Strategic Analyses of the National River Linking Project (NRLP) of India, Series 1. India’s water future: scenarios and issues

River basinsEnvironmental flowsDevelopment projectsWater requirementsIrrigated farmingWater demandFood demandGroundwater irrigationIrrigation efficiencyWater harvestingSupplemental irrigationWater productivityWater conservationDrip irrigationSprinkler irrigationRainfed farmingAgricultural policy

Benefit of irrigation water transfers in the National River Linking Project: a case study of the Ken-Betwa link

River basin managementRiver basin developmentDevelopment projectsWater transferIrrigation waterCrop productionCrop managementLivestock

A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

Background Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations are necessary to understand the physiology, development and adaptation of a plant and its interaction with the environment. Results RiceCyc is a metabolic pathway networks database for rice. It is a snapshot of the substrates, metabolites, enzymes, reactions and pathways of primary and intermediary metabolism in rice. RiceCyc version 3.3 features 316 pathways and 6,643 peptide-coding genes mapped to 2,103 enzyme-catalyzed and 87 protein-mediated transport reactions. The initial functional annotations of rice genes with InterPro, Gene Ontology, MetaCyc, and Enzyme Commission (EC) numbers were enriched with annotations provided by KEGG and Gramene databases. The pathway inferences and the network diagrams were first predicted based on MetaCyc reference networks and plant pathways from the Plant Metabolic Network, using the Pathologic module of Pathway Tools. This was enriched by manually adding metabolic pathways and gene functions specifically reported for rice. The RiceCyc database is hierarchically browsable from pathway diagrams to the associated genes, metabolites and chemical structures. Through the integrated tool OMICs Viewer, users can upload transcriptomic, proteomic and metabolomic data to visualize expression patterns in a virtual cell. RiceCyc, along with additional species-specific pathway databases hosted in the Gramene project, facilitates comparative pathway analysis. Conclusions Here we describe the RiceCyc network development and discuss its contribution to rice genome annotations. As a case study to demonstrate the use of RiceCyc network as a discovery environment we carried out an integrated bioinformatic analysis of rice metabolic genes that are differentially regulated under diurnal photoperiod and biotic stress treatments. The analysis of publicly available rice transcriptome datasets led to the hypothesis that the complete tryptophan biosynthesis and its dependent metabolic pathways including serotonin biosynthesis are induced by taxonomically diverse pathogens while also being under diurnal regulation. The RiceCyc database is available online for free access at http://www.gramene.org/pathway

Human and murine IFIT1 proteins do not restrict infection of negative-sense RNA viruses of the Orthomyxoviridae, Bunyaviridae, and Filoviridae families

UNLABELLED: Interferon-induced protein with tetratricopeptide repeats 1 (IFIT1) is a host protein with reported cell-intrinsic antiviral activity against several RNA viruses. The proposed basis for the activity against negative-sense RNA viruses is the binding to exposed 5\u27-triphosphates (5\u27-ppp) on the genome of viral RNA. However, recent studies reported relatively low binding affinities of IFIT1 for 5\u27-ppp RNA, suggesting that IFIT1 may not interact efficiently with this moiety under physiological conditions. To evaluate the ability of IFIT1 to have an impact on negative-sense RNA viruses, we infected Ifit1(-/-) and wild-type control mice and primary cells with four negative-sense RNA viruses (influenza A virus [IAV], La Crosse virus [LACV], Oropouche virus [OROV], and Ebola virus) corresponding to three distinct families. Unexpectedly, a lack of Ifit1 gene expression did not result in increased infection by any of these viruses in cell culture. Analogously, morbidity, mortality, and viral burdens in tissues were identical between Ifit1(-/-) and control mice after infection with IAV, LACV, or OROV. Finally, deletion of the human IFIT1 protein in A549 cells did not affect IAV replication or infection, and reciprocally, ectopic expression of IFIT1 in HEK293T cells did not inhibit IAV infection. To explain the lack of antiviral activity against IAV, we measured the binding affinity of IFIT1 for RNA oligonucleotides resembling the 5\u27 ends of IAV gene segments. The affinity for 5\u27-ppp RNA was approximately 10-fold lower than that for non-2\u27-O-methylated (cap 0) RNA oligonucleotides. Based on this analysis, we conclude that IFIT1 is not a dominant restriction factor against negative-sense RNA viruses. IMPORTANCE: Negative-sense RNA viruses, including influenza virus and Ebola virus, have been responsible for some of the most deadly outbreaks in recent history. The host interferon response and induction of antiviral genes contribute to the control of infections by these viruses. IFIT1 is highly induced after virus infection and reportedly has antiviral activity against several RNA and DNA viruses. However, its role in restricting infection by negative-sense RNA viruses remains unclear. In this study, we evaluated the ability of IFIT1 to inhibit negative-sense RNA virus replication and pathogenesis both in vitro and in vivo. Detailed cell culture and animal studies demonstrated that IFIT1 is not a dominant restriction factor against three different families of negative-sense RNA viruses

