Dataset Information

Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading.

ABSTRACT: The time-series topography change of a landfill site before its failure has rarely been surveyed in detail. However, this information is important for both landfill management and early warning of landslides. Here, we take the 2015 Shenzhen landslide as an example, and we use the radar shape-from-shading (SFS) technique to retrieve time-series digital elevation models of the landfill. The results suggest that the total filling volume reached 4,074,300 m³ in the one and a half years before the landslide, while 2,817,400?m³ slid down in the accident. Meanwhile, the landfill rate in most areas exceeded 2?m/month, which is the empirical upper threshold in landfill engineering. Using topography captured on December 12, 2015, the slope safety analysis gives a factor of safety of 0.932, suggesting that this slope was already hazardous before the landslide. We conclude that the synthetic aperture radar (SAR) SFS technique has the potential to contribute to landfill failure monitoring.

SUBMITTER: Wang C

PROVIDER: S-EPMC5335704 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading.

Wang Chisheng C Li Qingquan Q Zhu Jiasong J Gao Wei W Shan Xinjian X Song Jun J Ding Xiaoli X

Scientific reports 20170303

The time-series topography change of a landfill site before its failure has rarely been surveyed in detail. However, this information is important for both landfill management and early warning of landslides. Here, we take the 2015 Shenzhen landslide as an example, and we use the radar shape-from-shading (SFS) technique to retrieve time-series digital elevation models of the landfill. The results suggest that the total filling volume reached 4,074,300 m<sup>3</sup> in the one and a half years be ...[more]

PMID: 28256522

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Project description:Inhibitor discovery for protein-protein interactions has proven difficult due to the large protein surface areas and dynamic interfaces involved. This is particularly the case when targeting transcription-factor-protein interactions. To address this challenge, structural biology approaches for ligand discovery using X-ray crystallography, mass spectrometry, and nuclear magnetic resonance (NMR) spectroscopy have had a significant impact on advancing small molecule inhibitors into the clinic, including the U.S. Food and Drug Administration approved drug, Venetoclax. Inspired by the protein-observed NMR approach using 1H-15N-HSQC NMR which detects chemical shift perturbations of 15N-labeled amides, we have applied a complementary protein-observed 19F NMR approach using 19F-labeled side-chains that are enriched at protein-protein-interaction interfaces. This protein-observed 19F NMR assay is abbreviated PrOF NMR to distinguish the experiment from the more commonly employed ligand-observed 19F NMR methods. In this Account, we describe our efforts using PrOF NMR as a ligand discovery tool, particularly for fragment-based ligand discovery (FBLD). We metabolically label the aromatic amino acids on proteins due to the enrichment of aromatic residues at protein interfaces. We choose the 19F nucleus due to its high signal sensitivity and the hyperresponsiveness of 19F to changes in chemical environment. Simultaneous labeling with two different types of fluorinated aromatic amino acids for PrOF NMR has also been achieved. We first describe the technical aspects of considering the application of PrOF NMR for characterizing native protein-protein interactions and for ligand screening. Several test cases are further described with a focus on a transcription factor coactivator interaction with the KIX domain of CBP/p300 and two epigenetic regulatory domains, the bromodomains of BRD4 and BPTF. Through these case studies, we highlight medicinal chemistry applications in FBLD, selectivity screens, structure-activity relationship (SAR) studies, and ligand deconstruction approaches. These studies have led to the discovery of some of the first inhibitors for BPTF and a novel inhibitor class for the N-terminal bromodomain of BRD4. The speed, ease of interpretation, and relatively low concentration of protein needed for NMR-based binding experiments affords a rapid, structural biology-based method to discover and characterize both native and new ligands for bromodomains, and it may find utility in the study of additional epigenetic proteins and transcription-factor-protein interactions.

Dataset Information

Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading.

Publications

Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading.

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