969 resultados para Biological Markers -- analysis


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The CDKN1A (TP21)(2) gene encodes a 21-kD protein that is a critical downstream mediator of wild-type TP53 and an important regulator of the cell cycle. Failure in the function of this gene would be expected to result in abnormal cell proliferation and transformation. Tumor-associated mutations of the coding region of the TP21 are rare. on the other hand, some TP21 polymorphisms have been identified and characterized by single base substitutions. In the present study, we investigated the potential role of TP21 gene polymorphisms in skin, head, and neck tumorigenesis. A total of 261 samples were examined by polymerase chain reaction single-strand conformational analysis, and one mutation at codon 31 and four polymorphisms in exons 2 (codon 55) and 3 [nucleotide (nt)590] and in promoter region (nt2298) were identified. In conclusion, this investigation confirmed the rarity of mutations in this gene, arguing against a role for TP21 mutations in skin, head, and neck cancers. Also, our results show significant differences in nt2298 allele frequencies between normal individuals and skin malignant tumors (P < 0.05). The results suggest that this polymorphism affects TP21 transactivator binding and may be important during the pathogenesis of skin cancer. (C) 2003 Elsevier B.V. All rights reserved.

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Previous analyses of mitochondrial (mt)DNA and allozymes covering the range of the Iberian endemic golden-striped salamander, Chioglossa lusitanica, suggested a Pleistocene split of the historical species distribution into two population units (north and south of the Mondego river), postglacial expansion into the northernmost extant range, and secondary contact with neutral diffusion of genes close to the Mondego river. We extended analysis of molecular variation over the species range using seven microsatellite loci and the nuclear P-fibrinogen intron 7 (beta-fibint7). Both microsatellites and beta-fibint7 showed moderate to high levels of population structure, concordant with patterns detected with mtDNA and allozymes; and a general pattern of isolation-by-distance, contrasting the marked differentiation of two population groups suggested by mtDNA and allozymes. Bayesian multilocus analyses showed contrasting results as populations north and south of the Douro river were clearly differentiated based on microsatellites, whereas allozymes revealed differentiation north and south of the Mondego river. Additionally, decreased microsatellite variability in the north supported the hypothesis of postglacial colonization of this region. The well-documented evolutionary history of C. lusitanica, provides an excellent framework within which the advantages and limitations of different classes of markers can be evaluated in defining patterns of population substructure and inferring evolutionary processes across distinct spatio-temporal scales. The present study serves as a cautionary note for investigations that rely on a single type of molecular marker, especially when the organism under study exhibits a widespread distribution and complex natural history. (C) 2008 The Linnean Society of London, Biological Journal of the Linnean Society, 2008, 95, 371-387.

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The evaluation of the growth of incisor teeth of rats as influenced by colchicine (doses of 25, 50, 100 and 200 μg/kg) injected during 10 and 18 days is performed using a multivariated variance analysis, which allowed a global view of the results, showing that: there are differences in the growth of teeth of control group (untreated rats) and those treated with colchicine, in the measurements made at the 4th, 7th and 10th days of experiment); there is no difference in the growth of the teeth between the groups treated during 10 and 18 days, except in the measurements made at the 7th day; there is no influence of the doses of colchicine in the group treated during 10 days and in the group treated during 18 days - only at the 7th day is observed an influence of the doses used; and there was no significant interaction between treatment and days of measurement, showing the similarity of the groups during the experiment.

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The advent of molecular markers has created opportunities for a better understanding of quantitative inheritance and for developing novel strategies for genetic improvement of agricultural species, using information on quantitative trait loci (QTL). A QTL analysis relies on accurate genetic marker maps. At present, most statistical methods used for map construction ignore the fact that molecular data may be read with error. Often, however, there is ambiguity about some marker genotypes. A Bayesian MCMC approach for inferences about a genetic marker map when random miscoding of genotypes occurs is presented, and simulated and real data sets are analyzed. The results suggest that unless there is strong reason to believe that genotypes are ascertained without error, the proposed approach provides more reliable inference on the genetic map.

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OBJECTIVE: To carry out a retrospective study to determine whether human papillomavirus (HPV) infection and immunohistochemical expression of p53 and proliferating cell nuclear antigen (PCNA) are related to the risk of oral cancer. STUDY DESIGN: Fifty-seven oral biopsies, consisting of 30 oral squamous papillomas (OSPs) and 27 oral squamous cell carcinomas (OSCCs) were tested for the presence of HPV 6/11 and 16/18 by in situ hybridization using catalyzed signal amplification and in situ hybridization. p53 And PCNA expression was analyzed by immunohistochemistry and evaluated quantitatively by image analysis. RESULTS: Nineteen of the 57 oral lesions (33.3%) were positive for HPV. HPV 6/11 was found in 6 of 30 (20%) OSPs and 1 of 27 (3.7%) OSCCs. HPV 16/18 was found in 10 of 27 (37%) OSCCs and 2 of 30 (6.7%) OSPs. Sixteen of the 19 HPV-positive cases (84.2%) were p53 negative; 5 (9%) were HPV 6/11 and 11 (19%) HPV 16/18, with an inverse correlation between the presence of HPV DNA and p53 expression (P=.017, P < .05). PCNA expression appeared in 18 (94.7%) of HPV positive cases, showing that HPV 16/18 was associated with intensity of PCNA expression and with OSCCs (P=.037, P < .05). CONCLUSION: Quantitative evaluation of p53 by image analysis showed an inverse correlation between p53 expression and HPV presence, suggesting protein degradation. Image analysis also demonstrated that PCNA expression was more intense in HPV DNA 16/18 OSCCs. These findings suggest involvement of high-risk HPV types in oral carcinogenesis.

