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Search Results: 1 - 10 of 2041 matches for " Mari Sogayar "
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Stem cells in embryonic skin development
Maria F Forni,Marina Trombetta-Lima,Mari C Sogayar
Biological Research , 2012,
Abstract: The skin is a complex stratified organ which acts not only as a permeability barrier and defense against external agents, but also has essential thermoregulatory, sensory and metabolic functions. Due to its high versatility and activity, the skin undergoes continuous self-renewal to repair damaged tissue and replace old cells. Consequently, the skin is a reservoir for adult stem cells of different embryonic origins. Skin stem cell populations reside in the adult hair follicle, sebaceous gland, dermis and epidermis. However, the origin of most of the stem cell populations found in the adult epidermis is still unknown. Far more unknown is the embryonic origin of other stem cells that populate the other layers of this tissue. In this review we attempt to clarify the emergence, structure, markers and embryonic development of diverse populations of stem cells from the epidermis, dermis and related appendages such as the sebaceous gland and hair follicle.
Unveiling novel genes upregulated by both rhBMP2 and rhBMP7 during early osteoblastic transdifferentiation of C2C12 cells
Juan C Bustos-Valenzuela, Andre Fujita, Erik Halcsik, Jose M Granjeiro, Mari C Sogayar
BMC Research Notes , 2011, DOI: 10.1186/1756-0500-4-370
Abstract: BMPs (bone morphogenetic proteins) are members of the TGFβ (transforming growth factor-β) super-family of proteins, which regulate growth and differentiation of different cell types in various tissues, and play a critical role in the differentiation of mesenchymal cells into osteoblasts. In particular, rhBMP2 and rhBMP7 promote osteoinduction in vitro and in vivo, and both proteins are therapeutically applied in orthopaedics and dentistry.Using DNA microarrays and RT-qPCR, we identified both previously known and novel genes which are upregulated by rhBMP2 and rhBMP7 during the onset of osteoblastic transdifferentiation of pre-myoblastic C2C12 cells. Subsequent studies of these genes in C2C12 and mesenchymal or pre-osteoblastic cells should reveal more details about their role during this type of cellular differentiation induced by BMP2 or BMP7. These studies are relevant to better understanding the molecular mechanisms underlying osteoblastic differentiation and bone repair.Bone formation and fracture repair depends on the expression and action of the bone morphogenetic proteins (BMPs), which are members of the transforming growth factor beta (TGF-beta) superfamily of dimeric, disulphide-linked growth factors, comprising more than 15 related proteins. In addition to a crucial role in osteogenesis, BMPs display a myriad of roles in cell proliferation, differentiation, migration and apoptosis, in different cell types [1]. Their role is essential at early phases of development and organogenesis, such as axial embryo determination [2], as well as in limb, eye and kidney development, such that ablation of these genes results in death at very early stages of development, as observed in knock-out mice [3]. In humans, recombinant BMP2 and BMP7 have gained attention in bone repair and in non-union spinal fractures due to their capacity to stimulate the differentiation of mesenchymal stem cells from the periosteum near the lesion site after migration and proliferation induced
GEDI: a user-friendly toolbox for analysis of large-scale gene expression data
André Fujita, Jo?o R Sato, Carlos E Ferreira, Mari C Sogayar
BMC Bioinformatics , 2007, DOI: 10.1186/1471-2105-8-457
Abstract: Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al.GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.High-throughput DNA microarray technologies yield up to tens of thousands of gene expression data, which are useful to identify differentially expressed genes, biomarkers and molecular disease profiles. In recent years, microarray platforms have become available at relatively low costs, becoming more popular among research groups which are interested in gene expression analysis. On the other hand, much effort has been spent in developing improved methods to analyze the data derived from these microarrays. These methods involve advanced mathematical and statistical models, which are quite cumbersome to biomedical researchers who attempt to implement these methods. Due to this difficulty, some of these advanced methods are often abandoned and data analysis is carried out using only the classical methods, which are implemented in popular statistical softwares. An user-friendly software could make it possible to use recently developed methods to integrate, qualify, and infer biological insi
