Using multi-tissue transcriptome-wide association study to identify candidate susceptibility genes for respiratory infectious diseases

Objective: We explore the candidate susceptibility genes for influenza A virus (IAV), measles, rubella, and mumps and their underlying biological mechanisms.Methods: We downloaded the genome-wide association study summary data of four virus-specific immunoglobulin G (IgG) level data sets (anti-IAV IgG, anti-measles IgG, anti-rubella IgG, and anti-mumps virus IgG levels) and integrated them with reference models of three potential tissues from the Genotype-Tissue Expression (GTEx) project, namely, whole blood, lung, and transformed fibroblast cells, to identify genes whose expression is predicted to be associated with IAV, measles, mumps, and rubella.Results: We identified 19 significant genes (ULK4, AC010132.11, SURF1, NIPAL2, TRAP1, TAF1C, AC000078.5, RP4-639F20.1, RMDN2, ATP1B3, SRSF12, RP11-477D19.2, TFB1M, XXyac-YX65C7_A.2, TAF1C, PCGF2, and BNIP1) associated with IAV at a Bonferroni-corrected threshold of p < 0.05; 14 significant genes (SOAT1, COLGALT2, AC021860.1, HCG11, METTL21B, MRPL10, GSTM4, PAQR6, RP11-617D20.1, SNX8, METTL21B, ANKRD27, CBWD2, and TSFM) associated with measles at a Bonferroni-corrected threshold of p < 0.05; 15 significant genes (MTOR, LAMC1, TRIM38, U91328.21, POLR2J, SCRN2, Smpd4, UBN1, CNTROB, SCRN2, HOXB-AS1, SLC14A1, AC007566.10, AC093668.2, and CPD) associated with mumps at a Bonferroni-corrected threshold of p < 0.05; and 13 significant genes (JAGN1, RRP12, RP11-452K12.7, CASP7, AP3S2, IL17RC, FAM86HP, AMACR, RRP12, PPP2R1B, C11orf1, DLAT, and TMEM117) associated with rubella at a Bonferroni-corrected threshold of p < 0.05.Conclusions: We have identified several candidate genes for IAV, measles, mumps, and rubella in multiple tissues. Our research may further our understanding of the pathogenesis of infectious respiratory diseases

Arsenic and Cadmium Accumulation in Soil as Affected by Continuous Organic Fertilizer Application: Implications for Clean Production

As and Cd in soil can be assimilated and accumulated by vegetables and can be subsequently ingested by humans. Contradictory effects of organic fertilizer application on As and Cd accumulation in soil have been reported in previous studies. An eight-year greenhouse study was conducted on a sandy loam soil in Beijing, China to investigate the effects of organic fertilizer application rate on soil properties, and As and Cd accumulation in soil. The contamination risk of pak choi grown after eight years’ application of organic fertilizer was also evaluated. Soil organic carbon increased 3.0–3.8 times with low, medium and high rates of fertilizer application in 2018 compared to the initial soil. Organic fertilizer application significantly increased soil nutrients and microbial biomass while it mildly affected soil pH. The bioavailability of As/Cd has decreased after eight years’ application of organic fertilizer. Pak choi crop harvested from all three treatments in 2018 did not pose a threat to human health, even for life-time consumption. Soil total As content significantly decreased with organic fertilizer application, mainly due to the lower As content in the applied fertilizer than that in soil. Continuous application of clean organic fertilizer can be adopted to reduce the contamination risk of highly contaminated soil in the soil–plant system

Genomic analysis of oesophageal squamous-cell carcinoma identifies alcohol drinking-related mutation signature and genomic alterations

Approximately half of the world's 500,000 new oesophageal squamous-cell carcinoma (ESCC) cases each year occur in China. Here, we show whole-genome sequencing of DNA and RNA in 94 Chinese individuals with ESCC. We identify six mutational signatures (E1–E6), and Signature E4 is unique in ESCC linked to alcohol intake and genetic variants in alcohol-metabolizing enzymes. We discover significantly recurrent mutations in 20 protein-coding genes, 4 long non-coding RNAs and 10 untranslational regions. Functional analyses show six genes that have recurrent copy-number variants in three squamous-cell carcinomas (oesophageal, head and neck and lung) significantly promote cancer cell proliferation, migration and invasion. The most frequently affected genes by structural variation are LRP1B and TTC28. The aberrant cell cycle and PI3K-AKT pathways seem critical in ESCC. These results establish a comprehensive genomic landscape of ESCC and provide potential targets for precision treatment and prevention of the cancer

