The role of 1,25-dihydroxyvitamin D in the inhibition of bone formation induced by skeletal unloading

Skeletal unloading results in osteopenia. To examine the involvement of vitamin D in this process, the rear limbs of growing rats were unloaded and alterations in bone calcium and bone histology were related to changes in serum calcium (Ca), inorganic phosphorus (P sub i), 25-hydroxyvitamin D (25-OH-D), 24,25-dihydroxyvitamin D (24,25(OH)2D and 1,25-dihydroxyvitamin D (1,25(OH)2D. Acute skeletal unloading induced a transitory inhibition of Ca accumulation in unloaded bones. This was accompanied by a transitory rise in serum Ca, a 21% decrease in longitudinal bone growth (P 0.01), a 32% decrease in bone surface lined with osteoblasts (P .05), no change in bone surface lined with osteoclasts and a decrease in circulating (1,25(OH)2D. No significant changes in the serum concentrations of P sub i, 25-OH-D or 24,25(OH)2D were observed. After 2 weeks of unloading, bone Ca stabilized at approximately 70% of control and serum Ca and 1,25(OH)2D returned to control values. Maintenance of a constant serum 1,25(OH)2D concentration by chronic infusion of 1,25(OH)2D (Alza osmotic minipump) throughout the study period did not prevent the bone changes induced by acute unloading. These results suggest that acute skeletal unloading in the growing rat produces a transitory inhibition of bone formation which in turn produces a transitory hypercalcemia

Oxygen diffusion in alpha-Al2O3

Oxygen self diffusion coefficients were determined in single crystal alpha-Al2O3 using the gas exchange technique. The samples were semi-infinite slabs cut from five different boules with varying background impurities. The diffusion direction was parallel to the c-axis. The tracer profiles were determined by two techniques, single spectrum proton activation and secondary ion mass spectrometry. The SIMS proved to be a more useful tool. The determined diffusion coefficients, which were insensitive to impurity levels and oxygen partial pressure, could be described by D = .00151 exp (-572kJ/RT) sq m/s. The insensitivities are discussed in terms of point defect clustering. Two independent models are consistent with the findings, the first considers the clusters as immobile point defect traps which buffer changes in the defect chemistry. The second considers clusters to be mobile and oxygen diffusion to be intrinsic behavior, the mechanism for oxygen transport involving neutral clusters of Schottky quintuplets

Exploring Agricultural Production Systems and Their Fundamental Components with System Dynamics Modelling

Agricultural production in the United States is undergoing marked changes due to rapid shifts in consumer demands, input costs, and concerns for food safety and environmental impact. Agricultural production systems are comprised of multidimensional components and drivers that interact in complex ways to influence production sustainability. In a mixed-methods approach, we combine qualitative and quantitative data to develop and simulate a system dynamics model that explores the systemic interaction of these drivers on the economic, environmental and social sustainability of agricultural production. We then use this model to evaluate the role of each driver in determining the differences in sustainability between three distinct production systems: crops only, livestock only, and an integrated crops and livestock system. The result from these modelling efforts found that the greatest potential for sustainability existed with the crops only production system. While this study presents a stand-alone contribution to sector knowledge and practice, it encourages future research in this sector that employs similar systems-based methods to enable more sustainable practices and policies within agricultural production

Submarine groundwater discharge to a small estuary estimated from radon and salinity measurements and a box model