Evaluating different methods of microarray data normalization
André Fujita, Jo?o Sato, Leonardo Rodrigues, Carlos Ferreira, Mari Sogayar
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-469
Abstract: Here, we considered three commonly used normalization approaches, namely: Loess, Splines and Wavelets, and two non-parametric regression methods, which have yet to be used for normalization, namely, the Kernel smoothing and Support Vector Regression. The results obtained were compared using artificial microarray data and benchmark studies. The results indicate that the Support Vector Regression is the most robust to outliers and that Kernel is the worst normalization technique, while no practical differences were observed between Loess, Splines and Wavelets.In face of our results, the Support Vector Regression is favored for microarray normalization due to its superiority when compared to the other methods for its robustness in estimating the normalization curve.DNA microarray technology is a powerful approach for genomic research, playing an increasingly important role in biomedical research. This technology yields simultaneous measurement of gene expression levels of thousands of genes, allowing the analysis of differential gene expression patterns under different conditions such as disease (pathological) states or treatment with different chemotherapeutic drugs. Due to small differences in RNA quantities and fluctuations generated by the technique, the intensity levels may vary from one replicate to the other due to effects which are unrelated to the genes, requiring data normalization before they can be compared.Therefore, normalization is an important step for microarray data analysis. The purpose of data normalization is to minimize the effects caused by technical variations and, as a result, allow the data to be comparable in order to find actual biological changes. Several normalization approaches have been proposed, most of which derive from studies using two-color spotted microarrays. Some authors proposed normalization of the hybridization intensity ratios; others use global, linear methods, while others use local, non-linear methods. Several authors sugg
Cloning and characterization of a novel alternatively spliced transcript of the human CHD7 putative helicase
Christian Colin, Flávia S Tobaruella, Ricardo G Correa, Mari C Sogayar, Marcos A Demasi
BMC Research Notes , 2010, DOI: 10.1186/1756-0500-3-252
Abstract: Here, we report the cloning and characterization by experimental and computational studies of a novel alternative transcript of the human CHD7 (named CHD7 CRA_e), which lacks most of its coding exons. We confirmed by overexpression of CHD7 CRA_e alternative transcript that it is translated into a protein isoform lacking most of the domains displayed by the canonical isoform. Expression of the CHD7 CRA_e transcript was detected in normal liver, in addition to the DU145 human prostate carcinoma cell line from which it was originally isolated.Our findings indicate that the splicing event associated to the CHD7 CRA_e alternative transcript is functional. The characterization of the CHD7 CRA_e novel isoform presented here not only sets the basis for more detailed functional studies of this isoform, but, also, contributes to the alternative splicing annotation of the CHD7 gene and the design of future functional studies aimed at the elucidation of the molecular functions of its gene products.The CHD7 (Chromodomain Helicase DNA binding protein 7) gene encodes a member of the chromodomain family of ATP-dependent chromatin remodeling enzymes. In 2004, CHD7 was described as the major gene involved in the CHARGE syndrome [1], a complex genetic disorder related to multiple birth malformations and functional disorders, including ocular coloboma (C), heart disease (H), choanal atresia (A), retarded growth and/or anomalies of the central nervous system (R), genito-urinary defects and/or hypogonadism (G), and ear anomalies and/or deafness (E) [2]. De novo mutations in the CHD7 gene, especially nonsense and frameshift mutations, are found in approximately 60% of the individuals with CHARGE [1-4]. Embryonic lethality at E10.5-E11.5 in mice which are homozygous for null mutations in Chd7 support the haplo-insufficiency model as the most likely mechanism involved in this syndrome. Additionally, mice which are heterozygous for null mutations in Chd7 recapitulate many of the traits found
Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates
André Fujita, Luciana Gomes, Jo?o Sato, Rui Yamaguchi, Carlos Thomaz, Mari Sogayar, Satoru Miyano
BMC Systems Biology , 2008, DOI: 10.1186/1752-0509-2-106
Abstract: Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones.We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.Cancer is one of the main public health problems in the United States and worldwide [1]. Among the diverse types of neoplasia, prostate cancer is the third most common cancer in the World [2], being ranked as the second leading cause of death in men, the first being lung cancer [1]. Its incidence and mortality varies in different parts of the World, being highest in Western countries, mainly among Africans [3].With t
TGF-β1 modulates the homeostasis between MMPs and MMP inhibitors through p38 MAPK and ERK1/2 in highly invasive breast cancer cells
Luciana R Gomes, Letícia F Terra, Rosangela AM Wailemann, Leticia Labriola, Mari C Sogayar
BMC Cancer , 2012, DOI: 10.1186/1471-2407-12-26
Abstract: The mRNA expression levels of TGF-β isoforms and their receptors were analyzed by qRT-PCR in a panel of five human breast cancer cell lines displaying different degrees of invasiveness and metastatic potential. The highly invasive MDA-MB-231 cell line was treated with different concentrations of recombinant TGF-β1 and also with pharmacological inhibitors of p38 MAPK and ERK1/2. The migratory and invasive potential of these treated cells were examined in vitro by transwell assays.In general, TGF-β2, TβRI and TβRII are over-expressed in more aggressive cells, except for TβRI, which was also highly expressed in ZR-75-1 cells. In addition, TGF-β1-treated MDA-MB-231 cells presented significantly increased mRNA expression of MMP-2, MMP-9, MMP-14, TIMP-2 and RECK. TGF-β1 also increased TIMP-2, MMP-2 and MMP-9 protein levels but downregulated RECK expression. Furthermore, we analyzed the involvement of p38 MAPK and ERK1/2, representing two well established Smad-independent pathways, in the proposed mechanism. Inhibition of p38MAPK blocked TGF-β1-increased mRNA expression of all MMPs and MMP inhibitors analyzed, and prevented TGF-β1 upregulation of TIMP-2 and MMP-2 proteins. Moreover, ERK1/2 inhibition increased RECK and prevented the TGF-β1 induction of pro-MMP-9 and TIMP-2 proteins. TGF-β1-enhanced migration and invasion capacities were blocked by p38MAPK, ERK1/2 and MMP inhibitors.Altogether, our results support that TGF-β1 modulates the mRNA and protein levels of MMPs (MMP-2 and MMP-9) as much as their inhibitors (TIMP-2 and RECK). Therefore, this cytokine plays a crucial role in breast cancer progression by modulating key elements of ECM homeostasis control. Thus, although the complexity of this signaling network, TGF-β1 still remains a promising target for breast cancer treatment.Breast cancer is a worldwide health problem for women, since it is the first in incidence and the second in mortality among cancer types [1]. Similarly to the majority of solid tumors, the mai
Evaluation of the cytocompatibility of mixed bovine bone
Takamori, Esther Rieko;Figueira, Eduardo Aleixo;Taga, Rumio;Sogayar, Mari Cleide;Granjeiro, José Mauro;
Brazilian Dental Journal , 2007, DOI: 10.1590/S0103-64402007000300001
Abstract: treatment of bovine bone with peroxides and chaotropic agents aims to obtain an acellular bone matrix that is able to maintain the collagen-apatite complex and a higher mechanical resistance, a mixed biomaterial hereby named mixed bovine bone (mbb). the purpose of this study was to evaluate the cytocompatibility of mbb and cell-mbb interaction. cell morphology, number of viable cells, ability to reduce methyltetrazolium and to incorporate neutral red upon exposure to different concentrations of the hydrosoluble extract of mbb were assessed in balb-c 3t3 cells according to iso 10993-5 standard. the interaction between cells and mbb surface was evaluated by scanning electron microscopy. the water-soluble mbb extracts were cytotoxic and led to cell death possibly due to its effect on mitochondrial function and membrane permeability. cells plated directly onto the mbb did not survive, although after dialysis and material conditioning in dmem + 10% fcs, the cells adhered and proliferated onto the material. it may be concluded that, in vitro, water-soluble mbb extracts were cytotoxic. nevertheless, mbb cytotoxic effect was reverted by dialysis resulting in a material that is suitable for cell based-therapy in the bioengineering field.
