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1,138 results on '"Li, Chengwei"'

21. EFFECTS OF HUMAN URINE-DERIVED STEM CELL EXOSOMES ON THE PROLIFERATION AND DIFFERENTIATION OF NUCLEUS PULPOSUS-LIKE URINE-DERIVED STEM CELLS

Author

ZHU Youfu, LI Chengwei, SHEN Nana, XIANG Hongfei, CHEN Bohua, GUO Zhu

Subjects
stem cell research, nucleus pulposus, exosomes, cell differentiation, cell proliferation, tissue engineering, Medicine
Abstract

Objective To explore the relationship between degree of differentiation and time of differentiation of nucleus pulposus-like urine-derived stem cells (NP-USC) and the effects of human urine-derived stem cell exosomes (USC-EXO) on the proliferation and differentiation of NP-USC. Methods Nucleus pulposus cells (NPC) and urine-derived stem cells (USC) were extracted, identified, and cultured. According to the co-cultivation time, the cells were divided into group A (after 7 d of co-culture, the NP-USC were cultured in exosome-free USC medium for 14 d), group B (after 14 d of co-culture, the NP-USC were cultured in exosome-free USC medium for 7 d), group C (USC were cultured alone for 21 d), and NPC group (NPC were cultured alone for 21 d). Quantitative real-time PCR (RT-qPCR) and Western blot were used to measure the mRNA and protein expression of hypoxia-inducible factor 1α (HIF-1α), glucose transporter 1 (GLUT1), type Ⅱ collagen (COL2), and proteoglycan (ACAN) in the five groups. The cells in the five groups were cultured in exosome-free USC medium for 28 d, and CCK-8 was used to detect the cell proliferation on day 7, 14, 21, and 28. Results RT-qPCR and Western blot results showed that the relative mRNA and protein expression levels of HIF-1α, GLUT1, COL2, and ACAN increased sequentially in groups USC, A, B, and C (t=53.36-371.86,P0.05). There was no significant difference in the relative expression levels of the four genes in the cells of the five groups after adding USC-EXO (P>0.05). The results of CCK-8 showed that the cell viability decreased sequentially in groups USC, A, B, and C at each time point (F=3.77-103.58,P0.05). In each of the five groups, the cell viability gradually increased with the prolongation of culture time (F=9.96-121.68,P

Published
2023
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28. The Value of Ensemble Learning Model Based on Conventional Non-Contrast MRI in the Pathological Grading of Cervical Cancer

Author

He, Zhimin, Lv, Fajin, Li, Chengwei, Liu, Yang, Xiao, Zhibo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Qin, Wenjian, editor, Zaki, Nazar, editor, Zhang, Fa, editor, Wu, Jia, editor, Yang, Fan, editor, and Li, Chao, editor

Published
2023
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39. A Multi-Modal States based Vehicle Descriptor and Dilated Convolutional Social Pooling for Vehicle Trajectory Prediction

Author

Zhang, Huimin, Wang, Yafei, Liu, Junjia, Li, Chengwei, Ma, Taiyuan, and Yin, Chengliang

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Artificial Intelligence
Abstract

Precise trajectory prediction of surrounding vehicles is critical for decision-making of autonomous vehicles and learning-based approaches are well recognized for the robustness. However, state-of-the-art learning-based methods ignore 1) the feasibility of the vehicle's multi-modal state information for prediction and 2) the mutual exclusive relationship between the global traffic scene receptive fields and the local position resolution when modeling vehicles' interactions, which may influence prediction accuracy. Therefore, we propose a vehicle-descriptor based LSTM model with the dilated convolutional social pooling (VD+DCS-LSTM) to cope with the above issues. First, each vehicle's multi-modal state information is employed as our model's input and a new vehicle descriptor encoded by stacked sparse auto-encoders is proposed to reflect the deep interactive relationships between various states, achieving the optimal feature extraction and effective use of multi-modal inputs. Secondly, the LSTM encoder is used to encode the historical sequences composed of the vehicle descriptor and a novel dilated convolutional social pooling is proposed to improve modeling vehicles' spatial interactions. Thirdly, the LSTM decoder is used to predict the probability distribution of future trajectories based on maneuvers. The validity of the overall model was verified over the NGSIM US-101 and I-80 datasets and our method outperforms the latest benchmark.

Published
2020

48. Total glucosides of paeony alleviates cGAS-STING-mediated diseases by blocking the STING-IRF3 interaction

Author

XIU, Ye, primary, WANG, Sihao, additional, ZHANG, Ping, additional, LI, Chengwei, additional, WU, Zhixin, additional, WEN, Jincai, additional, XU, Yingjie, additional, LV, Guiji, additional, ZHAO, Xiaomei, additional, DONG, Xu, additional, CHEN, Yichong, additional, LI, Junjie, additional, WANG, Yan, additional, ZOU, Liang, additional, XIAO, Xiaohe, additional, and BAI, Zhaofang, additional

Published
2024
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