Author Posting. © 2005 Author(s). This work is licensed under a Creative Commons License. The definitive version was published Biogeosciences 2 (2005): 141-157, doi:10.5194/bg-2-141-2005.Submarine groundwater discharge was quantified by a variety of methods for a 4-day period during the early summer of 2004, in Salt Pond, adjacent to Nauset Marsh, on Cape Cod, USA. Discharge estimates based on radon and salinity took advantage of the presence of the narrow channel connecting Salt Pond to Nauset Marsh, which allowed constructing whole-pond mass balances as water flowed in and out due to tidal fluctuations. The data suggest that less than one quarter of the discharge in the vicinity of Salt Pond happened within the pond itself, while three quarters or more of the discharge occurred immediately seaward of the pond, either in the channel or in adjacent regions of Nauset Marsh. Much of this discharge, which maintains high radon activities and low salinity, is carried into the pond during each incoming tide. A box model was used as an aid to understand both the rates and the locations of discharge in the vicinity of Salt Pond. The model achieves a reasonable fit to both the salinity and radon data assuming submarine groundwater discharge is fresh and that most of it occurs either in the channel or in adjacent regions of Nauset Marsh. Salinity and radon data, together with seepage meter results, do not rule out discharge of saline groundwater, but suggest either that the saline discharge is at most comparable in volume to the fresh discharge or that it is depleted in radon. The estimated rate of fresh groundwater discharge in the vicinity of Salt Pond is 3000-7000 m3 d-1. This groundwater flux estimated from the radon and salinity data is comparable to a value of 3200-4500 m3 d-1 predicted by a recent hydrologic model (Masterson, 2004; Colman and Masterson, 2004), although the model predicts this rate of discharge to the pond whereas our data suggest most of the groundwater bypasses the pond prior to discharge. Additional work is needed to determine if the measured rate of discharge is representative of the long-term average, and to better constrain the rate of groundwater discharge seaward of Salt Pond.Financial support was provided by the US Geological Survey and by National Science Foundation grant #OCE-0346933 to MAC

Requirements for In-Situ Authoring of Location Based Experiences

In this paper we describe an investigation into the requirements for and the use of in-situ authoring in the creation of location based pervasive and UbiComp experiences. We will focus on the co-design process with users that resulted in a novel visitor experience to a historic country estate. This has informed the design of new, in-situ, authoring tools supplemented with tools for retrospective revisiting and reorganization of content. An initial trial of these new tools will be discussed and conclusions drawn as to the appropriateness of such tools. Further enhancements as part of future trials will also be described

A Biological Evaluation of Six Gene Set Analysis Methods for Identification of Differentially Expressed Pathways in Microarray Data

Gene-set analysis of microarray data evaluates biological pathways, or gene sets, for their differential expression by a phenotype of interest. In contrast to the analysis of individual genes, gene-set analysis utilizes existing biological knowledge of genes and their pathways in assessing differential expression. This paper evaluates the biological performance of five gene-set analysis methods testing “self-contained null hypotheses” via subject sampling, along with the most popular gene-set analysis method, Gene Set Enrichment Analysis (GSEA). We use three real microarray analyses in which differentially expressed gene sets are predictable biologically from the phenotype. Two types of gene sets are considered for this empirical evaluation: one type contains “truly positive” sets that should be identified as differentially expressed; and the other type contains “truly negative” sets that should not be identified as differentially expressed. Our evaluation suggests advantages of SAM-GS, Global, and ANCOVA Global methods over GSEA and the other two methods

Improving GSEA for Analysis of Biologic Pathways for Differential Gene Expression across a Binary Phenotype

Gene-set analysis evaluates the expression of biological pathways, or a priori defined gene sets, rather than that of single genes, in association with a binary phenotype, and is of great biologic interest in many DNA microarray studies. Gene Set Enrichment Analysis (GSEA) has been applied widely as a tool for gene-set analyses. We describe here some critical problems with GSEA and propose an alternative method by extending the single-gene analysis method, Significance Analysis of Microarray (SAM), to gene-set analyses (SAM-GS). Specifically, we illustrate, in a simulation study, that GSEA gives statistical significance to gene sets that have no gene associated with the phenotype (null gene sets), and has very low power to detect gene sets in which half the genes are highly associated with the phenotype (truly-associated gene sets). SAM-GS, on the other hand, performs perfectly in the simulation study: none of the null gene sets is identified with statistical significance, while all of the truly-associated gene sets are. The two methods are also compared in the analyses of three real microarray datasets and relevant pathways, the diverging results of which clearly show the advantages of SAM-GS over GSEA, both statistically and biologically

TOUCHtr4ck: democratic collaborative music

When electronic musicians compose collaboratively, they typically use their own single-user musical controllers. It may, therefore, be useful to develop novel controllers that support collaborative workflows and democratic principles. After describing the design principles for developing such controllers, we present TOUCHtr4ck, a prototype multi-touch system designed to facilitate such democratic relationships. Informal testing has revealed that this approach does facilitate democratic and collaborative music making, and can produce creative musical results

Achieving coordinated national immunity and cholera elimination in Haiti through vaccination: a modelling study

