Relevant bibliographies by topics / 1H-NMR metabolomics

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Academic literature on the topic '1H-NMR metabolomics'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "1H-NMR metabolomics"

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Sevastos, A., I. F. Kalampokis, A. Panagiotopoulou, M. Pelecanou, and K. A. Aliferis. "Fusarium graminearum 1H NMR metabolomics." Data in Brief 19 (August 2018): 1162–65. http://dx.doi.org/10.1016/j.dib.2018.04.112.

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Zhang, Bo, Robert Powers, and Elizabeth M. O’Day. "Evaluation of Non-Uniform Sampling 2D 1H–13C HSQC Spectra for Semi-Quantitative Metabolomics." Metabolites 10, no. 5 (May 16, 2020): 203. http://dx.doi.org/10.3390/metabo10050203.

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Metabolomics is the comprehensive study of metabolism, the biochemical processes that sustain life. By comparing metabolites between healthy and disease states, new insights into disease mechanisms can be uncovered. NMR is a powerful analytical method to detect and quantify metabolites. Standard one-dimensional (1D) 1H-NMR metabolite profiling is informative but challenged by significant chemical shift overlap. Multi-dimensional NMR can increase resolution, but the required long acquisition times lead to limited throughput. Non-uniform sampling (NUS) is a well-accepted mode of acquiring multi-dimensional NMR data, enabling either reduced acquisition times or increased sensitivity in equivalent time. Despite these advantages, the technique is not widely applied to metabolomics. In this study, we evaluated the utility of NUS 1H–13C heteronuclear single quantum coherence (HSQC) for semi-quantitative metabolomics. We demonstrated that NUS improved sensitivity compared to uniform sampling (US). We verified that the NUS measurement maintains linearity, making it possible to detect metabolite changes across samples and studies. Furthermore, we calculated the lower limit of detection and quantification (LOD/LOQ) of common metabolites. Finally, we demonstrate that the measurements are repeatable on the same system and across different systems. In conclusion, our results detail the analytical capability of NUS and, in doing so, empower the future use of NUS 1H–13C HSQC in metabolomic studies.
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Deutsch, Leon, Damjan Osredkar, Janez Plavec, and Blaž Stres. "Spinal Muscular Atrophy after Nusinersen Therapy: Improved Physiology in Pediatric Patients with No Significant Change in Urine, Serum, and Liquor 1H-NMR Metabolomes in Comparison to an Age-Matched, Healthy Cohort." Metabolites 11, no. 4 (March 30, 2021): 206. http://dx.doi.org/10.3390/metabo11040206.

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Spinal muscular atrophy (SMA) is a genetically heterogeneous group of rare neuromuscular diseases and was until recently the most common genetic cause of death in children. The effects of 2-month nusinersen therapy on urine, serum, and liquor 1H-NMR metabolomes in SMA males and females were not explored yet, especially not in comparison to the urine 1H-NMR metabolomes of matching male and female cohorts. In this prospective, single-centered study, urine, serum, and liquor samples were collected from 25 male and female pediatric patients with SMA before and after 2 months of nusinersen therapy and urine samples from a matching healthy cohort (n = 125). Nusinersen intrathecal application was the first therapy for the treatment of SMA by the Food and Drug Administration (FDA) and the European Medicines Agency (EMA). Metabolomes were analyzed using targeted metabolomics utilizing 600 MHz 1H-NMR, parametric and nonparametric multivariate statistical analyses, machine learning, and modeling. Medical assessment before and after nusinersen therapy showed significant improvements of movement, posture, and strength according to various medical tests. No significant differences were found in metabolomes before and after nusinersen therapy in urine, serum, and liquor samples using an ensemble of statistical and machine learning approaches. In comparison to a healthy cohort, 1H-NMR metabolomes of SMA patients contained a reduced number and concentration of urine metabolites and differed significantly between males and females as well. Significantly larger data scatter was observed for SMA patients in comparison to matched healthy controls. Machine learning confirmed urinary creatinine as the most significant, distinguishing SMA patients from the healthy cohort. The positive effects of nusinersen therapy clearly preceded or took place devoid of significant rearrangements in the 1H-NMR metabolomic makeup of serum, urine, and liquor. Urine creatinine was successful at distinguishing SMA patients from the matched healthy cohort, which is a simple systemic novelty linking creatinine and SMA to the physiology of inactivity and diabetes, and it facilitates the monitoring of SMA disease in pediatric patients through non-invasive urine collection.
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Stark, Pauline, Caroline Zab, Andrea Porzel, Katrin Franke, Paride Rizzo, and Ludger A. Wessjohann. "PSYCHE—A Valuable Experiment in Plant NMR-Metabolomics." Molecules 25, no. 21 (November 4, 2020): 5125. http://dx.doi.org/10.3390/molecules25215125.