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The Arachis section is the most important of the nine sections of the genus Arachis because it includes the cultivated peanut, Arachis hypogaea. The genetic improvement of A. hypogaea using wild relatives is at an early stage of development in spite of their potential as sources of genes, including those for disease and pests resistance, that are not found in the A. hypogaea primary gene pool. Section Arachis species germplasm has been collected and maintained in gene banks and its use and effective conservation depends on our knowledge of the genetic variability contained in this material. Microsatellites are routinely used for the analysis of genetic variability because they are highly polymorphic and codominant. The objective of this study was to evaluate the transferability of microsatellite primers and the assay of genetic variability between and within the germplasm of some species of the Arachis section. Fourteen microsatellite loci developed for three different species of Arachis were analyzed and 11 (78%) were found to be polymorphic. All loci had transferability to all the species analyzed. The polymorphic loci were very informative, with expected heterozygosity per locus ranging from 0.70 to 0.94. In general, the germplasm analyzed showed wide genetic variation. © 2006 Sociedade Brasileira de Genética.

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When searching for prospective novel peptides, it is difficult to determine the biological activity of a peptide based only on its sequence. The trial and error approach is generally laborious, expensive and time consuming due to the large number of different experimental setups required to cover a reasonable number of biological assays. To simulate a virtual model for Hymenoptera insects, 166 peptides were selected from the venoms and hemolymphs of wasps, bees and ants and applied to a mathematical model of multivariate analysis, with nine different chemometric components: GRAVY, aliphaticity index, number of disulfide bonds, total residues, net charge, pI value, Boman index, percentage of alpha helix, and flexibility prediction. Principal component analysis (PCA) with non-linear iterative projections by alternating least-squares (NIPALS) algorithm was performed, without including any information about the biological activity of the peptides. This analysis permitted the grouping of peptides in a way that strongly correlated to the biological function of the peptides. Six different groupings were observed, which seemed to correspond to the following groups: chemotactic peptides, mastoparans, tachykinins, kinins, antibiotic peptides, and a group of long peptides with one or two disulfide bonds and with biological activities that are not yet clearly defined. The partial overlap between the mastoparans group and the chemotactic peptides, tachykinins, kinins and antibiotic peptides in the PCA score plot may be used to explain the frequent reports in the literature about the multifunctionality of some of these peptides. The mathematical model used in the present investigation can be used to predict the biological activities of novel peptides in this system, and it may also be easily applied to other biological systems. © 2011 Elsevier Inc.

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In this paper is reported the use of the chromatographic profiles of volatiles to determine disease markers in plants - in this case, leaves of Eucalyptus globulus contaminated by the necrotroph fungus Teratosphaeria nubilosa. The volatile fraction was isolated by headspace solid phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography-fast quadrupole mass spectrometry (GC. ×. GC-qMS). For the correlation between the metabolic profile described by the chromatograms and the presence of the infection, unfolded-partial least squares discriminant analysis (U-PLS-DA) with orthogonal signal correction (OSC) were employed. The proposed method was checked to be independent of factors such as the age of the harvested plants. The manipulation of the mathematical model obtained also resulted in graphic representations similar to real chromatograms, which allowed the tentative identification of more than 40 compounds potentially useful as disease biomarkers for this plant/pathogen pair. The proposed methodology can be considered as highly reliable, since the diagnosis is based on the whole chromatographic profile rather than in the detection of a single analyte. © 2013 Elsevier B.V..

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Uma importante etapa na biologia da invasão é acessar variáveis biológicas que podem predizer o sucesso de invasão. O estudo da genética, evolução e interações entre invasores e espécies nativas no ambiente invadido pode prover uma oportunidade única para o estudo dos processos em genética de populações e a capacidade de uma espécie ampliar seu habitat. Nesse trabalho, nos utilizamos dados de marcadores de DNA microssatélites para testar se a variação genética é relacionada a pressão de propágulo na invasão bem sucedida do predador de topo (o ciclídeo Amazônico Cichla) nos rios do Sudeste Brasileiro. Populações invasoras de Cichla vem impactando negativamente diversas comunidades de água doce no Sudeste brasileiro deste 1960. A redução da variação genética foi observada em todas populações invasoras, tanto para Cichla kelberi (CK) como Cichla piquiti (CP). Por exemplo, a heterozigose foi menor no ambiente invadido quando comparada com as populações nativas da bacia Amazônica (CP HE = 0.179/0.44; CK HE = 0.258/0.536 respectivamente). Assim, apesar do sucesso da invasão de Cichla no sudoeste do Brasil, baixa diversidade genética foi observada nas populações introduzidas. Nós sugerimos que uma combinação de fatores, como as estratégias reprodutivas de Cichla, o efeito de "armadilha evolutiva" e a hipótese de resistências biótica superam o efeito que a diversidade genética depauperada exerce, sendo aspectos-chave na invasão desse predador de topo de cadeia.

