A Ubiquitous but Overlooked Side Reaction in Dimethyl Labeling of Peptides

10.1021/acs.analchem.8b03570Analytical Chemistry902213533-1354

Optimized Design of Shed Parameters for Polluted Hollow Porcelain Insulators at High Altitude

The pollution flashover problem of hollow insulators, one of the primary faults in substations, can be improved by optimizing the shed parameters. Combining the artificial pollution test and electric field simulation, this paper studies the optimal shed parameters for 220 kV hollow porcelain insulators at high altitudes. The AC artificial pollution flashover test was conducted by solid-layer and up-and-down methods in the artificial climate chamber to analyze the pollution flashover characteristics of the 220 kV hollow porcelain insulator at various altitudes and pollution degrees. After the validity of the artificial pollution flashover test and the direction of optimization of the shed parameters were clarified, electric field simulation was implemented on a two-dimensional axisymmetric model to analyze the effects of shed spacing and large shed overhang on the electric field distribution of the insulator. Based on the pollution flashover characteristics and the simulation analysis results, we find that appropriately increasing the shed spacing and reducing the large shed overhang can improve the surface electric field distribution of the hollow porcelain insulator, thereby improving its pollution flashover characteristics

seq-ImmuCC: Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data

The RNA sequencing approach has been broadly used to provide gene-, pathway-, and network-centric analyses for various cell and tissue samples. However, thus far, rich cellular information carried in tissue samples has not been thoroughly characterized from RNA-Seq data. Therefore, it would expand our horizons to better understand the biological processes of the body by incorporating a cell-centric view of tissue transcriptome. Here, a computational model named seq-ImmuCC was developed to infer the relative proportions of 10 major immune cells in mouse tissues from RNA-Seq data. The performance of seq-ImmuCC was evaluated among multiple computational algorithms, transcriptional platforms, and simulated and experimental datasets. The test results showed its stable performance and superb consistency with experimental observations under different conditions. With seq-ImmuCC, we generated the comprehensive landscape of immune cell compositions in 27 normal mouse tissues and extracted the distinct signatures of immune cell proportion among various tissue types. Furthermore, we quantitatively characterized and compared 18 different types of mouse tumor tissues of distinct cell origins with their immune cell compositions, which provided a comprehensive and informative measurement for the immune microenvironment inside tumor tissues. The online server of seq-ImmuCC are freely available at http://wap-lab.org:3200/immune/

Water Dynamics in Egg White Peptide, Asp-His-Thr-Lys-Glu, Powder Monitored by Dynamic Vapor Sorption and LF-NMR

Water absorbed into the bulk amorphous structure of peptides can have profound effects on their properties. Here, we elucidated water dynamics in Asp-His-Thr-Lys-Glu (DHTKE), an antioxidant peptide derived from egg white ovalbumin, using water dynamic vapor sorption (DVS) and low-field nuclear magnetic resonance (LF-NMR). The DVS results indicated that parallel exponential kinetics model fitted well to the data of sorption kinetics behavior of DHTKE. Four different proton fractions with different mobilities were identified based on the degree of interaction between peptide and water. The water could significantly change the proton distribution and structure of the sample. The different phases of moisture absorption were reflected in the <i>T</i>₂ parameters. In addition, the combined water content was dominant in the hygroscopicity of DHTKE. This study provides an effective real-time monitoring method for water mobility and distribution in synthetic peptides, and this method may have applications in promoting peptide quality assurance

Integrative physiological and transcriptome analyses provide insights into the Cadmium (Cd) tolerance of a Cd accumulator: Erigeron canadensis

Abstract Cadmium (Cd) is a highly toxic pollutant in soil and water that severely hampers the growth and reproduction of plants. Phytoremediation has been presented as a cost-effective and eco-friendly method for addressing heavy metal pollution. However, phytoremediation is restricted by the limited number of accumulators and the unknown mechanisms underlying heavy metal tolerance. In this study, we demonstrated that Erigeron canadensis (Asteraceae), with its strong adaptability, is tolerant to intense Cd stress (2 mmol/L CdCl2 solution). Moreover, E. canadensis exhibited a strong ability to accumulate Cd2+ when treated with CdCl2 solution. The activity of some antioxidant enzymes, as well as the malondialdehyde (MDA) level, was significantly increased when E. canadensis was treated with different CdCl2 solutions (0.5, 1, 2 mmol/L CdCl2). We found high levels of superoxide dismutase (SOD) and ascorbate peroxidase (APX) activities under 1 mmol/L CdCl2 treatment. Comparative transcriptomic analysis identified 5,284 differentially expressed genes (DEGs) in the roots and 3,815 DEGs in the shoots after E. canadensis plants were exposed to 0.5 mM Cd. Functional annotation of key DEGs indicated that signal transduction, hormone response, and reactive oxygen species (ROS) metabolism responded significantly to Cd. In particular, the DEGs involved in auxin (IAA) and ethylene (ETH) signal transduction were overrepresented in shoots, indicating that these genes are mainly involved in regulating plant growth and thus likely responsible for the Cd tolerance. Overall, these results not only determined that E. canadensis can be used as a potential accumulator of Cd but also provided some clues regarding the mechanisms underlying heavy metal tolerance

data_sheet_1_seq-ImmuCC: Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data.docx

<p>The RNA sequencing approach has been broadly used to provide gene-, pathway-, and network-centric analyses for various cell and tissue samples. However, thus far, rich cellular information carried in tissue samples has not been thoroughly characterized from RNA-Seq data. Therefore, it would expand our horizons to better understand the biological processes of the body by incorporating a cell-centric view of tissue transcriptome. Here, a computational model named seq-ImmuCC was developed to infer the relative proportions of 10 major immune cells in mouse tissues from RNA-Seq data. The performance of seq-ImmuCC was evaluated among multiple computational algorithms, transcriptional platforms, and simulated and experimental datasets. The test results showed its stable performance and superb consistency with experimental observations under different conditions. With seq-ImmuCC, we generated the comprehensive landscape of immune cell compositions in 27 normal mouse tissues and extracted the distinct signatures of immune cell proportion among various tissue types. Furthermore, we quantitatively characterized and compared 18 different types of mouse tumor tissues of distinct cell origins with their immune cell compositions, which provided a comprehensive and informative measurement for the immune microenvironment inside tumor tissues. The online server of seq-ImmuCC are freely available at http://wap-lab.org:3200/immune/.</p

data_sheet_2_seq-ImmuCC: Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data.PDF

<p>The RNA sequencing approach has been broadly used to provide gene-, pathway-, and network-centric analyses for various cell and tissue samples. However, thus far, rich cellular information carried in tissue samples has not been thoroughly characterized from RNA-Seq data. Therefore, it would expand our horizons to better understand the biological processes of the body by incorporating a cell-centric view of tissue transcriptome. Here, a computational model named seq-ImmuCC was developed to infer the relative proportions of 10 major immune cells in mouse tissues from RNA-Seq data. The performance of seq-ImmuCC was evaluated among multiple computational algorithms, transcriptional platforms, and simulated and experimental datasets. The test results showed its stable performance and superb consistency with experimental observations under different conditions. With seq-ImmuCC, we generated the comprehensive landscape of immune cell compositions in 27 normal mouse tissues and extracted the distinct signatures of immune cell proportion among various tissue types. Furthermore, we quantitatively characterized and compared 18 different types of mouse tumor tissues of distinct cell origins with their immune cell compositions, which provided a comprehensive and informative measurement for the immune microenvironment inside tumor tissues. The online server of seq-ImmuCC are freely available at http://wap-lab.org:3200/immune/.</p