996 resultados para TGS


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稀土掺杂硫酸三甘肽(TGS)的研究于亚勤刘艳馥(中国科学院长春应用化学研究所,长春130022)StudiesontheTriglycineSulphate(TGS)CrystalsDopedwithRareEarthIonsYuYaqinLiuYa...

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Basándose en la necesidad manifiesta de la empresa Thomas Greg & Sons de Colombia por controlar los costos en los que incurre por adoptar un Sistema de Gestión de Calidad, se realizó una investigación de los procesos que realiza la empresa a nivel productivo y el esquema de costos que utiliza a nivel organizacional, con el fin de proponer y concebir un modelo de administración de costos de la calidad y de la no calidad que sea conforme a lo esperado por la alta gerencia y que contribuya significativamente al control de costos.

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High time resolution aerosol mass spectrometry measurements were conducted during a field campaign at Mace Head Research Station, Ireland, in June 2007. Observations on one particular day of the campaign clearly indicated advection of aerosol from volcanoes and desert plains in Iceland which could be traced with NOAA Hysplit air mass back trajectories and satellite images. In conjunction with this event, elevated levels of sulphate and light absorbing particles were encountered at Mace Head. While sulphate concentration was continuously increasing, nitrate levels remained low indicating no significant contribution from anthropogenic pollutants. Sulphate concentration increased about 3.8 g/m3 in comparison with the background conditions. Corresponding sulphur flux from volcanic emissions was estimated to about 0.3 TgS/yr, suggesting that a large amount of sulphur released from Icelandic volcanoes may be distributed over distances larger than 1000 km. Overall, our results corroborate that transport of volcanogenic sulphate and dust particles can significantly change the chemical composition, size distribution, and optical properties of aerosol over the North Atlantic Ocean and should be considered accordingly by regional climate models.

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Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

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Drosophila possesses the core gene silencing machinery but, like all insects, lacks the canonical RNA-dependent RNA polymerases (RdRps) that in C. elegans either trigger or enhance two major small RNA-dependent gene silencing pathways. Introduction of two different nematode RdRps into Drosophila showed them to be functional, resulting in differing silencing activities. While RRF-1 enhanced transitive dsRNA-dependent silencing, EGO-1 triggered dsRNA-independent silencing, specifically of transgenes. The strain w; da-Gal4; UAST-ego-1, constitutively expressing ego-1, is capable of silencing transgene including dsRNA hairpin upon a single cross, which created a powerful tool for research in Drosophila. In C. elegans, EGO-1 is involved in transcriptional gene silencing (TGS) of chromosome regions that are unpaired during meiosis. There was no opportunity for meiotic interactions involving EGO-1 in Drosophila that would explain the observed transgene silencing. Transgene DNA is, however, unpaired during the pairing of chromosomes in embryonic mitosis that is an unusual characteristic of Diptera, suggesting that in Drosophila, EGO-1 triggers transcriptional silencing of unpaired DNA during embryonic mitosis. © 2012 Springer Basel.

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Next-generation sequencing techniques have revolutionized over the last decade providing researchers with low cost, high-throughput alternatives compared to the traditional Sanger sequencing methods. These sequencing techniques have rapidly evolved from first-generation to fourth-generation with very broad applications such as unravelling the complexity of the genome, in terms of genetic variations, and having a high impact on the biological field. In this review, we discuss the transition of sequencing from the second-generation to the third- and fourth-generations, and describe some of their novel biological applications. With the advancement in technology, the earlier challenges of minimal size of the instrument, flexibility of throughput, ease of data analysis and short run times are being addressed. However, the need for prospective analysis and effectiveness to test whether the knowledge of any given new variants identified has an effect on clinical outcome may need improvement.

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Rapid advances in sequencing technologies (Next Generation Sequencing or NGS) have led to a vast increase in the quantity of bioinformatics data available, with this increasing scale presenting enormous challenges to researchers seeking to identify complex interactions. This paper is concerned with the domain of transcriptional regulation, and the use of visualisation to identify relationships between specific regulatory proteins (the transcription factors or TFs) and their associated target genes (TGs). We present preliminary work from an ongoing study which aims to determine the effectiveness of different visual representations and large scale displays in supporting discovery. Following an iterative process of implementation and evaluation, representations were tested by potential users in the bioinformatics domain to determine their efficacy, and to understand better the range of ad hoc practices among bioinformatics literate users. Results from two rounds of small scale user studies are considered with initial findings suggesting that bioinformaticians require richly detailed views of TF data, features to compare TF layouts between organisms quickly, and ways to keep track of interesting data points.

