229 research outputs found

    Denitrification and nitrous oxide emissions from riparian forests soils exposed to prolonged nitrogen runoff

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    Compared to upland forests, riparian forest soils have greater potential to remove nitrate (NO3) from agricultural run-off through denitrification. It is unclear, however, whether prolonged exposure of riparian soils to nitrogen (N) loading will affect the rate of denitrification and its end products. This research assesses the rate of denitrification and nitrous oxide (N2O) emissions from riparian forest soils exposed to prolonged nutrient run-off from plant nurseries and compares these to similar forest soils not exposed to nutrient run-off. Nursery run-off also contains high levels of phosphate (PO4). Since there are conflicting reports on the impact of PO4 on the activity of denitrifying microbes, the impact of PO4 on such activity was also investigated. Bulk and intact soil cores were collected from N-exposed and non-exposed forests to determine denitrification and N2O emission rates, whereas denitrification potential was determined using soil slurries. Compared to the non-amended treatment, denitrification rate increased 2.7- and 3.4-fold when soil cores collected from both N-exposed and non-exposed sites were amended with 30 and 60 μg NO3-N g-1 soil, respectively. Net N2O emissions were 1.5 and 1.7 times higher from the N-exposed sites compared to the non-exposed sites at 30 and 60 μg NO3-N g-1 soil amendment rates, respectively. Similarly, denitrification potential increased 17 times in response to addition of 15 μg NO3-N g-1 in soil slurries. The addition of PO4 (5 μg PO4–P g-1) to soil slurries and intact cores did not affect denitrification rates. These observations suggest that prolonged N loading did not affect the denitrification potential of the riparian forest soils; however, it did result in higher N2O emissions compared to emission rates from non-exposed forests

    How a Diverse Research Ecosystem Has Generated New Rehabilitation Technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers

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    Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program

    Upregulation of the cell-cycle regulator RGC-32 in Epstein-Barr virus-immortalized cells

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    Epstein-Barr virus (EBV) is implicated in the pathogenesis of multiple human tumours of lymphoid and epithelial origin. The virus infects and immortalizes B cells establishing a persistent latent infection characterized by varying patterns of EBV latent gene expression (latency 0, I, II and III). The CDK1 activator, Response Gene to Complement-32 (RGC-32, C13ORF15), is overexpressed in colon, breast and ovarian cancer tissues and we have detected selective high-level RGC-32 protein expression in EBV-immortalized latency III cells. Significantly, we show that overexpression of RGC-32 in B cells is sufficient to disrupt G2 cell-cycle arrest consistent with activation of CDK1, implicating RGC-32 in the EBV transformation process. Surprisingly, RGC-32 mRNA is expressed at high levels in latency I Burkitt's lymphoma (BL) cells and in some EBV-negative BL cell-lines, although RGC-32 protein expression is not detectable. We show that RGC-32 mRNA expression is elevated in latency I cells due to transcriptional activation by high levels of the differentially expressed RUNX1c transcription factor. We found that proteosomal degradation or blocked cytoplasmic export of the RGC-32 message were not responsible for the lack of RGC-32 protein expression in latency I cells. Significantly, analysis of the ribosomal association of the RGC-32 mRNA in latency I and latency III cells revealed that RGC-32 transcripts were associated with multiple ribosomes in both cell-types implicating post-initiation translational repression mechanisms in the block to RGC-32 protein production in latency I cells. In summary, our results are the first to demonstrate RGC-32 protein upregulation in cells transformed by a human tumour virus and to identify post-initiation translational mechanisms as an expression control point for this key cell-cycle regulator

    MicroRNAs MiR-17, MiR-20a, and MiR-106b Act in Concert to Modulate E2F Activity on Cell Cycle Arrest during Neuronal Lineage Differentiation of USSC

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    MicroRNAs are short (∼22 nt) non-coding regulatory RNAs that control gene expression at the post-transcriptional level. Here the functional impact of microRNAs on cell cycle arrest during neuronal lineage differentiation of unrestricted somatic stem cells from human cord blood (USSC) was analyzed./M transition. Most strikingly, miR-17, -20a, and -106b were found to promote cell proliferation by increasing the intracellular activity of E2F transcription factors, despite the fact that miR-17, -20a, and -106b directly target the transcripts that encode for this protein family./S transition

    Evidence for an excess of B -> D(*) Tau Nu decays

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    Based on the full BaBar data sample, we report improved measurements of the ratios R(D(*)) = B(B -> D(*) Tau Nu)/B(B -> D(*) l Nu), where l is either e or mu. These ratios are sensitive to new physics contributions in the form of a charged Higgs boson. We measure R(D) = 0.440 +- 0.058 +- 0.042 and R(D*) = 0.332 +- 0.024 +- 0.018, which exceed the Standard Model expectations by 2.0 sigma and 2.7 sigma, respectively. Taken together, our results disagree with these expectations at the 3.4 sigma level. This excess cannot be explained by a charged Higgs boson in the type II two-Higgs-doublet model. We also report the observation of the decay B -> D Tau Nu, with a significance of 6.8 sigma.Comment: Expanded section on systematics, text corrections, improved the format of Figure 2 and included the effect of the change of the Tau polarization due to the charged Higg

