8 resultados para Clinical chemistry - Technique
em CentAUR: Central Archive University of Reading - UK
Resumo:
BACKGROUND: The serum peptidome may be a valuable source of diagnostic cancer biomarkers. Previous mass spectrometry (MS) studies have suggested that groups of related peptides discriminatory for different cancer types are generated ex vivo from abundant serum proteins by tumor-specific exopeptidases. We tested 2 complementary serum profiling strategies to see if similar peptides could be found that discriminate ovarian cancer from benign cases and healthy controls. METHODS: We subjected identically collected and processed serum samples from healthy volunteers and patients to automated polypeptide extraction on octadecylsilane-coated magnetic beads and separately on ZipTips before MALDI-TOF MS profiling at 2 centers. The 2 platforms were compared and case control profiling data analyzed to find altered MS peak intensities. We tested models built from training datasets for both methods for their ability to classify a blinded test set. RESULTS: Both profiling platforms had CVs of approximately 15% and could be applied for high-throughput analysis of clinical samples. The 2 methods generated overlapping peptide profiles, with some differences in peak intensity in different mass regions. In cross-validation, models from training data gave diagnostic accuracies up to 87% for discriminating malignant ovarian cancer from healthy controls and up to 81% for discriminating malignant from benign samples. Diagnostic accuracies up to 71% (malignant vs healthy) and up to 65% (malignant vs benign) were obtained when the models were validated on the blinded test set. CONCLUSIONS: For ovarian cancer, altered MALDI-TOF MS peptide profiles alone cannot be used for accurate diagnoses.
Resumo:
The time-course of metabolic events following response to a model hepatotoxin ethionine (800 mg/kg) was investigated over a 7 day period in rats using high-resolution (1)H NMR spectroscopic analysis of urine and multivariate statistics. Complementary information was obtained by multivariate analysis of (1)H MAS NMR spectra of intact liver and by conventional histopathology and clinical chemistry of blood plasma. (1)H MAS NMR spectra of liver showed toxin-induced lipidosis 24 h postdose consistent with the steatosis observed by histopathology, while hypertaurinuria was suggestive of liver injury. Early biochemical changes in urine included elevation of guanidinoacetate, suggesting impaired methylation reactions. Urinary increases in 5-oxoproline and glycine suggested disruption of the gamma-glutamyl cycle. Signs of ATP depletion together with impairment of the energy metabolism were given from the decreased levels in tricarboxylic acid cycle intermediates, the appearance of ketone bodies in urine, the depletion of hepatic glucose and glycogen, and also hypoglycemia. The observed increase in nicotinuric acid in urine could be an indication of an increase in NAD catabolism, a possible consequence of ATP depletion. Effects on the gut microbiota were suggested by the observed urinary reductions in the microbial metabolites 3-/4-hydroxyphenyl propionic acid, dimethylamine, and tryptamine. At later stages of toxicity, there was evidence of kidney damage, as indicated by the tubular damage observed by histopathology, supported by increased urinary excretion of lactic acid, amino acids, and glucose. These studies have given new insights into mechanisms of ethionine-induced toxicity and show the value of multisystem level data integration in the understanding of experimental models of toxicity or disease.
Resumo:
An NMR-based pharmacometabonomic approach was applied to investigate inter-animal variation in response to isoniazid (INH; 200 and 400 mg/kg) in male Sprague-Dawley rats, alongside complementary clinical chemistry and histopathological analysis. Marked inter-animal variability in central nervous system (CNS) toxicity was identified following administration of a high dose of INH, which enabled characterization of CNS responders and CNS non-responders. High-resolution post-dose urinary (1)H NMR spectra were modeled both by their xenobiotic and endogenous metabolic information sets, enabling simultaneous identification of the differential metabolic fate of INH and its associated endogenous metabolic consequences in CNS responders and CNS non-responders. A characteristic xenobiotic metabolic profile was observed for CNS responders, which revealed higher urinary levels of pyruvate isonicotinylhydrazone and β-glucosyl isonicotinylhydrazide and lower levels of acetylisoniazid compared to CNS non-responders. This suggested that the capacity for acetylation of INH was lower in CNS responders, leading to increased metabolism via conjugation with pyruvate and glucose. In addition, the endogenous metabolic profile of CNS responders revealed higher urinary levels of lactate and glucose, in comparison to CNS non-responders. Pharmacometabonomic analysis of the pre-dose (1)H NMR urinary spectra identified a metabolic signature that correlated with the development of INH-induced adverse CNS effects and may represent a means of predicting adverse events and acetylation capacity when challenged with high dose INH. Given the widespread use of INH for the treatment of tuberculosis, this pharmacometabonomic screening approach may have translational potential for patient stratification to minimize adverse events.
Resumo:
Summary Reasons for performing study: Metabonomics is emerging as a powerful tool for disease screening and investigating mammalian metabolism. This study aims to create a metabolic framework by producing a preliminary reference guide for the normal equine metabolic milieu. Objectives: To metabolically profile plasma, urine and faecal water from healthy racehorses using high resolution 1H-NMR spectroscopy and to provide a list of dominant metabolites present in each biofluid for the benefit of future research in this area. Study design: This study was performed using seven Thoroughbreds in race training at a single time-point. Urine and faecal samples were collected non-invasively and plasma was obtained from samples taken for routine clinical chemistry purposes. Methods: Biofluids were analysed using 1H-NMR spectroscopy. Metabolite assignment was achieved via a range of 1D and 2D experiments. Results: A total of 102 metabolites were assigned across the three biological matrices. A core metabonome of 14 metabolites was ubiquitous across all biofluids. All biological matrices provided a unique window on different aspects of systematic metabolism. Urine was the most populated metabolite matrix with 65 identified metabolites, 39 of which were unique to this biological compartment. A number of these were related to gut microbial host co-metabolism. Faecal samples were the most metabolically variable between animals; acetate was responsible for the majority (28%) of this variation. Short chain fatty acids were the predominant features identified within this biofluid by 1H-NMR spectroscopy. Conclusions: Metabonomics provides a platform for investigating complex and dynamic interactions between the host and its consortium of gut microbes and has the potential to uncover markers for health and disease in a variety of biofluids. Inherent variation in faecal extracts along with the relative abundance of microbial-mammalian metabolites in urine and invasive nature of plasma sampling, infers that urine is the most appropriate biofluid for the purposes of metabonomic analysis.