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1H-NMR is a very reproducible spectroscopic method and, therefore, a powerful tool for the metabolomic analysis of biological samples. However, due to the high complexity of natural samples, such as plant extracts, the evaluation of spectra is difficult because of signal overlap. The new NMR “Pure Shift” methods improve spectral resolution by suppressing homonuclear coupling and turning multiplets into singlets. The PSYCHE (Pure Shift yielded by Chirp excitation) and the Zangger–Sterk pulse sequence were tested. The parameters of the more suitable PSYCHE experiment were optimized, and the extracts of 21 Hypericum species were measured. Different evaluation criteria were used to compare the suitability of the PSYCHE experiment with conventional 1H-NMR. The relationship between the integral of a signal and the related bin value established by linear regression demonstrates an equal representation of the integrals in binned PSYCHE spectra compared to conventional 1H-NMR. Using multivariate data analysis based on both techniques reveals comparable results. The obtained data demonstrate that Pure Shift spectra can support the evaluation of conventional 1H-NMR experiments.
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Isha, Azizul, Nor Azah Yusof, Rosiah Osman, Mui-Yun Wong, and Siti Nor Akmar Abdullah. "NMR-based metabolomics reveals effect of Ganoderma boninense infection on oil palm leaf at 30 days post-infection." MAY 2020, no. 13(01): 2020 (May 20, 2020): 15–20. http://dx.doi.org/10.21475/poj.13.01.20.p2071.

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Basal stem rot is the major disease in oil palm industry that caused by a fungal named Ganoderma boninense (G. boninense) species. Infected palms are symptomless at the early stage of this disease which imposes difficulties in detecting the disease. Therefore, this study was carried out to obtain the 1H NMR metabolomic profiling of both non-infected and G. boninense infected oil palm leaf at 30 days post-infection (dpi). This combination has provided a rapid approach in investigating the changes in the compound variations of non-infected and G. boninense infected oil palm leaf. Non-infected and G. boninense infected oil palm leaf at 30 dpi was extracted using aqueous methanol (methanol: water, 80: 20 v/v). The crude extracts obtained were analyzed by 1H NMR-based metabolomics approach. Analysis of metabolomics data from 1H NMR was conducted by multivariate data analysis of principal component analysis (PCA). Significant differences were found between the two groups. Compared to the non-infected leaf, the G. boninense infected leaf had higher relative abundance of choline, asparagine, alanine, succinic acid, gallic acid, epicatechin, trimethylamine, N-acetylglucosamine, N-acetyltyrosine, β-sitosterol, 2,3-butanediol, lactic acid, caffeic acid, p-hydroxybenzoic acid, α-tocopherol, β-cryptoxanthin and kaempferol. The non-infected leaf showed higher level of sucrose, xylose, α-glucose, S-sulfocysteine and indole-3-acetic acid. NMR-based metabolomics applied in this study reveals that G. boninense alters a manifold of primary and secondary compounds in oil palm leaf.
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Cuperlovic-Culf, Miroslava, Dean Ferguson, Adrian Culf, Pier Morin, and Mohamed Touaibia. "1H NMR Metabolomics Analysis of Glioblastoma Subtypes." Journal of Biological Chemistry 287, no. 24 (April 23, 2012): 20164–75. http://dx.doi.org/10.1074/jbc.m111.337196.

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Wang, Roy Chih Chung, David A. Campbell, James R. Green, and Miroslava Čuperlović-Culf. "Automatic 1D 1H NMR Metabolite Quantification for Bioreactor Monitoring." Metabolites 11, no. 3 (March 9, 2021): 157. http://dx.doi.org/10.3390/metabo11030157.

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High-throughput metabolomics can be used to optimize cell growth for enhanced production or for monitoring cell health in bioreactors. It has applications in cell and gene therapies, vaccines, biologics, and bioprocessing. NMR metabolomics is a method that allows for fast and reliable experimentation, requires only minimal sample preparation, and can be set up to take online measurements of cell media for bioreactor monitoring. This type of application requires a fully automated metabolite quantification method that can be linked with high-throughput measurements. In this review, we discuss the quantifier requirements in this type of application, the existing methods for NMR metabolomics quantification, and the performance of three existing quantifiers in the context of NMR metabolomics for bioreactor monitoring.
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Lankadurai, Brian P., André J. Simpson, and Myrna J. Simpson. "1H NMR metabolomics of Eisenia fetida responses after sub-lethal exposure to perfluorooctanoic acid and perfluorooctane sulfonate." Environmental Chemistry 9, no. 6 (2012): 502. http://dx.doi.org/10.1071/en12112.

