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127 results on '"Zeng, Wei Zheng"'

4. Spatiotemporal dynamics of PIEZO1 localization controls keratinocyte migration during wound healing.

Author

Holt, Jesse R, Zeng, Wei-Zheng, Evans, Elizabeth L, Woo, Seung-Hyun, Ma, Shang, Abuwarda, Hamid, Loud, Meaghan, Patapoutian, Ardem, and Pathak, Medha M

Subjects
cell biology, cell migration, cellular retraction, collective migration, ion channel dynamics, mechanically activated ion channels, mechanotransduction, molecular biophysics, mouse, structural biology, Animals, Cell Movement, Female, Ion Channels, Keratinocytes, Male, Mice, Mice, Transgenic, Signal Transduction, Wound Healing, 1.1 Normal biological development and functioning, Skin, Biochemistry and Cell Biology
Abstract

Keratinocytes, the predominant cell type of the epidermis, migrate to reinstate the epithelial barrier during wound healing. Mechanical cues are known to regulate keratinocyte re-epithelialization and wound healing; however, the underlying molecular transducers and biophysical mechanisms remain elusive. Here, we show through molecular, cellular, and organismal studies that the mechanically activated ion channel PIEZO1 regulates keratinocyte migration and wound healing. Epidermal-specific Piezo1 knockout mice exhibited faster wound closure while gain-of-function mice displayed slower wound closure compared to littermate controls. By imaging the spatiotemporal localization dynamics of endogenous PIEZO1 channels, we find that channel enrichment at some regions of the wound edge induces a localized cellular retraction that slows keratinocyte collective migration. In migrating single keratinocytes, PIEZO1 is enriched at the rear of the cell, where maximal retraction occurs, and we find that chemical activation of PIEZO1 enhances retraction during single as well as collective migration. Our findings uncover novel molecular mechanisms underlying single and collective keratinocyte migration that may suggest a potential pharmacological target for wound treatment. More broadly, we show that nanoscale spatiotemporal dynamics of Piezo1 channels can control tissue-scale events, a finding with implications beyond wound healing to processes as diverse as development, homeostasis, disease, and repair.

Published
2021

5. PIEZO ion channel is required for root mechanotransduction in Arabidopsis thaliana

Author

Mousavi, Seyed AR, Dubin, Adrienne E, Zeng, Wei-Zheng, Coombs, Adam M, Do, Khai, Ghadiri, Darian A, Keenan, William T, Ge, Chennan, Zhao, Yunde, and Patapoutian, Ardem

Subjects
Plant Biology, Biological Sciences, Arabidopsis, Arabidopsis Proteins, Mechanotransduction, Cellular, Membrane Transport Proteins, Plant Roots, PIEZO, ion channels, mechanosensation, root
Abstract

Plant roots adapt to the mechanical constraints of the soil to grow and absorb water and nutrients. As in animal species, mechanosensitive ion channels in plants are proposed to transduce external mechanical forces into biological signals. However, the identity of these plant root ion channels remains unknown. Here, we show that Arabidopsis thaliana PIEZO1 (PZO1) has preserved the function of its animal relatives and acts as an ion channel. We present evidence that plant PIEZO1 is expressed in the columella and lateral root cap cells of the root tip, which are known to experience robust mechanical strain during root growth. Deleting PZO1 from the whole plant significantly reduced the ability of its roots to penetrate denser barriers compared to wild-type plants. pzo1 mutant root tips exhibited diminished calcium transients in response to mechanical stimulation, supporting a role of PZO1 in root mechanotransduction. Finally, a chimeric PZO1 channel that includes the C-terminal half of PZO1 containing the putative pore region was functional and mechanosensitive when expressed in naive mammalian cells. Collectively, our data suggest that Arabidopsis PIEZO1 plays an important role in root mechanotransduction and establish PIEZOs as physiologically relevant mechanosensitive ion channels across animal and plant kingdoms.

