ESNOQ, Proteomic Quantification of Endogenous S-Nitrosation

S-nitrosation is a post-translational protein modification and is one of the most important mechanisms of NO signaling. Endogenous S-nitrosothiol (SNO) quantification is a challenge for detailed functional studies. Here we developed an ESNOQ (Endogenous SNO Quantification) method which combines the stable isotope labeling by amino acids in cell culture (SILAC) technique with the detergent-free biotin-switch assay and LC-MS/MS. After confirming the accuracy of quantification in this method, we obtained an endogenous S-nitrosation proteome for LPS/IFN-γ induced RAW264.7 cells. 27 S-nitrosated protein targets were confirmed and using our method we were able to obtain quantitative information on the level of S-nitrosation on each modified Cys. With this quantitative information, over 15 more S-nitrosated targets were identified than in previous studies. Based on the quantification results, we found that the S-nitrosation levels of different cysteines varied within one protein, providing direct evidence for differences in the sensitivity of cysteine residues to reactive nitrosative stress and that S-nitrosation is a site-specific modification. Gene ontology clustering shows that S-nitrosation targets in the LPS/IFN-γ induced RAW264.7 cell model were functionally enriched in protein translation and glycolysis, suggesting that S-nitrosation may function by regulating multiple pathways. The ESNOQ method described here thus provides a solution for quantification of multiple endogenous S-nitrosation events, and makes it possible to elucidate the network of relationships between endogenous S-nitrosation targets involved in different cellular processes

Nitric Oxide Destabilizes Pias3 and Regulates Sumoylation

Small ubiquitin-related protein modifiers (SUMO) modification is an important mechanism for posttranslational regulation of protein function. However, it is largely unknown how the sumoylation pathway is regulated. Here, we report that nitric oxide (NO) causes global hyposumoylation in mammalian cells. Both SUMO E2 conjugating enzyme Ubc9 and E3 ligase protein inhibitor of activated STAT3 (Pias3) were targets for S-nitrosation. S-nitrosation did not interfere with the SUMO conjugating activity of Ubc9, but promoted Pias3 degradation by facilitating its interaction with tripartite motif-containing 32 (Trim32), a ubiquitin E3 ligase. On the one hand, NO promoted Trim32-mediated Pias3 ubiquitination. On the other hand, NO enhanced the stimulatory effect of Pias3 on Trim32 autoubiquitination. The residue Cys459 of Pias3 was identified as a target site for S-nitrosation. Mutation of Cys459 abolished the stimulatory effect of NO on the Pias3-Trim32 interaction, indicating a requirement of S-nitrosation at Cys459 for positive regulation of the Pias3-Trim32 interplay. This study reveals a novel crosstalk between S-nitrosation, ubiquitination, and sumoylation, which may be crucial for NO-related physiological and pathological processes

Long-Term Programming of Antigen-Specific Immunity from Gene Expression Signatures in the PBMC of Rhesus Macaques Immunized with an SIV DNA Vaccine

While HIV-1-specific cellular immunity is thought to be critical for the suppression of viral replication, the correlates of protection have not yet been determined. Rhesus macaques (RM) are an important animal model for the study and development of vaccines against HIV/AIDS. Our laboratory has helped to develop and study DNA-based vaccines in which recent technological advances, including genetic optimization and in vivo electroporation (EP), have helped to dramatically boost their immunogenicity. In this study, RMs were immunized with a DNA vaccine including individual plasmids encoding SIV gag, env, and pol alone, or in combination with a molecular adjuvant, plasmid DNA expressing the chemokine ligand 5 (RANTES), followed by EP. Along with standard immunological assays, flow-based activation analysis without ex vivo restimulation and high-throughput gene expression analysis was performed. Strong cellular immunity was induced by vaccination which was supported by all assays including PBMC microarray analysis that identified the up-regulation of 563 gene sequences including those involved in interferon signaling. Furthermore, 699 gene sequences were differentially regulated in these groups at peak viremia following SIVmac251 challenge. We observed that the RANTES-adjuvanted animals were significantly better at suppressing viral replication during chronic infection and exhibited a distinct pattern of gene expression which included immune cell-trafficking and cell cycle genes. Furthermore, a greater percentage of vaccine-induced central memory CD8+ T-cells capable of an activated phenotype were detected in these animals as measured by activation analysis. Thus, co-immunization with the RANTES molecular adjuvant followed by EP led to the generation of cellular immunity that was transcriptionally distinct and had a greater protective efficacy than its DNA alone counterpart. Furthermore, activation analysis and high-throughput gene expression data may provide better insight into mechanisms of viral control than may be observed using standard immunological assays