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Environmental contextPerfluoroalkyl acids are persistent environmental contaminants that are also found in soils. We use a metabolomics approach based on nuclear magnetic resonance analyses to investigate the responses of earthworms to exposure to sub-lethal levels of two perfluoroalkyl acids. The results indicate that this metabolomics approach is able to delineate the toxic mode of action of contaminants present at sub-lethal levels. AbstractMetabolomics entails the analysis of endogenous metabolites within organisms exposed to an external stressor such as an environmental contaminant. We utilised 1H NMR-based metabolomics to elucidate sub-lethal toxic mechanisms of Eisenia fetida earthworms after exposure to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). Earthworms were exposed to a range of concentrations of PFOA (6.25 to 50 μg cm–2) and PFOS (3.125 to 25 μg cm–2) by contact tests for 2 days. Earthworm tissues were extracted using a mixture of chloroform, methanol and water, and the polar fraction was analysed by 1H NMR spectroscopy. NMR-based metabolomic analysis revealed heightened E. fetida toxic responses with higher PFOA and PFOS exposure concentrations. Principal component analysis (PCA) exhibited significant separation between control and exposed earthworms along PC1 for all PFOA and PFOS exposure concentrations. Leucine, arginine, glutamate, maltose and adenosine triphosphate (ATP) are potential indicators of PFOA and PFOS exposure as these metabolite concentrations fluctuated with exposure. Our data also indicate that PFOA and PFOS exposure may increase fatty acid oxidation and interrupt ATP synthesis due to a disruption in the inner mitochondrial membrane structure. NMR-based metabolomics has promise as an insightful tool for elucidating the environmental toxicology of sub-lethal contaminant exposure.
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Gougeon, Louis, Gregory da Costa, François Guyon, and Tristan Richard. "1H NMR metabolomics applied to Bordeaux red wines." Food Chemistry 301 (December 2019): 125257. http://dx.doi.org/10.1016/j.foodchem.2019.125257.

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Nanda, Manisha, Vinod Kumar, Neha Arora, Mikhail S. Vlaskin, and Manoj K. Tripathi. "1H NMR-based metabolomics and lipidomics of microalgae." Trends in Plant Science 26, no. 9 (September 2021): 984–85. http://dx.doi.org/10.1016/j.tplants.2021.06.004.

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Dissertations / Theses on the topic "1H-NMR metabolomics"

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Gipson, Geoffrey T. Sokhansanj Bahrad. "Discovery Of discriminative LC-MS and 1H NMR metabolomics markers /." Philadelphia, Pa. : Drexel University, 2008. http://hdl.handle.net/1860/2766.

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Barrilero, Regadera Rubén. "Development of 1H-NMR Serum Profiling Methods for High-Throughput Metabolomics." Doctoral thesis, Universitat Rovira i Virgili, 2017. http://hdl.handle.net/10803/461603.