Review on Photomicrography based Full Blood Count (FBC) Testing and Recent Advancements

With advancements in related sub-fields, research on photomicrography in life science is emerging and this is a review on its application towards human full blood count testing which is a primary test in medical practices. For a prolonged period of time, analysis of blood samples is the basis for bio medical observations of living creatures. Cell size, shape, constituents, count, ratios are few of the features identified using DIP based analysis and these features provide an overview of the state of human body which is important in identifying present medical conditions and indicating possible future complications. In addition, functionality of the immune system is observed using results of blood tests. In FBC tests, identification of different blood cell types and counting the number of cells of each type is required to obtain results. Literature discuss various techniques and methods and this article presents an insightful review on human blood cell morphology, photomicrography, digital image processing of photomicrographs, feature extraction and classification, and recent advances. Integration of emerging technologies such as microfluidics, micro-electromechanical systems, and artificial intelligence based image processing algorithms and classifiers with cell sensing have enabled exploration of novel research directions in blood testing applications.

Plant Reactome: a resource for plant pathways and comparative analysis

Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX

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

Nuclear-localized human respiratory syncytial virus NS1 protein modulates host gene transcription

Human respiratory syncytial virus (RSV) is a common cause of lower respiratory tract infections in the pediatric, elderly, and immunocompromised individuals. RSV non-structural protein NS1 is a known cytosolic immune antagonist, but how NS1 modulates host responses remains poorly defined. Here, we observe NS1 partitioning into the nucleus of RSV-infected cells, including the human airway epithelium. Nuclear NS1 coimmunoprecipitates with Mediator complex and is chromatin associated. Chromatin-immunoprecipitation demonstrates enrichment of NS1 that overlaps Mediator and transcription factor binding within the promoters and enhancers of differentially expressed genes during RSV infection. Mutation of the NS1 C-terminal helix reduces NS1 impact on host gene expression. These data suggest that nuclear NS1 alters host responses to RSV infection by binding at regulatory elements of immune response genes and modulating host gene transcription. Our study identifies another layer of regulation by virally encoded proteins that shapes host response and impacts immunity to RSV

Crude oil yield and properties of rice bran oil from different varieties as affected by extraction conditions using soxhterm method

The current study was employed to investigate the effect of solvent type, extraction time and bran ratio on the rice bran oil (RBO) properties from three varieties of rice bran namely Bario, lowland and upland rice. RBO was extracted by using soxtherm extraction method using methanol solvent at different extraction time (3, 4 and 5 h) and bran ratio (10, 20 and 30 g). Free fatty acid (FFA), total phenolic content (TPC) and antioxidant properties were assessed. Solvent that has low polarity exhibited the attraction of polar component of oil with the highest yield by ethanol (16.16%), followed by methanol (15.38%). FFA contents occurred higher in lowland types of rice bran in all types of solvents at P<0.05 with ethanol (12.73%), methanol (11.96%) and hexane (11.13%), while the total phenolic content and antioxidant properties were influenced by the types of rice bran and solvents used for extracting components out of the bran. The highest phenolic content in the crude oil was extracted using ethanol in lowland (0.509 mg/ml), and the lowest was extracted by hexane in Bario (0.061 mg/ml). The highest antioxidant activity was observed in RBO extracted using methanol of lowland (73.74%) and RBO extracted using ethanol of upland (73.65%), while the lowest were observed in RBO extracted using hexane. The different types of solvent have the significant impact on the crude oil yield and properties of crude oil extracted

Evaluating end-to-end optimization for data analytics applications in weld

Modern analytics applications use a diverse mix of libraries and functions. Unfortunately, there is no optimization across these libraries, resulting in performance penalties as high as an order of magnitude in many applications. To address this problem, we proposed Weld, a common runtime for existing data analytics libraries that performs key physical optimizations such as pipelining under existing, imperative library APIs. In this work, we further develop the Weld vision by designing an automatic adaptive optimizer for Weld applications, and evaluating its impact on realistic data science workloads. Our optimizer eliminates multiple forms of overhead that arise when composing imperative libraries like Pandas and NumPy, and uses lightweight measurements to make data-dependent decisions at run-time in ad-hoc workloads where no statistics are available, with sub-second overhead. We also evaluate which optimizations have the largest impact in practice and whether Weld can be integrated into libraries incrementally. Our results are promising: using our optimizer, Weld accelerates data science workloads by up to 23X on one thread and 80X on eight threads, and its adaptive optimizations provide up to a 3.75X speedup over rule-based optimization. Moreover, Weld provides benefits if even just 4--5 operators in a library are ported to use it. Our results show that common runtime designs like Weld may be a viable approach to accelerate analytics