Measurement of 222Rn dissolved in water at the Sudbury Neutrino Observatory

The technique used at the Sudbury Neutrino Observatory (SNO) to measure the concentration of 222Rn in water is described. Water from the SNO detector is passed through a vacuum degasser (in the light water system) or a membrane contact degasser (in the heavy water system) where dissolved gases, including radon, are liberated. The degasser is connected to a vacuum system which collects the radon on a cold trap and removes most other gases, such as water vapor and nitrogen. After roughly 0.5 tonnes of H2O or 6 tonnes of D2O have been sampled, the accumulated radon is transferred to a Lucas cell. The cell is mounted on a photomultiplier tube which detects the alpha particles from the decay of 222Rn and its daughters. The overall degassing and concentration efficiency is about 38% and the single-alpha counting efficiency is approximately 75%. The sensitivity of the radon assay system for D2O is equivalent to ~3 E(-15) g U/g water. The radon concentration in both the H2O and D2O is sufficiently low that the rate of background events from U-chain elements is a small fraction of the interaction rate of solar neutrinos by the neutral current reaction.Comment: 14 pages, 6 figures; v2 has very minor change

MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

How and When Socially Entrepreneurial Nonprofit Organizations Benefit From Adopting Social Alliance Management Routines to Manage Social Alliances?

Social alliance is defined as the collaboration between for-profit and nonprofit organizations. Building on the insights derived from the resource-based theory, we develop a conceptual framework to explain how socially entrepreneurial nonprofit organizations (SENPOs) can improve their social alliance performance by adopting strategic alliance management routines. We test our framework using the data collected from 203 UK-based SENPOs in the context of cause-related marketing campaign-derived social alliances. Our results confirm a positive relationship between social alliance management routines and social alliance performance. We also find that relational mechanisms, such as mutual trust, relational embeddedness, and relational commitment, mediate the relationship between social alliance management routines and social alliance performance. Moreover, our findings suggest that different types of social alliance motivation can influence the impact of social alliance management routines on different types of the relational mechanisms. In general, we demonstrate that SENPOs can benefit from adopting social alliance management routines and, in addition, highlight how and when the social alliance management routines–social alliance performance relationship might be shaped. Our study offers important academic and managerial implications, and points out future research directions

Ginger extract inhibits LPS induced macrophage activation and function

<p>Abstract</p> <p>Background</p> <p>Macrophages play a dual role in host defence. They act as the first line of defence by mounting an inflammatory response to antigen exposure and also act as antigen presenting cells and initiate the adaptive immune response. They are also the primary infiltrating cells at the site of inflammation. Inhibition of macrophage activation is one of the possible approaches towards modulating inflammation. Both conventional and alternative approaches are being studied in this regard. Ginger, an herbal product with broad anti inflammatory actions, is used as an alternative medicine in a number of inflammatory conditions like rheumatic disorders. In the present study we examined the effect of ginger extract on macrophage activation in the presence of LPS stimulation.</p> <p>Methods</p> <p>Murine peritoneal macrophages were stimulated by LPS in presence or absence of ginger extract and production of proinflammatory cytokines and chemokines were observed. We also studied the effect of ginger extract on the LPS induced expression of MHC II, B7.1, B7.2 and CD40 molecules. We also studied the antigen presenting function of ginger extract treated macrophages by primary mixed lymphocyte reaction.</p> <p>Results</p> <p>We observed that ginger extract inhibited IL-12, TNF-α, IL-1β (pro inflammatory cytokines) and RANTES, MCP-1 (pro inflammatory chemokines) production in LPS stimulated macrophages. Ginger extract also down regulated the expression of B7.1, B7.2 and MHC class II molecules. In addition ginger extract negatively affected the antigen presenting function of macrophages and we observed a significant reduction in T cell proliferation in response to allostimulation, when ginger extract treated macrophages were used as APCs. A significant decrease in IFN-γ and IL-2 production by T cells in response to allostimulation was also observed.</p> <p>Conclusion</p> <p>In conclusion ginger extract inhibits macrophage activation and APC function and indirectly inhibits T cell activation.</p

In Vitro Characterization of a Nineteenth-Century Therapy for Smallpox

In the nineteenth century, smallpox ravaged through the United States and Canada. At this time, a botanical preparation, derived from the carnivorous plant Sarracenia purpurea, was proclaimed as being a successful therapy for smallpox infections. The work described characterizes the antipoxvirus activity associated with this botanical extract against vaccinia virus, monkeypox virus and variola virus, the causative agent of smallpox. Our work demonstrates the in vitro characterization of Sarracenia purpurea as the first effective inhibitor of poxvirus replication at the level of early viral transcription. With the renewed threat of poxvirus-related infections, our results indicate Sarracenia purpurea may act as another defensive measure against Orthopoxvirus infections

