917 resultados para periodic perturbations
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We introduce the use of Ingenuity Pathway Analysis to analyzing global metabonomics in order to characterize phenotypically biochemical perturbations and the potential mechanisms of the gentamicin-induced toxicity in multiple organs. A single dose of gentamicin was administered to Sprague Dawley rats (200 mg/kg, n = 6) and urine samples were collected at -24-0 h pre-dosage, 0-24, 24-48, 48-72 and 72-96 h post-dosage of gentamicin. The urine metabonomics analysis was performed by UPLC/MS, and the mass spectra signals of the detected metabolites were systematically deconvoluted and analyzed by pattern recognition analyses (Heatmap, PCA and PLS-DA), revealing a time-dependency of the biochemical perturbations induced by gentamicin toxicity. As result, the holistic metabolome change induced by gentamicin toxicity in the animal's organisms was characterized. Several metabolites involved in amino acid metabolism were identified in urine, and it was confirmed that gentamicin biochemical perturbations can be foreseen from these biomarkers. Notoriously, it was found that gentamicin induced toxicity in multiple organs system in the laboratory rats. The proof-of-knowledge based Ingenuity Pathway Analysis revealed gentamicin induced liver and heart toxicity, along with the previously known toxicity in kidney. The metabolites creatine, nicotinic acid, prostaglandin E2, and cholic acid were identified and validated as phenotypic biomarkers of gentamicin induced toxicity. Altogether, the significance of the use of metabonomics analyses in the assessment of drug toxicity is highlighted once more; furthermore, this work demonstrated the powerful predictive potential of the Ingenuity Pathway Analysis to study of drug toxicity and its valuable complementation for metabonomics based assessment of the drug toxicity.
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Atherosclerotic cardiovascular disease remains the leading cause of morbidity and mortality in industrialized societies. The lack of metabolite biomarkers has impeded the clinical diagnosis of atherosclerosis so far. In this study, stable atherosclerosis patients (n=16) and age- and sex-matched non-atherosclerosis healthy subjects (n=28) were recruited from the local community (Harbin, P. R. China). The plasma was collected from each study subject and was subjected to metabolomics analysis by GC/MS. Pattern recognition analyses (principal components analysis, orthogonal partial least-squares discriminate analysis, and hierarchical clustering analysis) commonly demonstrated plasma metabolome, which was significantly different from atherosclerotic and non-atherosclerotic subjects. The development of atherosclerosis-induced metabolic perturbations of fatty acids, such as palmitate, stearate, and 1-monolinoleoylglycerol, was confirmed consistent with previous publication, showing that palmitate significantly contributes to atherosclerosis development via targeting apoptosis and inflammation pathways. Altogether, this study demonstrated that the development of atherosclerosis directly perturbed fatty acid metabolism, especially that of palmitate, which was confirmed as a phenotypic biomarker for clinical diagnosis of atherosclerosis.
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BACKGROUND & AIMS Metabolomics is comprehensive analysis of low-molecular-weight endogenous metabolites in a biological sample. It could enable mapping of perturbations of early biochemical changes in diseases and hence provide an opportunity to develop predictive biomarkers that could provide valuable insights into the mechanisms of diseases. The aim of this study was to elucidate the changes in endogenous metabolites and to phenotype the metabolic profiling of d-galactosamine (GalN)-inducing acute hepatitis in rats by UPLC-ESI MS. METHODS The systemic biochemical actions of GalN administration (ip, 400 mg/kg) have been investigated in male wistar rats using conventional clinical chemistry, liver histopathology and metabolomic analysis of UPLC- ESI MS of urine. The urine was collected predose (-24 to 0 h) and 0-24, 24-48, 48-72, 72-96 h post-dose. Mass spectrometry of the urine was analysed visually and via conjunction with multivariate data analysis. RESULTS Results demonstrated that there was a time-dependent biochemical effect of GalN dosed on the levels of a range of low-molecular-weight metabolites in urine, which was correlated with developing phase of the GalN-inducing acute hepatitis. Urinary excretion of beta-hydroxybutanoic acid and citric acid was decreased following GalN dosing, whereas that of glycocholic acid, indole-3-acetic acid, sphinganine, n-acetyl-l-phenylalanine, cholic acid and creatinine excretion was increased, which suggests that several key metabolic pathways such as energy metabolism, lipid metabolism and amino acid metabolism were perturbed by GalN. CONCLUSION This metabolomic investigation demonstrates that this robust non-invasive tool offers insight into the metabolic states of diseases.
