Temozolomide Drives Ferroptosis via a DMT1-Dependent Pathway in Glioblastoma Cells

Qingxin Song,Shanxin Peng,Zhiqing Sun,Xueyuan Heng,Xiaosong Zhu 연세대학교의과대학 2021 Yonsei medical journal Vol.62 No.9

Purpose: Temozolomide is used in first-line treatment for glioblastoma. However, chemoresistance to temozolomide is commonin glioma patients. In addition, mechanisms for the anti-tumor effects of temozolomide are largely unknown. Ferroptosis is a formof programmed cell death triggered by disturbed redox homeostasis, overloaded iron, and increased lipid peroxidation. The presentstudy was performed to elucidate the involvement of ferroptosis in the anti-tumor mechanisms of temozolomide. Materials and Methods: We utilized the CCK8 assay to evaluate cytotoxicity. Levels of lactate dehydrogenase (LDH), malondialdehyde(MDA), iron, and glutathione (GSH) were measured. Flow cytometry and fluorescence microscope were used to detectthe production of reactive oxygen species (ROS). Western blotting, RT-PCR and siRNA transfection were used to investigate molecularmechanisms. Results: Temozolomide increased the levels of LDH, MDA, and iron and reduced GSH levels in TG905 cells. Furthermore, wefound that ROS levels and DMT1 expression were elevated in TG905 cells treated with temozolomide and were accompanied bya decrease in the expression of glutathione peroxidase 4, indicating an iron-dependent cell death, ferroptosis. Our results alsoshowed that temozolomide-induced ferroptosis is associated with regulation of the Nrf2/HO-1 pathway. Conversely, DMT1 knockdownby siRNA evidently blocked temozolomide-induced ferroptosis in TG905 cells. Conclusion: Taken together, our findings indicate that temozolomide may suppress cell growth partly by inducing ferroptosis bytargeting DMT1 expression in glioblastoma cells.

Identification of moving train loads on railway bridge based on strain monitoring

Hao Wang,Qingxin Zhu,Jian Li,Jianxiao Mao,Suoting Hu,Xinxin Zhao 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.23 No.3

Moving train load parameters, including train speed, axle spacing, gross train weight and axle weights, are identified based on strain-monitoring data. In this paper, according to influence line theory, the classic moving force identification method is enhanced to handle time-varying velocity of the train. First, the moments that the axles move through a set of fixed points are identified from a series of pulses extracted from the second derivative of the structural strain response. Subsequently, the train speed and axle spacing are identified. In addition, based on the fact that the integral area of the structural strain response is a constant under a unit force at a unit speed, the gross train weight can be obtained from the integral area of the measured strain response. Meanwhile, the corrected second derivative peak values, in which the effect of time-varying velocity is eliminated, are selected to distribute the gross train weight. Hence the axle weights could be identified. Afterwards, numerical simulations are employed to verify the proposed method and investigate the effect of the sampling frequency on the identification accuracy. Eventually, the method is verified using the real-time strain data of a continuous steel truss railway bridge. Results show that train speed, axle spacing and gross train weight can be accurately identified in the time domain. However, only the approximate values of the axle weights could be obtained with the updated method. The identified results can provide reliable reference for determining fatigue deterioration and predicting the remaining service life of railway bridges.

Investigation on vibration behavior of a high-speed railway bridge based on monitoring data

Hao Wang,Qingxin Zhu,Billie F. Spencer Jr 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.31 No.6

Field monitoring techniques offer an attractive approach for understanding bridge behavior under in-service loads. However, the investigations on bridge behavior under high-speed train load using field monitoring data are limited. The focus of this study is to explore the structural behavior of an in-service long-span steel truss arch bridge based on field monitoring data. First, the natural frequencies of the structure, as well as the train driving frequencies, are extracted. Then, the train-induced bearing displacement and structural strain are explored to identify the effects of train loads and bearings. Subsequently, a sensitivity analysis is performed for the impact factor of strain responses with respect to the train speed, train weight, and temperature to identify the fundamental issues affecting these responses. Additionally, a similar sensitivity analysis is conducted for the peak acceleration. The results indicate that the friction force in bearings provides residual deformations when two consecutive trains are in opposite directions. In addition, the impact factor and peak acceleration are primarily affected by train speed, particularly near train speeds that result in the resonance of the bridge response. The results can provide additional insight into the behavior of the long-span steel truss bridges under in-service high-speed train loads.

Temperature distribution analysis of steel box-girder based on long-term monitoring data

Hao Wang,Qingxin Zhu,Zhongqin Zou,Chenxi Xing,Dongming Feng,Tianyou Tao 국제구조공학회 2020 Smart Structures and Systems, An International Jou Vol.25 No.5

Temperature may have more significant influences on structural responses than operational loads or structural damage. Therefore, a comprehensive understanding of temperature distributions has great significance for proper design and maintenance of bridges. In this study, the temperature distribution of the steel box girder is systematically investigated based on the structural health monitoring system (SHMS) of the Sutong Cable-stayed Bridge. Specifically, the characteristics of the temperature and temperature difference between different measurement points are studied based on field temperature measurements. Accordingly, the probability density distributions of the temperature and temperature difference are calculated statistically, which are further described by the general formulas. The results indicate that: (1) the temperature and temperature difference exhibit distinct seasonal characteristics and strong periodicity, and the temperature and temperature difference among different measurement points are strongly correlated, respectively; (2) the probability density of the temperature difference distribution presents strong non-Gaussian characteristics; (3) the probability density function of temperature can be described by the weighted sum of four Normal distributions. Meanwhile, the temperature difference can be described by the weighted sum of Weibull distribution and Normal distribution.

A Fast Detection and Recognition Algorithm for Pedestrian at Night Based on Entropy Weight Fast Support Vector Machine

Liang Rui,Wei Honglei,Zhu Qingxin,Liao Shujiao,Deng Hongyao 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.5

In allusion to such problems as real-time requirement dissatisfaction and significant recognition difference caused by dimension difference existing in the imaging and recognition algorithm for pedestrian in dark scene, a fast head detection and recognition method for pedestrian at night based on fast support vector machine (FC-SVM) algorithm optimization and entropy weight is established in this paper according to relevant principle of statistics. Based on entropy weight, this method aims at improving the extraction process based on histogram gradient features in order to establish threebranch SVM for the deep recognition of pedestrian at night; meanwhile, FC-SVM algorithm is combined to optimize the recognition calculation overhead in order to ensure the real-time property of the recognition algorithm. Furthermore, the falsely detected pedestrians are evaluated on the basis of the head detection mode so as to improve pedestrian imaging matching accuracy. The simulation result shows that this method can not only effectively recognize FIR target of pedestrian at night, but also effectively adapt to such different application environments as urban and suburban areas on the basis of ensuring the real-time requirement for pedestrian recognition, thus presenting good practicability.

A Position Detection Method for Dynamic Wireless Inspection Robots Charging

Xue Ming,Yang Qingxin,Zhu Gaojia,Li Longnv 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.1

The paper proposes a new structure of the receiving coil, which features horizontal and vertical position detection of inspection robot, which eliminates the system dependence on complex detection control circuit and simplifi es the circuit design of the receiving end. The proposed design obtains the position information by comparing the induced voltage diff erence of the four-coil sets. Besides, the receiving coil is optimized in terms of the shape, dimension and the magnetic shielding structure by fi nite element analysis. Finally, the eff ectiveness of the receiving coil position detection is verifi ed by the experiment with misalignment disturbance. The results illustrate the eff ectiveness of the four-coil system to detect the load position and the position adjustment by the adjustment control system