Latent rank change detection for analysis of splice-junction microarrays with nonlinear effects
Jonathan Gelfond,Lee Ann Zarzabal,Tarea Burton,Suzanne Burns,Mari Sogayar,Luiz O. F. Penalva
Statistics , 2011, DOI: 10.1214/10-AOAS389
Abstract: Alternative splicing of gene transcripts greatly expands the functional capacity of the genome, and certain splice isoforms may indicate specific disease states such as cancer. Splice junction microarrays interrogate thousands of splice junctions, but data analysis is difficult and error prone because of the increased complexity compared to differential gene expression analysis. We present Rank Change Detection (RCD) as a method to identify differential splicing events based upon a straightforward probabilistic model comparing the over- or underrepresentation of two or more competing isoforms. RCD has advantages over commonly used methods because it is robust to false positive errors due to nonlinear trends in microarray measurements. Further, RCD does not depend on prior knowledge of splice isoforms, yet it takes advantage of the inherent structure of mutually exclusive junctions, and it is conceptually generalizable to other types of splicing arrays or RNA-Seq. RCD specifically identifies the biologically important cases when a splice junction becomes more or less prevalent compared to other mutually exclusive junctions. The example data is from different cell lines of glioblastoma tumors assayed with Agilent microarrays.
Correlation between MMPs and their inhibitors in breast cancer tumor tissue specimens and in cell lines with different metastatic potential
Rita CS Figueira, Luciana R Gomes, Jo?o S Neto, Fabricio C Silva, Ismael DCG Silva, Mari C Sogayar
BMC Cancer , 2009, DOI: 10.1186/1471-2407-9-20
Abstract: We analyzed the expression levels of MMP-2, MMP-9 and MMP-14 and their inhibitors (TIMP-1, TIMP-2 and RECK) by quantitative RT-PCR (qRT-PCR) in five human breast cancer cell lines presenting increased invasiveness and metastatic potential, 72 primary breast tumors and 30 adjacent normal tissues. Moreover, the role of cell-extracellular matrix elements interactions in the regulation of expression and activity of MMPs and their inhibitors was analyzed by culturing these cell lines on plastic or on artificial ECM (Matrigel).The results demonstrated that MMPs mRNA expression levels displayed a positive and statistically significant correlation with the transcriptional expression levels of their inhibitors both in the cell line models and in the tumor tissue samples. Furthermore, the expression of all MMP inhibitors was modulated by cell-Matrigel contact only in highly invasive and metastatic cell lines. The enzyme/inhibitor balance at the transcriptional level significantly favors the enzyme which is more evident in tumor than in adjacent non-tumor tissue samples.Our results suggest that the expression of MMPs and their inhibitors, at least at the transcriptional level, might be regulated by common factors and signaling pathways. Therefore, the multi-factorial analysis of these molecules could provide new and independent prognostic information contributing to the determination of more adequate therapy strategies for each patient.Among diverse cancer types, breast carcinoma stands out for its increasing incidence rates and high mortality worldwide [1]. Like most solid tumors, metastatic disease rather than the primary tumor itself is responsible for death [2-4]. The metastatic process involves a complex cascade of events, including the organized breakdown of the extracellular matrix (ECM) by matrix metalloproteinases (MMPs) [5,6]. Together, the MMPs are able to process or degrade all ECM components. Each ECM element is cleaved by a specific MMP or MMP group [7]. The acti
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