Electron tomography is becoming one of the most used methods for structural analysis at nanometric scale in biological and materials sciences. Combined with chemical mapping, it provides qualitative and semiquantitative information on the distribution of chemical elements on a given sample. Due to the current difficulties in obtaining three-dimensional (3D) maps by energy-filtered transmission electron microscopy (EFTEM), the use of 3D chemical mapping has not been widely adopted by the electron microscopy community. The lack of specialized software further complicates the issue, especially in the case of data with a low signal-to-noise ratio (SNR). Moreover, data interpretation is rendered difficult by the absence of efficient segmentation tools. Thus, specialized software for the computation of 3D maps by EFTEM needs to include optimized methods for image series alignment, algorithms to improve SNR, different background subtraction models, and methods to facilitate map segmentation. Here we present a software package (EFTEM-TomoJ, which can be downloaded from http://u759.curie.fr/fr/download/softwares/EFTEM-TomoJ), specifically dedicated to computation of EFTEM 3D chemical maps including noise filtering by image reconstitution based on multivariate statistical analysis. We also present an algorithm named BgART (for background removing algebraic reconstruction technique) allowing the discrimination between background and signal and improving the reconstructed volume in an iterative way.
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http://dx.doi.org/10.1017/S1431927613013317 | DOI Listing |
Elife
January 2025
Allen Discovery Center, Tufts University, Medford, United States.
Many applications in biomedicine and synthetic bioengineering rely on understanding, mapping, predicting, and controlling the complex behavior of chemical and genetic networks. The emerging field of diverse intelligence investigates the problem-solving capacities of unconventional agents. However, few quantitative tools exist for exploring the competencies of non-conventional systems.
View Article and Find Full Text PDFmBio
January 2025
Department of Microbiology and Molecular Genetics, University of California, Davis, California, USA.
Orthoflaviviruses are positive-sense single-stranded RNA viruses that hijack host proteins to promote their own replication. Zika virus (ZIKV) is infamous among orthoflaviviruses for its association with severe congenital birth defects, notably microcephaly. We previously mapped ZIKV-host protein interactions and identified the interaction between ZIKV non-structural protein 4A (NS4A) and host microcephaly protein ankyrin repeat and LEM domain-containing 2 (ANKLE2).
View Article and Find Full Text PDFMicrobial communities play a central role in transforming environments across Earth, driving both physical and chemical changes. By harnessing these capabilities, synthetic microbial communities, assembled from the bottom up, offer valuable insights into the mechanisms that govern community functions. These communities can also be tailored to produce desired outcomes, such as the synthesis of health-related metabolites or nitrogen fixation to improve plant productivity.
View Article and Find Full Text PDFProtein content is an important index in the assessment of dairy nutrition. As a crucial source of protein absorption in people's daily life, the quality of milk powder products not only has a deep impact on the development of the dairy industry, but also seriously damages the health of consumers. It is of great significance to find a faster and more accurate method for detecting milk protein content.
View Article and Find Full Text PDFChem Sci
December 2024
State Key Laboratory of Medical Proteomics, National Chromatographic R. & A. Center, CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 P. R. China
Small ubiquitin-like modifier (SUMO) plays a pivotal role in diverse cellular processes and is implicated in diseases such as cancer and neurodegenerative disorders. However, large-scale identification of endogenous SUMO-1 faces challenges due to limited enrichment methods and its lower abundance compared to SUMO-2/3. Here we propose a novel combinatorial peptide strategy, combined with anti-adhesive polymer development, to enrich endogenous SUMO-1 modified peptides, revealing a comprehensive SUMOylation landscape.
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