973 resultados para Data Profiles
Resumo:
The release of vast quantities of DNA sequence data by large-scale genome and expressed sequence tag (EST) projects underlines the necessity for the development of efficient and inexpensive ways to link sequence databases with temporal and spatial expression profiles. Here we demonstrate the power of linking cDNA sequence data (including EST sequences) with transcript profiles revealed by cDNA-AFLP, a highly reproducible differential display method based on restriction enzyme digests and selective amplification under high stringency conditions. We have developed a computer program (GenEST) that predicts the sizes of virtual transcript-derived fragments (TDFs) of in silico-digested cDNA sequences retrieved from databases. The vast majority of the resulting virtual TDFs could be traced back among the thousands of TDFs displayed on cDNA-AFLP gels. Sequencing of the corresponding bands excised from cDNA-AFLP gels revealed no inconsistencies. As a consequence, cDNA sequence databases can be screened very efficiently to identify genes with relevant expression profiles. The other way round, it is possible to switch from cDNA-AFLP gels to sequences in the databases. Using the restriction enzyme recognition sites, the primer extensions and the estimated TDF size as identifiers, the DNA sequence(s) corresponding to a TDF with an interesting expression pattern can be identified. In this paper we show examples in both directions by analyzing the plant parasitic nematode Globodera rostochiensis. Various novel pathogenicity factors were identified by combining ESTs from the infective stage juveniles with expression profiles of ∼4000 genes in five developmental stages produced by cDNA-AFLP.
Resumo:
A statistical modeling approach is proposed for use in searching large microarray data sets for genes that have a transcriptional response to a stimulus. The approach is unrestricted with respect to the timing, magnitude or duration of the response, or the overall abundance of the transcript. The statistical model makes an accommodation for systematic heterogeneity in expression levels. Corresponding data analyses provide gene-specific information, and the approach provides a means for evaluating the statistical significance of such information. To illustrate this strategy we have derived a model to depict the profile expected for a periodically transcribed gene and used it to look for budding yeast transcripts that adhere to this profile. Using objective criteria, this method identifies 81% of the known periodic transcripts and 1,088 genes, which show significant periodicity in at least one of the three data sets analyzed. However, only one-quarter of these genes show significant oscillations in at least two data sets and can be classified as periodic with high confidence. The method provides estimates of the mean activation and deactivation times, induced and basal expression levels, and statistical measures of the precision of these estimates for each periodic transcript.
Resumo:
The mixing regime of the upper 180 m of a mesoscale eddy in the vicinity of the Antarctic Polar Front at 47° S and 21° E was investigated during the R.V. Polarstern cruise ANT-XVIII/2 within the scope of the iron fertilization experiment EisenEx. On the basis of hydrographic CTD and ADCP profiles we deduced the vertical diffusivity Kz from two different parameterizations. Since these parameterizations bear the character of empirical functions, based on theoretical and idealized assumptions, they were inter alia compared with Cox-number and Thorpe-scale related diffusivities deduced from microstructure measurements, which supplied the first direct insights into turbulence of this ocean region. Values of Kz in the range of 10**-4 - 10**-3 m**2/s appear as a rather robust estimate of vertical diffusivity within the seasonal pycnocline. Values in the mixed layer above are more variable in time and reach 10**-1 m**2/s during periods of strong winds. The results confirm a close agreement between the microstructure-based eddy diffusivities and eddy diffusivities calculated after the parameterization of Pacanowski and Philander [1981, Journal of Physical Oceanography 11, 1443-1451, doi:10.1175/1520-0485(1981)011<1443:POVMIN>2.0.CO;2].
Resumo:
The data files give the basic field and laboratory data on five ponds in the northeast Siberian Arctic tundra on Samoylov. The files contain water and soil temperature data of the ponds, methane fluxes, measured with closed chambers in the centres without vascular plants and the margins with vascular plants, the contribution of plant mediated fluxes on total methane fluxes, the gas concentrations (methane and dissolved inorganic carbon, oxygen) in the soil and the water column of the ponds, microbial activities (methane production, methane oxidation, aerobic and anaerobic carbon dioxide production), total carbon pools in the different horizons of the bottom soils, soil bulk density, soil substance density, and soil porosity.
Resumo:
High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.
Resumo:
The new social panorama resulting from aging of the Brazilian population is leading to significant transformations within healthcare. Through the cluster analysis strategy, it was sought to describe the specific care demands of the elderly population, using frailty components. Cross-sectional study based on reviewing medical records, conducted in the geriatric outpatient clinic, Hospital de Clínicas, Universidade Estadual de Campinas (Unicamp). Ninety-eight elderly users of this clinic were evaluated using cluster analysis and instruments for assessing their overall geriatric status and frailty characteristics. The variables that most strongly influenced the formation of clusters were age, functional capacities, cognitive capacity, presence of comorbidities and number of medications used. Three main groups of elderly people could be identified: one with good cognitive and functional performance but with high prevalence of comorbidities (mean age 77.9 years, cognitive impairment in 28.6% and mean of 7.4 comorbidities); a second with more advanced age, greater cognitive impairment and greater dependence (mean age 88.5 years old, cognitive impairment in 84.6% and mean of 7.1 comorbidities); and a third younger group with poor cognitive performance and greater number of comorbidities but functionally independent (mean age 78.5 years old, cognitive impairment in 89.6% and mean of 7.4 comorbidities). These data characterize the profile of this population and can be used as the basis for developing efficient strategies aimed at diminishing functional dependence, poor self-rated health and impaired quality of life.
