-speed shaft with the root-mean-square value of its vibration speed less than 3.5 mm/s. A test rig is developed and the experimental vibration conditions are monitored by acceleration sensors. The experimental results are in accordance well with the theoretical results. In this way, the theoretical model is validated. The methodology reported in this paper can provide valuable guidance for practical industrial engineers.

Microstructure control of Fe catalyst films for the growth of multiwalled carbon nanotube arrays

Guo-an Cheng,Hua-ping Liu,Rui-ting Zheng,Yong Zhao,Chang-lin Liang 한국물리학회 2008 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.52 No.-

Fe catalyst films were deposited on silicon substrates by using a metal vapor vacuum arc (MEVVA) ion deposition system for the growth of aligned multiwalled carbon nanotubes. The effects of deposition angle and film thickness on the morphologies of catalyst films before and after thermal treatment were investigated. The results show that the uniformities of both 5-nm and 10-nm films are enhanced as the deposition angle decreases. With increase from 5 nm to 10 nm, the surface uniformities of pristine films prepared at higher deposition angles (60˚ and 90˚) are increased, while that of the films produced at 30˚ deposition angle is slightly decreased. The uniformity of Fe catalyst particle sizes after thermal treatment on the whole, clearly decreases as the thickness is increased from 5 nm to 10 nm in the case of the same deposition angle. 5-nm films deposited at 30˚ deposition angle show the most uniform features before and after thermal treatment and can be used for the synthesis of high-quality carbon nanotube arrays. Fe catalyst films were deposited on silicon substrates by using a metal vapor vacuum arc (MEVVA) ion deposition system for the growth of aligned multiwalled carbon nanotubes. The effects of deposition angle and film thickness on the morphologies of catalyst films before and after thermal treatment were investigated. The results show that the uniformities of both 5-nm and 10-nm films are enhanced as the deposition angle decreases. With increase from 5 nm to 10 nm, the surface uniformities of pristine films prepared at higher deposition angles (60˚ and 90˚) are increased, while that of the films produced at 30˚ deposition angle is slightly decreased. The uniformity of Fe catalyst particle sizes after thermal treatment on the whole, clearly decreases as the thickness is increased from 5 nm to 10 nm in the case of the same deposition angle. 5-nm films deposited at 30˚ deposition angle show the most uniform features before and after thermal treatment and can be used for the synthesis of high-quality carbon nanotube arrays.

New Insights into mTOR Signal Pathways in Ovarian-Related Diseases: Polycystic Ovary Syndrome and Ovarian Cancer

Liu, Ai Ling,Liao, Hong Qing,Li, Zhi Liang,Liu, Jun,Zhou, Cui Lan,Guo, Zi Fen,Xie, Hong Yan,Peng, Cui Ying Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.12

mTOR, the mammalian target of rapamycin, is a conserved serine/threonine kinase which belongs to the phosphatidyl-linositol kinase-related kinase (PIKK) family. It has two complexes called mTORC1 and mTORC2. It is well established that mTOR plays important roles in cell growth, proliferation and differentiation. Over-activation of the mTOR pathway is considered to have a relationship with the development of many types of diseases, including polycystic ovary syndrome (PCOS) and ovarian cancer (OC). mTOR pathway inhibitors, such as rapamycin and its derivatives, can directly or indirectly treat or relieve the symptoms of patients suffering from PCOS or OC. Moreover, mTOR inhibitors in combination with other chemical-molecular agents may have extraordinary efficacy. This paper will discuss links between mTOR signaling and PCOS and OC, and explore the mechanisms of mTOR inhibitors in treating these two diseases, with conclusions regarding the most effective therapeutic approaches.

Enhancing aircraft engine remaining useful life prediction via multiscale deep transfer learning with limited data

LIU QIAN,Zhang Zhiyao,GUO PENG,WANG YIFAN,Liang Junxin 한국CDE학회 2024 Journal of computational design and engineering Vol.11 No.1

Predicting the remaining useful life (RUL) of the aircraft engine based on historical data plays a pivotal role in formulating maintenance strategies and mitigating the risk of critical failures. None the less, attaining precise RUL predictions often encounters challenges due to the scarcity of historical condition monitoring data. This paper introduces a multiscale deep transfer learning framework via integrating domain adaptation principles. The framework encompasses three integral components: a feature extraction module, an encoding module, and an RUL prediction module. During pre-training phase, the framework leverages a multiscale convolutional neural network to extract distinctive features from data across varying scales. The ensuing parameter transfer adopts a domain adaptation strategy centered around maximum mean discrepancy. This method efficiently facilitates the acquisition of domain-invariant features from the source and target domains. The refined domain adaptation Transformer-based multiscale convolutional neural network model exhibits enhanced suitability for predicting RUL in the target domain under the condition of limited samples. Experiments on the C-MAPSS dataset have shown that the proposed method significantly outperforms state-of-the-art methods.

Metalens for improving optical coherence tomography

Guo Songming,Feng Weibin,Long Yong,Liu Zhihao,Fu Xiao,Liang Haowen,Li Juntao 한국물리학회 2022 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.81 No.1

Optical coherence tomography is one of the most attractive new tomographic techniques, especially in the detection and imaging of biological tissues. For the detection and imaging of human corneas, the current ultra-high-resolution optical coherence tomography technology faces the challenge that the depth of focus is too short to scan the entire human cornea in a single amplitude scan. Here, we propose and design a silicon metalens to replace the objective lens in the sample arm of the optical coherence tomography system. In our simulation, a uniform focused beam with a depth of focus of 886 μm, an axial resolution of 3.1 μm and a lateral resolution of 2.2 μm can be generated by the metalens, which is under the excitation of broadband Gaussian light with wavelength coverage from 800 to 900 nm. This metalens fully satisfies the depth of focus and resolution requirements of the ultra-high-resolution optical coherence tomography system for human corneas, hence expands the application of optical coherence tomography in medical science for the benefit of mankind.

Research on Adaptive Optimal Control Strategy of Parallel Plug-In Hybrid Electric Vehicle Based on Route Information

Liu Kangjie,Guo Jianhua,Chu Liang,Yu Yuanbin 한국자동차공학회 2021 International journal of automotive technology Vol.22 No.4

Since fuel consumption of parallel Plug-in hybrid electric vehicles (PHEVs) is significantly different in various driving cycles, an adaptive optimal control strategy based on route information is proposed. First, the energy management strategy structure of adaptive Pontryagin’s Minimum Principle (APMP) is established. Second, genetic algorithm is employed to obtain a Map, which is co-state function of driving distances and state of charge (SOC) and makes this strategy used online. Furthermore, co-state value is updated in real time according to route information and reference SOC, which improves the adaptability of APMP control strategy. Finally, MATLAB/Simulink and AVL/Cruise software are employed as simulation tools to verify the proposed APMP control strategy. The performance of APMP control strategy is compared to rule-based (RB) control strategy. Results show that the proposed APMP control strategy could greatly improve the fuel economy of the parallel PHEV for different driving conditions.