Evaluating hydrologic responses to soil characteristics using SWAT model in a paired-watersheds in the Upper Blue Nile Basin

Watershed responses are affected by the watershed characteristics and rainfall events. The characteristics of soil layers are among the fundamental characteristics of a watershed and they are input to hydrologic modeling similar to topography and land use/cover. Although the roles of soils have been perceived, there are limited studies that quantify the role of soil characteristics on watershed runoff responses due to the lack of field datasets. Using two adjacent watersheds (Ribb and Gumara) which have a significant different runoff response with a similar characterstics except geological settings (including soil characteristics), we studied the effects of soil characteristics on runoff and water balance. The Soil and Water Assessment Tool (SWAT) was used to simulate the surface runoff response at the outlet of the watershed and the optimal model parameters distribution was tested with a non-parametric test for similarity. Results indicated that SWAT model captured the observed flow very well with a Nash-Sutcliffe Efficiency (NSE) of greater than 0.74 and with a PBIAS of less than 10% for both calibration and validation period. The comparison of the optimal model parameter distributions of the SWAT model showed that the watershed characteristics could be uniquely defined and represented by a hydrologic model due to the differences in the soils. Using field observations and modeling experiments, this study demonstrates how sensitive watershed hydrology is to soils, emphasizing the importance of accurate soil information in hydrological modeling. We conclude that due emphasis should be given to soil information in hydrologic analysis

Gramene 2013: comparative plant genomics resources

Gramene (http://www.gramene.org) is a curated online resource for comparative functional genomics in crops and model plant species, currently hosting 27 fully and 10 partially sequenced reference genomes in its build number 38. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. Whole-genome alignments complemented by phylogenetic gene family trees help infer syntenic and orthologous relationships. Genetic variation data, sequences and genome mappings available for 10 species, including Arabidopsis, rice and maize, help infer putative variant effects on genes and transcripts. The pathways section also hosts 10 species-specific metabolic pathways databases developed in-house or by our collaborators using Pathway Tools software, which facilitates searches for pathway, reaction and metabolite annotations, and allows analyses of user-defined expression datasets. Recently, we released a Plant Reactome portal featuring 133 curated rice pathways. This portal will be expanded for Arabidopsis, maize and other plant species. We continue to provide genetic and QTL maps and marker datasets developed by crop researchers. The project provides a unique community platform to support scientific research in plant genomics including studies in evolution, genetics, plant breeding, molecular biology, biochemistry and systems biology

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

Funder: Bundesministerium für Bildung und ForschungFunder: Bundesministerium für Bildung und Forschung (BMBF)We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective

The association between strategic configurations and success for SMMEs supplying fuel in the South African commercial sector

MBA thesis - WBSThis study focuses on the South African commercial fuel industry, specifically the Small, Medium and Micro Enterprise (SMME) oil companies supplying diesel to commercial users. The supply and distribution of diesel is less regulated than that of petrol and price discounting is allowed. This has created a highly competitive environment for the commercial fuel industry. Within this industry there are two distinct sectors, the private and public sectors. Few SMME’s have had success in supplying fuel to the public sector despite the stated intention of organs of state to promote SMME businesses. Are some SMMEs finding success in the private and not the public sector? Is there a winning strategic style or configuration that promotes success in this industry? This study categorises SMME oil companies into one of four Miles and Snow (1978) strategic classifications, (1) Reactors, (2) Defenders, (3) Analysers and (4) Prospectors. Success in both the public and private sectors was measured and associations were then sought with strategic classification. In addition correlations were sought between public and private sector performance. The population of this study was the 26 SMME respondents to the 2010 tender for supply of fuel to the government transport parastatal, Transnet. Transnet accounted for 64.6% of public sector diesel usage in 2008 and the population was intended to be indicative of SMMEs trying to sell fuel in both the private and public sectors. Data was collected using a three part questionnaire in an interview environment. A total of 14 SMMEs participated in this study, all data collected was usable. No significant association was found between the SMMEs’ strategic classification or configuration, and the private sector performance. The rankings of public and private sector success were compared and a significant correlation was detected. None of the Miles and Snow strategic classifications work better in the commercial fuel industry. This may only be indicative of the industry as it is now as it has been undergoing much change. A more stable industry may yield different results. SMMEs that does well in the private sector tend to do well in selling fuel to the public sector. This implies an effective fuel supply tender process in Transne

Glucocorticoid-Induced Reversal of Interleukin-1β-Stimulated Inflammatory Gene Expression in Human Oviductal Cells

