Calbindin-D28k gene expression in the developing mouse kidney

Calbindin-D28k gene expression in the developing mouse kidney. Calbindin-D28k appears in the metanephric kidney during embryogenesis. We studied the temporal appearance and spatial distribution of calbindin-D28k mRNA in the developing kidneys of 12-day fetal through 21-day postnatal mice by in situ hybridization. 35S-UTP-labeled antisense (cRNA) probe to calbindin-D28k mRNA hybridized to the ureteric buds of 12-day embryos, whereas adjacent metanephrogenic tissue was unlabeled. By embryonic day 13, Y-shaped bodies of “advancing” ureteric buds were labeled intensely. In 16-day embryos, ampullae of ureteric buds were located immediately beneath the renal capsule and labeled strongly, in contrast to metanephric tubules and S-shaped bodies. The former were unlabeled and the latter were labeled only at points of contact with the ampullae. Subsequently, the ampullae of the metanephric ureteric buds hybridized with the cRNA probe, and from the 18th embryonic to the 21st postnatal day, this labeling was intense. The cRNA probe did not hybridize with the renal vesicles, proximal tubules, or tubular segments of Henle's loop derived from nephrogenic blastema, but it did label distal nephron segments. By the 21st postnatal day, collecting ducts and ureter no longer were labeled. In conclusion, calbindin-D28k mRNA is present in the developing mouse kidney, and its distribution during nephrogenesis is identical to that of calbindin-D28k per se. Collectively, these findings show that the calbindin-D28k gene is transcribed and its message is translated by the cells of the ureteric bud during the initial stage of renal morphogenesis

Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach

This paper is concerned with the modeling of infectious disease spread in a composite space-time domain under conditions of uncertainty. We focus on stochastic modeling that accounts for basic mechanisms of disease distribution and multi-sourced in situ uncertainties. Starting from the general formulation of population migration dynamics and the specification of transmission and recovery rates, the model studies the functional formulation of the evolution of the fractions of susceptible-infected-recovered individuals. The suggested approach is capable of: a) modeling population dynamics within and across localities, b) integrating the disease representation (i.e. susceptible-infected-recovered individuals) with observation time series at different geographical locations and other sources of information (e.g. hard and soft data, empirical relationships, secondary information), and c) generating predictions of disease spread and associated parameters in real time, while considering model and observation uncertainties. Key aspects of the proposed approach are illustrated by means of simulations (i.e. synthetic studies), and a real-world application using hand-foot-mouth disease (HFMD) data from China.J.M. Angulo and A.E. Madrid have been partially supported by grants MTM2009-13250 and MTM2012-32666 of SGPI, and P08-FQM-3834 of the Andalusian CICE, Spain. H-L Yu has been partially supported by a grant from National Science Council of Taiwan (NSC101-2628-E-002-017-MY3 and NSC102-2221-E-002-140-MY3). A. Kolovos was supported by SpaceTimeWorks, LLC. G. Christakos was supported by a Yongqian Chair Professorship (Zhejiang University, China)

On the Schoenberg Transformations in Data Analysis: Theory and Illustrations

The class of Schoenberg transformations, embedding Euclidean distances into higher dimensional Euclidean spaces, is presented, and derived from theorems on positive definite and conditionally negative definite matrices. Original results on the arc lengths, angles and curvature of the transformations are proposed, and visualized on artificial data sets by classical multidimensional scaling. A simple distance-based discriminant algorithm illustrates the theory, intimately connected to the Gaussian kernels of Machine Learning

Coupling models of cattle and farms with models of badgers for predicting the dynamics of bovine tuberculosis (TB)

Bovine TB is a major problem for the agricultural industry in several countries. TB can be contracted and spread by species other than cattle and this can cause a problem for disease control. In the UK and Ireland, badgers are a recognised reservoir of infection and there has been substantial discussion about potential control strategies. We present a coupling of individual based models of bovine TB in badgers and cattle, which aims to capture the key details of the natural history of the disease and of both species at approximately county scale. The model is spatially explicit it follows a very large number of cattle and badgers on a different grid size for each species and includes also winter housing. We show that the model can replicate the reported dynamics of both cattle and badger populations as well as the increasing prevalence of the disease in cattle. Parameter space used as input in simulations was swept out using Latin hypercube sampling and sensitivity analysis to model outputs was conducted using mixed effect models. By exploring a large and computationally intensive parameter space we show that of the available control strategies it is the frequency of TB testing and whether or not winter housing is practised that have the most significant effects on the number of infected cattle, with the effect of winter housing becoming stronger as farm size increases. Whether badgers were culled or not explained about 5%, while the accuracy of the test employed to detect infected cattle explained less than 3% of the variance in the number of infected cattle

