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Bone marrow and adipose tissue have provided two suitable sources of mesenchymal stem cells. Although previous studies have confirmed close similarities between bone marrow-derived stem cells (BM-MSCs) and adipose tissue-derived s...
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Bone marrow and adipose tissue have provided two suitable sources of mesenchymal stem cells. Although previous studies have confirmed close similarities between bone marrow-derived stem cells (BM-MSCs) and adipose tissue-derived stem cells (ADSCs), the molecular phenotype of ADSCs is still poorly identified. In the present study, mouse ADSCs were isolated from the inguinal fat pad of 12-14 weeks old mice. Freshly isolated and three passaged ADSCs were analyzed for the expression of OCT4, Sca-1, c-kit and CD34 by RT-PCR. Three passaged ADSCs were analyzed by flow cytometry for the presence of CD11b, CD45, CD31, CD29 and CD44. Moreover, cardiogenic, adipogenic and neurogenic differentiation of ADSCs were induced in vitro. Freshly isolated ADSCs showed the expression of OCT4, Sca-1, c-kit and CD34, and two days cultured ADSCs were positively immunostained with anti-OCT4 monoclonal antibody. After three passages, the expression of OCT4, c-kit and CD34 eliminated, while the expression of Sca-1 showed a striking enhancement. These cells were identified positive for CD29 and CD44 markers, and they showed the lack of CD45 and CD31 expression. Three passaged ADSCs were differentiated to adipocyte-, cardiomyocyte- and neuron-like cells that were identified based on the positive staining with Sudan black, anti-cardiac troponin I antibody and anti-map-2 antibody, respectively. In conclusion, adipose tissue contains a stem cell population that seems to be a good multipotential cell candidate for the future cell replacement therapy
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摘要 :
Bone marrow and adipose tissue have provided two suitable sources of mesenchymal stem cells. Although previous studies have confirmed close similarities between bone marrow-derived stem cells (BM-MSCs) and adipose tissue-derived s...
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Bone marrow and adipose tissue have provided two suitable sources of mesenchymal stem cells. Although previous studies have confirmed close similarities between bone marrow-derived stem cells (BM-MSCs) and adipose tissue-derived stem cells (ADSCs), the molecular phenotype of ADSCs is still poorly identified. In the present study, mouse ADSCs were isolated from the inguinal fat pad of 12-14 weeks old mice. Freshly isolated and three passaged ADSCs were analyzed for the expression of OCT4, Sca-1, c-kit and CD34 by RT-PCR. Three passaged ADSCs were analyzed by flow cytometry for the presence of CD11b, CD45, CD31, CD29 and CD44. Moreover, cardiogenic, adipogenic and neurogenic differentiation of ADSCs were induced in vitro. Freshly isolated ADSCs showed the expression of OCT4, Sca-1, c-kit and CD34, and two days cultured ADSCs were positively immunostained with anti-OCT4 monoclonal antibody. After three passages, the expression of OCT4, c-kit and CD34 eliminated, while the expression of Sca-1 showed a striking enhancement. These cells were identified positive for CD29 and CD44 markers, and they showed the lack of CD45 and CD31 expression. Three passaged ADSCs were differentiated to adipocyte-, cardiomyocyte- and neuron-like cells that were identified based on the positive staining with Sudan black, anti-cardiac troponin I antibody and anti-map-2 antibody, respectively. In conclusion, adipose tissue contains a stem cell population that seems to be a good multipotential cell candidate for the future cell replacement therapy
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We investigated relationship between the maturity and density of muscle cells and developed a rapid isolation method to acquire stem cells from skeletal muscle. Mononuclear cells were isolated from the lower hind-limb muscles of 7...
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We investigated relationship between the maturity and density of muscle cells and developed a rapid isolation method to acquire stem cells from skeletal muscle. Mononuclear cells were isolated from the lower hind-limb muscles of 7-d-old male Sprague-Dawley rats and separated by Percoll density gradient centrifugation. After centrifugation, the cells were layered in the interfaces between each Percoll density layer. Flow cytometry was used to investigate the Sca-1, Pax7, CD34, CD45, M-cadherin, and myosin expression of the cells in each density layer. We found that CD45-positive cells were not present in freshly isolated muscle cells. CD34-, Pax7-positive cells were mainly observed at the interface between the 15% and 25% Percoll layers and had a density of 1.0235-1.0355 g/ml. Cells positive for M-cadherin were at the 25-35% Percoll density interface and had a density of 1.0355-1.0492 g/ml. We conclude that because there appears to be a correlation between maturity and density, muscle-derived stem cells may be isolated successfully from the 15-25% Percoll interface.
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A great challenge for modern cell biology is the successful examination of the co-expression of thousands of genes under physiological or pathological conditions and how the expression patterns define the different states of a sin...
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A great challenge for modern cell biology is the successful examination of the co-expression of thousands of genes under physiological or pathological conditions and how the expression patterns define the different states of a single cell, tissue or a microorganism. Gene expression can be analyzed today on a large scale by advanced technical approaches for differential screening of proteins and mRNAs. The identification of differentially expressed mRNAs has been successfully applied to understand gene function and the underlying molecular mechanism(-s) of differentiation, development and disease state. Analysis of gene expression by the systematic mapping of thousands of proteins present in a cell or tissue can be achieved by the use of two-dimensional (2D) gel electrophoresis, quantitative computer image analysis, and protein identification techniques. In this article, we comment on some of these techniques and try to stress their advantages and drawbacks. We show how data from RNA/DNA mapping, sequence information from genome projects and protein pattern profiling can be linked with each other and annotated. These comprehensive approaches permit the study of differential gene and protein expressions in cells or tissues.
