40 research outputs found

    Crosstalk between MLO-Y4 osteocytes and C2C12 muscle cells is mediated by the Wnt/β-catenin pathway

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    We examined the effects of osteocyte secreted factors on myogenesis and muscle function. MLO-Y4 osteocyte-like cell conditioned media (CM) (10%) increased ex vivo soleus muscle contractile force by ∼25%. MLO-Y4 and primary osteocyte CM (1-10%) stimulated myogenic differentiation of C2C12 myoblasts, but 10% osteoblast CMs did not enhance C2C12 cell differentiation. Since WNT3a and WNT1 are secreted by osteocytes, and the expression level of Wnt3a is increased in MLO-Y4 cells by fluid flow shear stress, both were compared, showing WNT3a more potent than WNT1 in inducing myogenesis. Treatment of C2C12 myoblasts with WNT3a at concentrations as low as 0.5ng/mL mirrored the effects of both primary osteocyte and MLO-Y4 CM by inducing nuclear translocation of β-catenin with myogenic differentiation, suggesting that Wnts might be potential factors secreted by osteocytes that signal to muscle cells. Knocking down Wnt3a in MLO-Y4 osteocytes inhibited the effect of CM on C2C12 myogenic differentiation. Sclerostin (100ng/mL) inhibited both the effects of MLO-Y4 CM and WNT3a on C2C12 cell differentiation. RT-PCR array results supported the activation of the Wnt/β-catenin pathway by MLO-Y4 CM and WNT3a. These results were confirmed by qPCR showing up-regulation of myogenic markers and two Wnt/β-catenin downstream genes, Numb and Flh1. We postulated that MLO-Y4 CM/WNT3a could modulate intracellular calcium homeostasis as the trigger mechanism for the enhanced myogenesis and contractile force. MLO-Y4 CM and WNT3a increased caffeine-induced Ca2+ release from the sarcoplasmic reticulum (SR) of C2C12 myotubes and the expression of genes directly associated with intracellular Ca2+ signaling and homeostasis. Together, these data show that in vitro and ex vivo, osteocytes can stimulate myogenesis and enhance muscle contractile function and suggest that Wnts could be mediators of bone to muscle signaling, likely via modulation of intracellular Ca2+ signaling and the Wnt/ β-Catenin pathway

    An Integrated Model for User Attribute Discovery: A Case Study on Political Affiliation Identification

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    Discovering user demographic attributes from social media is a problem of considerable interest. The problem setting can be generalized to include three components - users, topics and behaviors. In recent studies on this problem, however, the behavior between users and topics are not effectively incorporated. In our work, we proposed an integrated unsupervised model which takes into consideration all the three components integral to the task. Furthermore, our model incorporates collaborative filtering with probabilistic matrix factorization to solve the data sparsity problem, a computational challenge common to all such tasks. We evaluated our method on a case study of user political affiliation identification, and compared against state-of-the-art baselines. Our model achieved an accuracy of 70.1% for user party detection task. ? 2014 Springer International Publishing.EI

    The Human Phenotype Ontology project:linking molecular biology and disease through phenotype data

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    The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online

    The Human Phenotype Ontology in 2017.

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    Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology

    Vertical wind retrieved by airborne lidar and analysis of island induced gravity waves in combination with numerical models and in situ particle measurements

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    This study presents the analysis of island induced gravity waves observed by an airborne Doppler wind lidar (DWL) during SALTRACE. First, the instrumental corrections required for the retrieval of high spatial resolution vertical wind measurements from an airborne DWL are presented and the measurement accuracy estimated by means of two different methods. The estimated systematic error is below −0.05 m s−1 for the selected case of study, while the random error lies between 0.1 and 0.16 m s−1 depending on the estimation method. Then, the presented method is applied to two measurement flights during which the presence of island induced gravity waves was detected. The first case corresponds to a research flight conducted on 17 June 2013 in the Cabo Verde islands region, while the second case corresponds to a measurement flight on 26 June 2013 in the Barbados region. The presence of trapped lee waves predicted by the calculated Scorer parameter profiles was confirmed by the lidar and in situ observations. The DWL measurements are used in combination with in situ wind and particle number density measurements, large-eddy simulations (LES), and wavelet analysis to determine the main characteristics of the observed island induced trapped waves

    Investigations of boundary layer structure, cloud characteristics and vertical mixing of aerosols at Barbados with large eddy simulations

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    Large eddy simulations (LESs) are performed for the area of the Caribbean island Barbados to investigate island effects on boundary layer modification, cloud generation and vertical mixing of aerosols. Due to the presence of a topographically structured island surface in the domain center, the model setup has to be designed with open lateral boundaries. In order to generate inflow turbulence consistent with the upstream marine boundary layer forcing, we use the cell perturbation method based on finite amplitude potential temperature perturbations. In this work, this method is for the first time tested and validated for moist boundary layer simulations with open lateral boundary conditions. Observational data obtained from the SALTRACE field campaign is used for both model initialization and a comparison with Doppler wind and Raman lidar data. Several numerical sensitivity tests are carried out to demonstrate the problems related to “gray zone modeling” when using coarser spatial grid spacings beyond the inertial subrange of three-dimensional turbulence or when the turbulent marine boundary layer flow is replaced by laminar winds. Especially cloud properties in the downwind area west of Barbados are markedly affected in these kinds of simulations. Results of an additional simulation with a strong trade-wind inversion reveal its effect on cloud layer depth and location. Saharan dust layers that reach Barbados via long-range transport over the North Atlantic are included as passive tracers in the model. Effects of layer thinning, subsidence and turbulent downward transport near the layer bottom at <i>z</i> ≈ 1800 m become apparent. The exact position of these layers and strength of downward mixing is found to be mainly controlled atmospheric stability (especially inversion strength) and wind shear. Comparisons of LES model output with wind lidar data show similarities in the downwind vertical wind structure. Additionally, the model results accurately reproduce the development of the daytime convective boundary layer measured by the Raman lidar
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