<div><p>Studies indicate that high-grade serous ovarian carcinoma (HGSOC), the most common epithelial ovarian carcinoma histotype, originates from the fallopian tube epithelium (FTE). Risk factors for this cancer include reproductive parameters associated with lifetime ovulatory events. Ovulation is an acute inflammatory process during which the FTE is exposed to follicular fluid containing both pro- and anti-inflammatory molecules, such as interleukin-1 (IL1), tumor necrosis factor (TNF), and cortisol. Repeated exposure to inflammatory cytokines may contribute to transforming events in the FTE, with glucocorticoids exerting a protective effect. The global response of FTE cells to inflammatory cytokines or glucocorticoids has not been investigated. To examine the response of FTE cells and the ability of glucocorticoids to oppose this response, an immortalized human FTE cell line, OE-E6/E7, was treated with IL1β, dexamethasone (DEX), IL1β and DEX, or vehicle and genome-wide gene expression profiling was performed. IL1β altered the expression of 47 genes of which 17 were reversed by DEX. DEX treatment alone altered the expression of 590 genes, whereas combined DEX and IL1β treatment altered the expression of 784 genes. Network and pathway enrichment analysis indicated that many genes altered by DEX are involved in cytokine, chemokine, and cell cycle signaling, including NFκΒ target genes and interacting proteins. Quantitative real time RT-PCR studies validated the gene array data for <i>IL8</i>, <i>IL23A</i>, <i>PI3</i> and <i>TACC2</i> in OE-E6/E7 cells. Consistent with the array data, Western blot analysis showed increased levels of PTGS2 protein induced by IL1β that was blocked by DEX. A parallel experiment using primary cultured human FTE cells indicated similar effects on <i>PTGS2</i>, <i>IL8</i>, <i>IL23A</i>, <i>PI3</i> and <i>TACC2</i> transcripts. These findings support the hypothesis that pro-inflammatory signaling is induced in FTE cells by inflammatory mediators and raises the possibility that dysregulation of glucocorticoid signaling could contribute to increased risk for HGSOC.</p></div

Annotating Cancer Variants and Anti-Cancer Therapeutics in Reactome

Reactome describes biological pathways as chemical reactions that closely mirror the actual physical interactions that occur in the cell. Recent extensions of our data model accommodate the annotation of cancer and other disease processes. First, we have extended our class of protein modifications to accommodate annotation of changes in amino acid sequence and the formation of fusion proteins to describe the proteins involved in disease processes. Second, we have added a disease attribute to reaction, pathway, and physical entity classes that uses disease ontology terms. To support the graphical representation of “cancer” pathways, we have adapted our Pathway Browser to display disease variants and events in a way that allows comparison with the wild type pathway, and shows connections between perturbations in cancer and other biological pathways. The curation of pathways associated with cancer, coupled with our efforts to create other disease-specific pathways, will interoperate with our existing pathway and network analysis tools. Using the Epidermal Growth Factor Receptor (EGFR) signaling pathway as an example, we show how Reactome annotates and presents the altered biological behavior of EGFR variants due to their altered kinase and ligand-binding properties, and the mode of action and specificity of anti-cancer therapeutics

List of primers used for RT-qPCR.

<p>F =  forward, R =  reverse.</p

Increased PTGS2 levels in OE-E6/E7 cells by IL1β and TNFα treatment is blocked by DEX.

<p>A, Cells were treated with 50/ml IL1β for 24 h or 48 h and Western blot analysis was performed for PTSG2 and tubulin. B, Cells were treated with 10 nM DEX or vehicle 30 h prior to treatment with IL1β or vehicle and harvested 24 h later. Western blot analysis was performed for PTGS2 and tubulin. C, Western blot analysis was performed on OE-E6/E7 cells for glucocorticoid receptor and tubulin levels with BT20 breast cancer cells used as positive control. D, Cells were treated with DEX or vehicle 30 h prior to treatment with TNFα or vehicle. Cells treated with TNFα alone were harvested at 24 and 48 h after treatment and cells treated with DEX+TNFα were harvested at the 48 h time point. Western blot analysis was performed for PTGS2 and tubulin. Histograms summarize quantification of PTGS2 levels normalized to tubulin in 3 to 6 immunoblots. Bars represent the mean ± SEM relative to control. Bars with different letters are statistically different from one another as determined by ANOVA followed by a Student-Newman-Keuls post-hoc multiple comparison test (<i>p</i><0.05).</p