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A circuit capable of producing bipolar square pulses of voltages up to +or-400 V, employing an integrated circuit timer and two mercury wetted relays is described. The frequency of the pulses can be varied from a cycle min-1 to 2 kHz. A variable temperature sample chamber and the temperature control and measurement circuits are also described. The performance of the circuit is evaluated using samples of TGS and NaNO2.

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Triglycine selenate (TGSe) is isomorphous with Triglycine sulphate and is ferroelectric below 22°C. It is interesting to study the switching process in TGSe in the ferro-state with a view to comparing the results with TSG. The switching process was studied by applying electrical square pulses to produce fields up to 5 kV/cm on the sample, and measuring the parameters characterizing the transient current flowing in the sample, according to the Merz method. The temperature range in which the process was studied was 15°C to -20°C. The results were analysed by applying the Pulvari-Kuebler theory and the parameters α the activation field and µ the mobility of the domains were evaluated. It is found that µ varies with temperature in TGSe in a manner similar to TGS. µ is lesser for TGSe than for TGS for the same shift of temperature from Tc. The switching behaviour of γ-irradiated TGSe is qualitatively similar to that of unirradiated crystal eventhougth the process gets slowed down as a result of irradiation.

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The switching transients in dicalcium strontium propionate and azoxybenzene were studied by the use of the Merz method. It was observed that the switching time depends linearly on the applied electric field. Under similar electric fields, the switching processes in DSP and azoxybenzene are slower than in triglycine sulphate (TGS) at 27°C.

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Both diglycine sulphate (DGS) and diglycine sulphate monohydrate (DGS.H2O) are reported to crystallize from solution with pH < 1(1,2). DGS.H2O (point group 2/m; Z = 4) shows a dielectric anomaly at 72°C suggestive of antiferroelectric transition(1). The crystals obtained by us from solution with pH < 0.5 at 20-25°C were always DGS (point group mmm; Z = 8) as confirmed by X-ray studies. The measurement of its dielectric constant along [100], [010] and [001] did not indicate any phase transition in the range 5-400°K. Thus DGS is a normal dielectric unlike TGS. The polarized Raman spectra and the infrared spectra were recorded to examine the configuration of glycine in DGS(3). The vibration spectra reveals that both the glycines in DGS exist as NH3+CH2COOH, thus precluding the hydrogen bond of the type N+-H…O- which exists between two glycine units in TGS. This seems to be a good reason for the difference in the dielectric behaviour of these two glycine sulphates.

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The phase transition in gamma-irradiated triglycine sulphate (TGS) has been investigated by using a method based on the measurement of thermal noise. The results of a study of the polarization switching characteristics of gamma irradiated TGS and sodium nitrite (NaNO2) have also been presented. The effect of irradiation on the phase transition and the switching processes has been discussed.

