5,847 research outputs found

    Recombinant Vgr-1/BMP-6-expressing tumors induce fibrosis and endochondral bone formation in vivo.

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    Members of the TGF-beta superfamily appear to modulate mesenchymal differentiation, including the processes of cartilage and bone formation. Nothing is yet known about the function of the TGF-beta-related factor vgr-1, also called bone morphogenetic protein-6 (BMP-6), and only limited studies have been conducted on the most closely related factors BMP-5, osteogenic protein-1 (OP-1) or BMP-7, and OP-2. Because vgr-1 mRNA has been localized in hypertrophic cartilage, this factor may play a vital role in endochondral bone formation. We developed antibodies to vgr-1, and documented that vgr-1 protein was expressed in hypertrophic cartilage of mice. To further characterize the role of this protein in bone differentiation, we generated CHO cells that overexpressed recombinant murine vgr-1 protein. Western blot analysis documented that recombinant vgr-1 protein was secreted into the media and was proteolytically processed to yield the mature vgr-1 molecule. To assess the biological activity of recombinant vgr-1 in vivo, we introduced the vgr-1-expressing CHO cells directly into the subcutaneous tissue of athymic nude mice. CHO-vgr-1 cells produced localized tumors, and the continuous secretion of vgr-1 resulted in tumors with a strikingly different gross and histological appearance as compared to the parental CHO cells. The tumors of control CHO cells were hemorrhagic, necrotic, and friable, whereas the CHO-vgr-1 tumors were dense, firm, and fibrotic. In contrast with control CHO tumors, the nests of CHO-vgr-1 tumor cells were surrounded by extensive connective tissue, which contained large regions of cartilage and bone. Further analysis indicated that secretion of vgr-1 from the transfected CHO tumor cells induced the surrounding host mesenchymal cells to develop along the endochondral bone pathway. These findings suggest that endochondral bone formation

    Higher resources decrease fluctuating selection during host-parasite coevolution

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    This is the final version of the article. Available from the publisher via the DOI in this record.We still know very little about how the environment influences coevolutionary dynamics. Here, we investigated both theoretically and empirically how nutrient availability affects the relative extent of escalation of resistance and infectivity (arms race dynamic; ARD) and fluctuating selection (fluctuating selection dynamic; FSD) in experimentally coevolving populations of bacteria and viruses. By comparing interactions between clones of bacteria and viruses both within- and between-time points, we show that increasing nutrient availability resulted in coevolution shifting from FSD, with fluctuations in average infectivity and resistance ranges over time, to ARD. Our model shows that range fluctuations with lower nutrient availability can be explained both by elevated costs of resistance (a direct effect of nutrient availability), and reduced benefits of resistance when population sizes of hosts and parasites are lower (an indirect effect). Nutrient availability can therefore predictably and generally affect qualitative coevolutionary dynamics by both direct and indirect (mediated through ecological feedbacks) effects on costs of resistance.This work was funded by NERC (UK). ABu was supported by the Royal Society and ABe by a the Leverhulme Trust Early Career Fellowship

    A Microservice Infrastructure for Distributed Communities of Practice

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    Non-formal learning in Communities of Practice (CoPs) makes up a significant portion of today’s knowledge gain. However, only little technological support is tailored specifically towards CoPs and their particular strengths and challenges. Even worse, CoPs often do not possess the resources to host or even develop a software ecosystem to support their activities. In this paper, we describe a distributed, microservice-based Web infrastructure for non-formal learning in CoPs. It mitigates the need for central infrastructures, coordination or facilitation and takes into account the constant change of these communities. As a real use case, we implement an inquiry-based learning application on-top of our infrastructure. Our evaluation results indicate the usefulness of this learning application, which shows promise for future work in the domain of community-hosted, microservice-based Web infrastructures for learning outside of formal settings

    Multilocus sequence typing (MLST) and Random Polymorphic DNA (RAPD) comparisons of geographic isolates of Neoparamoeba perurans, the causative agent of Amoebic Gill Disease

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    Neoparamoba perurans, is the aetiological agent of amoebic gill disease (AGD), a disease that affects farmed Atlantic salmon worldwide. Multilocus sequence typing (MLST) and Random Amplified Polymorphic DNA (RAPD) are PCR-based typing methods that allow for the highly reproducible genetic analysis of population structure within microbial species. To the best of our knowledge, this study represents the first use of these typing methods applied to N. perurans with the objective of distinguishing geographical isolates. These analyses were applied to a total of 16 isolates from Australia, Canada, Ireland, Scotland, Norway, and the USA. All the samples from Australia came from farm sites on the island state of Tasmania. Genetic polymorphism among isolates was more evident from the RAPD analysis compared to the MLST that used conserved housekeeping genes. Both techniques consistently identified that isolates of N. perurans from Tasmania, Australia were more similar to each other than to the isolates from other countries. While genetic differences were identified between geographical isolates, a BURST analysis provided no evidence of a founder genotype. This suggests that emerging outbreaks of AGD are not due to rapid translocation of this important salmonid pathogen from the same area