Effect of single-pass friction stir processing parameters on the microstructure and properties of 2 mm thick AA2524

Friction stir processing (FSP) is an important method for obtaining fine grains. To determine the effects of FSP and processing parameters on the microstructure and mechanical properties of rolled sheets, we performed single-pass FSP of a 2 mm thick 2524 aluminium alloy (AA2524) rolled sheet by comparing the combination of different processing parameters. The results show that lamellar grains (rolled state) are replaced by fine dynamic recrystallisation in the stir zone (SZ), and more Al _2 CuMg phases are precipitated simultaneously. As the rotation speed increases, the grain size and width of the pin stir zone (PSZ) increase, the microhardness first decreases and then increases; with the traverse speed increase, the grain size first decreases and then increases, and the width of the PSZ and microhardness decrease. The SZ has the smallest grain size, highest high-angle grain boundaries (HAGBs, with misorientation angles ( θ ) >15°) ratio, and largest ultimate tensile strength (UTS), when the rotation and traverse speed were 1000 r·min ^−1 and 125 mm·min ^−1 , are 1.59 ± 0.82 μ m, 0.91 and 451.23 ± 0.52 MPa, respectively, and the elongation to fracture is 13%. The UTS and elongation were only 95.12% and 98.48% of those of the base metals (BM), respectively, because of the significant decrease in the dislocation density. Fracture analysis revealed ductile fracture of the joint due to the large number of dimples and fine second-phase particles

UAV Remote Sensing Prediction Method of Winter Wheat Yield Based on the Fused Features of Crop and Soil

The early and accurate acquisition of crop yields is of great significance for maintaining food market stability and ensuring global food security. Unmanned aerial vehicle (UAV) remote sensing offers the possibility of predicting crop yields with its advantages of flexibility and high resolution. However, most of the existing remote sensing yield estimation studies focused solely on crops but did not fully consider the influence of soil on yield formation. As an integrated system, the status of crop and soil together determines the final yield. Compared to crop-only yield prediction, the approach that additionally considers soil background information will effectively improve the accuracy and reduce bias in the results. In this study, a novel method for segmenting crop and soil spectral images based on different vegetation coverage is first proposed, in which pixels of crop and soil can be accurately identified by determining the discriminant value Q. On the basis of extracting crop and soil waveband’s information by individual pixel, an innovative approach, projected non-negative matrix factorization based on good point set and matrix cross fusion (PNMF-MCF), was developed to effectively extract and fuse the yield-related features of crop and soil. The experimental results on winter wheat show that the proposed segmentation method can accurately distinguish crop and soil pixels under complex soil background of four different growth periods. Compared with the single reflectance of crop or soil and the simple combination of crop and soil reflectance, the fused yield features spectral matrix FP obtained with PNMF−MCF achieved the best performance in yield prediction at the flowering, flag leaf and pustulation stages, with R2 higher than 0.7 in these three stages. Especially at the flowering stage, the yield prediction model based on PNMF-MCF had the highest R2 with 0.8516 and the lowest RMSE with 0.0744 kg/m2. Correlation analysis with key biochemical parameters (nitrogen and carbon, pigments and biomass) of yield formation showed that the flowering stage was the most vigorous season for photosynthesis and the most critical stage for yield prediction. This study provides a new perspective and complete framework for high-precision crop yield forecasting using UAV remote sensing technology

