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477 results on '"Zhang, Chengyun"'

9. Diagnostic efficacy of serum IL-17 and NF-κB expression levels in early detection of lung consolidation in children with Mycoplasma pneumoniae pneumonia

Author

Li Linnan, Wang Yongfang, Cheng Yanbo, Xu Yufang, Xu Weifang, Li Xia, Zhang Chengyun, Ran Shaoyun

Subjects
mycoplasma pnuemoniae pneumonia, lung consolidation, interleukin-17, nuclear factor-κb, diagnosis, Medicine
Abstract

Objective To investigate the expression levels and significance of serum interleukin-17 （IL-17） and nuclear factor-κB （NF-κB） in Mycoplasma pneumoniae pneumonia （MPP） children in acute stage with lung consolidation. Methods Sixty-four children diagnosed with MPP in acute stage were selected. According to the imaging features of chest CT scan or chest X-ray upon admission， all patients were divided into the lung consolidation group （n = 32） and non-lung consolidation group （n = 32）. The serum levels of IL-17 and NF-κB in MPP children were detected and compared between two groups. The relationship between IL-17 and NF-κB was analyzed. The receiver operating characteristic （ROC） curve was drawn. The diagnostic efficacy of serum IL-17 and NF-κB levels for lung consolidation was assessed in MPP children in acute stage. Results The serum levels of IL-17 and NF-κB in the lung consolidation group were higher than those in the non-lung consolidation group （both P < 0.05）. Spearman correlation analysis showed that IL-17 level was positively correlated with NF-κB level in MPP children （rs = 0.818， P < 0.05）. When the serum level of IL-17 was 10.45 pg/mL， the area under the ROC curve （AUC） was 0.806， and the sensitivity and specificity for the diagnosis of lung consolidation in MPP children were 75.0% and 78.1%. When the serum level of NF-κB was 534.13 pg/mL， the AUC was 0.951， and the sensitivity and specificity for the diagnosis of lung consolidation in children with MPP were 90.6% and 84.4%. Conclusions The expression levels of IL-17 and NF-κB are up-regulated in MPP children with lung consolidation in acute stage. Early detection of serum levels of IL-17 and NF-κB has certain diagnostic efficacy for lung consolidation in MPP.

Published
2023
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16. Retrosynthesis with Attention-Based NMT Model and Chemical Analysis of the 'Wrong' Predictions

Author

Duan, Hongliang, Wang, Ling, Zhang, Chengyun, and Li, Jianjun

Subjects
Physics - Chemical Physics, Computer Science - Machine Learning
Abstract

We cast retrosynthesis as a machine translation problem by introducing a special Tensor2Tensor, an entire attention-based and fully data-driven model. Given a data set comprising about 50,000 diverse reactions extracted from USPTO patents, the model significantly outperforms seq2seq model (34.7%) on a top-1 accuracy by achieving 54.1%. For yielding better results, parameters such as batch size and training time are thoroughly investigated to train the model. Additionally, we offer a novel insight into the causes of grammatically invalid SMILES, and conduct a test in which experienced chemists pick out and analyze the "wrong" predictions that may be chemically plausible but differ from the ground truth. Actually, the effectiveness of our model is un-derestimated and the "true" top-1 accuracy can reach to 64.6%., Comment: 15 pages, 10 figures, 3 tables

Published
2019

25. Shoulder work-related musculoskeletal disorders and related factors of workers in 15 industries of China: a cross-sectional study

Author

Liang, Jing, Jia, Ning, Zhang, Feiruo, HuadongZhang, Ling, Ruijie, Liu, Yimin, Li, Gang, Li, Dongxia, Yin, Yan, Shao, Hua, Zhang, Hengdong, Qiu, Bing, Fang, Xinglin, Wang, Dayu, Zeng, Qiang, Chen, Jianchao, Zhang, Danying, Mei, Liangying, Liu, Yongquan, Liu, Jixiang, Zhang, Chengyun, Li, Tianlai, Li, Yu, Tao, Huaiying, Luo, Huan, Wang, Rugang, and Wang, Zhongxu

Published
2022
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26. Prevalence and risk factors analysis for low back pain among occupational groups in key industries of China

