Publications by authors named "F Ye"

3,012 Publications

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Tunable Circularly Polarized Luminescence from Single Crystal and Powder of the Simplest Tetraphenylethylene Helicate.

ACS Nano 2021 Sep 21. Epub 2021 Sep 21.

Key Laboratory of Material Chemistry for Energy Conversion and Storage, Ministry of Education, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.

Tetraphenylethylene and its derivatives are a class of aggregation-induced emission (AIE) compounds that are most extensively and successfully studied. It has been found that the simplest TPE is easy to crystallize into homochiral M crystals or P crystals. However, no research on circularly polarized luminescence (CPL) of TPE solid is documented. In this paper, we report that TPE can grow into big and nonefflorescent single crystals in single helical conformation and has large birefringence that is comparative with commercially available products. The TPE single crystals can emit strong CPL with a very high value up to 0.53. Moreover, the sense and magnitude of CPL signals can be willfully tuned by simple rotation of the single crystal due to anisotropy of the crystals. This simple and promising CPL photonic material integrates emission, chirality, and birefringence together in one single crystal without needing an additional chiral dopant or conjugate polymer that can produce linearly polarized light. After being ground into fine powder and pressed as KBr pellets, the obtained nanocrystals of TPE also emit strong CPL light. Exceptionally, by mixing other achiral luminescent dyes together with TPE powder in KBr pellets, induced CPL signals were obtained, which could give full-color CPL emission. Although there were no interactions between TPE and the dyes in the pellets, induced CPL signals were realized through radiative energy transfer, providing a very simple method for the tuning of CPL emission.
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http://dx.doi.org/10.1021/acsnano.1c06644DOI Listing
September 2021

Orthogonal genome-wide screens of bat cells identify MTHFD1 as a target of broad antiviral therapy.

Proc Natl Acad Sci U S A 2021 Sep;118(39)

MOE Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Beijing Advanced Innovation Center for Structural Biology, School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Center for Infectious Disease Research, School of Medicine, Tsinghua University, 100084 Beijing, China;

Bats are responsible for the zoonotic transmission of several major viral diseases, including those leading to the 2003 SARS outbreak and likely the ongoing COVID-19 pandemic. While comparative genomics studies have revealed characteristic adaptations of the bat innate immune system, functional genomic studies are urgently needed to provide a foundation for the molecular dissection of the viral tolerance in bats. Here we report the establishment of genome-wide RNA interference (RNAi) and CRISPR libraries for the screening of the model megabat, We used the complementary RNAi and CRISPR libraries to interrogate cells for infection with two different viruses: mumps virus and influenza A virus, respectively. Independent screening results converged on the endocytosis pathway and the protein secretory pathway as required for both viral infections. Additionally, we revealed a general dependence of the C1-tetrahydrofolate synthase gene, MTHFD1, for viral replication in bat cells and human cells. The MTHFD1 inhibitor, carolacton, potently blocked replication of several RNA viruses, including SARS-CoV-2. We also discovered that bats have lower expression levels of MTHFD1 than humans. Our studies provide a resource for systematic inquiry into the genetic underpinnings of bat biology and a potential target for developing broad-spectrum antiviral therapy.
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http://dx.doi.org/10.1073/pnas.2104759118DOI Listing
September 2021

Automatic flow delay through passive wax valves for paper-based analytical devices.

Lab Chip 2021 Sep 20. Epub 2021 Sep 20.

School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China.