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Microsatellites are well-known DNA markers used in a variety of studies such as genome mapping, genetic diversity analysis, genetic conservation and phylogenetic studies. Although microsatellites are important markers, their development and characterization demands extensive time and high cost. Thus, before new markers are developed for a particular species, it is worthwhile to test the available markers from related species. In the present study, we evaluate cattle-derived microsatellite markers for genetic studies of water buffalo. Eighty-five percents of a total of 120 microsatellite markers were optimized using buffalo DNA (Bubalus bubalis). The results showed in this paper were also deposited in the National Center for Biological Information database (NCBI) (ProbeDB and UniSTS) for use in population genetic studies of buffalo by the scientific community. The use of heterologous primers significantly reduces the cost of developing specific markers for buffalo, providing a useful short cut for the genetic population analysis and gene mapping studies.

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The work of biochemists and molecular biologists often is dependent or extremely favored by a preliminary computer analysis. Thus, the development of an efficient and friendly computational tool is very important. In this work, we developed a package of programs in Javascript language which can be used online or locally. The programs depend exclusively of Web browsers and are compatible with Internet Explorer, Opera, Mozilla Firefox and Google Chrome. With the EBiAn package it is can perform the main analysis and manipulation of DNA, RNA, proteins and peptides sequences. The programs can be freely accessed and adapted or modified to generate new programs.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Background: Penile carcinoma (PeCa) is frequently associated with high morbidity rates. Unlikely of the vast majority of tumors, there is no molecular markers described that are able to assist in diagnosis and prognosis or with potential to be therapeutic targets in PeCa. Patients and methods: DNA methylation status (244K Human DNA Methylation Microarray platform, Agilent Technologies) and large-scale expression analysis (4x44K Whole Human Genome Microarray, Agilent Technologies) were performed in 35 and 37 PeCa, respectively. Quantitative bisulfite pyrosequencing (qBP) and RT-qPCR were used to validate the findings in 93 samples. HPV status was assessed using the Linear Array HPV Genotyping kit (Roche Molecular Diagnostics, CA, USA). Results: Methylome analysis revealed 171 hypermethylated and 449 hypomethylated CpGs sites and the transcriptome profiling showed 2986 down- and 2817 over-expressed genes. HPV positivity was found in 32.7% of the cases, mainly the HPV16. The integrative analysis in 32 PeCa revealed a panel of 96 genes with inverse correlation between methylation and gene expression levels. The CpG hypermetlylation and gene downexpression, was confirmed for TWIST1, RSOP2, SOX3, SOX17, CD133, OTX2, HOXA3 and MEIS. In addition, BIRC5, DNMT1 and DNMT3B presented low levels of methylation and overexpression. The comparison of the results with clinical findings revealed that LIN28A, NKX2.2, NKX2.3, LHX5, BDNF, FOXA1 and CDX2 were associated with poor prognosis features. Conclusion: Putative prognostic markers were detected revealing that DNA methylation modulates the expression of several genes in PeCa. These data may prove instrumental for biomarker discovery in clinics and molecular epidemiology of PeCa.

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Background and Aim: The identification of gastric carcinomas (GC) has traditionally been based on histomorphology. Recently, DNA microarrays have successfully been used to identify tumors through clustering of the expression profiles. Random forest clustering is widely used for tissue microarrays and other immunohistochemical data, because it handles highly-skewed tumor marker expressions well, and weighs the contribution of each marker according to its relatedness with other tumor markers. In the present study, we e identified biologically- and clinically-meaningful groups of GC by hierarchical clustering analysis of immunohistochemical protein expression. Methods: We selected 28 proteins (p16, p27, p21, cyclin D1, cyclin A, cyclin B1, pRb, p53, c-met, c-erbB-2, vascular endothelial growth factor, transforming growth factor [TGF]-beta I, TGF-beta II, MutS homolog-2, bcl-2, bax, bak, bcl-x, adenomatous polyposis coli, clathrin, E-cadherin, beta-catenin, mucin (MUC) 1, MUC2, MUC5AC, MUC6, matrix metalloproteinase [ MMP]-2, and MMP-9) to be investigated by immunohistochemistry in 482 GC. The analyses of the data were done using a random forest-clustering method. Results: Proteins related to cell cycle, growth factor, cell motility, cell adhesion, apoptosis, and matrix remodeling were highly expressed in GC. We identified protein expressions associated with poor survival in diffuse-type GC. Conclusions: Based on the expression analysis of 28 proteins, we identified two groups of GC that could not be explained by any clinicopathological variables, and a subgroup of long-surviving diffuse-type GC patients with a distinct molecular profile. These results provide not only a new molecular basis for understanding the biological properties of GC, but also better prediction of survival than the classic pathological grouping.

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Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.