Author

Jia, Ning, Zhang, Meibian, Zhang, Huadong, Ling, Ruijie, Liu, Yimin, Li, Gang, Yin, Yan, Shao, Hua, Zhang, Hengdong, Qiu, Bing, Li, Dongxia, Wang, Dayu, Zeng, Qiang, Wang, Rugang, Chen, Jianchao, Zhang, Danying, Mei, Liangying, Fang, Xinglin, Liu, Yongquan, Liu, Jixiang, Zhang, Chengyun, Li, Tianlai, Xu, Qing, Qu, Ying, Zhang, Xueyan, Sun, Xin, and Wang, Zhongxu

Published
2022
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34. Controlling and probing heat generation in an optical heater system

Author

Tuxun Hairegu, Cai Zefeng, Ji Min, Zhang Baobao, Zhang Chengyun, Li Jinping, Yu Xudong, Fu Zhengkun, Zhang Zhenglong, and Zheng Hairong

Subjects
optical thermometry, plasmonic optical heater, rare-earth doped microrod, silver nano-islands, Physics, QC1-999
Abstract

Understanding how plasmonic nanostructures generate heat upon exposure to light, and thus increase the local temperature of the surrounding medium is important for many applications. Reliable temperature manipulation requires analyzing the local temperature distribution as a function of laser density. In this work, an optical heating system containing silver nano-islands (Ag NIs) is designed to enable heat generation at the micro/nanometer scale and the local temperature can reach 1458 K. The heat generation by Ag NIs exposed to near-IR laser light, and the temperature distribution, are detected in situ via the fluorescence intensity ratio technique. It was found that the temperature of the system can be controlled by changing the excitation power. Furthermore, the temperature-dependent UCL of a single Y2O3:Yb3+/Er3+ microrod is studied by taking advantage of the controllable local temperature in the optical heating system. It was found that the color of the upconversion luminescence can be tuned by managing the local temperature, and conversely, the local temperature at the optical heater can be monitored by observing the color change of the rare-earth microrod. The real-time manipulation of plasmonic heating offers an opportunity to control outcomes of thermo-plasmonic effects, which then enables a myriad of practical applications.

Published
2022
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35. White light emission from silicon nanoparticles

Author

Zhang, Chengyun, Xu, Yi, Liu, Jin, Li, Juntao, Xiang, Jin, Li, Hui, Li, Jinxiang, Dai, Qiaofeng, Lan, Sheng, and Miroshnichenko, Andrey E.

Subjects
Physics - Optics, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

As one of the most important semiconductors, silicon (Si) has been used to fabricate electronic devices, waveguides, detectors, and solar cells etc. However, its indirect bandgap hinders the use of Si for making good emitters1. For integrated photonic circuits, Si-based emitters with sizes in the range of 100-300 nm are highly desirable. Here, we show that efficient white light emission can be realized in spherical and cylindrical Si nanoparticles with feature sizes of ~200 nm. The up-converted luminescence appears at the magnetic and electric multipole resonances when the nanoparticles are resonantly excited at their magnetic and electric dipole resonances by using femtosecond (fs) laser pulses with ultralow low energy of ~40 pJ. The lifetime of the white light is as short as ~52 ps, almost three orders of magnitude smaller than the state-of-the-art results reported so far for Si (~10 ns). Our finding paves the way for realizing efficient Si-based emitters compatible with current semiconductor fabrication technology, which can be integrated to photonic circuits., Comment: Comments are welcome! :-)

Published
2017

36. HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints.

Author

Zhang, Chenhao, Zhang, Chengyun, Shang, Tianfeng, Zhu, Ning, Wu, Xinyi, and Duan, Hongliang

Subjects
*CYCLIC peptides, *COMPUTER-assisted drug design, *PEPTIDES, *DRUG development
Abstract

In recent years, cyclic peptides have emerged as a promising therapeutic modality due to their diverse biological activities. Understanding the structures of these cyclic peptides and their complexes is crucial for unlocking invaluable insights about protein target–cyclic peptide interaction, which can facilitate the development of novel-related drugs. However, conducting experimental observations is time-consuming and expensive. Computer-aided drug design methods are not practical enough in real-world applications. To tackles this challenge, we introduce HighFold, an AlphaFold-derived model in this study. By integrating specific details about the head-to-tail circle and disulfide bridge structures, the HighFold model can accurately predict the structures of cyclic peptides and their complexes. Our model demonstrates superior predictive performance compared to other existing approaches, representing a significant advancement in structure–activity research. The HighFold model is openly accessible at https://github.com/hongliangduan/HighFold. [ABSTRACT FROM AUTHOR]

Published
2024
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