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El perfilat de sèrum per ressonància magnètica nuclear de protó (1H-RMN) està especialment indicat per a anàlisi a gran escala en estudis epidemiològics, nutricionals o farmacològics. L’espectroscòpia 1H-RMN requereix mínima manipulació de mostra i gràcies a la seva resposta quantitativa permet la comparació directa entre laboratoris. Un perfilat complet de sèrum per 1H-RMN requereix de tres mesures que es corresponen amb tres espècies moleculars diferents: lipoproteïnes, metabòlits de baix pes molecular i lípids. El perfilat de sèrum per 1H-RMN permet obtenir informació de grandària, nombre de partícules i contingut lipídic de les subfraccions lipoproteiques, així com l'abundància d'aminoàcids, productes de la glicòlisi, cossos cetònics, àcids grassos i fosfolípids, entre d'altres. No obstant això, la complexitat espectral afavoreix la inclusió d'errors en l'anàlisi manual de les dades, mentre que les múltiples interaccions moleculars en el sèrum comprometen la seva precisió quantitativa. És per tant necessari desenvolupar mètodes robustos de perfilat metabòlic per consolidar la 1H-RMN en la pràctica clínica. Per a això, aquesta tesi presenta diverses estratègies metodològiques i computacionals. En el primer treball, es van desenvolupar mètodes de regressió dels lípids del perfil lipídic clàssic, generalitzables a mostres de població sana i amb valors de lípids i lipoproteïnes anormals. Aquests lípids representen els principals indicadors de risc cardiovascular i els objectius terapèutics primaris. En el segon estudi caracteritzem els errors de quantificació en el perfilat 1H-RMN de metabòlits clínicament rellevants, que són deguts a la seva agregació a la proteïna sanguínia. També proposem un mètode que fomenta la competició per l'agregació i que ens permet obtenir quantificacions dels nostres metabòlits properes a les absolutes. Finalment, el tercer treball presenta LipSpin: una eina bioinformàtica de codi obert específicament dissenyada per al perfilat de lípids per 1H-RMN. A més, aquest estudi exposa alguns aspectes metodològics per millorar l'anàlisi de lípids per RMN.
El perfilado de suero por resonancia magnética nuclear de protón (1H-RMN) está especialmente indicado para el análisis a gran escala en estudios epidemiológicos, nutricionales o farmacológicos. La espectroscopía 1H-RMN requiere mínima manipulación de muestra y gracias a su respuesta cuantitativa permite la comparación directa entre laboratorios. Un perfilado completo de suero por 1H-RMN requiere de tres mediciones que se corresponden con tres especies moleculares distintas: lipoproteínas, metabolitos de bajo peso molecular y lípidos. El perfilado de suero por 1H-RMN permite obtener información de tamaño, número de partículas y contenido lipídico de las subfracciones lipoproteicas, así como la abundancia de aminoácidos, productos de la glicólisis, cuerpos cetónicos, ácidos grasos y fosfolípidos, entre otros. Sin embargo, la complejidad espectral favorece la inclusión de errores en el análisis manual de los datos, mientras que las múltiples interacciones moleculares en el suero comprometen su precisión cuantitativa. Es por tanto necesario desarrollar métodos robustos de perfilado metabólico para consolidar la 1H-RMN en la práctica clínica. Para ello, esta tesis presenta varias estrategias metodológicas y computacionales. En el primer trabajo, se desarrollaron métodos de regresión de los lípidos del perfil lipídico clásico, generalizables a muestras de población sana y con valores de lípidos y lipoproteínas anormales. Estos lípidos representan los principales indicadores de riesgo cardiovascular y los objetivos terapéuticos primarios. En el segundo estudio caracterizamos los errores de cuantificación en el perfilado 1H-RMN de metabolitos clínicamente relevantes, que son debidos a su agregación a la proteína sanguínea. También proponemos un método que fomenta la competición por la agregación y que nos permite obtener cuantificaciones de nuestros metabolitos cercanas a las absolutas. Por último, el tercer trabajo presenta LipSpin: una herramienta bioinformática de código abierto específicamente diseñada para el perfilado de lípidos por 1H-RMN. Además, este estudio expone algunos aspectos metodológicos para mejorar el análisis de lípidos por RMN.
1H-NMR serum profiling is especially suitable for high-throughput epidemiological studies and large-scale nutritional studies and drug monitoring. It requires minimal sample manipulation and its quantitative response allows inter-laboratory comparison. A comprehensive 1H-NMR serum profiling consists of three measurements encoding different molecular species: lipoproteins, low-molecular-weight metabolites and lipids. 1H-NMR serum profiling provides information of size, particle number and lipid content of lipoprotein subclasses, as well as abundance of amino acids, glycolysis-related metabolites, ketone bodies, fatty acids and phospholipids, among others. However, the spectral complexity promotes errors in manual data analysis and the multiple molecular interactions within the sample compromise reliable quantifications. Developing robust methods of metabolite serum profiling is therefore desirable to consolidate high-throughput 1H-NMR in the clinical practice. This thesis presents several methodological and computational strategies to that end. In the first study, we developed generalizable regression methods for lipids in routine clinical practice (known as “lipid panel”), to be applied in healthy population and in a wide spectrum of lipid and lipoprotein abnormalities. These standard lipids are still the main measurements of cardiovascular risk and therapy targets. In the second study, we characterised the quantitative errors introduced by protein binding in 1H-NMR profiling of clinically-relevant LMWM in native serum. Then, we proposed a competitive binding strategy to achieve quantifications closer to absolute concentrations, being fully compatible with high-throughput NMR. Finally, the third study presents LipSpin: an open source bioinformatics tool specifically designed for 1H-NMR profiling of serum lipids. Moreover, some methodological aspects to improve NMR-based serum lipid analysis are discussed.
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Savage, Angela Karen. "Identification of antioxidant compounds in grape juice by 1H NMR based metabolomics." Thesis, University of Nottingham, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.546554.

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Obidan, Amnah Mahmoud. "Urinary Metabolomics to Detect Polycystic Kidney Disease at Early Stage." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1514093416800549.

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Lopes, Thiago Inácio Barros 1987. "Avaliação do perfil de ácidos graxos em pacientes com sobrepeso tratados com orlistate usando CG-EM e avaliação do perfil metabólico de plasma por RMN de 1H." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/248819.