Published
2021

18. Efficacy and safety of lubiprostone for the treatment of functional constipation in Chinese adult patients: A multicenter, randomized, double‐blind, placebo‐controlled trial

Author

Xiao, Ying Lian, primary, Dai, Ning, additional, He, Shui Xiang, additional, Tian, De An, additional, Liu, Si De, additional, Tian, Zi Bin, additional, Wang, Xiao Yan, additional, Li, Yan Qing, additional, Hou, Xiao Hua, additional, Fang, Xiu Cai, additional, Wen, Zhi Li, additional, Zeng, Wei Zheng, additional, Xu, Hong, additional, Sun, Ming Jun, additional, Liu, Yu Lan, additional, Wu, Yong Dong, additional, Shen, Xi Zhong, additional, Liu, Xiao Wei, additional, Liu, De Liang, additional, and Chen, Min Hu, additional

Published
2021
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29. Lamivudine plus adefovir is a good option for chronic hepatitis B patients with viral relapse after cessation of lamivudine treatment

Author

Zhang Yong, Xu Hui, Zeng Wei-Zheng, Wu Xiao-Ling, Wang Zhao, Qin Jian-Ping, and Jiang Ming-De

Subjects
ADV plus LAM, LAM alone, retreatment, chronic hepatitis B, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Aim Currently, there is no consensus on the retreatment recommendation of chronic hepatitis B (CHB) patients with viral rebound after cessation of treatment. In the search of reasonable treatment, we compared the efficacy and safety of adefovir (ADV) plus lamivudine (LAM) and LAM alone for the retreatment of patients with viral relapse but without genotypic resistance after cessation of LAM. Methods This is a prospective controlled study, and a total of 53 hepatitis B e antigen (HBeAg)-positive patients with viral rebound but without resistance were received either LAM plus ADV or LAM alone treatment. Results After 1-year treatment, more patients who received LAM plus ADV than those who received LAM alone had ALT normalization (84% versus 53.6%, P = 0.018) or HBV DNA levels below 1000 copies/mL (80% versus 42.9%, P < 0.006). Seven patients receiving LAM plus ADV had HBeAg seroconversion, as compared with 0 in patients receiving ALM alone (28% versus 0%, P = 0.003). During 1-year retreatment, five patients receiving LAM alone had virological breakthrough and all of them had LAM resistance strains (rtM204V/I), while no LAM- or ADV- associated resistance strains were detected in patients receiving LAM plus ADV. All patients receiving LAM plus ADV were well tolerated, and no serious side effects were noted. Conclusions Patients treated with LAM plus ADV exhibited significantly greater virological, biochemical and serological responses compared with LAM alone. These data suggested that combination of LAM plus ADV would be a good option for the retreatment of CHB patients with viral relapse after cessation of LAM.

Published
2011
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30. Short-Term Prediction Model for a Grid-Connected Photovoltaic System Using EMD and GABPNN

Author

Minyi Guo, Zeng Wei Zheng, Yuan Yi Chen, Bo Zhao, Xiao Wei Zhou, and Mei Mei Huo

Subjects
Engineering, Artificial neural network, business.industry, Photovoltaic system, General Medicine, Grid, computer.software_genre, Hilbert–Huang transform, Power (physics), Component (UML), Genetic algorithm, Grid-connected photovoltaic power system, Data mining, business, computer
Abstract

The integration between photovoltaic systems and tradition grid have a lot of challenges. To accurately predict is a key to solve these challenges. Due to complex, non-linear and non-stationary characteristics, it is difficult to accurately predict the power of photovoltaic systems. In this paper, a short-term prediction model based on empirical mode decomposition (EMD)and back propagation neural network(BPNN) was constructed, and use genetic algorithm as the learn algorithm of BPNN. The power data after pre-processing is decomposed into several components, then using prediction model based on BPNN and genetic algorithm to predict each component, and all the component prediction values were aggregated to obtain the ultimate predicted result. The simulation shows the purposed prediction model has higher prediction precision compare with traditional neural network prediction method and it is an effective prediction method of photovoltaic systems.

Published
2013

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