    The performance of robust adaptive modulation over wireless channels with non reciprocal interference

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    A closer look at chaotic advection in the stratosphere: part II: statistical diagnostics

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    Statistical diagnostics of mixing and transport are computed for a numerical model of forced shallow-water flow on the sphere and a middle-atmosphere general circulation model. In particular, particle dispersion statistics, transport fluxes, Liapunov exponents (probability density functions and ensemble averages), and tracer concentration statistics are considered. It is shown that the behavior of the diagnostics is in accord with that of kinematic chaotic advection models so long as stochasticity is sufficiently weak. Comparisons with random-strain theory are made

    Adaptation and Validation of the MapMe Body Image Scales in Spanish Parents of Schoolchildren

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    \ua9 2024 by the authors.Childhood overweight and obesity is a worldwide problem and to treat it parents’ detection has to be improved. The MapMe Body Image Scales (BIS) are a visual tool developed to improve parental perception of child weight in the United Kingdon (UK) based on British growth reference criteria. The aim of this study was to make a transcultural adaptation and validation of the MapMe BIS in Spain based on International Obesity Task Force (IOTF) cut offs A descriptive cross-sectional study was done. First, a translation and cultural adaptation was carried out. A total of 155 10–11-year-old children and their parents participated in this study. Children were measured to calculate their weight status, Body Mass Index (BMI), Body Fat Percentage (BFP) and Waist Circumference (WC), and their parents completed a purpose designed questionnaire about their perception and satisfaction of child’s body weight status using the adapted BIS. Test-retest reliability, criterion validity and concurrent validity of the adapted BIS were analyzed. This study shows that the adapted MapMe BIS has good psychometric properties and is a suitable visual scale to assess parental perception of weight status in 10 and 11-year-old children in Spain

    How and why DNA barcodes underestimate the diversity of microbial eukaryotes

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    Background: Because many picoplanktonic eukaryotic species cannot currently be maintained in culture, direct sequencing of PCR-amplified 18S ribosomal gene DNA fragments from filtered sea-water has been successfully used to investigate the astounding diversity of these organisms. The recognition of many novel planktonic organisms is thus based solely on their 18S rDNA sequence. However, a species delimited by its 18S rDNA sequence might contain many cryptic species, which are highly differentiated in their protein coding sequences. Principal Findings: Here, we investigate the issue of species identification from one gene to the whole genome sequence. Using 52 whole genome DNA sequences, we estimated the global genetic divergence in protein coding genes between organisms from different lineages and compared this to their ribosomal gene sequence divergences. We show that this relationship between proteome divergence and 18S divergence is lineage dependant. Unicellular lineages have especially low 18S divergences relative to their protein sequence divergences, suggesting that 18S ribosomal genes are too conservative to assess planktonic eukaryotic diversity. We provide an explanation for this lineage dependency, which suggests that most species with large effective population sizes will show far less divergence in 18S than protein coding sequences. Conclusions: There is therefore a trade-off between using genes that are easy to amplify in all species, but which by their nature are highly conserved and underestimate the true number of species, and using genes that give a better description of the number of species, but which are more difficult to amplify. We have shown that this trade-off differs between unicellular and multicellular organisms as a likely consequence of differences in effective population sizes. We anticipate that biodiversity of microbial eukaryotic species is underestimated and that numerous ''cryptic species'' will become discernable with the future acquisition of genomic and metagenomic sequences

    Potential of mathematical modeling in fruit quality

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    A review of mathematical modeling applied to fruit quality showed that these models ranged inresolution from simple yield equations to complex  representations of processes as respiration, photosynthesis and assimilation of nutrients. The latter models take into account complex  genotype environment interactions to estimate their effects on growth and yield. Recently, models are used to estimate seasonal changes in quality traits as fruit size, dry matter, water content and the concentration of sugars and acids, which are very important for flavor and aroma. These models have demonstrated their ability to generate relationships between physiological variables and quality attributes (allometric relations). This new kind of hybrid models has sufficient complexity to predict quality traits behavior
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