875 resultados para Metabolic flux analysis


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The primary goal of systems biology is to integrate complex omics data, and data obtained from traditional experimental studies in order to provide a holistic understanding of organismal function. One way of achieving this aim is to generate genome-scale metabolic models (GEMs), which contain information on all metabolites, enzyme-coding genes, and biochemical reactions in a biological system. Drosophila melanogaster GEM has not been reconstructed to date. Constraint-free genome-wide metabolic model of the fruit fly has been reconstructed in our lab, identifying gaps, where no enzyme was identified and metabolites were either only produced or consume. The main focus of the work presented in this thesis was to develop a pipeline for efficient gap filling using metabolomics approaches combined with standard reverse genetics methods, using 5-hydroxyisourate hydrolase (5-HIUH) as an example. 5-HIUH plays a role in urate degradation pathway. Inability to degrade urate can lead to inborn errors of metabolism (IEMs) in humans, including hyperuricemia. Based on sequence analysis Drosophila CG30016 gene was hypothesised to encode 5- HIUH. CG30016 knockout flies were examined to identify Malpighian tubules phenotype, and shortened lifespan might reflect kidney disorders in hyperuricemia in humans. Moreover, LC-MS analysis of mutant tubules revealed that CG30016 is involved in purine metabolism, and specifically urate degradation pathway. However, the exact role of the gene has not been identified, and the complete method for gap filling has not been developed. Nevertheless, thanks to the work presented here, we are a step closer towards the development of a gap-filling pipeline in Drosophila melanogaster GEM. Importantly, the areas that require further optimisation were identified and are the focus of future research. Moreover, LC-MS analysis confirmed that tubules rather than the whole fly were more suitable for metabolomics analysis of purine metabolism. Previously, Dow/Davies lab has generated the most complete tissue-specific transcriptomic atlas for Drosophila – FlyAtlas.org, which provides data on gene expression across multiple tissues of adult fly and larva. FlyAtlas revealed that transcripts of many genes are enriched in specific Drosophila tissues, and that it is possible to deduce the functions of individual tissues within the fly. Based on FlyAtlas data, it has become clear that the fly (like other metazoan species) must be considered as a set of tissues, each 2 with its own distinct transcriptional and functional profile. Moreover, it revealed that for about 30% of the genome, reverse genetic methods (i.e. mutation in an unknown gene followed by observation of phenotype) are only useful if specific tissues are investigated. Based on the FlyAtlas findings, we aimed to build a primary tissue-specific metabolome of the fruit fly, in order to establish whether different Drosophila tissues have different metabolomes and if they correspond to tissue-specific transcriptome of the fruit fly (FlyAtlas.org). Different fly tissues have been dissected and their metabolome elucidated using LC-MS. The results confirmed that tissue metabolomes differ significantly from each other and from the whole fly, and that some of these differences can be correlated to the tissue function. The results illustrate the need to study individual tissues as well as the whole organism. It is clear that some metabolites that play an important role in a given tissue might not be detected in the whole fly sample because their abundance is much lower in comparison to other metabolites present in all tissues, which prevent the detection of the tissue-specific compound.

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Background: Hyperuricemia is related to Metabolic Syndrome (MetS) and cardiovascular diseases, but the use of serum uric acid (UA) to diagnose MetS is currently ignored in clinical practices. Objectives: To examine the impact of serum UA on the diagnostic of MetS and the relationship of serum UA with cardiometabolic risk factors in apparently healthy Brazilian middle-aged men residents in a city of Minas Gerais. Methods: In a cross-sectional analysis, 289 apparently healthy middle-aged men underwent anthropometric, clinical, sociodemographic and blood serum biochemical evaluation. By using receive operating curve the internal cutoff of serum UA was determined (5.25 mg/dL). Results: Subjects with two or more components of MetS exhibited higher serum UA as compared to those with one or none component. The inclusion of serum UA ≥ 5.25mg/dL as an additional component of MetS increased the occurrence of this syndrome by 13%. Subjects with UA ≥ 5.25mg/dL showed high prevalence for MetS and association with its components (central obesity, hypertriglyceridemia, dyslipidemia and hypertension) as well as atherogenic risk. Conclusions: Serum UA has an important impact on the diagnostic of MetS and is related to cardiometabolic risk factors in apparently healthy Brazilian middle-aged men. Its use in clinical practices could aggregate accuracy to diagnose MetS.

