955 resultados para analytical methods


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Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

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In this work, separation methods have been developed for the analysis of anthropogenic transuranium elements plutonium, americium, curium and neptunium from environmental samples contaminated by global nuclear weapons testing and the Chernobyl accident. The analytical methods utilized in this study are based on extraction chromatography. Highly varying atmospheric plutonium isotope concentrations and activity ratios were found at both Kurchatov (Kazakhstan), near the former Semipalatinsk test site, and Sodankylä (Finland). The origin of plutonium is almost impossible to identify at Kurchatov, since hundreds of nuclear tests were performed at the Semipalatinsk test site. In Sodankylä, plutonium in the surface air originated from nuclear weapons testing, conducted mostly by USSR and USA before the sampling year 1963. The variation in americium, curium and neptunium concentrations was great as well in peat samples collected in southern and central Finland in 1986 immediately after the Chernobyl accident. The main source of transuranium contamination in peats was from global nuclear test fallout, although there are wide regional differences in the fraction of Chernobyl-originated activity (of the total activity) for americium, curium and neptunium.

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In this paper, common criterions about residual strength evaluation at home and abroad are generalized and seven methods are acquired, namely ASME-B31G, DM, Wes-2805-97, CVDA-84, Burdekin, Irwin and J integral methods. BP neural network are Combined with Genetic Algorithm (GA) named by modified BP-GA methods to successfully predict residual strength and critical pressure of injecting water, corrosion pipelines. Examples are shown that calculation results of every kind of method have great difference and calculating values of Wes-2805-97 criterion, ASME-B31G criterion, CVDA-84 criterion and Irwin fracture mechanics model are conservative and higher than, those of J integral methods while calculating values of Burdiken model and DM fracture mechanics model are dangerous and less than those of J integral methods and calculating values of modified BP-GA methods are close and moderate to those of J integral methods. Therefore modified BP-GA methods and J integral methods are considered better methods to calculate residual strength and critical pressure of injecting water corrosion pipelines

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This document describes the analytical methods used to quantify core organic chemicals in tissue and sediment collected as part of NOAA’s National Status and Trends Program (NS&T) for the years 2000-2006. Organic contaminat analytical methods used during the early years of the program are described in NOAA Technical Memoranda NOS ORCA 71 and 130 (Lauenstein and Cantillo, 1993; Lauenstein and Cantillo, 1998) for the years 1984-1992 and 1993-1996, respectively. These reports are available from our website (http://www.ccma.nos.gov) The methods detailed in this document were utilized by the Mussel Watch Project and Bioeffects Project, which are both part of the NS&T program. The Mussel Watch Project has been monitoring contaminants in bivalves and sediments since 1986 and is the longest active national contaminant monitoring program operating in U.S. costal waters. Approximately 280 Mussel Watch sites are sampled on a biennial and decadal timescale for bivalve tissue and sediment respectively. Similarly, the Bioeffects Assessment Project began in 1986 to characterize estuaries and near coastal environs. Using the sediment quality triad approach that measures; (1) levels of contaminants in sediments, (2) incidence and severity of toxicity, and (3) benthic macrofaunal conmmunities, the Bioeffects Project describes the spatial extent of sediment toxicity. Contaminant assessment is a core function of both projects. These methods, while discussed here in the context of sediment and bivalve tissue, were also used with other matricies including: fish fillet, fish liver, nepheloid layer, and suspended particulate matter. The methods described herein are for the core organic contaminants monitored in the NS&T Program and include polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), butyltins, and organochlorines that have been analyzed consistently over the past 15-20 years. Organic contaminants such as dioxins, perfluoro compounds and polybrominated biphenyl ethers (PBDEs) were analyzed periodically in special studies of the NS&T Program and will be described in another document. All of the analytical techniques described in this document were used by B&B Laboratories, Inc, an affiliate of TDI-Brook International, Inc. in College Station, Texas under contract to NOAA. The NS&T Program uses a performance-based system approach to obtain the best possible data quality and comparability, and requires laboratories to demonstrate precision, accuracy, and sensitivity to ensure results-based performance goals and measures. (PDF contains 75 pages)

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Polycyclic aromatic hydrocarbons, butyltins, polychlorinated biphenyls, DDT and metabolites, other chlorinated pesticides, trace and major elements, and a number of measures of contaminant effects are quantified in bivalves and sediments collected as part of the NOAA National Status and Trends (NS&T) Program. This document contains descriptions of some of the sampling and analytical protocols used by NS&T contract laboratories from 1993 through 1996. (PDF contains 257 pages)

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After 20 annual meetings it is worth to have a look back and to see how it has started. There has been very little collaboration on research projects between member institutes under the auspices of WEFTA, co-operation in more neutral areas of common interest was developed at an early stage. The area which has proved very fruitful is methodology. It was agreed that probably the best way to make progress was to arrange meetings at each laboratory in turn where experienced, practising scientists could describe in detail how they carried out analyses. In this way, difficulties could be demonstrated or uncovered, and the accuracy, precision, efficiency and cost of the methods used in different laboratories could be compared.