    Search for the decay modes D^0 → e^+e^-, D^0 → μ^+μ^-, and D^0 → e^±μ∓

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    We present searches for the rare decay modes D^0→e^+e^-, D^0→μ^+μ^-, and D^0→e^±μ^∓ in continuum e^+e^-→cc events recorded by the BABAR detector in a data sample that corresponds to an integrated luminosity of 468  fb^(-1). These decays are highly Glashow–Iliopoulos–Maiani suppressed but may be enhanced in several extensions of the standard model. Our observed event yields are consistent with the expected backgrounds. An excess is seen in the D^0→μ^+μ^- channel, although the observed yield is consistent with an upward background fluctuation at the 5% level. Using the Feldman–Cousins method, we set the following 90% confidence level intervals on the branching fractions: B(D^0→e^+e^-)<1.7×10^(-7), B(D^0→μ^+μ^-) within [0.6,8.1]×10^(-7), and B(D^0→e^±μ^∓)<3.3×10^(-7)

    Study of the reaction e^{+}e^{-} -->J/psi\pi^{+}\pi^{-} via initial-state radiation at BaBar

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    We study the process e+eJ/ψπ+πe^+e^-\to J/\psi\pi^{+}\pi^{-} with initial-state-radiation events produced at the PEP-II asymmetric-energy collider. The data were recorded with the BaBar detector at center-of-mass energies 10.58 and 10.54 GeV, and correspond to an integrated luminosity of 454 fb1\mathrm{fb^{-1}}. We investigate the J/ψπ+πJ/\psi \pi^{+}\pi^{-} mass distribution in the region from 3.5 to 5.5 GeV/c2\mathrm{GeV/c^{2}}. Below 3.7 GeV/c2\mathrm{GeV/c^{2}} the ψ(2S)\psi(2S) signal dominates, and above 4 GeV/c2\mathrm{GeV/c^{2}} there is a significant peak due to the Y(4260). A fit to the data in the range 3.74 -- 5.50 GeV/c2\mathrm{GeV/c^{2}} yields a mass value 4244±54244 \pm 5 (stat) ±4 \pm 4 (syst)MeV/c2\mathrm{MeV/c^{2}} and a width value 11415+16114 ^{+16}_{-15} (stat)±7 \pm 7(syst)MeV\mathrm{MeV} for this state. We do not confirm the report from the Belle collaboration of a broad structure at 4.01 GeV/c2\mathrm{GeV/c^{2}}. In addition, we investigate the π+π\pi^{+}\pi^{-} system which results from Y(4260) decay

    Measuring and Modeling Risk Using High-Frequency Data

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    Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management. The recent availability of high-frequency data allows for refined methods in this field. In particular, more precise measures for the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns. In turn, this so-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure of volatility. Moreover, non-parametric measures of systematic risk are attainable, that can straightforwardly be used to model the commonly observed time-variation in the betas. The discussion of these new measures and methods is accompanied by an empirical illustration using high-frequency data of the IBM incorporation and of the DJIA index

    The First Illumina-Based De Novo Transcriptome Sequencing and Analysis of Safflower Flowers

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    BACKGROUND: The safflower, Carthamus tinctorius L., is a worldwide oil crop, and its flowers, which have a high flavonoid content, are an important medicinal resource against cardiovascular disease in traditional medicine. Because the safflower has a large and complex genome, the development of its genomic resources has been delayed. Second-generation Illumina sequencing is now an efficient route for generating an enormous volume of sequences that can represent a large number of genes and their expression levels. METHODOLOGY/PRINCIPAL FINDINGS: To investigate the genes and pathways that might control flavonoids and other secondary metabolites in the safflower, we used Illumina sequencing to perform a de novo assembly of the safflower tubular flower tissue transcriptome. We obtained a total of 4.69 Gb in clean nucleotides comprising 52,119,104 clean sequencing reads, 195,320 contigs, and 120,778 unigenes. Based on similarity searches with known proteins, we annotated 70,342 of the unigenes (about 58% of the identified unigenes) with cut-off E-values of 10(-5). In total, 21,943 of the safflower unigenes were found to have COG classifications, and BLAST2GO assigned 26,332 of the unigenes to 1,754 GO term annotations. In addition, we assigned 30,203 of the unigenes to 121 KEGG pathways. When we focused on genes identified as contributing to flavonoid biosynthesis and the biosynthesis of unsaturated fatty acids, which are important pathways that control flower and seed quality, respectively, we found that these genes were fairly well conserved in the safflower genome compared to those of other plants. CONCLUSIONS/SIGNIFICANCE: Our study provides abundant genomic data for Carthamus tinctorius L. and offers comprehensive sequence resources for studying the safflower. We believe that these transcriptome datasets will serve as an important public information platform to accelerate studies of the safflower genome, and may help us define the mechanisms of flower tissue-specific and secondary metabolism in this non-model plant
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