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We investigate the structure of strongly nonlinear Rayleigh–Bénard convection cells in the asymptotic limit of large Rayleigh number and fixed, moderate Prandtl number. Unlike the flows analyzed in prior theoretical studies of infinite Prandtl number convection, our cellular solutions exhibit dynamically inviscid constant-vorticity cores. By solving an integral equation for the cell-edge temperature distribution, we are able to predict, as a function of cell aspect ratio, the value of the core vorticity, details of the flow within the thin boundary layers and rising/falling plumes adjacent to the edges of the convection cell, and, in particular, the bulk heat flux through the layer. The results of our asymptotic analysis are corroborated using full pseudospectral numerical simulations and confirm that the heat flux is maximized for convection cells that are roughly square in cross section.

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Metamamterials are 1D, 2D or 3D arrays of articial atoms. The articial atoms, called "meta-atoms", can be any component with tailorable electromagnetic properties, such as resonators, LC circuits, nano particles, and so on. By designing the properties of individual meta-atoms and the interaction created by putting them in a lattice, one can create a metamaterial with intriguing properties not found in nature. My Ph. D. work examines the meta-atoms based on radio frequency superconducting quantum interference devices (rf-SQUIDs); their tunability with dc magnetic field, rf magnetic field, and temperature are studied. The rf-SQUIDs are superconducting split ring resonators in which the usual capacitance is supplemented with a Josephson junction, which introduces strong nonlinearity in the rf properties. At relatively low rf magnetic field, a magnetic field tunability of the resonant frequency of up to 80 THz/Gauss by dc magnetic field is observed, and a total frequency tunability of 100% is achieved. The macroscopic quantum superconducting metamaterial also shows manipulative self-induced broadband transparency due to a qualitatively novel nonlinear mechanism that is different from conventional electromagnetically induced transparency (EIT) or its classical analogs. A near complete disappearance of resonant absorption under a range of applied rf flux is observed experimentally and explained theoretically. The transparency comes from the intrinsic bi-stability and can be tuned on/ off easily by altering rf and dc magnetic fields, temperature and history. Hysteretic in situ 100% tunability of transparency paves the way for auto-cloaking metamaterials, intensity dependent filters, and fast-tunable power limiters. An rf-SQUID metamaterial is shown to have qualitatively the same behavior as a single rf-SQUID with regards to dc flux, rf flux and temperature tuning. The two-tone response of self-resonant rf-SQUID meta-atoms and metamaterials is then studied here via intermodulation (IM) measurement over a broad range of tone frequencies and tone powers. A sharp onset followed by a surprising strongly suppressed IM region near the resonance is observed. This behavior can be understood employing methods in nonlinear dynamics; the sharp onset, and the gap of IM, are due to sudden state jumps during a beat of the two-tone sum input signal. The theory predicts that the IM can be manipulated with tone power, center frequency, frequency difference between the two tones, and temperature. This quantitative understanding potentially allows for the design of rf-SQUID metamaterials with either very low or very high IM response.

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In natural environments, bacterial physiology is frequently characterized by slow metabolic rates and complex cellular heterogeneities. The opportunistic pathogen Pseudomonas aeruginosa provides one such example; P. aeruginosa forms untreatable chronic biofilm infections of the cystic fibrosis lung, where oxygen limitation can lead to states of metabolic dormancy. To better understand the biology of these states, in vitro experiments must be adapted to better recapitulate natural settings. However, low rates of protein turnover and cellular or phenotypic complexity make these systems difficult to study using established methods. Here we adapt the bioorthogonal noncanonical amino acid tagging (BONCAT) method for time- and cell-selective proteomic analysis to the study of P. aeruginosa. Analysis of proteins synthesized in an anoxic dormancy state led to the discovery of a new type of transcriptional regulator which we designated SutA. We performed detailed analyses of SutA’s role in transcription under slow growth states and we elucidated the structural basis for its regulatory behavior. Additionally, we used cell-selective targeting of BONCAT labeling to measure the dynamic proteomic response of an antibiotic-tolerant biofilm subpopulation. Overall this work shows the utility of selective proteomics as applied to bacterial physiology and describes the broad biological insight obtained from that application.

