New Generation of Electrochemical Sensors for Nitric Oxide;Ruthenium/Carbon-Based Nanostructures and Colloids as Electrocatalytic Platforms

Nitric oxide (NO) is an important intercellular messenger that acts in many tissues to regulate a diverse range of physiological and pathological processes. The physiologically implications of NO function are far from being completely understood. The multifaceted reactivity of NO prompted the need for accurate determination of the concentration of this molecule. However, it is difficult to detect nitric oxide, particularly in biological media and near live cells due to its short half-life, a result of its reactivity and the low levels of NO produced in vivo. As a result, the accurate and reliable detection of NO under varying experimental conditions has always posed a challenging task. The main goal was to develop ultra-sensitive electrocatalytic sensors for accurate quantification of NO. We report the fabrication and characterization of improved NO sensors based on electrocatalytic platforms such as ruthenium (colloids, nanoparticles, and nanotubes) and carbon (pastes and nanotubes), acting as catalytic sites for NO oxidation. These sensors are characterized using various surface analytical tools. The electrocatalytic oxidation of NO is assessed by cyclic voltammetry and amperometry both in solution phase and gas phase. Excellent sensitivity and linearity are observed for our modified electrodes towards NO quantification. Our new NO detection sensors also show superior limit of detection and selectivity against common interference species. Our NO sensors are tested for various applications including in the measurement of NO released from human umbilical vein endothelial cells (HUVECs

New Generation of Electrochemical Sensors for Nitric Oxide;Ruthenium/Carbon-Based Nanostructures and Colloids as Electrocatalytic Platforms

Nitric oxide (NO) is an important intercellular messenger that acts in many tissues to regulate a diverse range of physiological and pathological processes. The physiologically implications of NO function are far from being completely understood. The multifaceted reactivity of NO prompted the need for accurate determination of the concentration of this molecule. However, it is difficult to detect nitric oxide, particularly in biological media and near live cells due to its short half-life, a result of its reactivity and the low levels of NO produced in vivo. As a result, the accurate and reliable detection of NO under varying experimental conditions has always posed a challenging task. The main goal was to develop ultra-sensitive electrocatalytic sensors for accurate quantification of NO. We report the fabrication and characterization of improved NO sensors based on electrocatalytic platforms such as ruthenium (colloids, nanoparticles, and nanotubes) and carbon (pastes and nanotubes), acting as catalytic sites for NO oxidation. These sensors are characterized using various surface analytical tools. The electrocatalytic oxidation of NO is assessed by cyclic voltammetry and amperometry both in solution phase and gas phase. Excellent sensitivity and linearity are observed for our modified electrodes towards NO quantification. Our new NO detection sensors also show superior limit of detection and selectivity against common interference species. Our NO sensors are tested for various applications including in the measurement of NO released from human umbilical vein endothelial cells (HUVECs

New Generation of Electrochemical Sensors for Nitric Oxide;Ruthenium/Carbon-Based Nanostructures and Colloids as Electrocatalytic Platforms

Nitric oxide (NO) is an important intercellular messenger that acts in many tissues to regulate a diverse range of physiological and pathological processes. The physiologically implications of NO function are far from being completely understood. The multifaceted reactivity of NO prompted the need for accurate determination of the concentration of this molecule. However, it is difficult to detect nitric oxide, particularly in biological media and near live cells due to its short half-life, a result of its reactivity and the low levels of NO produced in vivo. As a result, the accurate and reliable detection of NO under varying experimental conditions has always posed a challenging task. The main goal was to develop ultra-sensitive electrocatalytic sensors for accurate quantification of NO. We report the fabrication and characterization of improved NO sensors based on electrocatalytic platforms such as ruthenium (colloids, nanoparticles, and nanotubes) and carbon (pastes and nanotubes), acting as catalytic sites for NO oxidation. These sensors are characterized using various surface analytical tools. The electrocatalytic oxidation of NO is assessed by cyclic voltammetry and amperometry both in solution phase and gas phase. Excellent sensitivity and linearity are observed for our modified electrodes towards NO quantification. Our new NO detection sensors also show superior limit of detection and selectivity against common interference species. Our NO sensors are tested for various applications including in the measurement of NO released from human umbilical vein endothelial cells (HUVECs

Using meta-networks to identify key intervention points in nuclear WMD development

The ability to identify key intervention points in the nuclear WMD development process is vital for the development of effective intervention strategies against nuclear proliferation efforts. This paper describes research in progress to investigate nuclear weapons development as a meta-network of people, knowledge, resources, locations and tasks, and to design a software tool which will be capable of identifying the key intervention points of the process based upon the available information

Oncogenic fusion protein BCR-FGFR1 requires the breakpoint cluster region-mediated oligomerization and chaperonin Hsp90 for activation.

