The Experts below are selected from a list of 201 Experts worldwide ranked by ideXlab platform
Roger C Haut - One of the best experts on this subject based on the ideXlab platform.
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the extent of Matrix damage and chondrocyte death in mechanically traumatized articular cartilage explants depends on rate of Loading
Journal of Orthopaedic Research, 2001Co-Authors: Benjamin J Ewers, D Dvoracekdriksna, M W Orth, Roger C HautAbstract:Abstract Mechanical loads can lead to Matrix damage and chondrocyte death in articular cartilage. This damage has been implicated in the pathogenesis of secondary osteoarthritis. Studies on cartilage explants with the attachment of underlying bone at high rates of Loading have documented cell death adjacent to surface lesions. On the other hand, studies involving explants removed from bone at low rates of Loading suggest no clear spatial association between cell death and Matrix damage. The current study hypothesized that the observed differences in the distribution of cell death in these studies are attributed to the rate of Loading. Ninety bovine cartilage explants were cultured for two days. Sixty explants were loaded in unconfined compression to 40 MPa in either a fast rate of Loading experiment (∼900 MPa/s) or a low rate of Loading experiment (40 MPa/s). The remaining 30 explants served as a control population. All explants were cultured for four days after Loading. Matrix damage was assessed by measuring the total length and average depth of surface lesions and the release of glycosaminoglycans to the culture media. Explants were sectioned and stained with calcein and ethidium bromide homodimer to document the number of live and dead cells. Greater Matrix damage was documented in explants subjected to a high rate of Loading, compared to explants exposed to a low rate of Loading. The high rate of Loading experiments resulted in cell death adjacent to fissures, whereas more dead cells were observed in the low rate of Loading experiments and a more diffuse distribution of dead cells was observed away from the fissures. In conclusion, this study indicated that the rate of Loading can significantly affect the degree of Matrix damage, the distribution of dead cells, and the amount of cell death in unconfined compression experiments on explants of articular cartilage.
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the extent of Matrix damage and chondrocyte death in mechanically traumatized articular cartilage explants depends on rate of Loading
Journal of Orthopaedic Research, 2001Co-Authors: Benjamin J Ewers, D Dvoracekdriksna, M W Orth, Roger C HautAbstract:Mechanical loads can lead to Matrix damage and chondrocyte death in articular cartilage. This damage has been implicated in the pathogenesis of secondary osteoarthritis. Studies on cartilage explants with the attachment of underlying bone at high rates of Loading have documented cell death adjacent to surface lesions. On the other hand, studies involving explants removed from bone at low rates of Loading suggest no clear spatial association between cell death and Matrix damage. The current study hypothesized that the observed differences in the distribution of cell death in these studies are attributed to the rate of Loading. Ninety bovine cartilage explants were cultured for two days. Sixty explants were loaded in unconfined compression to 40 MPa in either a fast rate of Loading experiment (approximately 900 MPa/s) or a low rate of Loading experiment (40 MPa/s). The remaining 30 explants served as a control population. All explants were cultured for four days after Loading. Matrix damage was assessed by measuring the total length and average depth of surface lesions and the release of glycosaminoglycans to the culture media. Explants were sectioned and stained with calcein and ethidium bromide homodimer to document the number of live and dead cells. Greater Matrix damage was documented in explants subjected to a high rate of Loading, compared to explants exposed to a low rate of Loading. The high rate of Loading experiments resulted in cell death adjacent to fissures, whereas more dead cells were observed in the low rate of Loading experiments and a more diffuse distribution of dead cells was observed away from the fissures. In conclusion, this study indicated that the rate of Loading can significantly affect the degree of Matrix damage, the distribution of dead cells, and the amount of cell death in unconfined compression experiments on explants of articular cartilage.
Benjamin J Ewers - One of the best experts on this subject based on the ideXlab platform.
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the extent of Matrix damage and chondrocyte death in mechanically traumatized articular cartilage explants depends on rate of Loading
Journal of Orthopaedic Research, 2001Co-Authors: Benjamin J Ewers, D Dvoracekdriksna, M W Orth, Roger C HautAbstract:Abstract Mechanical loads can lead to Matrix damage and chondrocyte death in articular cartilage. This damage has been implicated in the pathogenesis of secondary osteoarthritis. Studies on cartilage explants with the attachment of underlying bone at high rates of Loading have documented cell death adjacent to surface lesions. On the other hand, studies involving explants removed from bone at low rates of Loading suggest no clear spatial association between cell death and Matrix damage. The current study hypothesized that the observed differences in the distribution of cell death in these studies are attributed to the rate of Loading. Ninety bovine cartilage explants were cultured for two days. Sixty explants were loaded in unconfined compression to 40 MPa in either a fast rate of Loading experiment (∼900 MPa/s) or a low rate of Loading experiment (40 MPa/s). The remaining 30 explants served as a control population. All explants were cultured for four days after Loading. Matrix damage was assessed by measuring the total length and average depth of surface lesions and the release of glycosaminoglycans to the culture media. Explants were sectioned and stained with calcein and ethidium bromide homodimer to document the number of live and dead cells. Greater Matrix damage was documented in explants subjected to a high rate of Loading, compared to explants exposed to a low rate of Loading. The high rate of Loading experiments resulted in cell death adjacent to fissures, whereas more dead cells were observed in the low rate of Loading experiments and a more diffuse distribution of dead cells was observed away from the fissures. In conclusion, this study indicated that the rate of Loading can significantly affect the degree of Matrix damage, the distribution of dead cells, and the amount of cell death in unconfined compression experiments on explants of articular cartilage.
