Spring Flood Forecasting Based on the WRF-TSRM Mode

The snowmelt process is becoming more complex in the context of global warming, and the current existing studies are not effective in using the short-term prediction model to drive the distributed hydrological model to predict snowmelt floods. In this study, we selected the Juntanghu Watershed in Hutubi County of China on the north slope of the Tianshan Mountains as the study area with which to verify the snowmelt flood prediction accuracy of the coupling model. The weather research and forecasting (WRF) model was used to drive a double-layer distributed snowmelt runoff model called the Tianshan Snowmelt Runoff Model (TSRM), which is based on multi-year field snowmelt observations. Moreover, the data from NASA’s moderate resolution imaging spectroradiometer (MODIS) was employed to validate the snow water equivalent during the snow-melting period. Results show that, based on the analysis of the flow lines in 2009 and 2010, the WRF-driven TSRM has an overall 80% of qualification ratios (QRs), with determination coefficients of 0.85 and 0.82 for the two years, respectively, which demonstrates the high accuracy of the model. However, due to the influence of the ablation of frozen soils, the forecasted flood peak is overestimated. This problem can be solved by an improvement to the modeled frozen soil layers. The conclusion reached in this study suggests that the WRF-driven TSRM can be used to forecast short-term snowmelt floods on the north slope of the Tianshan Mountains, which can effectively improve the local capacity for the forecasting and early warning of snowmelt floods

Regulation of Δ6Fads2 Gene Involved in LC-PUFA Biosynthesis Subjected to Fatty Acid in Large Yellow Croaker (<i>Larimichthys crocea</i>) and Rainbow Trout (<i>Oncorhynchus mykiss</i>)

Δ6 fatty acyl desaturase (Δ6Fads2) is regarded as the first rate-limiting desaturase that catalyzes the biosynthesis of long-chain polyunsaturated fatty acids (LC-PUFA) from 18-carbon fatty acid in vertebrates, but the underlying regulatory mechanism of fads2 has not been comprehensively understood. This study aimed to investigate the regulation role of fads2 subjected to fatty acid in large yellow croaker and rainbow trout. In vivo, large yellow croaker and rainbow trout were fed a fish oil (FO) diet, a soybean oil (SO) diet or a linseed oil (LO) diet for 10 weeks. The results show that LO and SO can significantly increase fads2 expression (p fads2. The results show that CCAAT/enhancer-binding protein α (C/EBPα) can up-regulate fads2 expression. GATA binding protein 3 (GATA3) can up-regulate fads2 expression in rainbow trout but showed opposite effect in large yellow croaker. Furthermore, C/EBPα protein levels were significantly increased by LO and SO (p gata3 expression was increased in rainbow trout by LO but decreased in large yellow croaker by LO and SO. In conclusion, we revealed that FO replaced by LO and SO increased fads2 expression through a C/EBPα and GATA3 dependent mechanism in large yellow croaker and rainbow trout. This study might provide critical insights into the regulatory mechanisms of fads2 expression and LC-PUFA biosynthesis

The Evolution in Catalytic Activity Driven by Periodic Transformation in the Inner Sites of Gold Clusters

It is extremely difficult to distinguish the contributions of different sites on the surface and in the inner sites of a catalyst to the overall catalytic performance, as the observed catalytic results reflect an ensemble average from almost all the active sites. How do the inner sites of a catalyst that seem to be not directly involved in a catalytic process exactly contribute to the catalytic performance? Toward this goal, herein the studies not only provide fundamental insights into how the alteration of Au8n+4(SR)(4n+8) clusters by only the inner structure can dramatically change the intrinsic catalytic properties, where Au8n+4(SR)(4n+8) (n = 3, 4, 5) clusters have the same surface motifs but share a periodic kernel structure, but also further demonstrate that the evolution in catalytic activity can potentially be determined by periodic transformation in the inner kernels

WebGIVI: a web-based gene enrichment analysis and visualization tool

Publisher's PDFBACKGROUND: A major challenge of high throughput transcriptome studies is presenting the data to researchers in an interpretable format. In many cases, the outputs of such studies are gene lists which are then examined for enriched biological concepts. One approach to help the researcher interpret large gene datasets is to associate genes and informative terms (iTerm) that are obtained from the biomedical literature using the eGIFT text-mining system. However, examining large lists of iTerm and gene pairs is a daunting task. RESULTS: We have developed WebGIVI, an interactive web-based visualization tool (http://raven.anr.udel.edu/webgivi/) to explore gene:iTerm pairs. WebGIVI was built via Cytoscape and Data Driven Document JavaScript libraries and can be used to relate genes to iTerms and then visualize gene and iTerm pairs. WebGIVI can accept a gene list that is used to retrieve the gene symbols and corresponding iTerm list. This list can be submitted to visualize the gene iTerm pairs using two distinct methods: a Concept Map or a Cytoscape Network Map. In addition, WebGIVI also supports uploading and visualization of any two-column tab separated data. CONCLUSIONS: WebGIVI provides an interactive and integrated network graph of gene and iTerms that allows filtering, sorting, and grouping, which can aid biologists in developing hypothesis based on the input gene lists. In addition, WebGIVI can visualize hundreds of nodes and generate a high-resolution image that is important for most of research publications. The source code can be freely downloaded at https://github.com/sunliang3361/WebGIVI. The WebGIVI tutorial is available at http://raven.anr.udel.edu/webgivi/tutorial.php.University of Delaware. Department of Animal and Food Sciences.University of Delaware. Department of Computer and Information Sciences.University of Delaware. Center for Bioinformatics & Computational Biology

Additional file 2: of WebGIVI: a web-based gene enrichment analysis and visualization tool

NCBI Entrez IDs for Comparison of WebGIVI, DAVID and AmiGO2. This file contains NCBI gene Entrez ID list which is identifed by WebGIVI, DAVID and AmiGO2 to be associated with the concept of cell cycle regulation. (TXT 1 kb

Additional file 1: of WebGIVI: a web-based gene enrichment analysis and visualization tool

NCBI Gene Entrez ID List for the Case Scenario. This file contains NCBI gene Entrez ID list. The first column is Entrez ID, and the second column is the gene symbol. (XLSX 9 kb