Antibiotics and antibiotic resistance genes in global lakes:A review and meta-analysis

Lakes are an important source of freshwater, containing nearly 90% of the liquid surface fresh water worldwide. Long retention times in lakes mean pollutants from discharges slowly circulate around the lakes and may lead to high ecological risk for ecosystem and human health. In recent decades, antibiotics and antibiotic resistance genes (ARGs) have been regarded as emerging pollutants. The occurrence and distribution of antibiotics and ARGs in global freshwater lakes are summarized to show the pollution level of antibiotics and ARGs and to identify some of the potential risks to ecosystem and human health. Fifty-seven antibiotics were reported at least once in the studied lakes. Our meta-analysis shows that sulfamethoxazole, sulfamerazine, sulfameter, tetracycline, oxytetracycline, erythromycin, and roxithromycin were found at high concentrations in both lake water and lake sediment. There is no significant difference in the concentration of sulfonamides in lake water from China and that from other countries worldwide; however, there was a significant difference in quinolones. Erythromycin had the lowest predicted hazardous concentration for 5% of the species (HC5) and the highest ecological risk in lakes. There was no significant difference in the concentration of sulfonamide resistance genes (sul1 and sul2) in lake water and river water. There is surprisingly limited research on the role of aquatic biota in propagation of ARGs in freshwater lakes. As an environment that is susceptible to cumulative build-up of pollutants, lakes provide an important environment to study the fate of antibiotics and transport of ARGs with a broad range of niches including bacterial community, aquatic plants and animals

A multi-algorithm block fusion method based on set-valued mapping for dual-modal infrared images

It is always a goal to make use of difference-features between infrared intensity and polarization (degree of polarization) images to drive selection of targeted algorithms rather than using fixed algorithm, and improve the fusion efficiency under the premise of ensuring the high-quality fusion performance in the field of infrared images fusion. In this paper, with the source of infrared intensity and polarization images, a multi-algorithm block fusion method is proposed based on set-valued mapping relationship between the difference-features and the optimal fusion algorithms. Firstly, by comparing the basic imaging process, the respective characteristics of dual-modal infrared images are identified, and then the salient difference-features are selected according to their image characteristics and complementary information. Further, the optimal fusion algorithm for each difference-feature is developed by using the proposed fusion validity formula. Based on the above, we establish the probability distribution between the difference-features set and the optimal fusion algorithms set, and further determine the set-valued mapping relationship between them. Second, the source images are divided into blocks and the main difference-feature of each image block is extracted, then the optimal fusion algorithm is selected according to the established mapping relationship for block fusion. Finally, the fused image blocks are stitched into a complete fusion image by the corresponding splicing processing. Through experimental comparison, the proposed method not only improves the fusion quality, but also has satisfactory work efficiency. In addition, the proposed method can fully exploit the ability of difference-features to drive selecting optimal fusion algorithm

An Empirical Model for Correction of Topographic Effect in Microwave Radiation of Mountainous Area

The topographic effect is one of the essential factors affecting microwave radiation in mountainous regions. This effect's correction can improve the inversion accuracy of key surface parameters. Here, a new terrain correction model in microwave pixel scale is proposed by regression. Using the rugosity (RU) measure the relief of land surface, and analyze its correlation with the brightness temperature difference between the undulating surface and flat surface ($\Delta T{B}_{{\varphi }_{Ri}}$). The topographic effects are simulated by the mountain microwave radiation model. Through the regression analysis of the topographic effects with RU in different regions, we find that: first, RU has a linear relationship with the average $\Delta T{B}_{{\varphi }_{Ri}}$for different azimuths of the pixel ($\overline {\Delta TB}$), with the value of R2 above 0.9 for both polarization; then, the effects of azimuths and ground characteristics on brightness temperature can also be corrected by establishing their regression relationship with brightness temperature. Combined with these analyses, an empirical model is developed to measure the topographic effect according to RU. The verification results show that the $\Delta T{B}_{\text{model}}$ calculated by the empirical model is similar to the $\Delta T{B}_{\text{simulated}}$ of microwave radiation model (r >0.9), which indicates that the empirical model is suitable for mountainous areas with different terrains. Results also provide a theoretical basis for improving the accuracy of passive microwave remote sensing of mountainous areas