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the extent of Matrix damage and chondrocyte death in mechanically traumatized articular cartilage explants depends on rate of Loading
Journal of Orthopaedic Research, 2001Co-Authors: Benjamin J Ewers, D Dvoracekdriksna, M W Orth, Roger C HautAbstract:Mechanical loads can lead to Matrix damage and chondrocyte death in articular cartilage. This damage has been implicated in the pathogenesis of secondary osteoarthritis. Studies on cartilage explants with the attachment of underlying bone at high rates of Loading have documented cell death adjacent to surface lesions. On the other hand, studies involving explants removed from bone at low rates of Loading suggest no clear spatial association between cell death and Matrix damage. The current study hypothesized that the observed differences in the distribution of cell death in these studies are attributed to the rate of Loading. Ninety bovine cartilage explants were cultured for two days. Sixty explants were loaded in unconfined compression to 40 MPa in either a fast rate of Loading experiment (approximately 900 MPa/s) or a low rate of Loading experiment (40 MPa/s). The remaining 30 explants served as a control population. All explants were cultured for four days after Loading. Matrix damage was assessed by measuring the total length and average depth of surface lesions and the release of glycosaminoglycans to the culture media. Explants were sectioned and stained with calcein and ethidium bromide homodimer to document the number of live and dead cells. Greater Matrix damage was documented in explants subjected to a high rate of Loading, compared to explants exposed to a low rate of Loading. The high rate of Loading experiments resulted in cell death adjacent to fissures, whereas more dead cells were observed in the low rate of Loading experiments and a more diffuse distribution of dead cells was observed away from the fissures. In conclusion, this study indicated that the rate of Loading can significantly affect the degree of Matrix damage, the distribution of dead cells, and the amount of cell death in unconfined compression experiments on explants of articular cartilage.
D Dvoracekdriksna - One of the best experts on this subject based on the ideXlab platform.
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the extent of Matrix damage and chondrocyte death in mechanically traumatized articular cartilage explants depends on rate of Loading
Journal of Orthopaedic Research, 2001Co-Authors: Benjamin J Ewers, D Dvoracekdriksna, M W Orth, Roger C HautAbstract:Abstract Mechanical loads can lead to Matrix damage and chondrocyte death in articular cartilage. This damage has been implicated in the pathogenesis of secondary osteoarthritis. Studies on cartilage explants with the attachment of underlying bone at high rates of Loading have documented cell death adjacent to surface lesions. On the other hand, studies involving explants removed from bone at low rates of Loading suggest no clear spatial association between cell death and Matrix damage. The current study hypothesized that the observed differences in the distribution of cell death in these studies are attributed to the rate of Loading. Ninety bovine cartilage explants were cultured for two days. Sixty explants were loaded in unconfined compression to 40 MPa in either a fast rate of Loading experiment (∼900 MPa/s) or a low rate of Loading experiment (40 MPa/s). The remaining 30 explants served as a control population. All explants were cultured for four days after Loading. Matrix damage was assessed by measuring the total length and average depth of surface lesions and the release of glycosaminoglycans to the culture media. Explants were sectioned and stained with calcein and ethidium bromide homodimer to document the number of live and dead cells. Greater Matrix damage was documented in explants subjected to a high rate of Loading, compared to explants exposed to a low rate of Loading. The high rate of Loading experiments resulted in cell death adjacent to fissures, whereas more dead cells were observed in the low rate of Loading experiments and a more diffuse distribution of dead cells was observed away from the fissures. In conclusion, this study indicated that the rate of Loading can significantly affect the degree of Matrix damage, the distribution of dead cells, and the amount of cell death in unconfined compression experiments on explants of articular cartilage.