Background: Cholera was introduced into Haiti in 2010. Since then, more than 820 000 cases and nearly 10 000 deaths have been reported. Oral cholera vaccine (OCV) is safe and effective, but has not been seen as a primary tool for cholera elimination due to a limited period of protection and constrained supplies. Regionally, epidemic cholera is contained to the island of Hispaniola, and the lowest numbers of cases since the epidemic began were reported in 2019. Hence, Haiti may represent a unique opportunity to eliminate cholera with OCV. Methods: In this modelling study, we assessed the probability of elimination, time to elimination, and percentage of cases averted with OCV campaign scenarios in Haiti through simulations from four modelling teams. For a 10-year period from January 19, 2019, to Jan 13, 2029, we compared a no vaccination scenario with five OCV campaign scenarios that differed in geographical scope, coverage, and rollout duration. Teams used weekly department-level reports of suspected cholera cases from the Haiti Ministry of Public Health and Population to calibrate the models and used common vaccine-related assumptions, but other model features were determined independently. Findings: Among campaigns with the same vaccination coverage (70% fully vaccinated), the median probability of elimination after 5 years was 0–18% for no vaccination, 0–33% for 2-year campaigns focused in the two departments with the highest historical incidence, 0–72% for three-department campaigns, and 35–100% for nationwide campaigns. Two-department campaigns averted a median of 12–58% of infections, three-department campaigns averted 29–80% of infections, and national campaigns averted 58–95% of infections. Extending the national campaign to a 5-year rollout (compared to a 2-year rollout), reduced the probability of elimination to 0–95% and the proportion of cases averted to 37–86%. Interpretation: Models suggest that the probability of achieving zero transmission of Vibrio cholerae in Haiti with current methods of control is low, and that bolder action is needed to promote elimination of cholera from the region. Large-scale cholera vaccination campaigns in Haiti would offer the opportunity to synchronise nationwide immunity, providing near-term population protection while improvements to water and sanitation promote long-term cholera elimination. Funding: Bill & Melinda Gates Foundation, Global Good Fund, Institute for Disease Modeling, Swiss National Science Foundation, and US National Institutes of Health

Improving gene set analysis of microarray data by SAM-GS

<p>Abstract</p> <p>Background</p> <p><it>Gene-set </it>analysis evaluates the expression of biological pathways, or <it>a priori </it>defined gene sets, rather than that of individual genes, in association with a binary phenotype, and is of great biologic interest in many DNA microarray studies. Gene Set Enrichment Analysis (GSEA) has been applied widely as a tool for gene-set analyses. We describe here some critical problems with GSEA and propose an alternative method by extending the individual-gene analysis method, Significance Analysis of Microarray (SAM), to gene-set analyses (SAM-GS).</p> <p>Results</p> <p>Using a mouse microarray dataset with simulated gene sets, we illustrate that GSEA gives statistical significance to gene sets that have no gene associated with the phenotype (null gene sets), and has very low power to detect gene sets in which half the genes are moderately or strongly associated with the phenotype (truly-associated gene sets). SAM-GS, on the other hand, performs very well. The two methods are also compared in the analyses of three real microarray datasets and relevant pathways, the diverging results of which clearly show advantages of SAM-GS over GSEA, both statistically and biologically. In a microarray study for identifying biological pathways whose gene expressions are associated with <it>p53 </it>mutation in cancer cell lines, we found biologically relevant performance differences between the two methods. Specifically, there are 31 additional pathways identified as significant by SAM-GS over GSEA, that are associated with the presence vs. absence of <it>p53</it>. Of the 31 gene sets, 11 actually involve <it>p53 </it>directly as a member. A further 6 gene sets directly involve the extrinsic and intrinsic apoptosis pathways, 3 involve the cell-cycle machinery, and 3 involve cytokines and/or JAK/STAT signaling. Each of these 12 gene sets, then, is in a direct, well-established relationship with aspects of <it>p53 </it>signaling. Of the remaining 8 gene sets, 6 have plausible, if less well established, links with <it>p53</it>.</p> <p>Conclusion</p> <p>We conclude that GSEA has important limitations as a gene-set analysis approach for microarray experiments for identifying biological pathways associated with a binary phenotype. As an alternative statistically-sound method, we propose SAM-GS. A free Excel Add-In for performing SAM-GS is available for public use.</p