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Your search keyword '"Zhang, Yichao"' showing total 442 results
Start Over Author "Zhang, Yichao" Publication Type Academic Journals
442 results on '"Zhang, Yichao"'

15. Author Correction: Identification of recurrent USP48 and BRAF mutations in Cushing’s disease

Author

Chen, Jianhua, Jian, Xuemin, Deng, Siyu, Ma, Zengyi, Shou, Xuefei, Shen, Yue, Zhang, Qilin, Song, Zhijian, Li, Zhiqiang, Peng, Hong, Peng, Cheng, Chen, Min, Luo, Cheng, Zhao, Dan, Ye, Zhao, Shen, Ming, Zhang, Yichao, Zhou, Juan, Fahira, Aamir, Wang, Yongfei, Li, Shiqi, Zhang, Zhaoyun, Ye, Hongying, Li, Yiming, Shen, Jiawei, Chen, Hong, Tang, Feng, Yao, Zhenwei, Shi, Zhifeng, Chen, Chunjui, Xie, Lu, Wang, Ye, Fu, Chaowei, Mao, Ying, Zhou, Liangfu, Gao, Daming, Yan, Hai, Zhao, Yao, Huang, Chuanxin, and Shi, Yongyong

Published
2023
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18. TXNIP aggravates cardiac fibrosis and dysfunction after myocardial infarction in mice by enhancing the TGFB1/Smad3 pathway and promoting NLRP3 inflammasome activation

Author

Zhang Yan, Wang Jin, Wang Xuejiao, Li Aiyun, Lei Zhandong, Li Dongxue, Xing Dehai, Zhang Yichao, Su Wanzhen, and Jiao Xiangying

Subjects
cardiac fibrosis, cardiac function, inflammasome, myocardial infarction, thioredoxin-interacting protein, Biochemistry, QD415-436, Genetics, QH426-470
Abstract

Myocardial infarction (MI) results in high mortality. The size of fibrotic scar tissue following MI is an independent predictor of MI outcomes. Thioredoxin-interacting protein (TXNIP) is involved in various fibrotic diseases. Its role in post-MI cardiac fibrosis, however, remains poorly understood. In the present study, we investigate the biological role of TXNIP in post-MI cardiac fibrosis and the underlying mechanism using mouse MI models of the wild-type (WT), Txnip-knockout (Txnip-KO) type and Txnip-knock-in (Txnip-KI) type. After MI, the animals present with significantly upregulated TXNIP levels, and their fibrotic areas are remarkably expanded with noticeably impaired cardiac function. These changes are further aggravated under Txnip-KI conditions but are ameliorated in Txnip-KO animals. MI also leads to increased protein levels of the fibrosis indices Collagen I, Collagen III, actin alpha 2 (ACTA2), and connective tissue growth factor (CTGF). The Txnip-KI group exhibits the highest levels of these proteins, while the lowest levels are observed in the Txnip-KO mice. Furthermore, Txnip-KI significantly upregulates the levels of transforming growth factor (TGF)B1, p-Smad3, NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3), Cleaved Caspase-1, and interleukin (IL)1B after MI, but these effects are markedly offset by Txnip-KO. In addition, after MI, the Smad7 level significantly decreases, particularly in the Txnip-KI mice. TXNIP may aggravate the progression of post-MI fibrosis and cardiac dysfunction by activating the NLRP3 inflammasome, followed by IL1B generation and then the enhancement of the TGFB1/Smad3 pathway. As such, TXNIP might serve as a novel potential therapeutic target for the treatment of post-MI cardiac fibrosis.

Published
2023
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38. An intelligent adverse delivery outcomes prediction model based on the fusion of multiple obstetric clinical data.