Resumo:
The atmospheric chemistry of several gases used in industrial applications, C4F9OC2H5 (HFE-7200), C4F9OCH3 (HFE-7100), C3F7OCH3 (HFE-7000) and C3F7CH2OH, has been studied. The discharge flow technique coupled with mass-spectrometric detection has been used to study the kinetics of their reactions with OH radicals as a function of temperature. The infrared spectra of the compounds have also been measured. The following Arrhenius expressions for the reactions were determined (in units of cm3 molecule-1 s-1): k(OH + HFE-7200) = (6.9+2.3-1.7) × 10-11 exp(-(2030 ± 190)/T); k(OH + HFE-7100) = (2.8+3.2-1.5) × 10-11 exp(-(2200 ± 490)/T); k(OH + HFE-7000) = (2.0+1.2-0.7) × 10-11 exp(-(2130 ± 290)/T); and k(OH + C3F7CH2OH) = (1.4+0.3-0.2) × 10-11 exp(-(1460 ± 120)/T). From the infrared spectra, radiative forcing efficiencies were determined and compared with earlier estimates in the literature. These were combined with the kinetic data to estimate 100-year time horizon global warming potentials relative to CO2 of 69, 337, 499 and 36 for HFE-7200, HFE-7100, HFE-7000 and CF3CF2CF2CH2OH, respectively.
Resumo:
Tremor is a clinical feature characterized by oscillations of a part of the body. The detection and study of tremor is an important step in investigations seeking to explain underlying control strategies of the central nervous system under natural (or physiological) and pathological conditions. It is well established that tremorous activity is composed of deterministic and stochastic components. For this reason, the use of digital signal processing techniques (DSP) which take into account the nonlinearity and nonstationarity of such signals may bring new information into the signal analysis which is often obscured by traditional linear techniques (e.g. Fourier analysis). In this context, this paper introduces the application of the empirical mode decomposition (EMD) and Hilbert spectrum (HS), which are relatively new DSP techniques for the analysis of nonlinear and nonstationary time-series, for the study of tremor. Our results, obtained from the analysis of experimental signals collected from 31 patients with different neurological conditions, showed that the EMD could automatically decompose acquired signals into basic components, called intrinsic mode functions (IMFs), representing tremorous and voluntary activity. The identification of a physical meaning for IMFs in the context of tremor analysis suggests an alternative and new way of detecting tremorous activity. These results may be relevant for those applications requiring automatic detection of tremor. Furthermore, the energy of IMFs was visualized as a function of time and frequency by means of the HS. This analysis showed that the variation of energy of tremorous and voluntary activity could be distinguished and characterized on the HS. Such results may be relevant for those applications aiming to identify neurological disorders. In general, both the HS and EMD demonstrated to be very useful to perform objective analysis of any kind of tremor and can therefore be potentially used to perform functional assessment.
Resumo:
The night-time tropospheric chemistry of two stress-induced volatile organic compounds (VOCs), (Z)-pent-2-en-1-ol and pent-1-en-3-ol, has been studied at room temperature. Rate coefficients for reactions of the nitrate radical (NO3) with these pentenols were measured using the discharge-flow technique. Because of the relatively low volatility of these compounds, we employed off-axis continuous-wave cavity-enhanced absorption spectroscopy for detection of NO3 in order to be able to work in pseudo first-order conditions with the pentenols in large excess over NO3. The rate coefficients were determined to be (1.53 +/- 0.23) x 10(-13) and (1.39 +/- 0.19) x 10(-14) cm(3) molecule(-1) s(-1) for reactions of NO3 with (Z)-pent-2-en-1-ol and pent-1-en-3-ol. An attempt to study the kinetics of these reactions with a relative-rate technique, using N2O5 as source of NO3 resulted in significantly higher apparent rate coefficients. Performing relative-rate experiments in known excesses of NO2 allowed us to determine the rate coefficients for the N2O5 reactions to be (5.0 +/- 2.8) x 10(-19) cm(3) molecule(-1) s(-1) for (Z)-pent-2-en-1-ol, and (9.1 +/- 5.8) x 10(-19) cm(3) molecule(-1) s(-1) for pent-1-en-3-ol. We show that these relatively slow reactions can indeed interfere with rate determinations in conventional relative-rate experiments.
Resumo:
Active learning plays a strong role in mathematics and statistics, and formative problems are vital for developing key problem-solving skills. To keep students engaged and help them master the fundamentals before challenging themselves further, we have developed a system for delivering problems tailored to a student‟s current level of understanding. Specifically, by adapting simple methodology from clinical trials, a framework for delivering existing problems and other illustrative material has been developed, making use of macros in Excel. The problems are assigned a level of difficulty (a „dose‟), and problems are presented to the student in an order depending on their ability, i.e. based on their performance so far on other problems. We demonstrate and discuss the application of the approach with formative examples developed for a first year course on plane coordinate geometry, and also for problems centred on the topic of chi-square tests.