Microfluidic paper-based analytical devices (μPADs) have been widely explored for point-of-care testing due to their simplicity, low cost, and portability. μPADs with multiple-step reactions usually require precise flow control, especially flow-delay. This paper reports the numerical, mathematical, and experimental studies of flow delay through wax valves surrounded by PDMS walls on paper microfluidics. The predried surfactant in the sample zone diffuses into the liquid sample which can therefore flow through the wax valves. The delay time is automatically regulated by the diffusion of the surfactant after sample loading. The numerical study suggested that both the elevated contact angle and the reduced porosity and pore size in the wax printed region could effectively prevent water but allow liquids with lower contact angles (, surfactant solutions) to flow through. The PDMS walls fabricated using a low-cost liquid dispenser effectively prevented the leakage of surfactant solutions. By controlling the quantity, diffusion distance, and type of the surfactant predried on the chip, the system successfully achieved a delay time ranging from 1.6 to 20 minutes. A mathematical model involving the above parameters was developed based on Fick's second law to predict the delay time. Finally, the flow-delay systems were applied in sequential mixing and distance-based detection of either glucose or alcohol. Linear ranges of 1-100 mg dL and 1-40 mg dL were achieved for glucose and alcohol, respectively. The lower limit detection (LOD) of glucose and alcohol was 1 mg dL. The LOD of glucose was only 1/11 of that detected using μPADs without flow control, indicating the advantage of controlling fluid flow. The systematic findings in this study provide critical guidelines for the development and applications of wax valves in automatic flow delay for point-of-care testing.
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http://dx.doi.org/10.1039/d1lc00638jDOI Listing
September 2021

Application of CNN Algorithm Based on Chaotic Recursive Diagonal Model in Medical Image Processing.

Comput Intell Neurosci 2021 8;2021:6168562. Epub 2021 Sep 8.

School of Information and Science Technology, Zhejiang Shuren University, Hangzhou 310015, Zhejiang, China.

With the gradual improvement of people's living standards, the production and drinking of all kinds of food is increasing. People's disease rate has increased compared with before, which leads to the increasing number of medical image processing. Traditional technology cannot meet most of the needs of medicine. At present, convolutional neural network (CNN) algorithm using chaotic recursive diagonal model has great advantages in medical image processing and has become an indispensable part of most hospitals. This paper briefly introduces the use of medical science and technology in recent years. The hybrid algorithm of CNN in chaotic recursive diagonal model is mainly used for technical research, and the application of this technology in medical image processing is analysed. The CNN algorithm is optimized by using chaotic recursive diagonal model. The results show that the chaotic recursive diagonal model can improve the structure of traditional neural network and improve the efficiency and accuracy of the original CNN algorithm. Then, the application research and comparison of medical image processing are performed according to CNN algorithm and optimized CNN algorithm. The experimental results show that the CNN algorithm optimized by chaotic recursive diagonal model can help medical image automatic processing and patient condition analysis.
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http://dx.doi.org/10.1155/2021/6168562DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445709PMC
September 2021

Network-Based Identification and Experimental Validation of Drug Candidates Toward SARS-CoV-2 Targeting Virus-Host Interactome.

Front Genet 2021 1;12:728960. Epub 2021 Sep 1.

Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Despite that several therapeutic agents have exhibited promising prevention or treatment on Coronavirus disease-2019 (COVID-19), there is no specific drug discovered for this pandemic. Targeting virus-host interactome provides a more effective strategy for antivirus drug discovery compared with targeting virus proteins. In this study, we developed a network-based infrastructure to prioritize promising drug candidates from natural products and approved drugs targeting host proteins of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). We firstly measured the network distances between drug targets and COVID-19 disease module utilizing the network proximity approach, and identified 229 approved drugs as well as 432 natural products had significant associations with SARS-CoV-2. After searching for previous literature evidence, we found that 60.7% (139/229) of approved drugs and 39.6% (171/432) of natural products were confirmed with antivirus or anti-inflammation. We further integrated our network-based predictions and validated anti-SARS-CoV-2 activities of some compounds. Four drug candidates, including hesperidin, isorhapontigenin, salmeterol, and gallocatechin-7-gallate, have exhibited activity on SARS-COV-2 virus-infected Vero cells. Finally, we showcased the mechanism of actions of isorhapontigenin and salmeterol network analysis. Overall, this study offers forceful approaches for identification of drug candidates on COVID-19, which may facilitate the discovery of antiviral drug therapies.
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http://dx.doi.org/10.3389/fgene.2021.728960DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440948PMC
September 2021
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