Author

Zou, Chen, Zhang, Yichao, and Yuan, Zhenming

Subjects
*ARTIFICIAL neural networks, *WOMEN'S mental health, *TIME series analysis, *PREDICTION models, *UNITS of time
Abstract

Adverse delivery outcomes is a major re-productive health problem that affects the physical and mental health of pregnant women. Obviously, obstetric clinical data has periodically time series characteristics. This paper proposed a three stage adverse delivery outcomes prediction model via the fusion of multiple time series clinical data. The first stage is data aggregation, in which the data set is collected from the obstetric clinical data and divided based on time series features. In the second stage, a multi-channel gated cycle unit is used to solve the calculation error caused by irregular sampling of time series data. The hidden layer feature vector is connected with the fully connected layer, reshaped into a new one-dimensional feature, and fused with the non-time series data into a new data set. The third stage is the prediction stage of adverse delivery outcomes. By connecting the multi-channel gated cycle unit with the extreme gradient lift, the data transmitted in the corresponding channel is used in the feature extraction stage, in which the weighted entropy-based feature extraction is adopted. With the help of the extracted features, a hybrid artificial neural network architecture (MGRU-XGB) was developed to predict adverse delivery outcomes. The experimental results showed that the hybrid model had the best prediction performance for adverse delivery outcomes compared with other single models in terms of sensitivity, specificity, AUC and other evaluation indexes. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Novel Frequency Regulation Scenarios Generation Method Serving for Battery Energy Storage System Participating in PJM Market.

Author

Zhang, Yichao, Anvari-Moghaddam, Amjad, Peyghami, Saeed, and Blaabjerg, Frede

Subjects
*BATTERY storage plants, *DISTRIBUTION (Probability theory), *K-means clustering, *DATA protection
Abstract

As one of the largest frequency regulation markets, the Pennsylvania-New Jersey-Maryland Interconnection (PJM) market allows extensive access of Battery Energy Storage Systems (BESSs). The designed signal regulation D (RegD) is friendly for use with BESSs with a fast ramp rate but limited energy. Designing operating strategies and optimizing the sizing of BESSs in this market are significantly influenced by the regulation signal. To represent the inherent randomness of the RegD signal and reduce the computational burden, typical frequency regulation scenarios with lower resolution are often generated. However, due to the rapid changes and energy neutrality of the RegD signal, generating accurate and representative scenarios presents challenges for the methods based on shape similarity. This paper proposes a novel probability-based method for generating typical regulation scenarios. The method relies on the joint probability distribution of two features with a 15-min resolution, extracted from the RegD signal with a 2 s resolution. The two features can effectively portray the characteristic of RegD signal and its influence on BESS operation. Multiple regulation scenarios are generated based on the joint probability distributions of these features at first, with the final typical scenarios chosen based on their probability distribution similarity to the actual distribution. Utilizing regulation data from the PJM market in 2020, this paper validates and analyzes the performance of the generated typical scenarios in comparison to existing methods, specifically K-means clustering and the forward scenarios reduction method. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Sinuous Is a Claudin Required for Locust Molt in Locusta migratoria.

Author

Zhang, Yichao, Li, Hongjing, Lan, Qiuyan, Liu, Xiaoman, Wu, Haihua, Zhang, Jianzhen, Zhao, Xiaoming, and Wang, Yanli

Subjects
*MIGRATORY locust, *CYTOSKELETAL proteins, *EPITHELIAL cells, *ELECTRON microscopy, *CLAUDINS, *MOLTING
Abstract

The epidermal cells of insects are polarized epithelial cells that play a pivotal role in the insect's molting process. Sinuous, a pivotal structural protein involved in the formation of septate junctions among epithelial cells, is essential for its physiological function. In this study, to determine whether sinuous participates in the regulation of insect molting, we identified the sinuous gene, Lmsinu, in Locusta migratoria, which encodes a protein belonging to the claudin family and shares 62.6% identity with Drosophila's sinuous protein. Lmsinu is expressed in multiple tissues, and its expression level in the integument significantly increases prior to molting. Knockdown of Lmsinu in L. migratoria results in larval mortality during molting. Furthermore, hematoxylin and eosin and chitin staining demonstrate that the downregulation of Lmsinu led to a prolonged degradation process of the old cuticle during the molting process. Electron microscopy analysis further revealed that knockdown of Lmsinu disrupts the formation of septate junctions among epidermal cells, which are a monolayer of polarized epithelial cells, which may hinder the functionality of epidermal cells during the process of molting. In summary, these findings suggest that Lmsinu plays a role in nymph molting by regulating the formation of septate junctions among epidermal cells. [ABSTRACT FROM AUTHOR]

Published
2024
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