UAV Remote Sensing Prediction Method of Winter Wheat Yield Based on the Fused Features of Crop and Soil

The early and accurate acquisition of crop yields is of great significance for maintaining food market stability and ensuring global food security. Unmanned aerial vehicle (UAV) remote sensing offers the possibility of predicting crop yields with its advantages of flexibility and high resolution. However, most of the existing remote sensing yield estimation studies focused solely on crops but did not fully consider the influence of soil on yield formation. As an integrated system, the status of crop and soil together determines the final yield. Compared to crop-only yield prediction, the approach that additionally considers soil background information will effectively improve the accuracy and reduce bias in the results. In this study, a novel method for segmenting crop and soil spectral images based on different vegetation coverage is first proposed, in which pixels of crop and soil can be accurately identified by determining the discriminant value Q. On the basis of extracting crop and soil waveband’s information by individual pixel, an innovative approach, projected non-negative matrix factorization based on good point set and matrix cross fusion (PNMF-MCF), was developed to effectively extract and fuse the yield-related features of crop and soil. The experimental results on winter wheat show that the proposed segmentation method can accurately distinguish crop and soil pixels under complex soil background of four different growth periods. Compared with the single reflectance of crop or soil and the simple combination of crop and soil reflectance, the fused yield features spectral matrix FP obtained with PNMF−MCF achieved the best performance in yield prediction at the flowering, flag leaf and pustulation stages, with R2 higher than 0.7 in these three stages. Especially at the flowering stage, the yield prediction model based on PNMF-MCF had the highest R2 with 0.8516 and the lowest RMSE with 0.0744 kg/m2. Correlation analysis with key biochemical parameters (nitrogen and carbon, pigments and biomass) of yield formation showed that the flowering stage was the most vigorous season for photosynthesis and the most critical stage for yield prediction. This study provides a new perspective and complete framework for high-precision crop yield forecasting using UAV remote sensing technology

Rapid Determination of Tetracyclines in Drinking and Environmental Waters Using Fully Automatic Solid-Phase Extraction with Ultra-Performance Liquid Chromatography–Tandem Mass Spectrometry

The abuse and irrational use of tetracyclines (TCs) in human medicine and animal husbandry has become a serious concern, affecting the ecological environment and human health. The aim of this study was to develop a sensitive and selective method using fully automatic solid-phase extraction coupled with ultra-performance liquid chromatography–tandem mass spectrometry for the determination of twelve TCs in water. Four isotope-labeled internal standards for TCs were used to correct matrix effects. Several parameters affecting extraction efficiency were systematically optimized, and the optimum experimental conditions found were 1.0 L water sample with 0.5 g/L Na2EDTA (pH 3.0) extracted and enriched by CNW HLB cartridge and eluted by 4 mL of acetone:methanol (v/v, 1:1). The enrichment factors were up to 798−1059 but only requiring about 60 min per six samples. Under the optimized conditions, the linearity of the method ranged from 0.2 to 100 μg/L for 12 TCs, the detection limits were as low as 0.01−0.15 ng/L, and the recoveries were in the range of 70%–118%, with relative standard deviations less than 15%. The developed method can be successfully utilized for the determination of 12 TCs in pure water, tap water, river water, and mariculture seawater. In summary, three and six TCs were detected in river water and mariculture seawater, respectively, with total concentrations of 0.074–0.520 ng/L (mean 0.248 ng/L) and 0.792–58.369 ng/L (12.629 ng/L), respectively. Tetracycline (TC) and oxytetracycline (OTC) were the dominant TCs in river water, while doxytetracycline (DXC) and OTC were dominant in mariculture seawater

Years of life lost and life expectancy attributable to ambient temperature: A time series study in 93 Chinese cities