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the extent of Matrix damage and chondrocyte death in mechanically traumatized articular cartilage explants depends on rate of Loading
Journal of Orthopaedic Research, 2001Co-Authors: Benjamin J Ewers, D Dvoracekdriksna, M W Orth, Roger C HautAbstract:Mechanical loads can lead to Matrix damage and chondrocyte death in articular cartilage. This damage has been implicated in the pathogenesis of secondary osteoarthritis. Studies on cartilage explants with the attachment of underlying bone at high rates of Loading have documented cell death adjacent to surface lesions. On the other hand, studies involving explants removed from bone at low rates of Loading suggest no clear spatial association between cell death and Matrix damage. The current study hypothesized that the observed differences in the distribution of cell death in these studies are attributed to the rate of Loading. Ninety bovine cartilage explants were cultured for two days. Sixty explants were loaded in unconfined compression to 40 MPa in either a fast rate of Loading experiment (approximately 900 MPa/s) or a low rate of Loading experiment (40 MPa/s). The remaining 30 explants served as a control population. All explants were cultured for four days after Loading. Matrix damage was assessed by measuring the total length and average depth of surface lesions and the release of glycosaminoglycans to the culture media. Explants were sectioned and stained with calcein and ethidium bromide homodimer to document the number of live and dead cells. Greater Matrix damage was documented in explants subjected to a high rate of Loading, compared to explants exposed to a low rate of Loading. The high rate of Loading experiments resulted in cell death adjacent to fissures, whereas more dead cells were observed in the low rate of Loading experiments and a more diffuse distribution of dead cells was observed away from the fissures. In conclusion, this study indicated that the rate of Loading can significantly affect the degree of Matrix damage, the distribution of dead cells, and the amount of cell death in unconfined compression experiments on explants of articular cartilage.
M W Orth - One of the best experts on this subject based on the ideXlab platform.
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the extent of Matrix damage and chondrocyte death in mechanically traumatized articular cartilage explants depends on rate of Loading
Journal of Orthopaedic Research, 2001Co-Authors: Benjamin J Ewers, D Dvoracekdriksna, M W Orth, Roger C HautAbstract:Abstract Mechanical loads can lead to Matrix damage and chondrocyte death in articular cartilage. This damage has been implicated in the pathogenesis of secondary osteoarthritis. Studies on cartilage explants with the attachment of underlying bone at high rates of Loading have documented cell death adjacent to surface lesions. On the other hand, studies involving explants removed from bone at low rates of Loading suggest no clear spatial association between cell death and Matrix damage. The current study hypothesized that the observed differences in the distribution of cell death in these studies are attributed to the rate of Loading. Ninety bovine cartilage explants were cultured for two days. Sixty explants were loaded in unconfined compression to 40 MPa in either a fast rate of Loading experiment (∼900 MPa/s) or a low rate of Loading experiment (40 MPa/s). The remaining 30 explants served as a control population. All explants were cultured for four days after Loading. Matrix damage was assessed by measuring the total length and average depth of surface lesions and the release of glycosaminoglycans to the culture media. Explants were sectioned and stained with calcein and ethidium bromide homodimer to document the number of live and dead cells. Greater Matrix damage was documented in explants subjected to a high rate of Loading, compared to explants exposed to a low rate of Loading. The high rate of Loading experiments resulted in cell death adjacent to fissures, whereas more dead cells were observed in the low rate of Loading experiments and a more diffuse distribution of dead cells was observed away from the fissures. In conclusion, this study indicated that the rate of Loading can significantly affect the degree of Matrix damage, the distribution of dead cells, and the amount of cell death in unconfined compression experiments on explants of articular cartilage.
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the extent of Matrix damage and chondrocyte death in mechanically traumatized articular cartilage explants depends on rate of Loading
Journal of Orthopaedic Research, 2001Co-Authors: Benjamin J Ewers, D Dvoracekdriksna, M W Orth, Roger C HautAbstract:Mechanical loads can lead to Matrix damage and chondrocyte death in articular cartilage. This damage has been implicated in the pathogenesis of secondary osteoarthritis. Studies on cartilage explants with the attachment of underlying bone at high rates of Loading have documented cell death adjacent to surface lesions. On the other hand, studies involving explants removed from bone at low rates of Loading suggest no clear spatial association between cell death and Matrix damage. The current study hypothesized that the observed differences in the distribution of cell death in these studies are attributed to the rate of Loading. Ninety bovine cartilage explants were cultured for two days. Sixty explants were loaded in unconfined compression to 40 MPa in either a fast rate of Loading experiment (approximately 900 MPa/s) or a low rate of Loading experiment (40 MPa/s). The remaining 30 explants served as a control population. All explants were cultured for four days after Loading. Matrix damage was assessed by measuring the total length and average depth of surface lesions and the release of glycosaminoglycans to the culture media. Explants were sectioned and stained with calcein and ethidium bromide homodimer to document the number of live and dead cells. Greater Matrix damage was documented in explants subjected to a high rate of Loading, compared to explants exposed to a low rate of Loading. The high rate of Loading experiments resulted in cell death adjacent to fissures, whereas more dead cells were observed in the low rate of Loading experiments and a more diffuse distribution of dead cells was observed away from the fissures. In conclusion, this study indicated that the rate of Loading can significantly affect the degree of Matrix damage, the distribution of dead cells, and the amount of cell death in unconfined compression experiments on explants of articular cartilage.
