PubMed · 13717881
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W IRMER, G ROTTHOFF. 1961. [Aortic ring anomalies].. https://pubmed.ncbi.nlm.nih.gov/13717881/
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Our previous study demonstrated that TGF-beta1 could induce the differentiation of vascular adventitial fibroblasts (AFs) to myofibroblasts (MFs). The aim of this study was to identify the genes which might be responsible for the cell phenotypic change using genechips. Cultured rat AFs were treated with TGF-beta1 (10 ng/ml) for 0 min, 5 min, 15 min, 2 h, 12 h and 24 h, respectively. Then the cells were gathered to prepare total RNA. We examined TGF-beta1-induced gene expression profiling using Affymetrix oligonucleotide microarrays and analyzed data by GCOS1.2 software. Moreover, expressional similarity was measured by hierarchical clustering. Some of genechip results were confirmed by real-time quantitative RT-PCR. Microarray analysis identified 2121 genes with a 2-fold change or above after TGF-beta1 stimulation. 1318 genes showed a greater than 2-fold increase and 761 genes were reduced 2 folds or more at mRNA levels, whereas a small portion of the total regulated genes (42 genes) displayed dynamically up- and down-regulated pattern. Genes were further segregated for early (peak at 5 min, 15 min and/or 2 h), late (peak at 12 h and/or 24 h), and sustained (2-fold change or above at five time points) temporal response groups according to the time of their peak expression level. Among 1318 up-regulated genes, 333 genes (25.3%) responded rapidly to TGF-beta1 and 159 genes (12.1%) responded in a sustained manner. Most genes (826, 62.6%) were regulated at 12 h or later. For the 761 down-regulated genes, numbers of early and late responsive genes were 335 (44%) and 267 (36.1%), respectively. There were also 159 genes, 19.9% of total down-regulated genes, decreased at five time points treated by TGF-beta1. The results suggested that the gene expressions of secreted phosphoprotein 1 (APP1) and Rho-associated coiled-coil forming kinase 2 (ROCK2) had the same trends as alpha-smooth muscle-actin, a marker of MF differentiation. In addition, the gene expression of potassium voltage-gated channel, Shal-related family and member 2 (KCND2) was up-regulated. Furthermore, it was found that endothelin 1 (EDN1), some complement components, NADPH oxidase 4 (NOX4) and NAD(P)H dehydrogenase, quinone 1 (NQO1) might be involved in MF differentiation. Using microarrary technique, we confirmed some genes that have been identified by other techniques were implicated in MF differentiation and observed new genes involved in this process. Our results suggest that gene expression profiling study is helpful in identifying genes and pathways potentially involved in cell differentiation.
Numerical simulations, which are based on reliable biomechanical models of blood vessels, can help to get a better understanding of cardiovascular diseases such as atherosclerosis, and can be used to develop optimal medical treatment strategies.The adventitia is the outer most layer of blood vessels and its mechanical properties are essentially determined by the three-dimensional, structural arrangement of collagen fibre bundles embedded in the tissue. Global information such as the orientation statistics of the fibre bundles as well as detailed information as the crimp of the single fibres within the bundles is of particular interest in biomechanical modeling.In order to obtain a sufficiently large amount of data for biomechanical modeling, a fully automatic method for the structural analysis of the soft tissue is required. In this contribution we present methods based on computer vision to fulfill this task. We start by discussing proper tissue preparation and imaging techniques that have to be used to obtain data, which reliably represents the real three-dimensional tissue structure. The next step is concerned with algorithms that robustly segment the collagen fibre bundles and cope with various kinds of artifacts. Novel segmentation techniques for robust segmentation of individual fibril bundles and methods for estimation of their parameters, such as location, shape, mean fibril orientation, crimp of fibrils, etc, is discussed. The proposed algorithms are based on novel perceptual grouping methods operating on the extracted orientation data of fibrils.Finally, we demonstrate the results obtained by our fully automatic method on real data. In addition, for a more quantitative assessment, we introduce a generative structural model that enables the synthesis of three-dimensional fibre bundles with well-defined characteristics.
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