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In Australia, and elsewhere, the movement of trains on long-haul rail networks is usually planned in advance. Typically, a train plan is developed to confirm that the required train movements and track maintenance activities can occur. The plan specifies when track segments will be occupied by particular trains and maintenance activities. On the day of operation, a train controller monitors and controls the movement of trains and maintenance crews, and updates the train plan in response to unplanned disruptions. It can be difficult to predict how good a plan will be in practice. The main performance indicator for a train service should be reliability - the proportion of trains running the service that complete at or before the scheduled time. We define the robustness of a planned train service to be the expected reliability. The robustness of individual train services and for a train plan as a whole can be estimated by simulating the train plan many times with random, but realistic, perturbations to train departure times and segment durations, and then analysing the distributions of arrival times. This process can also be used to set arrival times that will achieve a desired level of robustness for each train service.
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Objectives The aim of this study was to evaluate the role of cardiac K+ channel gene variants in families with atrial fibrillation (AF). Background The K+ channels play a major role in atrial repolarization but single mutations in cardiac K+ channel genes are infrequently present in AF families. The collective effect of background K+ channel variants of varying prevalence and effect size on the atrial substrate for AF is largely unexplored. Methods Genes encoding the major cardiac K+ channels were resequenced in 80 AF probands. Nonsynonymous coding sequence variants identified in AF probands were evaluated in 240 control subjects. Novel variants were characterized using patch-clamp techniques and in silico modeling was performed using the Courtemanche atrial cell model. Results Nineteen nonsynonymous variants in 9 genes were found, including 11 rare variants. Rare variants were more frequent in AF probands (18.8% vs. 4.2%, p < 0.001), and the mean number of variants was greater (0.21 vs. 0.04, p < 0.001). The majority of K+ channel variants individually had modest functional effects. Modeling simulations to evaluate combinations of K+ channel variants of varying population frequency indicated that simultaneous small perturbations of multiple current densities had nonlinear interactions and could result in substantial (>30 ms) shortening or lengthening of action potential duration as well as increased dispersion of repolarization. Conclusions Families with AF show an excess of rare functional K+ channel gene variants of varying phenotypic effect size that may contribute to an atrial arrhythmogenic substrate. Atrial cell modeling is a useful tool to assess epistatic interactions between multiple variants.
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The synthesis and evaluation of novel resveratrol-based nitroxides have been explored for the potential treatment of hypertension. New methodology for the direct aryl iodination of isoindoline and isoindoline nitroxide using periodic acid and potassium iodide in concentrated sulphuric acid was developed. Diiodinated tetramethyl and tetraethyl isoindolines and a tetramethyl isoindoline nitroxide were prepared in excellent yields (70 – 82%). A diiodinated tetraethyl isoindoline nitroxide was generated from the corresponding nitroxide in modest yield (37%) alongside iodinated nitrones. The mono-iodinated species were also generated in modest yields (34 – 48%). Incorporation of the nitroxide unit into the structure of resveratrol was achieved using palladium-catalysed Heck coupling. Use of the previously prepared iodo products 5-iodo-1,1,3,3-tetramethylisoindolin-2-yloyl 18 and 5,6-diiodo-1,1,3,3-tetramethylisoindolin-2-yloyl 22 gave resveratrol nitroxides 12 and 13 in yields of 50% (optimized) and 1.6% respectively. Preliminary evaluation of the resveratrol analogue 12 as a treatment for hypertension was undertaken in the DOCA-salt rat model. A reduction in systolic blood pressure as well as alleviation of ventricular hypertrophy was observed. A larger study involving the DOCA salt rats is currently in progress.
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We have studied weak links and dc-SQUIDs made from pulsed laser deposited YBa2Cu3O7-δ thin films on Y-ZrO 2 bicrystal substrates. The transport properties of the weak links were studied as a function of the misorientation angle (θ) between the two halves of the bicrystal and an exponential dependence of the weak link critical current density was observed for angles up to 40°at 77 K. Josephson effects with clear microwave and magnetic field responses were observed. An optimum dc-SQUID performance at 77 K was obtained for θ=32°. At this temperature, we achieved a periodic magnetic field response with a modulation depth of 12 μV.