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Orientador: Anita Jocelyne Marsaioli
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Química
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Resumo: A organização mundial de saúde (OMS) estima que existam atualmente mais de 1,5 bilhões de adultos com sobrepeso, número que é esperado dobrar até 2015. Obesidade e sobrepeso são enfermidades caracterizadas pelo acúmulo excessivo de gordura corporal e têm sido associadas a vários problemas de saúde. Vários fármacos têm sido utilizados no tratamento desta enfermidade, entre os mais utilizados se encontra o Orlistate, um inibidor de lipases gástricas utilizado na redução da absorção de gordura da dieta, auxiliando na perda e manutenção do peso. Esta dissertação teve como objetivo principal avaliar as alterações metabólicas sofridas por pacientes com sobrepeso tratados com Orlistate por 120 dias. Para tornar mais didático, o trabalho foi divido em duas Partes: Parte I, implementação da metodologia analítica para análise de ácidos graxos por CG-EM e avaliação do perfil de ácidos graxos em indivíduos com sobrepeso tratados com Orlistate; e Parte II, avaliação do perfil metabólico de plasma por RMN de ¹H de indivíduos com sobrepeso tratados com Orlistate. Na primeira etapa do trabalho, análise de componentes principais foi aplicada na seleção íons (m/z) para quantificação de ácidos graxos, após preparação de ésteres metílicos correspondentes, por CG-EM usando monitoramento de íons selecionados. Quatro íons foram então selecionados de forma a aumentar a detectividade sem perda completa de informação qualitativa. Os íons de m/z 74, 79, 81 e 87 foram selecionados e permitiram a quantificação de vários ácidos graxos, além da determinação do número de insaturações dos mesmos relacionando a abundância relativa dos íons à presença de insaturações. A metodologia analítica implementada permitiu quantificar ácidos graxos esterificados em vários lipídios presentes no sangue, após transesterificação para produção dos ésteres metílicos de ácidos graxos, com adequada precisão, repetitividade e baixos limites de detecção e quantificação. Na segunda etapa, a metodologia analítica foi aplicada no estudo do perfil de ácidos graxos de 20 mulheres com sobrepeso tratadas com Orlistate durante 120 dias. O tratamento não reduziu o índice de massa corpórea contribuiu para diminuição significativa dos níveis de colesterol-HDL no plasma e do conteúdo de colesterol na membrana de eritrócitos, além de alterar as proporções relativas de vários ácidos graxos essenciais e exógenos em vários lipídios estudados. Adicionalmente foi observado um perfil de ácido graxo significativamente diferente para os indivíduos magros (controles) em comparação com indivíduos com sobrepeso. Na última etapa, o perfil metabólico de plasma por RMN de ¹H foi estudado por uma abordagem metabolômica. A análise discriminatória por quadrados mínimos parciais (PLS-DA) revelou que alterações nos níveis de lactato e magnésio são importantes na diferenciação entre indivíduos com sobrepeso tratados e não-tratados com Orlistate, sinalizando diminuição destes metabólitos relacionada ao tratamento. Não há relatos anteriores da alteração dos níveis de lactato devido ao tratamento. Adicionalmente, os níveis de triacilglicerídios, alanina e lactato contribuíram significativamente na distinção entre indivíduos magros e com sobrepeso
Abstract: The World Health Organization (WHO) estimates that there are currently more than 1.5 billion overweight adults, a number that is expected to double until 2015. Obesity and overweight are diseases characterized by excessive accumulation of body fat and linked to various health problems. Several drugs have been used to treat such diseases. Orlistat is a gastric lipase inhibitor largely used to reduce the absorption of dietary fat, helping weight loss. Thus this thesis aimed at the metabolic variation of overweight subjects treated with Orlistat for 120 days. This work is divided into two parts: Part I, implementation of the analytical methodology for analysis of fatty acids by GC-MS and evaluation of the fatty acid profile in overweight subjects treated with Orlistat; and Part II, evaluation of the metabolic profile of plasma of overweight subjects treated with Orlistat using ¹H NMR. In the Part I of this work, principal component analysis was applied to selected ions (m/z) for determination of fatty acids, after preparation of the corresponding methyl esters, by GC-MS using selected ion monitoring. Four ions were selected. The ions of m/z 74, 79, 81 and 87 allowed the quantification of various fatty acids and determination of the number of double bounds in theo fatty acids through the relative abundance of these selected ions. The analytical methodology implemented permitted quantify esterifing fatty acids in various lipids in blood, after transesterification for production of methyl esters of fatty acids, with adequate accuracy, repeatability and low limits of detection and quantification. In the second step, the analytical methodology was applied to study the fatty acid profile of 20 overweight women treated with Orlistat for 120 days. Although there was no significant reduction in body mass index, the treatment contributed to significant reduction of HDL-cholesterol levels in plasma and the cholesterol content in erythrocyte membranes. The Orlistat also alters the relative proportions of various fatty acids in the several lipids studied. Additionally, a significantly different fatty acid profile was observed for lean subjects (controls) compared to overweight subjects. In Part II, the metabolic profile of plasma obtained by ¹H NMR was studied by a metabolomics approach. The partial least squares discriminant analysis (PLS-DA) revealed changes in lactate and magnesium level, these metabolites were important to differentiating between overweight subjects treated and not-treated with Orlistat, suggesting that the level of these metabolites decreased with treatment. There are no previous reports of changes in lactate levels. Additionally, levels of triglycerides, alanine and lactate were highlighted by PLS-DA into distinguishing between lean and overweight individuals
Mestrado
Quimica Organica
Mestre em Química
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Battarra, Claudia. "Brewing Production investigated by 1H NMR Metabolomics on samples from Finnish American IPA and Sweet Stout Beers." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