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The synthesis of facial expressions has applications in areas such as interactive games, biometrics systems, and training of people with disorders, among others. Although this is an area relatively well explored in the literature,...
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The synthesis of facial expressions has applications in areas such as interactive games, biometrics systems, and training of people with disorders, among others. Although this is an area relatively well explored in the literature, there are no recent studies proposing to systematize an overview of research in the area. This systematic review analyzes the approaches to the synthesis of facial expressions in photographs, as well as important aspects of the synthesis process, such as preprocessing techniques, databases, and evaluation metrics. Forty-eight studies from three different scientific databases were analyzed. From these studies, we established an overview of the process, including all the stages used to synthesize expressions in facial images. We also analyze important aspects involved in these stages such as methods and techniques of each stage, databases, and evaluation metrics. We observed that machine learning approaches are the most widely used to synthesize expressions. Landmark identification, deformation, mapping, fusion, and training are common tasks considered in the approaches. We also found that few studies used metrics to evaluate the results, and most studies used public databases. Although the studies analyzed generated consistent and realistic results while preserving the identity of the subject, there are still research themes to be exploited.
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This work proposes a real-time virtual human multimodal expression model. Five modalities explore the affordances of the body: deterministic, non-deterministic, gesticulation, facial, and vocal expression. Deterministic expression...
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This work proposes a real-time virtual human multimodal expression model. Five modalities explore the affordances of the body: deterministic, non-deterministic, gesticulation, facial, and vocal expression. Deterministic expression is keyframe body animation. Non-deterministic expression is robotics-based procedural body animation. Vocal expression is voice synthesis, through Festival, and parameterization, through SABLE. Facial expression is lip-synch and emotion expression through a parametric muscle-based face model. Inspired by psycholinguistics, gesticulation expression is unconventional, idiosyncratic, and unconscious hand gestures animation described as sequences of Portuguese Sign Language hand shapes, positions and orientations. Inspired by the arts, one modality goes beyond the body to explore the affordances of the environment and express emotions through camera, lights, and music. To control multimodal expression, this work proposes a high-level integrated synchronized markup language—expressive markup language. Finally, three studies, involving a total of 197 subjects, evaluated the model in storytelling contexts and produced promising results.
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Analyses of gene expression data sets for multiple indi-viduals and species promise to shed light on the mode ofevolution of gene expression. However, complementarycomplexities challenge this goal. Characterization of thegenetic v...
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Analyses of gene expression data sets for multiple indi-viduals and species promise to shed light on the mode ofevolution of gene expression. However, complementarycomplexities challenge this goal. Characterization of thegenetic variation underlying gene expression can easilybe compromised by lack of environmental control. Con-versely, the breadth of conclusions from studies ofenvironmental effects has been limited by the use ofsingle strains. Controlled studies have hinted at exten-sive gene x environment interaction. Thus, bothgenetics and environment are key components inmodels of the evolution of gene expression. We reviewthe literature on the evolution of gene expression interms of genetics (G), environmental response (E) andG x E interactions to make this conceptual point.
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The aquaporins (AQPs) are a family of homologous water channels expressed in many tissues. In this study, the expression and immunolocalization of different AQP subtypes in rat brains were investigated by RT-PCR, immunohistochemis...
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The aquaporins (AQPs) are a family of homologous water channels expressed in many tissues. In this study, the expression and immunolocalization of different AQP subtypes in rat brains were investigated by RT-PCR, immunohistochemistry and immunofluorescence. The data showed that AQP1 was expressed in the subpial processes of astrocytes, choroid plexus and ependyma. AQP3, AQP5 and AQP8 had similar distribution patterns in piriform cortex, choroid plexus, hippocampus and dorsal thalamus. AQP4 and AQP9 were widely expressed in the rat brain and distributed in the subpial processes of astrocytes, ependyma, dorsal thalamus, hippocampus, white matter, suprachiasmatic nucleus (SCN) and supraoptic nucleus. AQP3, AQP4, AQP5, AQP8 and AQP9 were found in the Bergmann glial cells of cerebellum, cochlear nucleus and trapezoid nuclei. The distinct localization of various AQPs in cerebrum and the similarities of distribution patterns within cerebellum, cochlear nucleus and trapezoid nuclei suggest that AQPs may play an important role in maintaining the specific microenvironments of the brain.
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This paper presents a data-driven approach for facial expression retargeting in video, i.e., synthesizing a face video of a target subject that mimics the expressions of a source subject in the input video. Our approach takes adva...
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This paper presents a data-driven approach for facial expression retargeting in video, i.e., synthesizing a face video of a target subject that mimics the expressions of a source subject in the input video. Our approach takes advantage of a pre-existing facial expression database of the target subject to achieve realistic synthesis. First, for each frame of the input video, a new facial expression similarity metric is proposed for querying the expression database of the target person to select multiple candidate images that are most similar to the input. The similarity metric is developed using a metric learning approach to reliably handle appearance difference between different subjects. Secondly, we employ an optimization approach to choose the best candidate image for each frame, resulting in a retrieved sequence that is temporally coherent. Finally, a spatio-temporal expression mapping method is employed to further improve the synthesized sequence. Experimental results show that our system is capable of generating high quality facial expression videos that match well with the input sequences, even when the source and target subjects have big identity difference. In addition, extensive evaluations demonstrate the high accuracy of the learned expression similarity metric and the effectiveness of our retrieval strategy.
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