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

This study was supported by the NSF China Programs (Grant No. 31300539 and 31570629) and the Public Welfare Technology Application Research Program of Zhejiang province (Grant No. 2015C31004).Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.Yeshttp://www.plosone.org/static/editorial#pee

Characterization of the Autocrine/Paracrine Function of Vitamin D in Human Gingival Fibroblasts and Periodontal Ligament Cells

Background: We previously demonstrated that 25-hydroxyvitamin D-3, the precursor of 1 alpha,25-dihydroxyvitamin D-3, is abundant around periodontal soft tissues. Here we investigate whether 25-hydroxyvitamin D-3 is converted to 1 alpha,25-dihydroxyvitamin D-3 in periodontal soft tissue cells and explore the possibility of an autocrine/paracrine function of 1 alpha,25-dihydroxyvitamin D-3 in periodontal soft tissue cells. Methodology/Principal Findings: We established primary cultures of human gingival fibroblasts and human periodontal ligament cells from 5 individual donors. We demonstrated that 1 alpha-hydroxylase was expressed in human gingival fibroblasts and periodontal ligament cells, as was cubilin. After incubation with the 1 alpha-hydroxylase substrate 25-hydroxyvitamin D-3, human gingival fibroblasts and periodontal ligament cells generated detectable 1 alpha,25-dihydroxyvitamin D-3 that resulted in an up-regulation of CYP24A1 and RANKL mRNA. A specific knockdown of 1 alpha-hydroxylase in human gingival fibroblasts and periodontal ligament cells using siRNA resulted in a significant reduction in both 1 alpha, 25-dihydroxyvitamin D-3 production and mRNA expression of CYP24A1 and RANKL. The classical renal regulators of 1 alpha-hydroxylase (parathyroid hormone, calcium and 1 alpha,25-dihydroxyvitamin D-3) and Porphyromonas gingivalis lipopolysaccharide did not influence 1 alpha-hydroxylase expression significantly, however, interleukin-1 beta and sodium butyrate strongly induced 1 alpha-hydroxylase expression in human gingival fibroblasts and periodontal ligament cells. Conclusions/Significance: In this study, the expression, activity and functionality of 1 alpha-hydroxylase were detected in human gingival fibroblasts and periodontal ligament cells, raising the possibility that vitamin D acts in an autocrine/paracrine manner in these cells.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000305781700070&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Multidisciplinary SciencesSCI(E)PubMed13ARTICLE6e39878

Ethnic differences in urinary calcium and phosphate excretion between Gambian and British older adults

Summary: Ethnic differences in renal calcium and phosphate excretion exist, which may depend on differences in their dietary intakes and regulatory factors. We report highly significant differences in urinary calcium and phosphate excretion between white British and Gambian adults after statistical adjustment for mineral intakes, indicating an independent effect of ethnicity.  Introduction: Populations vary in their risk of age-related osteoporosis. There are racial or ethnic differences in the metabolism of the bone-forming minerals calcium (Ca) and phosphate (P), with a lower renal Ca and P excretion in African-Americans compared to white counterparts, even at similar intakes and rates of absorption. Also, Africans in The Gambia have a lower Ca excretion compared to white British subjects, groups known to differ in their dietary Ca intake. Here, we report on differences in urinary Ca and P excretion between Gambian and white British adults while allowing for known predictors, including dietary intakes.  Methods: Participants were healthy white British (n = 60) and Gambian (n = 61) men and women aged 60–75 years. Fasting blood and 2-h urine samples were collected. Markers of Ca and P metabolism were analysed. Dietary intake was assessed with country-specific methods.  Results: White British older adults had higher creatinine-corrected urinary Ca and P excretion (uCa/uCr, uP/uCr) and lower tubular maximum of Ca and P compared to Gambian counterparts. The predictors of urinary Ca and P differed between groups. Multiple regression analysis showed that dietary Ca and Ca/P were predictors of uCa/uCr and uP/uCr, respectively. Ethnicity remained a significant predictor of uCa/uCr and uP/uCr after adjustment for diet and other factors.  Conclusions: Gambian older adults have higher renal Ca conservation than British counterparts. Dietary mineral intakes were predictors of the differences in urinary Ca and P excretion, but ethnicity remained a highly significant predictor after statistical adjustment. This suggests that ethnicity has an independent effect on renal Ca and P handling