Barbara E Engelhardt - One of the best experts on this subject based on the ideXlab platform.
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bayesian group factor analysis with structured sparsity
Journal of Machine Learning Research, 2016Co-Authors: Shiwen Zhao, Chuan Gao, Sayan Mukherjee, Barbara E EngelhardtAbstract:Latent factor models are the canonical statistical tool for exploratory analyses of low-dimensional linear structure for a Matrix of p features across n samples. We develop a structured Bayesian group factor analysis model that extends the factor model to multiple coupled observation matrices; in the case of two observations, this reduces to a Bayesian model of canonical correlation analysis. Here, we carefully define a structured Bayesian prior that encourages both element-wise and column-wise shrinkage and leads to desirable behavior on high-dimensional data. In particular, our model puts a structured prior on the joint factor Loading Matrix, regularizing at three levels, which enables element-wise sparsity and unsupervised recovery of latent factors corresponding to structured variance across arbitrary subsets of the observations. In addition, our structured prior allows for both dense and sparse latent factors so that covariation among either all features or only a subset of features can be recovered. We use fast parameter-expanded expectation-maximization for parameter estimation in this model. We validate our method on simulated data with substantial structure. We show results of our method applied to three high-dimensional data sets, comparing results against a number of state-of-the-art approaches. These results illustrate useful properties of our model, including i) recovering sparse signal in the presence of dense effects; ii) the ability to scale naturally to large numbers of observations; iii) flexible observation- and factor-specific regularization to recover factors with a wide variety of sparsity levels and percentage of variance explained; and iv) tractable inference that scales to modern genomic and text data sizes.
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bayesian group latent factor analysis with structured sparsity
arXiv: Methodology, 2014Co-Authors: Shiwen Zhao, Chuan Gao, Sayan Mukherjee, Barbara E EngelhardtAbstract:Latent factor models are the canonical statistical tool for exploratory analyses of low-dimensional linear structure for an observation Matrix with p features across n samples. We develop a structured Bayesian group factor analysis model that extends the factor model to multiple coupled observation matrices; in the case of two observations, this reduces to a Bayesian model of canonical correlation analysis. The main contribution of this work is to carefully define a structured Bayesian prior that encourages both element-wise and column-wise shrinkage and leads to desirable behavior on high-dimensional data. In particular, our model puts a structured prior on the joint factor Loading Matrix, regularizing at three levels, which enables element-wise sparsity and unsupervised recovery of latent factors corresponding to structured variance across arbitrary subsets of the observations. In addition, our structured prior allows for both dense and sparse latent factors so that covariation among either all features or only a subset of features can both be recovered. We use fast parameter-expanded expectation-maximization for parameter estimation in this model. We validate our method on both simulated data with substantial structure and real data, comparing against a number of state-of-the-art approaches. These results illustrate useful properties of our model, including i) recovering sparse signal in the presence of dense effects; ii) the ability to scale naturally to large numbers of observations; iii) flexible observation- and factor-specific regularization to recover factors with a wide variety of sparsity levels and percentage of variance explained; and iv) tractable inference that scales to modern genomic and document data sizes.
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a latent factor model with a mixture of sparse and dense factors to model gene expression data with confounding effects
arXiv: Applications, 2013Co-Authors: Chuan Gao, Christopher D Brown, Barbara E EngelhardtAbstract:One important problem in genome science is to determine sets of co-regulated genes based on measurements of gene expression levels across samples, where the quantification of expression levels includes substantial technical and biological noise. To address this problem, we developed a Bayesian sparse latent factor model that uses a three parameter beta prior to flexibly model shrinkage in the Loading Matrix. By applying three layers of shrinkage to the Loading Matrix (global, factor-specific, and element-wise), this model has non-parametric properties in that it estimates the appropriate number of factors from the data. We added a two-component mixture to model each factor Loading as being generated from either a sparse or a dense mixture component; this allows dense factors that capture confounding noise, and sparse factors that capture local gene interactions. We developed two statistics to quantify the stability of the recovered matrices for both sparse and dense matrices. We tested our model on simulated data and found that we successfully recovered the true latent structure as compared to related models. We applied our model to a large gene expression study and found that we recovered known covariates and small groups of co-regulated genes. We validated these gene subsets by testing for associations between genotype data and these latent factors, and we found a substantial number of biologically important genetic regulators for the recovered gene subsets.