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Introduction: Chromium is an essential trace mineral for carbohydrate and lipid metabolism, which is currently prescribed to control diabetes mellitus. Results of previous systematic reviews and meta-analyses of chromium supplementation and metabolic profiles in diabetes have been inconsistent. Aim: The objective of this meta-analysis was to assess the effects on metabolic profiles and safety of chromium supplementation in type 2 diabetes mellitus and cholesterol. Methods: Literature searches in PubMed, Scopus and Web of Science were made by use of related terms-keywords and randomized clinical trials during the period of 2000-2014. Results: Thirteen trials fulfilled the inclusion criteria and were included in this systematic review. Total doses of Cr supplementation and brewer's yeast ranged from 42 to 1,000 µg/day, and duration of supplementation ranged from 30 to 120 days. The analysis indicated that there was a significant effect of chromium supplementation in diabetics on fasting plasma glucose with a weighted average effect size of -29.26 mg/dL, p = 0.01, CI 95% = -52.4 to -6.09; and on total cholesterol with a weighted average effect size of -6.7 mg/dL, p = 0.01, CI 95% = -11.88 to -1.53. Conclusions: The available evidence suggests favourable effects of chromium supplementation on glycaemic control in patients with diabetes. Chromium supplementation may additionally improve total cholesterol levels.

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Background: Mutation analysis has identified a G-> A transition in the promoter region of TNF-alpha gene at position -308 (rs1800629). Objective: The aim of our study was to investigate the influence of polymorphism in -308 GA promoter variant of the TNF alpha gene on metabolic response and weight loss secondary to two hypocaloric diets. Method: A sample of 283 obese subjects was enrolled in a consecutive prospective way. In the basal visit, patients were randomly allocated during 9 months to diet HP (high protein/low carbohydrate hypocaloric diet) and diet S (standard hypocaloric diet). Results: There were no significant differences between the positive effects on weight loss in either genotype group with both diets. With both diets and only in wild genotype (diet HP vs. diet S), total cholesterol (-9.1 ± 3.4 mg/dL vs. -6.9 ± 2.0 mg/dL; p > 0.05), LDL cholesterol (-9.0 ± 2.9 mg/dL vs. -6.5 ± 2.1 mg/dL; p > 0.05) and triglycerides (-23.1 ± 5.1 mg/dL vs. -12.3 ± 4.8 mg/dL; p < 0.05) decreased. The improvement in triglycerides was higher in subjects without A allele. With diet HP and only in wild genotype, insulin levels (-3.1 ± 1.8 UI/L; p < 0.05) and HOMA-R (-0.8 ± 0.1 units; p < 0.05) decreased. Conclusion: Carriers of -308 GG promoter variant of TNF-alpha gene have a better metabolic response than -308 GA obese with a high protein hypocaloric diet.

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Introduction: The inadequate reporting of cross-sectional studies, as in the case of the prevalence of metabolic syndrome, could cause problems in the synthesis of new evidence and lead to errors in the formulation of public policies. Objective: To evaluate the reporting quality of the articles regarding metabolic syndrome prevalence in Peruvian adults using the STROBE recommendations. Methods: We conducted a thorough literature search with the terms "Metabolic Syndrome", "Sindrome Metabolico" and "Peru" in MEDLINE/PubMed, LILACS, SciELO, LIPECS and BVS-Peru until December 2014. We selected those who were populationbased observational studies with randomized sampling that reported prevalence of metabolic syndrome in adults aged 18 or more of both sexes. Information was analysed through the STROBE score per item and recommendation. Results: Seventeen articles were included in this study. All articles met the recommendations related to the report of the study’s rationale, design, and provision of summary measures. The recommendations with the lowest scores were those related to the sensitivity analysis (8%, n= 1/17), participant flowchart (18%, n= 3/17), missing data analysis (24%, n= 4/17), and number of participants in each study phase (24%, n= 4/17). Conclusion: Cross-sectional studies regarding the prevalence of metabolic syndrome in peruvian adults have an inadequate reporting on the methods and results sections. We identified a clear need to improve the quality of such studies.