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Atomic scale periodic ripples that extend for several nanometers on the surface of adjacent graphitic grains have been observed for the first time on highly ordered pyrolitic graphite by UHV-STM. The ripples emanate from a grain boundary, and are explained in terms of a mechanical deformation due to the elastic strain accumulated along the GB, which is relieved out-of-plane in the topmost graphene layer. We present a molecular dynamics model that accounts for the formation of similar ripples as result of the lattice mismatch induced by two different grain orientations.
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A new method for the direct aryl iodination of isoindolines and isoindoline nitroxides which utilizes periodic acid and potassium iodide in sulfuric acid is presented. Di-iodo functionalized tetramethyl and tetraethyl isoindolines and a di-iodo tetramethyl isoindoline nitroxide were prepared in high yield (70-82%). The analogous mono-iodo species were afforded in modest yield (34-48%). Iodinated nitrones were also obtained from a tetraethyl isoindoline nitroxide.
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Bone, a hard biological material, possesses a combination of high stiffness and toughness, even though the main basic building blocks of bone are simply mineral platelets and protein molecules. Bone has a very complex microstructure with at least seven hierachical levels. This unique material characteristic attracts great attention, but the deformation mechanisms in bone have not been well understood. Simulation at nano-length scale such as molecular dynamics (MD) is proven to be a powerful tool to investigate bone nanomechanics for developing new artificial biological materials. This study focuses on the ultra large and thin layer of extrafibrillar protein matrix (thickness = ~ 1 nm) located between mineralized collagen fibrils (MCF). Non-collagenous proteins such as osteopontin (OPN) can be found in this protein matrix, while MCF consists mainly of hydroxyapatite (HA) nanoplatelets (thickness = 1.5 – 4.5 nm). By using molecular dynamics method, an OPN peptide was pulled between two HA mineral platelets with water in presence. Periodic boundary condition (PBC) was applied. The results indicate that the mechanical response of OPN peptide greatly depends on the attractive electrostatics interaction between the acidic residues in OPN peptide and HA mineral surfaces. These bonds restrict the movement of OPN peptide, leading to a high energy dissipation under shear loading.
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Bacterial siderophores are a group of chemically diverse, virulence-associated secondary metabolites whose expression exerts metabolic costs. A combined bacterial genetic and metabolomic approach revealed differential metabolomic impacts associated with biosynthesis of different siderophore structural families. Despite myriad genetic differences, the metabolome of a cheater mutant lacking a single set of siderophore biosynthetic genes more closely approximate that of a nonpathogenic K12 strain than its isogenic, uropathogen parent strain. Siderophore types associated with greater metabolomic perturbations are less common among human isolates, suggesting that metabolic costs influence success in a human population. Although different siderophores share a common iron acquisition function, our analysis shows how a metabolomic approach can distinguish their relative metabolic impacts in E.coli.
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Interdisciplinary research is often funded by national government initiatives or large corporate sponsorship, and as such, demands periodic reporting on the use of those funds. For reasons of accountability, governance and communication to the tax payer, knowledge of the outcomes of the research need to be measured and understood. The interdisciplinary approach to research raises many challenges for impact reporting. This presentation will consider what are the best practice workflow models and methodologies.Novel methodologies that can be added to the usual metrics of academic publications include analysis of percentage share of total publications in a subject or keyword field, calculating most cited publication in a key phrase category, analysis of who has cited or reviewed the work, and benchmarking of this data against others in that same category. At QUT, interest in how collaborative networking is trending in a research theme has led to the creation of some useful co-authorship graphs that demonstrate the network positions of authors and the strength of their scientific collaborations within a group. The scale of international collaborations is also worth including in the assessment. However, despite all of the tools and techniques available, the most useful way a researcher can help themselves and the process is to set up and maintain their researcher identifier and profile.
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For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.
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Wireless networked control systems (WNCSs) have been increasingly deployed in industrial applications. As they require timely data packet transmissions, it is difficult to make efficient use of the limited channel resources, particularly in contention based wireless networks in the layered network architecture. Aiming to maintain the WNCSs under critical real-time traffic condition at which the WNCSs marginally meet the real-time requirements, a cross-layer design (CLD) approach is presented in this paper to adaptively adjust the control period to achieve improved channel utilization while still maintaining effective and timely packet transmissions. The effectiveness of the proposed approach is demonstrated through simulation studies.
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Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.