Constraints on Nucleon Decay via "Invisible" Modes from the Sudbury Neutrino Observatory

Data from the Sudbury Neutrino Observatory have been used to constrain the lifetime for nucleon decay to ``invisible'' modes, such as n -> 3 nu. The analysis was based on a search for gamma-rays from the de-excitation of the residual nucleus that would result from the disappearance of either a proton or neutron from O16. A limit of tau_inv > 2 x 10^{29} years is obtained at 90% confidence for either neutron or proton decay modes. This is about an order of magnitude more stringent than previous constraints on invisible proton decay modes and 400 times more stringent than similar neutron modes.Comment: Update includes missing efficiency factor (limits change by factor of 2) Submitted to Physical Review Letter

Accounting for density reduction and structural loss in standing dead trees: Implications for forest biomass and carbon stock estimates in the United States

<p>Abstract</p> <p>Background</p> <p>Standing dead trees are one component of forest ecosystem dead wood carbon (C) pools, whose national stock is estimated by the U.S. as required by the United Nations Framework Convention on Climate Change. Historically, standing dead tree C has been estimated as a function of live tree growing stock volume in the U.S.'s National Greenhouse Gas Inventory. Initiated in 1998, the USDA Forest Service's Forest Inventory and Analysis program (responsible for compiling the Nation's forest C estimates) began consistent nationwide sampling of standing dead trees, which may now supplant previous purely model-based approaches to standing dead biomass and C stock estimation. A substantial hurdle to estimating standing dead tree biomass and C attributes is that traditional estimation procedures are based on merchantability paradigms that may not reflect density reductions or structural loss due to decomposition common in standing dead trees. The goal of this study was to incorporate standing dead tree adjustments into the current estimation procedures and assess how biomass and C stocks change at multiple spatial scales.</p> <p>Results</p> <p>Accounting for decay and structural loss in standing dead trees significantly decreased tree- and plot-level C stock estimates (and subsequent C stocks) by decay class and tree component. At a regional scale, incorporating adjustment factors decreased standing dead quaking aspen biomass estimates by almost 50 percent in the Lake States and Douglas-fir estimates by more than 36 percent in the Pacific Northwest.</p> <p>Conclusions</p> <p>Substantial overestimates of standing dead tree biomass and C stocks occur when one does not account for density reductions or structural loss. Forest inventory estimation procedures that are descended from merchantability standards may need to be revised toward a more holistic approach to determining standing dead tree biomass and C attributes (i.e., attributes of tree biomass outside of sawlog portions). Incorporating density reductions and structural loss adjustments reduces uncertainty associated with standing dead tree biomass and C while improving consistency with field methods and documentation.</p

Nonrandom Mixing Models of HIV Transmission

Models of HIV transmission and the AIDS epidemic generally assume random mixing among those infected with HIV and those who are not. For sexually transmitted HIV, this implies that individuals select sex partners without regard to attributes such as familiarity, attractiveness, or risk of infection. This paper formulates a model for examining the impact of nonrandom mixing on HIV transmission. We present threshold conditions that determine when HIV epidemics can occur within the framework of this model. Nonrandom mixing is introduced by assuming that sexually active individuals select sex partners to minimize the risk of infection. In addition to variability in risky sex rates, some versions of our model allow for error (or noise) in information exchanged between prospective partners. We investigate several models including random partner selection (or proportionate mixing), segregation of the population by risky sex rates, a probabilistic combination of segregation and random selection induced by imperfect information (or preferred mixing), and a model of costly search with perfect information. We develop examples which show that nonrandom mixing can lead to epidemics that are more severe or less severe than random mixing. For reasonable parameter choices describing the AIDS epidemic, however, the results suggest that random mixing models overstate the number of HIV infections that will occur

First Neutrino Observations from the Sudbury Neutrino Observatory

The first neutrino observations from the Sudbury Neutrino Observatory are presented from preliminary analyses. Based on energy, direction and location, the data in the region of interest appear to be dominated by 8B solar neutrinos, detected by the charged current reaction on deuterium and elastic scattering from electrons, with very little background. Measurements of radioactive backgrounds indicate that the measurement of all active neutrino types via the neutral current reaction on deuterium will be possible with small systematic uncertainties. Quantitative results for the fluxes observed with these reactions will be provided when further calibrations have been completed.Comment: Latex, 7 pages, 10 figures, Invited paper at Neutrino 2000 Conference, Sudbury, Canada, June 16-21, 2000 to be published in the Proceeding