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IDOKI SCF Technologies S.L. is a technology-based company, set up on September 2006 in Derio (Biscay) with the main scope of developing extraction and purification processes based on the use of supercritical fluid extraction technology (SFE) in food processing, extraction of natural products and the production of personal care products. IDOKI¿s researchers have been working on many different R&D projects so far, most of them using this technology. However, the optimization of a SFE method for the different matrices cannot be performed unless we have an analytical method for the characterisation of the extracts obtained in each experiment. The analytical methods are also essential for the quality control of the raw materials that are going to be used and also for the final product. This PhD thesis was born to tackle this problem and therefore, it is based on the development of different analytical methods for the characterisation of the extracts and products. The projects that we could include in this thesis were the following: the extraction propolis, the recovery of agroindustrial residues (soy and wine) and the dealcoholisation of wine.On the one hand, for the extraction of propolis, several UV-Vis spectroscopic methods were used in order to measure the antioxidant capacity and the total polyphenol and flavonoid content of the extracts. A SFC method was also developed in order to measure more specific phenolic compounds. On the other hand, for the recovery of agroindustrial residues UV-Vis spectroscopy was used to determine the total polyphenol content and two SFC methods were developed to analyse different phenolic compounds. Extraction methods such as MAE, FUSE and rotary agitation were also evaluated for the characterisation of the raw materials.Finally, for the dealcoholisation of wine, the development of a SBSE-TD-GC-MS and DHS-TD-GC-MS methods for the analysis of aromas and a NIR spectroscopic method for the determination of ethanol content with the help of chemometrics was necessary. Most of these methods are typically used in IDOKI¿s lab as routine analyses apart from others not included in this PhD thesis.

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This document contains analytical methods that detail the procedures for determining major and trace element concentrations in bivalve tissue and sediment samples collected as part of the National Status and Trends Program (NS&T) for the years 2000-2006. Previously published NOAA Technical Memoranda NOS ORCA 71 and 130 (Lauenstein and Cantillo, 1993; Lauenstein and Cantillo, 1998) detail trace element analyses for the years 1984-1992 and 1993-1996, respectively, and include ancillary, histopathology, and contaminant (organic and trace element) analytical methods. The methods presented in this document for trace element analysis were utilized by the NS&T Mussel Watch and Bioeffects Projects. The Mussel Watch Project has been monitoring contaminants in bivalves and sediment for over 20 years, and is the longest active contaminant monitoring program operating in U.S. costal waters. Approximately 280 Mussel Watch sites are monitored on biennial and decadal timescales using bivalve tissue and sediment, respectively. The Bioeffects Project applies the sediment quality approach, which uses sediment contamination measurements, toxicity tests and benthic macroinfauna quantification to characterize pollution in selected estuaries and coastal embayments. Contaminant assessment is a core function of both projects. Although only one contract laboratory was used by the NS&T Program during the specified time period, several analytical methods and instruments were employed. The specific analytical method, including instrumentation and detection limit, is noted for each measurement taken and can be found at http://NSandT.noaa.gov. The major and trace elements measured by the NS&T Program include: Al, Si, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Sn, Sb, Ag, Cd, Hg, Tl and Pb.