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Introduction: The inadequate reporting of cross-sectional studies, as in the case of the prevalence of metabolic syndrome, could cause problems in the synthesis of new evidence and lead to errors in the formulation of public policies. Objective: To evaluate the reporting quality of the articles regarding metabolic syndrome prevalence in Peruvian adults using the STROBE recommendations. Methods: We conducted a thorough literature search with the terms "Metabolic Syndrome", "Sindrome Metabolico" and "Peru" in MEDLINE/PubMed, LILACS, SciELO, LIPECS and BVS-Peru until December 2014. We selected those who were population-based observational studies with randomized sampling that reported prevalence of metabolic syndrome in adults aged 18 or more of both sexes. Information was analysed through the STROBE score per item and recommendation. Results: Seventeen articles were included in this study. All articles met the recommendations related to the report of the study’s rationale, design, and provision of summary measures. The recommendations with the lowest scores were those related to the sensitivity analysis (8%, n= 1/17), participant flowchart (18%, n= 3/17), missing data analysis (24%, n= 4/17), and number of participants in each study phase (24%, n= 4/17). Conclusion: Cross-sectional studies regarding the prevalence of metabolic syndrome in peruvian adults have an inadequate reporting on the methods and results sections. We identified a clear need to improve the quality of such studies.

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The emergence of mass spectrometry-based proteomics has revolutionized the study of proteins and their abundances, functions, interactions, and modifications. However, in a multicellular organism, it is difficult to monitor dynamic changes in protein synthesis in a specific cell type within its native environment. In this thesis, we describe methods that enable the metabolic labeling, purification, and analysis of proteins in specific cell types and during defined periods in live animals. We first engineered a eukaryotic phenylalanyl-tRNA synthetase (PheRS) to selectively recognize the unnatural L-phenylalanine analog p-azido-L-phenylalanine (Azf). Using Caenorhabditis elegans, we expressed the engineered PheRS in a cell type of choice (i.e. body wall muscles, intestinal epithelial cells, neurons, pharyngeal muscles), permitting proteins in those cells -- and only those cells -- to be labeled with azides. Labeled proteins are therefore subject to "click" conjugation to cyclooctyne-functionalized affnity probes, separation from the rest of the protein pool and identification by mass spectrometry. By coupling our methodology with heavy isotopic labeling, we successfully identified proteins -- including proteins with previously unknown expression patterns -- expressed in targeted subsets of cells. While cell types like body wall or pharyngeal muscles can be targeted with a single promoter, many cells cannot; spatiotemporal selectivity typically results from the combinatorial action of multiple regulators. To enhance spatiotemporal selectivity, we next developed a two-component system to drive overlapping -- but not identical -- patterns of expression of engineered PheRS, restricting labeling to cells that express both elements. Specifically, we developed a split-intein-based split-PheRS system for highly efficient PheRS-reconstitution through protein splicing. Together, these tools represent a powerful approach for unbiased discovery of proteins uniquely expressed in a subset of cells at specific developmental stages.

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Analyzing large-scale gene expression data is a labor-intensive and time-consuming process. To make data analysis easier, we developed a set of pipelines for rapid processing and analysis poplar gene expression data for knowledge discovery. Of all pipelines developed, differentially expressed genes (DEGs) pipeline is the one designed to identify biologically important genes that are differentially expressed in one of multiple time points for conditions. Pathway analysis pipeline was designed to identify the differentially expression metabolic pathways. Protein domain enrichment pipeline can identify the enriched protein domains present in the DEGs. Finally, Gene Ontology (GO) enrichment analysis pipeline was developed to identify the enriched GO terms in the DEGs. Our pipeline tools can analyze both microarray gene data and high-throughput gene data. These two types of data are obtained by two different technologies. A microarray technology is to measure gene expression levels via microarray chips, a collection of microscopic DNA spots attached to a solid (glass) surface, whereas high throughput sequencing, also called as the next-generation sequencing, is a new technology to measure gene expression levels by directly sequencing mRNAs, and obtaining each mRNA’s copy numbers in cells or tissues. We also developed a web portal (http://sys.bio.mtu.edu/) to make all pipelines available to public to facilitate users to analyze their gene expression data. In addition to the analyses mentioned above, it can also perform GO hierarchy analysis, i.e. construct GO trees using a list of GO terms as an input.