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Cell proliferation, transcription and metabolism are regulated by complex partly overlapping signaling networks involving proteins in various subcellular compartments. The objective of this study was to increase our knowledge on such regulatory networks and their interrelationships through analysis of MrpL55, Vig, and Mat1 representing three gene products implicated in regulation of cell cycle, transcription, and metabolism. Genome-wide and biochemical in vitro studies have previously revealed MrpL55 as a component of the large subunit of the mitochondrial ribosome and demonstrated a possible role for the protein in cell cycle regulation. Vig has been implicated in heterochromatin formation and identified as a constituent of the RNAi-induced silencing complex (RISC) involved in cell cycle regulation and RNAi-directed transcriptional gene silencing (TGS) coupled to RNA polymerase II (RNAPII) transcription. Mat1 has been characterized as a regulatory subunit of cyclin-dependent kinase 7 (Cdk7) complex phosphorylating and regulating critical targets involved in cell cycle progression, energy metabolism and transcription by RNAPII. The first part of the study explored whether mRpL55 is required for cell viability or involved in a regulation of energy metabolism and cell proliferation. The results revealed a dynamic requirement of the essential Drosophila mRpL55 gene during development and suggested a function of MrpL55 in cell cycle control either at the G1/S or G2/M transition prior to cell differentiation. This first in vivo characterization of a metazoan-specific constituent of the large subunit of mitochondrial ribosome also demonstrated forth compelling evidence of the interconnection of nuclear and mitochondrial genomes as well as complex functions of the evolutionarily young metazoan-specific mitochondrial ribosomal proteins. In studies on the Drosophila RISC complex regulation, it was noted that Vig, a protein involved in heterochromatin formation, unlike other analyzed RISC associated proteins Argonaute2 and R2D2, is dynamically phosphorylated in a dsRNA-independent manner. Vig displays similarity with a known in vivo substrate for protein kinase C (PKC), human chromatin remodeling factor Ki-1/57, and is efficiently phosphorylated by PKC on multiple sites in vitro. These results suggest that function of the RISC complex protein Vig in RNAi-directed TGS and chromatin modification may be regulated through dsRNA-independent phosphorylation by PKC. In the third part of this study the role of Mat1 in regulating RNAPII transcription was investigated using cultured murine immortal fibroblasts with a conditional allele of Mat1. The results demonstrated that phosphorylation of the carboxy-terminal domain (CTD) of the large subunit of RNAPII in the heptapeptide YSPTSPS repeat in Mat-/- cells was over 10-fold reduced on Serine-5 and subsequently on Serine-2. Occupancy of the hypophosphorylated RNAPII in gene bodies was detectably decreased, whereas capping, splicing, histone methylation and mRNA levels were generally not affected. However, a subset of transcripts in absence of Mat1 was repressed and associated with decreased occupancy of RNAPII at promoters as well as defective capping. The results identify the Cdk7-CycH-Mat1 kinase submodule of TFIIH as a stimulatory non-essential regulator of transcriptional elongation and a genespecific essential factor for stable binding of RNAPII at the promoter region and capping. The results of these studies suggest important roles for both MrpL55 and Mat1 in cell cycle progression and their possible interplay at the G2/M stage in undifferentiated cells. The identified function of Mat1 and of TFIIH kinase complex in gene-specific transcriptional repression is challenging for further studies in regard to a possible link to Vig and RISC-mediated transcriptional gene silencing.

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Polygenic profiling has been proposed for elite endurance performance, using an additive model determining the proportion of optimal alleles in endurance athletes. To investigate this model’s utility for elite triathletes, we genotyped seven polymorphisms previously associated with an endurance polygenic profile (ACE Ins/Del, ACTN3 Arg577Ter, AMPD1 Gln12Ter, CKMM 1170bp/985+185bp, HFE His63Asp, GDF8 Lys153Arg and PPARGC1A Gly482Ser) in a cohort of 196 elite athletes who participated in the 2008 Kona Ironman championship triathlon. Mean performance time (PT) was not significantly different in individual marker analysis. Age, sex, and continent of origin had a significant influence on PT and were adjusted for. Only the AMPD1 endurance-optimal Gln allele was found to be significantly associated with an improvement in PT (model p=5.79 x 10-17, AMPD1 genotype p=0.01). Individual genotypes were combined into a total genotype score (TGS); TGS distribution ranged from 28.6 to 92.9, concordant with prior studies in endurance athletes (mean±SD: 60.75±12.95). TGS distribution was shifted toward higher TGS in the top 10% of athletes, though the mean TGS was not significantly different (p=0.164) and not significantly associated with PT even when adjusted for age, sex, and origin. Receiver operating characteristic curve analysis determined that TGS alone could not significantly predict athlete finishing time with discriminating sensitivity and specificity for three outcomes (less than median PT, less than mean PT, or in the top 10%), though models with the age, sex, continent of origin, and either TGS or AMPD1 genotype could. These results suggest three things: that more sophisticated genetic models may be necessary to accurately predict athlete finishing time in endurance events; that non-genetic factors such as training are hugely influential and should be included in genetic analyses to prevent confounding; and that large collaborations may be necessary to obtain sufficient sample sizes for powerful and complex analyses of endurance performance.