Resumo:
Background: MicroRNA (miR) are a class of small RNAs that regulate gene expression by inhibiting translation of protein encoding transcripts. To evaluate the role of miR in skeletal muscle of swine, global microRNA abundance was measured at specific developmental stages including proliferating satellite cells, three stages of fetal growth, day-old neonate, and the adult. Results: Twelve potential novel miR were detected that did not match previously reported sequences. In addition, a number of miR previously reported to be expressed in mammalian muscle were detected, having a variety of abundance patterns through muscle development. Muscle-specific miR-206 was nearly absent in proliferating satellite cells in culture, but was the highest abundant miR at other time points evaluated. In addition, miR-1 was moderately abundant throughout developmental stages with highest abundance in the adult. In contrast, miR-133 was moderately abundant in adult muscle and either not detectable or lowly abundant throughout fetal and neonate development. Changes in abundance of ubiquitously expressed miR were also observed. MiR-432 abundance was highest at the earliest stage of fetal development tested (60 day-old fetus) and decreased throughout development to the adult. Conversely, miR-24 and miR-27 exhibited greatest abundance in proliferating satellite cells and the adult, while abundance of miR-368, miR-376, and miR-423-5p was greatest in the neonate. Conclusion: These data present a complete set of transcriptome profiles to evaluate miR abundance at specific stages of skeletal muscle growth in swine. Identification of these miR provides an initial group of miR that may play a vital role in muscle development and growth.
Resumo:
Background: Ezetimibe specifically blocks the absorption of dietary and biliary cholesterol and plant sterols. Synergism of ezetimibe-statin therapy on LDL-cholesterol has been demonstrated, but data concerning the pleiotropic effects of this combination are controversial. Objective: This open-label trial evaluated whether the combination of simvastatin and ezetimibe also results in a synergistic effect that reduces the pro-inflammatory status of pre-diabetic subjects. Methods: Fifty pre-diabetic subjects were randomly assigned to one of 2 groups, one receiving ezetimibe (10 mg/day), the other, simvastatin (20 mg/d) for 12 weeks, followed by an additional 12-week period of combined therapy. Blood samples were collected at baseline, 12 and 24 weeks. RESULTS: Total cholesterol, LDL-cholesterol and apolipoprotein B levels decreased in all the periods analyzed (p < 0.01), but triglycerides declined significantly only after combined therapy. Both drugs induced reductions in C-reactive protein, reaching statistical significance after combining ezetimibe with the simvastatin therapy (baseline 0.59 +/- 0.14, simvastatin monotherapy 0.48 +/- 0.12 mg/dL and 0.35 +/- 0.12 mg/dL, p < 0.023). Such a reduction was independent of LDL-cholesterol change. However, mean levels of TNF-alpha and interleukin-6 and leukocyte count did not vary during the whole study. Conclusion: Expected synergistic lowering effects of a simvastatin and ezetimibe combination on LDL-cholesterol, apolipoprotein B and triglycerides levels were confirmed in subjects with early disturbances of glucose metabolism. We suggest an additive effect of this combination also on inflammatory status based on the reduction of C-reactive protein. Attenuation of pro-inflammatory conditions may be relevant in reducing cardiometabolic risk.
Resumo:
Background: Without intensive selection, the majority of bovine oocytes submitted to in vitro embryo production (IVP) fail to develop to the blastocyst stage. This is attributed partly to their maturation status and competences. Using the Affymetrix GeneChip Bovine Genome Array, global mRNA expression analysis of immature (GV) and in vitro matured (IVM) bovine oocytes was carried out to characterize the transcriptome of bovine oocytes and then use a variety of approaches to determine whether the observed transcriptional changes during IVM was real or an artifact of the techniques used during analysis. Results: 8489 transcripts were detected across the two oocyte groups, of which similar to 25.0% (2117 transcripts) were differentially expressed (p < 0.001); corresponding to 589 over-expressed and 1528 under-expressed transcripts in the IVM oocytes compared to their immature counterparts. Over expression of transcripts by IVM oocytes is particularly interesting, therefore, a variety of approaches were employed to determine whether the observed transcriptional changes during IVM were real or an artifact of the techniques used during analysis, including the analysis of transcript abundance in oocytes in vitro matured in the presence of a-amanitin. Subsets of the differentially expressed genes were also validated by quantitative real-time PCR (qPCR) and the gene expression data was classified according to gene ontology and pathway enrichment. Numerous cell cycle linked (CDC2, CDK5, CDK8, HSPA2, MAPK14, TXNL4B), molecular transport (STX5, STX17, SEC22A, SEC22B), and differentiation (NACA) related genes were found to be among the several over-expressed transcripts in GV oocytes compared to the matured counterparts, while ANXA1, PLAU, STC1and LUM were among the over-expressed genes after oocyte maturation. Conclusion: Using sequential experiments, we have shown and confirmed transcriptional changes during oocyte maturation. This dataset provides a unique reference resource for studies concerned with the molecular mechanisms controlling oocyte meiotic maturation in cattle, addresses the existing conflicting issue of transcription during meiotic maturation and contributes to the global goal of improving assisted reproductive technology.