Tissue-Characteristic Expression of Mouse Proteome

The mouse is a valuable model organism for biomedical research. Here, we established a comprehensive spectral library and the data-independent acquisition–based quantitative proteome maps for 41 mouse organs, including some rarely reported organs such as the cornea, retina, and nine paired organs. The mouse spectral library contained 178,304 peptides from 12,320 proteins, including 1678 proteins not reported in previous mouse spectral libraries. Our data suggested that organs from the nervous system and immune system expressed the most distinct proteome compared with other organs. We also found characteristic protein expression of immune-privileged organs, which may help understanding possible immune rejection after organ transplantation. Each tissue type expressed characteristic high-abundance proteins related to its physiological functions. We also uncovered some tissue-specific proteins which have not been reported previously. The testis expressed highest number of tissue-specific proteins. By comparison of nine paired organs including kidneys, testes, and adrenal glands, we found left organs exhibited higher levels of antioxidant enzymes. We also observed expression asymmetry for proteins related to the apoptotic process, tumor suppression, and organ functions between the left and right sides. This study provides a comprehensive spectral library and a quantitative proteome resource for mouse studies.     

基于空间面板STIRPAT模型的水足迹影响因素分析——以山东省为例

随着中国水资源供需矛盾加剧，虚拟水成为地区水资源管理中不可或缺的一环，为提高地区水资源综合利用效率和探索水资源区域一体化管理提供了新思路。采用"自下而上"法核算了山东省17个城市农业、工业、生活、生态与灰水足迹，在分析2009-2018年水足迹时空分布规律基础上，综合运用探索性空间数据分析方法、面板数据STIRPAT模型和空间杜宾模型，揭示了水足迹的空间自相关特征，量化分析了人口数量、富裕程度、技术进步、城镇化和产业升级等影响因素对水足迹的本地影响效应与空间溢出效应。结果显示：①2009-2018年山东省水足迹总量均呈现波动上升的变化趋势；空间布局上呈现东部沿海和西部平原水足迹高，中部山地水足迹低的特点。②山东省水足迹具有正向的空间自相关性，相比地理位置相邻，水足迹的空间相关性受人口数量因素影响更大，表现出明显的"高高"聚集和"低低"聚集特征，但是受到经济因素的主要影响，区域间水足迹空间相关性随时间发展逐渐下降。③人口数量是山东省水足迹增长的重要来源，经济增长是推动各地区间水资源竞争关系的最重要因素。城镇化能够缓解本地水资源压力，技术进步和产业升级不仅能缓解本地水资源压力，而且通过空间溢出效应有效缓解临近地区水资源压力，是实施水资源区域一体化管理策略的重要着眼点。     

The Blue Water Footprint of Primary Copper Production in Northern Chile

Water consumption related to the life cycle of metals is seldom reported, even though mines are often situated in very dry regions. In this study we quantified the life cycle consumption of groundwater and fresh surface water (blue water footprint [WF_blue]) for the extraction and production of high‐grade copper refined from both a copper sulfide ore and a copper oxide ore in the Atacama Desert of northern Chile. Where possible, we used company‐specific data. The processes for extracting copper from the two types of ore are quite different from each other, and the WF_blue of the sulfide ore refining process is 2.4 times higher than that of the oxide ore refining process (i.e., 96 cubic meters per metric ton [tonne] of copper versus 40 cubic meters per tonne of copper). Most of the water consumption (59% of WF_blue) in the sulfide ore process occurred at the concentrator plant, via seepage, accumulation, and also by evaporation. In the oxide ore process, the main user of water is the heap‐leaching process, with 45% of WF_blue. The crushing and agglomeration operations, electrowinning cells, and solution pools are also significant contributors to the total consumption of water in the oxide ore process. Most of the water consumed in the oxide ore process was lost to evaporation. The WF_blue of the oxide ore process can be reduced by preventing water evaporation and using more sophisticated devices during irrigation of the leaching heaps. The WF_blue of the sulfide ore refining process can be reduced by improving water recovery (i.e., reducing seepage, accumulation, and evaporation) from the tailings dam at the concentrator plant. Using seawater in the production of copper is also a promising option to reduce the WF_blue by up to 62%.     

Local and Regional vs. Global Contingency Testing

Contingency analysis of r × c-tables is systematized as follows: Global contingency testing based on the total chisquare under H₀ of independent row and column variables is least favorable to exhaustive interpretation. Local contingency testing based on chi-square components of the individual cells of an r × c-table and realized in Configural frequency analysis (KRAUTH and LIENERT, 1973) is more favourable to substantive interpretation. Compromising between global and local contingency testing leads to so-called generalized local and regional contingency testing. Every contingency testing (local, regional and naturally global) is including all N individuals of a sample supposed to have been drawn randomly from a defined population. Extension to 3-and t-dimensional contingency analysis is outlined, and biomedical applications are discussed.     

Three-dimensional chromatin ensemble reconstruction via stochastic embedding

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ImShot: An Open-Source Software for Probabilistic Identification of Proteins In Situ and Visualization of Proteomics Data

Imaging mass spectrometry (IMS) has developed into a powerful tool allowing label-free detection of numerous biomolecules in situ. In contrast to shotgun proteomics, proteins/peptides can be detected directly from biological tissues and correlated to its morphology leading to a gain of crucial clinical information. However, direct identification of the detected molecules is currently challenging for MALDI–IMS, thereby compelling researchers to use complementary techniques and resource intensive experimental setups. Despite these strategies, sufficient information could not be extracted because of lack of an optimum data combination strategy/software. Here, we introduce a new open-source software ImShot that aims at identifying peptides obtained in MALDI–IMS. This is achieved by combining information from IMS and shotgun proteomics (LC–MS) measurements of serial sections of the same tissue. The software takes advantage of a two-group comparison to determine the search space of IMS masses after deisotoping the corresponding spectra. Ambiguity in annotations of IMS peptides is eliminated by introduction of a novel scoring system that identifies the most likely parent protein of a detected peptide in the corresponding IMS dataset. Thanks to its modular structure, the software can also handle LC–MS data separately and display interactive enrichment plots and enriched Gene Ontology terms or cellular pathways. The software has been built as a desktop application with a conveniently designed graphic user interface to provide users with a seamless experience in data analysis. ImShot can run on all the three major desktop operating systems and is freely available under Massachusetts Institute of Technology license.