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This study has characterized beer samples taken from two different Finnish beer: Claudia’s Citra Stout (Mustialan Kartano Panimo) and Thunder Chief (Hopping Brewsters Panimo). Both of them have been analyzed from several steps of the brewing process, in order to characterize the final product (4.) and the metabolites change (1. after mashing, 2. after Whirlpool and 3. after secondary fermentation). The aim of this research was to discover how each compound changed during the beer making process, how this could be useful to characterize different styles of beers and if there was any by-product, in the liquids extract discarded, that could be valorized. The beermaking process has been followed from a metabolomics perspective, based on 1H NMR (Nuclear Magnetic Resonance) . In order to get a representative result, 33 NMR spectra have been analyzed, which we obtained by experimenting with different samples preparation methods [(a),(b),(c),(d)], to get the best characterization possible. The majority of the metabolites identified decreased in concentration from the steps before fermentation to post-secondary fermentation. In particular, it has been possible to distinguish 73 metabolites in unfiltered and unpasteurized beer (artigianal), and in commercial beer (Viktor), which has been used as reference. All of them were different in quantitative terms and through their characterization it was possible to identify exactly their presence in others beer samples. Furthermore was possible to obtain an objective opinion on the specific molecules and metabolisms acting on them, in order to optimize a recipe or to modify one that presents problems. Just for this last purpose, it was useful to verify changes that occur during the main steps (1-2-3-4), in order to identify not only the problem, but also in which step this is presented, and consequently how to intervene.
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Martins, Lucas Gelain 1984. "Tecnicas de RMN de 'ANTIPOT. 1H¿ aplicadas a metabolomica de Theobroma cacao e as interações proteinas - ligantes." [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/248863.

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Orientador: Anita Jocelyne Marsaioli
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Quimica
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Resumo: Técnicas de RMN de H foram aplicadas no estudo de metabolômica de Theobroma cacao e interações proteínas ¿ ligantes. Esses dois tópicos são reportados em dois capítulos. O primeiro descreve a análise quantitativa por RMN de H de 8 metabolitos de Theobroma cacao endógenos ou produzidos durante a fermentação de 10 diferentes variedades resistentes ao fungo Moniliophthora perniciosa. Os espectros foram obtidos de extratos aquosos saturando o sinal da água com pressaturação. Os metabólitos monitorados foram: glicose, sacarose, frutose, etanol, cafeínas e os ácidos acético, lático e succínico. O teor dos metabólitos presentes em 7 dessas variedades são similares àqueles de T. cacao comum e análise sensorial selecionou aquelas com maior teor de cafeína como as melhores. O segundo capítulo descreve as interações acetilcolinesterase/alcalóides de Amaryllidaceae e proteína de membrana bacteriana/fosfomicina, com os mapas de epitopo de interação dos ligantes com as macromoléculas determinados por RMN de H ¿ STD (Saturation Transfer Difference). O mapa de epitopo para acetilcolinesterase/fisostigmina foi confirmado por cálculos de ¿doking¿ molecular. A constante de dissociação aparente da fisostigmina com acetilcolinesterase foi obtida através das medidas de T1 seletivo. Interação entre células integras de Escherichia coli CCT 5050, Serratia liquefaciens CCT 7262 e fosfomicina indicaram que microrganismo resistente ao antibiótico (Serratia liquefaciens) não apresentaram sinais no experimento de RMN de H ¿ STD enquanto que o microrganismo não resistente (Escherichia coli) apresenta sinais no mesmo experimento. Esses resultados certamente contribuirão para a elucidação do mecanismo de ação da fosfomicina
Abstract: H NMR tecniques were applied to study Theobroma cacao metabolomics and protein-ligand supramolecular interactions. These two topics are reported in two chapters. First chapter describes the H NMR quantitative analysis of 8 Theobroma cacao secondary metabolites which are endogenous or produced during the fermentation process of 10 different varieties resistent to the Moniliophthora perniciosa fungus. The spectra were obtained from the aqueous extracts saturating the water signal with the PRESAT tecnique. The monitored metabolites were: glucose, sacharose, fructose, ethanol, cafeine and the acids acetic, latic and succinic. The abundance of the metabolites present in 7 of these varieties were similar to those in comon T. Cacao and sensory analysis selected those with high cafeine content as the best. The second chapter describes the supramolecular interactions of acetylcholisterase/Amaryllidaceae alkaloids and bacterial membrane protein /fosfomicine, with the epitope mapping of the interactions of the ligands to the macromolecules obtained by H NMR STD (saturation transfer difference). The epitope mapping of acetylcholisterase/Amaryllidaceae alkaloids was confirmed by molecular docking calculations. The apparent dissociation constant of the fisostigmine which is an acetylcholinesterase inhibitor was obtained by applying selective T1. Interactions of Escherichia coli CCT 5050, Serratia liquefaciens CCT 7262 whole cells and fosfomycin indicated that microorganisms resistent to this antibiotic (Serratia liquefaciens) did not show signal in the H NMR STD experiment while non resistent microorganism (Escherichia coli) showed signals in the same experiment. This data will certainly contribute to the elucidation of fosfomycin action mechanism
Mestrado
Quimica Organica
Mestre em Química
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Kutzner, Erika Maria [Verfasser]. "Stoffwechseluntersuchungen von pathogenen Bakterien und Pflanzen durch Isotopolog-Profiling (GC/MS) und 1H-NMR Metabolomics / Erika Maria Kutzner." München : Verlag Dr. Hut, 2017. http://d-nb.info/1135594899/34.

