Homogeneous Detection of Trypsin in Protein Mixtures Based on Fluorescence Resonance Energy Transfer between Anionic Conjugated Polymer and Fluorescent Probe

Herein we describe a novel and simple conjugated polymer‐fluorescent probe based platform for trypsin detection from protein mixtures in homogeneous solution. This platform takes advantage of specific interaction between the probe and the active site of trypsin and the electrostatic interaction between the polymer and the protein to mediate energy transfer between the polymer and the probe. This method does not require any separation steps, which should facilitate high‐throughput protease screening and drug discovery.

     

Lagrange exponential stability of quaternion-valued memristive neural networks with time delays

This paper investigates the Lagrange global exponential stability of the quaternion-valued memristive neural networks (QVMNNs). Two kinds of activation functions based on different assumptions are considered. Then, based on the Lyapunov function approach, decomposition method, and some inequality skills, two novel sufficient conditions for lagrange stability of QVMNNs are provided corresponding to different types of activation functions. Lastly, simulation examples are provided to demonstrate the correctness of our theoretical results.     

Detection of non‐small cell lung cancer cells based on microfluidic polarization microscopic image analysis

In early diagnosis of lung cancer, a polarization microscopy is a powerful tool to obtain the optical information of biological tissues. In this paper, a new microfluidic polarization imaging and analysis method was proposed for the detection and classification of cancer‐associated fibroblasts and the two kinds of non‐small cell lung cancer cells, A549 and H322. A polarizing microscopy system was constructed based on a commercial microscope to obtain 3*3 Mueller matrix of cells. Based on the Muller matrix decomposition algorithm and analysis in spatial domain and frequency domain, appropriate classification parameters were selected for the characterization of different polarization characteristics of cells. Finally, the logistic regression models based on machine learning were applied to determine optimal feature parameters and classify cells. This method integrated the morphological information of the cells, and the polarization characteristics of the cells in different polarization states. It is for the first time that the polarization microscopic image analysis method has been applied to the detection and classification of non‐small cell lung cancer cells. The results show that the presented microfluidic polarization microscopic image analysis method could classify cells effectively. Compared with the Muller matrix measurement and calculation methods, the method proposed in this paper was greatly simplified in both the acquisition of polarized images and the analysis and processing of polarized images.     

传统Spar平台垂荡主共振时非线性耦合响应的研究

考虑瞬时波面影响,建立了Spar平台垂荡-纵摇运动的参数激励耦合运动方程,应用多尺度法导出了波浪频率接近垂荡固有频率时响应方程的一阶摄动解并做数值验证。计算结果显示:当波浪高度达到一定值时,纵摇运动中出现大量的亚谐频率成分;随着波浪高度进一步增大,纵摇运动将出现明显的幅值跳跃现象。研究结果表明,能量渗透现象是纵摇运动失稳的主要原因,波浪激励力矩对于纵摇本身的贡献很小。由于垂荡模态存在能量饱和现象,多余的垂荡能量将会向纵摇模态转移,导致出现大幅值的纵摇运动。     

Fluorogenic Trp(redBODIPY) cyclopeptide targeting keratin 1 for imaging of aggressive carcinomas

Keratin 1 (KRT1) is overexpressed in squamous carcinomas and associated with aggressive pathologies in breast cancer. Herein we report the design and preparation of the first Trp-based red fluorogenic amino acid, which is synthetically accessible in a few steps and displays excellent photophysical properties, and its application in a minimally-disruptive labelling strategy to prepare a new fluorogenic cyclopeptide for imaging of KRT1+ cells in whole intact tumour tissues.

Trp(redBODIPY) is the first red-emitting Trp-based amino acid for the preparation of fluorogenic peptides with retention of target binding affinity.     