Mutation and translocation of fibroblast growth factor receptors often lead to aberrant signaling and cancer. This work focuses on the t(8;22)(p11;q11) chromosomal translocation which creates the breakpoint cluster region (BCR) fibroblast growth factor receptor1 (FGFR1) (BCR-FGFR1) fusion protein. This fusion occurs in stem cell leukemia/lymphoma, which can progress to atypical chronic myeloid leukemia, acute myeloid leukemia, or B-cell lymphoma. This work focuses on the biochemical characterization of BCR-FGFR1 and identification of novel therapeutic targets. The tyrosine kinase activity of FGFR1 is required for biological activity as shown using transformation assays, interleukin-3 independent cell proliferation, and liquid chromatography/mass spectroscopy analyses. Furthermore, BCR contributes a coiled-coil oligomerization domain, also essential for oncogenic transformation by BCR-FGFR1. The importance of salt bridge formation within the coiled-coil domain is demonstrated, as disruption of three salt bridges abrogates cellular transforming ability. Lastly, BCR-FGFR1 acts as a client of the chaperonin heat shock protein 90 (Hsp90), suggesting that BCR-FGFR1 relies on Hsp90 complex to evade proteasomal degradation. Transformed cells expressing BCR-FGFR1 are sensitive to the Hsp90 inhibitor Ganetespib, and also respond to combined treatment with Ganetespib plus the FGFR inhibitor BGJ398. Collectively, these data suggest novel therapeutic approaches for future stem cell leukemia/lymphoma treatment: inhibition of BCR oligomerization by disruption of required salt bridges; and inhibition of the chaperonin Hsp90 complex

Bayesian Analysis of Inflation III: Slow Roll Reconstruction Using Model Selection

We implement Slow Roll Reconstruction -- an optimal solution to the inverse problem for inflationary cosmology -- within ModeCode, a publicly available solver for the inflationary dynamics. We obtain up-to-date constraints on the reconstructed inflationary potential, derived from the WMAP 7-year dataset and South Pole Telescope observations, combined with large scale structure data derived from SDSS Data Release 7. Using ModeCode in conjunction with the MultiNest sampler, we compute Bayesian evidence for the reconstructed potential at each order in the truncated slow roll hierarchy. We find that the data are well-described by the first two slow roll parameters, \epsilon and \eta, and that there is no need to include a nontrivial \xi parameter.Comment: 14 pages, 12 figures, minor changes; final version; accepted in PR

International Laboratory Comparison of Influenza Microneutralization Assays for A(H1N1) pdm09, A(H3N2), and A(H5N1) Influenza Viruses by CONSISE

The microneutralization assay is commonly used to detect antibodies to influenza virus, and multiple protocols are used worldwide. These protocols differ in the incubation time of the assay as well as in the order of specific steps, and even within protocols there are often further adjustments in individual laboratories. The impact these protocol variations have on influenza serology data is unclear. Thus, a laboratory comparison of the 2-day enzyme-linked immunosorbent assay (ELISA) and 3-day hemagglutination (HA) microneutralization (MN) protocols, using A(H1N1)pdm09, A(H3N2), and A(H5N1) viruses, was performed by the CONSISE Laboratory Working Group. Individual laboratories performed both assay protocols, on multiple occasions, using different serum panels. Thirteen laboratories from around the world participated. Within each laboratory, serum sample titers for the different assay protocols were compared between assays to determine the sensitivity of each assay and were compared between replicates to assess the reproducibility of each protocol for each laboratory. There was good correlation of the results obtained using the two assay protocols in most laboratories, indicating that these assays may be interchangeable for detecting antibodies to the influenza A viruses included in this study. Importantly, participating laboratories have aligned their methodologies to the CONSISE consensus 2-day ELISA and 3-day HA MN assay protocols to enable better correlation of these assays in the future

Use of seasonal climate information to predict coconut production in Sri Lanka

Accurate forecasting of annual national coconut production (ANCP) is important for national agricultural planning and negotiating forward contracts. Climate and the long-term trends (attributed to 'technology') are major factors that determine ANCP. The effect of climate on ANCP of the following year was studied for the seven agro-ecological regions (AER's) in the principal coconut growing areas for the period 1950-2002. Climate was studied based on seasons aggregated by the monsoon calendar and by quarters that are consistent with the agricultural calendar. The use of quarterly seasons explained more of the variability of ANCP than the use of monsoon based seasons. January-March rainfall in all AER's and July-September rainfall in the wetter regions are positively correlated with the ANCP (p < 0.005). The technology effect was estimated using a log-linear trend model. The regression model integrates both climate and technology effects developed to predict ANCP with high fidelity (R2 = 0.94). The climate effect was estimated by regressing production data that had been de-trended to remove the technology effects with quarterly rainfall in the year prior to harvest. The most significant predictors were found to be the quarterly rainfall from the AER's in the coconut growing regions that are designated as wet and intermediate. Representative rainfall from each quarter was used in a regression model with corrections for the technology effect. The correlation between observed and predicted values of the ANCP was 0.83 (p < 0.001). The prediction of ANCP for 2003 and 2004 gave errors of only 6.5 and 7.0%. The estimated value of ANCP for 2005 is 2715 million nuts, which is 12% higher than the mean. The lead time of the prediction extends to 15 months but it may be extended with the use of seasonal climate forecasts to 24 months

Constraining Inflation

Slow roll reconstruction is derived from the Hamilton-Jacobi formulation of inflationary dynamics. It automatically includes information from sub-leading terms in slow roll, and facilitatesthe inclusion of priors based on the duration on inflation. We show that at low inflationary scales the Hamilton-Jacobi equations simplify considerably. We provide a new classification scheme for inflationary models, based solely on the number of parameters needed to specify the potential, and provide forecasts for likely bounds on the slow roll parameters from future datasets. A minimal running of the spectral index, induced solely by the first two slow roll parameters (\epsilon and \eta) appears to be effectively undetectable by realistic Cosmic Microwave Background experiments. However, we show that the ability to detect this signal increases with the lever arm in comoving wavenumber, and we conjecture that high redshift 21 cm data may allow tests of second order consistency conditions on inflation. Finally, we point out that the second order corrections to the spectral index are correlated with the inflationary scale, and thus the amplitude of the CMB B-mode.Comment: 32 pages. v