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Baldissera, Giulia. "1H NMR-based metabolomics investigation on the impacts of feeding in aquaculture of Gilthead sea bream (Sparus aurata)." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23674/.

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In questo lavoro di tesi sono stati analizzati campioni di orate (Sparus aurata) da acquacoltura allevate con differenti diete, commerciali o innovative, con lo scopo di verificare se le diverse formulazioni dei mangimi hanno un effetto sul profilo molecolare dei pesci. A tal proposito, è stata utilizzata la spettroscopia di Risonanza Magnetica Nucleare (1H NMR) accoppiata ad un approccio metabolomico poiché, rispetto ad altre tecniche, consente la determinazione simultanea di un’ampia classe di metaboliti che caratterizzano il campione attraverso la generazione di spettri che contengono un ampio spettro di informazioni. Questo lavoro di tesi si sposa bene con l’attuale tendenza di sviluppo dell’acquacoltura, che viene vista come uno strumento interessante per fornire cibo e migliorare la sicurezza alimentare, ma allo stesso tempo esso è in accordo anche con la sempre più elevata attenzione verso sostenibilità, qualità e conformità alle richieste dei consumatori, che sono oggi le principali tendenze nel settore alimentare. Negli ultimi anni si è assistito ad un ampio sviluppo dell’acquacoltura e questo ha portato alla necessità di ricercare strategie per migliorare l’efficienza, la produttività, ma anche la sostenibilità di questi sistemi. Questo ha condotto ad un elevato aumento delle ricerche riguardanti questi aspetti dell’acquacoltura, e l’impatto che la dieta ha sul metabolismo dei pesci è uno di questi. I dati spettroscopici sono stati interpretati attraverso analisi statistica multivariata, nello specifico attraverso l’analisi delle componenti principali, PCA, per individuare eventuali differenze significative tra i tre gruppi a seguito della diversa tipologia di alimentazione. Dal presente lavoro di tesi è stato possibile concludere che i campioni vengono distribuiti e classificati in funzione della dieta. Inoltre, è stato possibile individuare i metaboliti che maggiormente determinano questa separazione.
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Ruiz-Rodado, Victor. "New developments in 1H NMR-linked metabolomics : identification of new biomarkers for the metabolomic classification of Niemann-Pick disease, type C1, and its response to treatment." Thesis, De Montfort University, 2016. http://hdl.handle.net/2086/12486.

