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Your search keyword '"Gao, Wenyuan"' showing total 280 results
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280 results on '"Gao, Wenyuan"'

2. CryoGEM: Physics-Informed Generative Cryo-Electron Microscopy

Author

Zhang, Jiakai, Chen, Qihe, Zeng, Yan, Gao, Wenyuan, He, Xuming, Liu, Zhijie, and Yu, Jingyi

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In the past decade, deep conditional generative models have revolutionized the generation of realistic images, extending their application from entertainment to scientific domains. Single-particle cryo-electron microscopy (cryo-EM) is crucial in resolving near-atomic resolution 3D structures of proteins, such as the SARS- COV-2 spike protein. To achieve high-resolution reconstruction, a comprehensive data processing pipeline has been adopted. However, its performance is still limited as it lacks high-quality annotated datasets for training. To address this, we introduce physics-informed generative cryo-electron microscopy (CryoGEM), which for the first time integrates physics-based cryo-EM simulation with a generative unpaired noise translation to generate physically correct synthetic cryo-EM datasets with realistic noises. Initially, CryoGEM simulates the cryo-EM imaging process based on a virtual specimen. To generate realistic noises, we leverage an unpaired noise translation via contrastive learning with a novel mask-guided sampling scheme. Extensive experiments show that CryoGEM is capable of generating authentic cryo-EM images. The generated dataset can used as training data for particle picking and pose estimation models, eventually improving the reconstruction resolution.

Published
2023

44. Dual targeting of wild‐type p53 and gut microbiota by Magnolol represses key metabolic process and kills CRC cells.

Author

Ji, Haixia, Qiao, Ou, Zhang, Yi, Wang, Wenzhe, Han, Xiaoyin, Zhang, Xinyu, Liu, Changxiao, and Gao, Wenyuan

Abstract

Cancer cells consume considerable glucose quantities and majorly employ glycolysis for ATP generation. This metabolic signature (the Warburg effect) allows cancer cells to channel glucose to biosynthesis to support and maintain their dramatic growth along with proliferation. Currently, our understanding of the metabolic and mechanistic implications of the Warburg effect along with its relationship with biosynthesis remains unclear. Herein, we illustrate that the tumor repressor p53 mediate Magnolol (MAG) triggers colon cancer cell apoptosis. And MAG regulates the glycolytic and oxidative phosphorylation steps through transcriptional modulation of its downstream genes TP53‐induced glycolysis modulator and biosynthesis of cytochrome c oxidase, attenuating cell proliferation and tumor growth in vivo and in vitro. Meanwhile, we show that MAG cooperates with its own intestinal microflora characteristic metabolites to repress tumors, especially remarkably declined kynurenine (Kyn)/tryptophan (Trp) ratio. Besides, strong relationships of MAG influenced genes, microbiota, as well as metabolites, were explored. Therefore, we established that p53‐microbiota‐metabolites function as a mechanism, which enable therapy approaches against metabolism‐implicated colorectal cancer, in particular MAG as a prospective candidate for treating colorectal cancer. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Analysis and Prediction of Atmospheric Environmental Quality Based on the Autoregressive Integrated Moving Average Model (ARIMA Model) in Hunan Province, China.

Author

Gao, Wenyuan, Xiao, Tongjue, Zou, Lin, Li, Huan, and Gu, Shengbo

Abstract

Based on the panel data of atmospheric environmental pollution in Hunan Province from 2016 to 2023, the autoregressive integrated moving average model (ARIMA) is introduced to evaluate and predict the current status of atmospheric environmental quality in Hunan Province of China, and the constructed ARIMA model has an excellent prediction effect on the atmospheric environmental quality in Hunan Province. The following conclusions are obtained through the prediction and analysis based on the ARIMA model: (1) the atmospheric environmental quality in Hunan Province shows a year-on-year improvement trend; (2) the ARIMA model prediction method is reliable and effective and can accurately analyze and predict the concentrations of air pollutants (PM2.5, PM10, SO2, and CO) and atmospheric environmental quality, and the prediction results show that the outdoor air quality of Hunan Province will improve gradually each year from 2024 to 2028; (3) this study contributes a better understanding of the ambient air quality in Hunan Province during 2016–2023 and provides good forecasting results for air pollutants during the period of 2024–2028. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Hosts engineering and in vitro enzymatic synthesis for the discovery of novel natural products and their derivatives.

Author

Zhang, Huanyu, Guo, Lanping, Su, Yaowu, Wang, Rubing, Yang, Wenqi, Mu, Wenrong, Xuan, Liangshuang, Huang, Luqi, Wang, Juan, and Gao, Wenyuan

Subjects
DRUG discovery, TRITERPENOID saponins, GENE expression, NATURAL products, GENE clusters
Abstract

Novel natural products (NPs) and their derivatives are important sources for drug discovery, which have been broadly applied in the fields of agriculture, livestock, and medicine, making the synthesis of NPs and their derivatives necessarily important. In recent years, biosynthesis technology has received increasing attention due to its high efficiency in the synthesis of high value-added novel products and its advantages of green, environmental protection, and controllability. In this review, the technological advances of biosynthesis strategies in the discovery of novel NPs and their derivatives are outlined, with an emphasis on two areas of host engineering and in vitro enzymatic synthesis. In terms of hosts engineering, multiple microorganisms, including Streptomyces, Aspergillus, and Penicillium, have been used as the biosynthetic gene clusters (BGCs) provider and host strain for the expression of BGCs to discover new compounds over the past years. In addition, the use of in vitro enzymatic synthesis strategy to generate novel compounds such as triterpenoid saponins and flavonoids is also hereby described. [ABSTRACT FROM AUTHOR]

Published
2024
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