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

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

The Effect of Cortex/Medulla Proportions on Molecular Diagnoses in Kidney Transplant Biopsies: Rejection and Injury Can Be Assessed in Medulla

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137720/1/ajt14233_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137720/2/ajt14233.pd

What Is the Best Way to Identify Malignant Transformation Within Pancreatic IPMN: A Systematic Review and Meta-Analyses

OBJECTIVES: Pancreatic intraductal papillary mucinous neoplasias (IPMNs) represent 25% of all cystic neoplasms and are precursor lesions for pancreatic ductal adenocarcinoma. This study aims to identify the best imaging modality for detecting malignant transformation in IPMN, the sensitivity and specificity of risk features on imaging, and the usefulness of tumor markers in serum and cyst fluid to predict malignancy in IPMN. METHODS: Databases were searched from November 2006 to March 2014. Pooled sensitivity and specificity of diagnostic techniques/imaging features of suspected malignancy in IPMN using a hierarchical summary receiver operator characteristic (HSROC) approach were performed. RESULTS: A total of 467 eligible studies were identified, of which 51 studies met the inclusion criteria and 37 of these were incorporated into meta-analyses. The pooled sensitivity and specificity for risk features predictive of malignancy on computed tomography/magnetic resonance imaging were 0.809 and 0.762 respectively, and on positron emission tomography were 0.968 and 0.911. Mural nodule, cyst size, and main pancreatic duct dilation found on imaging had pooled sensitivity for prediction of malignancy of 0.690, 0.682, and 0.614, respectively, and specificity of 0.798, 0.574, and 0.687. Raised serum carbohydrate antigen 19-9 (CA19-9) levels yielded sensitivity of 0.380 and specificity of 0903. Combining parameters yielded a sensitivity of 0.743 and specificity of 0.906. CONCLUSIONS: PET holds the most promise in identifying malignant transformation within an IPMN. Combining parameters increases sensitivity and specificity; the presence of mural nodule on imaging was the most sensitive whereas raised serum CA19-9 (>37 KU/l) was the most specific feature predictive of malignancy in IPMNs

Global analysis of the controls on seawater dimethylsulfide spatial variability

Dimethylsulfide (DMS) emitted from the ocean makes a significant global contribution to natural marine aerosol and cloud condensation nuclei, and therefore our planet&rsquo;s climate. Oceanic DMS concentrations show large spatiotemporal variability, but observations are sparse, so products describing global DMS distribution rely on interpolation or modelling. Understanding the mechanisms driving DMS variability, especially at local scales, is required to reduce uncertainty in large scale DMS estimates. We present a study of mesoscale and sub-mesoscale (&lt;100 km) seawater DMS variability that takes advantage of the recent expansion in high frequency seawater DMS observations and uses all available data to investigate the typical distances over which DMS varies in all major ocean basins. These DMS spatial variability lengthscales (VLS) are uncorrelated with DMS concentrations. DMS concentrations and VLS can therefore be used separately to help identify mechanisms underpinning DMS variability. When data are grouped by sampling campaigns, almost 80 % of the DMS VLS can be explained using the VLS of sea surface height anomalies, density, and chlorophyll-a. Our global analysis suggests that both physical and biogeochemical processes play an equally important role in controlling DMS variability, in contrast with previous results based on data from the low&ndash;mid latitudes. The explanatory power of sea surface height anomalies indicates the importance of mesoscale eddies in driving DMS variability, previously unrecognised at a global scale and in agreement with recent regional studies. DMS VLS differs regionally, including surprisingly high frequency variability in low latitude waters. Our results independently confirm that relationships used in the literature to parameterise DMS at large scales appear to be considering the right variables. However, contrasts in regional DMS VLS highlight that important driving mechanisms remain elusive. The role of sub-mesoscale features should be resolved or accounted for in DMS process models and parameterisations. Future attempts to map DMS distributions should consider the length scale of variability.</p

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

FluTE, a Publicly Available Stochastic Influenza Epidemic Simulation Model

Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them. To help prepare for future influenza seasonal epidemics or pandemics, we developed a new stochastic model of the spread of influenza across a large population. Individuals in this model have realistic social contact networks, and transmission and infections are based on the current state of knowledge of the natural history of influenza. The model has been calibrated so that outcomes are consistent with the 1957/1958 Asian A(H2N2) and 2009 pandemic A(H1N1) influenza viruses. We present examples of how this model can be used to study the dynamics of influenza epidemics in the United States and simulate how to mitigate or delay them using pharmaceutical interventions and social distancing measures. Computer simulation models play an essential role in informing public policy and evaluating pandemic preparedness plans. We have made the source code of this model publicly available to encourage its use and further development

A missing dimension in measures of vaccination impacts

Immunological protection, acquired from either natural infection or vaccination, varies among hosts, reflecting underlying biological variation and affecting population-level protection. Owing to the nature of resistance mechanisms, distributions of susceptibility and protection entangle with pathogen dose in a way that can be decoupled by adequately representing the dose dimension. Any infectious processes must depend in some fashion on dose, and empirical evidence exists for an effect of exposure dose on the probability of transmission to mumps-vaccinated hosts [1], the case-fatality ratio of measles [2], and the probability of infection and, given infection, of symptoms in cholera [3]. Extreme distributions of vaccine protection have been termed leaky (partially protects all hosts) and all-or-nothing (totally protects a proportion of hosts) [4]. These distributions can be distinguished in vaccine field trials from the time dependence of infections [5]. Frailty mixing models have also been proposed to estimate the distribution of protection from time to event data [6], [7], although the results are not comparable across regions unless there is explicit control for baseline transmission [8]. Distributions of host susceptibility and acquired protection can be estimated from dose-response data generated under controlled experimental conditions [9]–[11] and natural settings [12], [13]. These distributions can guide research on mechanisms of protection, as well as enable model validity across the entire range of transmission intensities. We argue for a shift to a dose-dimension paradigm in infectious disease science and community health

Evidence for a multi-species coccolith volume change over the past two centuries: understanding a potential ocean acidification response

Major questions surround the species-specific nature of coccolithophore calcification in response to rising atmospheric CO2 levels. Here we present CaCO3 particle volume distribution data from the coccolith size-fraction of a rapidly accumulating North Atlantic sediment core. Without direct volume measurements on coccoliths produced by individual coccolithophore species, and knowledge of organic, as well as inorganic carbon production, it is not possible to state conclusively the coccolithophore calcification change at this site. However, by analysing the size distribution of CaCO3 particles in the less than 10 μm sediment fraction, we demonstrate a changing particle volume since the late 20th Century consistent with an increase in the mass of coccoliths produced by the larger coccolithophore species, and potentially a decrease in mass of coccoliths produced by the smaller species, present at this location. This finding has significant implications for the realistic representation of an assemblage-wide coccolithophore CO2-calcification response in numerical models