Ni离子辐照国产ZIRLO合金的辐照性能研究

国产ZIRLO合金是CAP1400重要的燃料包壳管候选材料之一,因此需要在使用前对该材料进行辐照性能考验。研究了国产ZIRLO合金的辐照性能随辐照温度和损伤剂量的变化。辐照实验在中国原子能科学研究院HI-13串列加速器上,采用80 MeV的Ni离子进行,辐照产生的损伤采用透射电子显微镜、能量色散谱和纳米压痕法等方法表征。国产ZIRLO合金在300℃经10 dpa损伤剂量辐照后观察到均匀分布的析出颗粒,同样剂量在700℃辐照析出颗粒数目减少,析出相的主要成分为Nb。辐照后出现硬化现象,辐照损伤剂量越大,硬化程度越高;随着辐照温度升高,辐照硬化呈减小趋势。The domestic ZIRLO is a promising candidate of cladding materials for CAP1400. It is necessary to test its radiation properties before its use. In this paper, the radiation properties of the domestic ZIRLO have been studied as functions of irradiation temperature and dose respectively. The experiment was performed at the HI-13 tandem accelerator of China Institute of Atomic Energy by using 80 MeV Ni ions at different temperature and different dose. The transmission electron microscopy, electron dispersive spectroscopy and nano-indentation were used to characterize the radiation damage. The experimental results show that the precipitates are uniformly distributed at 10 dpa and 300℃, while at 700℃ the number of precipitates is reduced. Among all the precipitates, Nbisthe dominant element. Hardening phenomenon was also observed after irradiation, the higher the radiation dose, the higher the degree of hardening, and it illustrates a decreasing tendency with the increasing of the irradiation temperature.     

A Fractal Model for Oil Transport in Tight Porous Media

Tight porous media are mainly composed of micro/nano-pores and throats, which leads to obvious microscale effect and nonlinear seepage characteristics. Based on the capillary bundle model and the fractal theory, a new nonlinear seepage equation was deduced, and a further fractal permeability model was obtained for oil transport in tight porous media by considering the effect of the boundary layer. The predictions of the model were then compared with experimental data to demonstrate that the model is valid. This model clarifies the oil transport mechanisms in tight porous media: the effective permeability is no longer a constant value and is governed by properties of tight porous media and oil. Furthermore, parameters influencing effective permeability were analyzed. The model can accurately present the seepage characteristics of the oil in tight porous media and provide a reliable basis for the development of unconventional reservoirs.     

软体机器人实践与创新教学

实践教学课程可以帮助学生培养动手与团队协作能力,了解理论知识的实际应用。软体机器人是近年新兴研究领域,蕴含了丰富的力学机理。本文探讨了将其应用于力学教学的选题和组织方法,并介绍了2019年清华大学空天技术科学创新实践营软体机器人项目的实施情况。14位本科生参与项目,成功制作了5个采用不同驱动方法及运动步态的软体机器人。     

A Highly Compatible Phototrophic Community for Carbon-Negative Biosynthesis

CO₂ sequestration engineering is promising for carbon-negative biosynthesis, and artificial communities can solve more complex problems than monocultures. However, obtaining an ideal photosynthetic community is still a great challenge. Herein, we describe the development of a highly compatible photosynthetic community (HCPC) by integrating a sucrose-producing CO₂ sequestration module and a super-coupled module. The cyanobacteria CO₂ sequestration module was obtained using stepwise metabolic engineering and then coupled with the efficient sucrose utilization module Vibrio natriegens. Integrated omics analysis indicated that enhanced photosynthetic electron transport and extracellular vesicles promote intercellular communication. Additionally, the HCPC was used to channel CO₂ into valuable chemicals, enabling the overall release of −22.27 to −606.59 kgCO₂e kg⁻¹ in the end products. This novel light-driven community could facilitate circular economic implementation in the future.     

机器学习在新材料筛选方面的应用进展

新材料产业是许多相关领域技术变革的基础,也是新能源、航空航天、电子信息等高新技术产业发展的先导.传统研发手段由于成本高、效率低、商业化周期长等不利因素无法满足现代社会的发展需求.近年来大数据与人工智能不断深入结合,以数据驱动为核心的机器学习在新材料设计、筛选以及性能预测等方面取得巨大进展,极大促进了新材料的研发与应用.本综述总结了机器学习的基本过程及其在材料科学中常用的算法和相关材料数据库,重点介绍了机器学习在不同功能上的应用以及在催化剂材料、锂离子电池、半导体材料和合金材料等领域的性能预测和材料开发中的最新进展,并对其下一步在新材料应用方面提出展望.