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Background. Cardiovascular disease (CVD) remains the most serious threat to life and health in industrialized countries. Atherosclerosis is the main underlying pathology associated with CVD, in particular coronary artery disease (CAD), ischaemic stroke, and peripheral arterial disease. Risk factors play an important role in initiating and accelerating the complex process of atherosclerosis. Most studies of risk factors have focused on the presence or absence of clinically defined CVD. Less is known about the determinants of the severity and extent of atherosclerosis in symptomatic patients. Aims. To clarify the association between coronary and carotid artery atherosclerosis, and to study the determinants associated with these abnormalities with special regard to novel cardiovascular risk factors. Subjects and methods. Quantitative coronary angiography (QCA) and B-mode ultrasound were used to assess coronary and carotid artery atherosclerosis in 108 patients with clinically suspected CAD referred for elective coronary angiography. To evaluate anatomic severity and extent of CAD, several QCA parameters were incorporated into indexes. These measurements reflected CAD severity, extent, and overall atheroma burden and were calculated for the entire coronary tree and separately for different coronary segments (i.e., left main, proximal, mid, and distal segments). Maximum and mean intima-media thickness (IMT) values of carotid arteries were measured and expressed as mean aggregate values. Furthermore, the study design included extensive fasting blood samples, oral glucose tolerance test, and an oral fat-load test to be performed in each participant. Results. Maximum and mean IMT values were significantly correlated with CAD severity, extent, and atheroma burden. There was heterogeneity in associations between IMT and CAD indexes according to anatomical location of CAD. Maximum and mean IMT values, respectively, were correlated with QCA indexes for mid and distal segments but not with the proximal segments of coronary vessels. The values of paraoxonase-1 (PON1) activity and concentration, respectively, were lower in subjects with significant CAD and there was a significant relationship between PON1 activity and concentration and coronary atherosclerosis assessed by QCA. PON1 activity was a significant determinant of severity of CAD independently of HDL cholesterol. Neither PON1 activity nor concentration was associated with carotid IMT. The concentration of triglycerides (TGs), triglyceride-rich lipoproteins (TRLs), oxidized LDL (oxLDL), and the cholesterol content of remnant lipoprotein particle (RLP-C) were significantly increased at 6 hours after intake of an oral fatty meal as compared with fasting values. The mean peak size of LDL remained unchanged 6 hours after the test meal. The correlations between total TGs, TRLs, and RLP-C in fasting and postprandial state were highly significant. RLP-C correlated with oxLDL both in fasting and in fed state and inversely with LDL size. In multivariate analysis oxLDL was a determinant of severity and extent of CAD. Neither total TGs, TRLs, oxLDL, nor LDL size were linked to carotid atherosclerosis. Insulin resistance (IR) was associated with an increased severity and extent of coronary atherosclerosis and seemed to be a stronger predictor of coronary atherosclerosis in the distal parts of the coronary tree than in the proximal and mid parts. In the multivariate analysis IR was a significant predictor of the severity of CAD. IR did not correlate with carotid IMT. Maximum and mean carotid IMT were higher in patients with the apoE4 phenotype compared with subjects with the apoE3 phenotype. Likewise, patients with the apoE4 phenotype had a more severe and extensive CAD than individuals with the apoE3 phenotype. Conclusions. 1) There is an association between carotid IMT and the severity and extent of CAD. Carotid IMT seems to be a weaker predictor of coronary atherosclerosis in the proximal parts of the coronary tree than in the mid and distal parts. 2) PON1 activity has an important role in the pathogenesis of coronary atherosclerosis. More importantly, the study illustrates how the protective role of HDL could be modulated by its components such that equivalent serum concentrations of HDL cholesterol may not equate with an equivalent, potential protective capacity. 3) RLP-C in the fasting state is a good marker of postprandial TRLs. Circulating oxLDL increases in CAD patients postprandially. The highly significant positive correlation between postprandial TRLs and postprandial oxLDL suggests that the postprandial state creates oxidative stress. Our findings emphasize the fundamental role of LDL oxidation in the development of atherosclerosis even after inclusion of conventional CAD risk factors. 4) Disturbances in glucose metabolism are crucial in the pathogenesis of coronary atherosclerosis. In fact, subjects with IR are comparable with diabetic subjects in terms of severity and extent of CAD. 5) ApoE polymorphism is involved in the susceptibility to both carotid and coronary atherosclerosis.