Abstract Although increasing evidence has reported that unfavorable temperature may lead to increased premature mortality, a systematic assessment is lacking on the impact of ambient temperature on years of life lost (YLL) and life expectancy in China. Daily data on mortality, YLL, meteorological factors and air pollution were obtained from 93 Chinese cities during 2013–2016. A two-stage analytic approach was applied for statistical analysis. At the first stage, a distributed lag non-linear model with a Gaussian link was used to estimate the city-specific association between ambient temperature and YLLs. At the second stage, a meta-analysis was used to obtain the effect estimates at regional and national levels. We further estimated the corresponding YLLs and average life expectancy loss per deceased person attributable to the non-optimum temperature exposures based on the established associations. We observed ‘U’ or ‘J’ shaped associations between daily temperature and YLL. The heat effect appeared on the current day and lasted for only a few days, while the cold effect appeared a few days later and lasted for longer. In general, 6.90% (95% confidence interval (CI): 4.62%, 9.18%) of YLLs could be attributed to non-optimum temperatures at the national level, with differences across different regions, ranging from 5.36% (95% CI: −3.36%, 6.89%) in east region to 9.09% (95% CI: −5.55%, 23.73%) in northwest region. For each deceased person, we estimated that non-optimum temperature could cause a national-averaged 1.02 years (95% CI: 0.68, 1.36) of life loss, with a significantly higher effect due to cold exposure (0.89, 95% CI: 0.59, 1.19) than that of hot exposure (0.13, 95% CI: 0.09, 0.16). This national study provides evidence that both cold and hot weather might result in significant YLL and lower life expectancy. Regional adaptive policies and interventions should be considered to reduce the mortality burden associated with the non-optimum temperature exposures

Systematic Review and Meta-Analysis of Factors Influencing Self-Medication in Children

To evaluate the prevalence, influencing factors, and behavior rules of self-medication in children. Articles on self-medication in children from various electronic databases (PubMed, Cochrane Library, Web of Science, the WHO website ( https://www.who.int/ ), ABI, CNKI, and Wanfang), were searched to August 2022. The single-group meta-analyses of the prevalence, influencing factors, and behavior rules of self-medication in children were performed using Revman 5.3 and Stata 16.0. The overall pooled prevalence of self-medication in children was 57% (95% CI: 0.39-0.75, I²  = 100%, P  < .00001 Z  = 6.22). The pooled prevalence for main influencing factors, in terms of caregivers, was: 73% (95% CI: 0.72-0.75, I²  = 100%, P  < .00001, Z  = 111.18) for those in rural areas; 55% (95% CI: 0.51-0.59, P  = .04, Z  = 26.92, I²  = 68%, P  < .00001) for females; 75% (95% CI: 0.74-0.76, I²  = 68%, P  < .00001, Z  = 106.66) for those whose income was less than 716 dollars; 77% (95% CI: 0.75-0.79, I²  = 99%, P  < .000001, Z  = 92.59) for the middle-aged and elderly; and 72% (95% CI: 0.58-87, I²  = 99%, P  < .00001, Z  = 9.82) for those with a degree below bachelor. In the process of self-medication for children, 19% (95% CI: 0.06-0.32, I²  = 99%, P  < .00001, Z  = 2.82) of the caregivers did not read the instructions, 28% (95% CI: −0.03-0.60, I²  = 100%, P  < .000001, Z  = 1.77) neglected adverse effects, 49% (95% CI: 0.11-0.87, I²  = 100%, P  = .01, Z  = 2.51) spontaneously increased or decreased the dosages, 49% (95% CI: 0.48-0.55, I²  = 65%, P  < .00001, Z  = 16.51) had an awareness of over-the-counter (OTC) drugs, and 41% (95% CI: 0.18-0.64, I²  = 99%, P  < .00001, Z  = 3.49) misrecognized the antibiotics. Self-medication for children was common, although the overall prevalence was not very high. The prevalence of self-medication in children was relatively higher among those caregivers who were female, rural, had low-income, were elder, or had a degree below bachelor. Common behaviors during self-medication in children included spontaneous dose increase or decrease, a lack of awareness of OTC drugs, and misconception of antibiotics. Government departments should formulate corresponding policies to provide quality health education resources for the caregivers of children