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  • MDPI AG  (3)
  • 1
    Online Resource
    Online Resource
    Structural Insights into the Binding of Red Fluorescent Protein mCherry-Specific Nanobodies
    MDPI AG ; 2023
    In:  International Journal of Molecular Sciences Vol. 24, No. 8 ( 2023-04-09), p. 6952-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 24, No. 8 ( 2023-04-09), p. 6952-
    Abstract: Red fluorescent proteins (RFPs) have broad applications in life science research, and the manipulation of RFPs using nanobodies can expand their potential uses. However, the structural information available for nanobodies that bind with RFPs is still insufficient. In this study, we cloned, expressed, purified, and crystallized complexes formed by mCherry with LaM1, LaM3, and LaM8. Then, we analyzed the biochemical properties of the complexes using mass spectrometry (MS), fluorescence-detected size exclusion chromatography (FSEC), isothermal titration calorimetry (ITC), and bio-layer interferometry (BLI) technology. We determined the crystal structure of mCherry-LaM1, mCherry-LaM3, and mCherry-LaM8, with resolutions of 2.05 Å, 3.29 Å, and 1.31 Å, respectively. In this study, we systematically compared various parameters of several LaM series nanobodies, including LaM1, LaM3, and LaM8, with previously reported data on LaM2, LaM4, and LaM6, specifically examining their structural information. After designing multivalent tandem LaM1-LaM8 and LaM8-LaM4 nanobodies based on structural information, we characterized their properties, revealing their higher affinity and specificity to mCherry. Our research provides novel structural insights that could aid in understanding nanobodies targeting a specific target protein. This could provide a starting point for developing enhanced mCherry manipulation tools.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms24086952
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Feature-Based Laser Scan Matching and Its Application for Indoor Mapping
    MDPI AG ; 2016
    In:  Sensors Vol. 16, No. 8 ( 2016-08-10), p. 1265-
    Details
    In: Sensors, MDPI AG, Vol. 16, No. 8 ( 2016-08-10), p. 1265-
    Abstract: Scan matching, an approach to recover the relative position and orientation of two laser scans, is a very important technique for indoor positioning and indoor modeling. The iterative closest point (ICP) algorithm and its variants are the most well-known techniques for such a problem. However, ICP algorithms rely highly on the initial guess of the relative transformation, which will reduce its power for practical applications. In this paper, an initial-free 2D laser scan matching method based on point and line features is proposed. We carefully design a framework for the detection of point and line feature correspondences. First, distinct feature points are detected based on an extended 1D SIFT, and line features are extracted via a modified Split-and-Merge algorithm. In this stage, we also give an effective strategy for discarding unreliable features. The point and line features are then described by a distance histogram; the pairs achieving best matching scores are accepted as potential correct correspondences. The histogram cluster technique is adapted to filter outliers and provide an accurate initial value of the rigid transformation. We also proposed a new relative pose estimation method that is robust to outliers. We use the lq-norm (0 〈 q 〈 1) metric in this approach, in contrast to classic optimization methods whose cost function is based on the l2-norm of residuals. Extensive experiments on real data demonstrate that the proposed method is almost as accurate as ICPs and is initial free. We also show that our scan matching method can be integrated into a simultaneous localization and mapping (SLAM) system for indoor mapping.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s16081265
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
    detail.hit.zdb_id: 2052857-7
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  • 3
    Online Resource
    Online Resource
    Identifying the Critical Risks in Railway Projects Based on Fuzzy and Sensitivity Analysis: A Case Study of Belt and Road Projects
    MDPI AG ; 2019
    In:  Sustainability Vol. 11, No. 5 ( 2019-03-01), p. 1302-
    Details
    In: Sustainability, MDPI AG, Vol. 11, No. 5 ( 2019-03-01), p. 1302-
    Abstract: The Belt and Road Initiative (BRI) is a Chinese development strategy developed in order to establish connectivity and deepen cooperation between China and other countries, increase trade, and support the socio-economic development of vast regions. A significant number of railway projects are planned to be constructed under BRI since railways are the most efficient means of transportation. This paper investigates the critical risks in railway projects implemented under BRI. In total, 24 potential risks in BRI railway projects are identified and categorized into 6 groups. A questionnaire survey is conducted in order to collect data about the probability of risk occurrence and their impact. To identify the critical risks in railway projects, a novel method based on fuzzy and sensitivity analysis is developed and applied for risk assessment. This method uses a fuzzy synthetic evaluation approach to assess risks and sensitivity analysis as criteria for critical risk identification. The results show that the most critical risks in railway projects are changes in design, design errors, cooperation between China and BRI country, loan risk, complex geological conditions of terrain, and geopolitical risk. The theoretical contribution of this paper is a novel method which combines fuzzy and sensitivity analysis into a single approach.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su11051302
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2518383-7
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