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Environmental transport of pollutants comprises distinct processes such as volatilization, leaching and surface runoff. Sorption is one of the most important phenomena that affects leaching, and thus the fate of hydrophobic organic pollutants in soils and also control their distribution in the soil/water environment. The work developed focuses the optimization of analytical techniques for monitoring the sorption behaviour of organic pollutants, 17α- ethinylestradiol (EE2) and atrazine, and their fate in aqueous environment. Initially, the development of several analytical techniques, such as micellar electrokinetic chromatography, spectral deconvolution, using UV-Vis and fluorescence spectroscopy, and also enzyme linked immunosorbent assay was performed. Optimization, method performance and recovery tests are described and results discussed. Moreover, in order to evaluate the applicability of the previously optimized method, atrazine and EE2 sorption to soil samples was performed. The work developed provide several options, in terms of methodology to follow sorption of atrazine onto soils, however the choice depends on the laboratory conditions and on the analyst preferences. The advantages and disadvantages of each methodology should be evaluated first. The second part of this work consisted in the sorption behaviour study of those two different hydrophobic organic pollutants onto different soil samples. Soil organic matter chemical characterization, being essential to understand the binding mechanism responsible for the interactions, was made. The results of atrazine binding to organic matter pointed out that carboxyl units and aromaticrich organic matter are the most efficient binding agents for atrazine. EE2 adsorbs strongly to soil organic matter and is mainly stabilized by hydrophobic interactions, through aromatic nuclei face to face with surface and/or another EE2 molecule association. Farmyard manure soil contains higher aromatic and carboxyl units, indicating that this type of manure can be effectively used to minimize the residual toxicity of EE2 and atrazine present in soils, increasing the sorption and reducing leaching onto water resources. Since the final destination of organic pollutants can be ground, surface and/or waste water, atrazine and 17α-ethinylestradiol were quantified in several water samples.

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Die Verordnung des Europäischen Rates (EC) 834/2007 erkennt das Recht des Konsumenten auf eine Entscheidung basierend auf vollständiger Information bezüglich der enthaltenen Zutaten im Produkt und deren Herkunft (Qualität der Verarbeitung). Die primäre Kennzeichnungsverordnung betont „organische“ Produktionsstandards ebenso wie die Notwendigkeit zur Kontrolle und Aufsicht. Jedoch ist zurzeit keine validierte Methode zur analytischen Diskriminierung zwischen „organischer“ und „konventioneller“ Herkunft von angebotenen Lebensmitteln verfügbar. Das Ziel der Dissertationsarbeit war die Überprüfung der Möglichkeit mit ausgewählten analytischen und holistischen Methoden zwischen organisch und konventionell angebautem Weizen objektiv zu unterscheiden. Dies beinhaltete die Bestimmung des Gesamtstickstoff (Protein) nach Dumas, zweidimensionale Fluoreszenzdifferenz Gelelektrophorese (2D DIGE) und die Kupferchloridkristallisation. Zusätzlich wurde die Anzahl der Körner pro Ähre (Kornzahl) bestimmt. Alle Bestimmungen wurden an rückverfolgbaren in den Jahren 2005 – 2007 in Belgien gesammelten Proben des Winterweizen (Triticum aestivum L. cv. Cubus) durchgeführt. Statistisch signifikante (p < 0.05) Unterschiede wurden innerhalb der untersuchten Probengruppen sowohl in der Kornzahl, dem Gesamtsticksoff (Eiweißgehalt), als auch in der Gesamtausbeute gefunden, wobei in den meisten Fällen die konventionellen Proben höhere Kornzahlen und Gesamtsticksoff (Eiweißgehalte) aufwiesen. Eine mit der 2D DIGE kompatible Probenvorbereitungsmethode für Winterweizen wurde entwickelt und auf einen internen Winterweizenstandard sowie die entsprechenden Proben angewendet. Die organischen Proben waren im Vergleich mit den konventionellen Gegenstücken in allen Fällen durch eine kleinere Anzahl von signifikant (p < 0.05) stärker exprimierten Proteinspots gekennzeichnet. Gewisse Tendenzen in Richtung der Bevorzugung bestimmter Regionen von stärker ausgeprägten Proteinspots auf aufeinanderfolgenden 2D Abbildungen in Abhängigkeit von der landwirtschaftlichen Methode konnten zwar beobachtet werden, jedoch konnte kein universelles Markerprotein zur Unterscheidung von konventionell und biologisch angebautem Winterweizen identifiziert werden. Die rechnergestützte Verarbeitung der digitalisierten Kristallisierungsbilder mittels multivariater statistischer Analyse und der Regression partieller kleinster Quadrate ermöglichte eine 100%ig korrekte Vorhersage der landwirtschaftlichen Methode unbekannter Proben sowie der Beschreibung der Kristallisierungsbilder. Diese Vorhersage bezieht sich nur auf den hier verwendeten Datensatz (Proben einer Sorte von drei Standorten über zwei Jahre) und kann nicht ohne weiteres übertragen (generalisiert) werden. Die Ergebnisse deuten an, dass die Quantifizierung der beschriebenen Parameter ein hohes Potential zur Lösung der gestellten Aufgabe besitzt.