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Bladder cancer is among the most common cancers in the UK and conventional detection techniques suffer from low sensitivity, low specificity, or both. Recent attempts to address the disparity have led to progress in the field of autofluorescence as a means to diagnose the disease with high efficiency, however there is still a lot not known about autofluorescence profiles in the disease. The multi-functional diagnostic system "LAKK-M" was used to assess autofluorescence profiles of healthy and cancerous bladder tissue to identify novel biomarkers of the disease. Statistically significant differences were observed in the optical redox ratio (a measure of tissue metabolic activity), the amplitude of endogenous porphyrins and the NADH/porphyrin ratio between tissue types. These findings could advance understanding of bladder cancer and aid in the development of new techniques for detection and surveillance.

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Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults.

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Abstract Objectives: To assess the adherence to therapeutic regimen; to determine the Hemoglobin Glycation Index (HbA1c); to analyse the relationship that exists between the adherence to therapeutic regimen and metabolic control. Design: correlational analytical study, carried out according to a cross-sectional perspective. Participants: A non-probabilistic sample of 266 people with type 1 diabetes aged between 18 and 78 years old (mean M = 51.02 ± SD = 18.710), attending follow-up diabetes consultations. Mostly male individuals (51.88%), with low schooling level (50.75% had only inished elementar school). Measuring Instruments: We used the following data collection tools: a questionnaire on clinical and socio-demographic data, blood analysis of venous blood to determine the glycated hemoglobin level (HbA1c).Three self-report scales were used: Accession to Diabetes Treatment (Matos, 1999), Self-perception Scale (Vaz Serra, 1986) and Social Support Scale (Matos & Rodrigues, 2000). Results: In a sample in which the mean disease duration is 12.75 years, 69.17% of the sample run glycemic control tests between once a day and four times a year and 42.86% of them undergo insulin treatment. In the last 3 weeks, 26.32% of these people have experienced an average of 4.22 to 44.36%, hypoglycemic crises and experienced an average of 6.18 hyperglycemic crises. 57% of the individuals have showed a poor metabolic control (mean HbA1c higher than 7.5% (HbA1c mean M ≥ 7.50%). The mean psychosocial proile revealed individuals who show a decent self-esteem (M = 70.81) and acceptable social support (M = 58.89). Conclusions: The results suggest we should develop a kind of investigation that could be used to monitor the strenght of the mediation effect effect of the psychosocial predictive dimension of the adherence, since it has become essential to support a multidisciplinary approach which center lays in the promotion of a co-responsible self-management from the person who suffers from diabetes. This will enable a better quality of life; fewer years of people’s lives lost prematurely and a better health with less economical costs for citizens and healthcare systems.

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In this paper we prove well-posedness for a measure-valued continuity equation with solution-dependent velocity and flux boundary conditions, posed on a bounded one-dimensional domain. We generalize the results of an earlier paper [J. Differential Equations, 259 (2015), pp. 10681097] to settings where the dynamics are driven by interactions. In a forward-Euler-like approach, we construct a time-discretized version of the original problem and employ those results as a building block within each subinterval. A limit solution is obtained as the mesh size of the time discretization goes to zero. Moreover, the limit is independent of the specific way of partitioning the time interval [0, T]. This paper is partially based on results presented in Chapter 5 of [Evolution Equations for Systems Governed by Social Interactions, Ph.D. thesis, Eindhoven University of Technology, 2015], while a number of issues that were still open there are now resolved.