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NMR-linked metabolomics analysis was employed to investigate urinary and human plasma profiles collected from Niemann Pick type C1 disease patients (NP-C1), in addition to aqueous extracts of liver samples of an NP-C1 mouse model. NP-C1 is a lysosomal storage disorder caused by mutations in the lysosomal proteins NPC1 and NPC2, which are involved in lysosomal cholesterol trafficking. NP-C1 disease is a fatal genetic disorder, characterised by neurodegeneration and hepatic damage. Miglustat (MGS) is the only approved drug for this disease, and consequently, plasma and urine samples collected from MGS-treated patients were also investigated. The ability of 1H NMR analysis to detect a wide range of metabolites simultaneously served to characterize the metabolic profiles of urine, plasma and hepatic tissue samples investigated in order to perform linked multivariate analysis (MVA). Additionally, MGS was identified in urine samples collected from NP-C1 treated patients. MVA employing both parametric and machine learning-based techniques was conducted to classify samples according to their disease status, and also to seek biomarkers that could aid in the diagnosis and/or prognosis of the disease. Moreover, a new technique was introduced in a metabolomics context, Correlated Component Regression (CCR), and the suitability of Random Forests (RFs) for variable selection was also explored. We were able to differentiate urine samples collected from NP-C1 patients from those collected from heterozygous controls, and also propose several metabolites as NP-C1 urinary biomarkers such as bile acids, 2-hydroxy-3-methylbutyrate, 3-aminoisobutyrate, 5-aminovalerate, trimethylamine, methanol, creatine and quinolinate. The 1H NMR linked metabolomics study of plasma samples revealed major distinctions among the groups investigated, metabolic alterations ascribable to the disease pathology were mainly observed as changes in the lipoprotein profiles of NP-C1 patients. Hepatic tissue extracts analysed revealed major disturbances in amino acid metabolism, along with impairments in the NAD+/NADH production and redox status. Gut microbiota and bile acid metabolism were also highlighted as features altered in NP-C1 disease. CCR linked to Linear Discriminant Analysis was evaluated as a new tool for metabolomics analysis, giving accurate results when compared to alternative techniques tested. Additionally, the suitability of Random Forests and associated recursive feature elimination for variable selection in metabolomics studies was contrasted, suggesting that those strategies relying on a variable ranking to select the top features for discrimination are more suitable for metabolomics investigations than those that iteratively remove a percentage of the least effective features until the classification performance decays.
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Book chapters on the topic "1H-NMR metabolomics"

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Gil, Miriam, Sara Samino, Rubén Barrilero, and Xavier Correig. "Lipid Profiling Using 1H NMR Spectroscopy." In NMR-Based Metabolomics, 35–47. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9690-2_3.

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Saric, Jasmina, Sabrina D. Lamour, and Jia V. Li. "CHAPTER 10. 1H NMR-based Metabolic Profiling in Infectious Disease Research." In NMR-based Metabolomics, 264–79. Cambridge: Royal Society of Chemistry, 2018. http://dx.doi.org/10.1039/9781782627937-00264.

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Nagana Gowda, G. A., and Daniel Raftery. "Analysis of Plasma, Serum, and Whole Blood Metabolites Using 1H NMR Spectroscopy." In NMR-Based Metabolomics, 17–34. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9690-2_2.

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Nagana Gowda, G. A., and Daniel Raftery. "Analysis of Coenzymes and Antioxidants in Tissue and Blood Using 1D 1H NMR Spectroscopy." In NMR-Based Metabolomics, 97–110. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9690-2_6.

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Orr, Daniel J., Gregory A. Barding, Christiana E. Tolley, Glenn R. Hicks, Natasha V. Raikhel, and Cynthia K. Larive. "1H NMR-Based Metabolomics Methods for Chemical Genomics Experiments." In Methods in Molecular Biology, 225–39. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-592-7_21.

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Shree, Manu, Maneesh Lingwan, and Shyam K. Masakapalli. "Metabolite Profiling and Metabolomics of Plant Systems Using 1H NMR and GC-MS." In OMICS-Based Approaches in Plant Biotechnology, 129–44. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2019. http://dx.doi.org/10.1002/9781119509967.ch7.

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Kim, Kyoung Soo, and Eunjung Bang. "Metabolomics Profiling of the Effects of Taurine Supplementation on Dyslipidemia in a High-Fat-Diet-Induced Rat Model by 1H NMR Spectroscopy." In Advances in Experimental Medicine and Biology, 329–36. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1079-2_29.

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Pontes, João G. M., Antonio J. M. Brasil, Guilherme C. F. Cruz, Rafael N. de Souza, and Ljubica Tasic. "1H NMR Metabolomic Profiling of Human and Animal Blood Serum Samples." In Multiplex Biomarker Techniques, 275–82. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-6730-8_24.

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Casadei, Luca, and Mariacristina Valerio. "1H NMR Metabolomic Footprinting Analysis for the In Vitro Screening of Potential Chemopreventive Agents." In Methods in Molecular Biology, 89–97. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3191-0_8.

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Mahadeo, Keshika, Isabelle Grondin, Hippolyte Kodja, Hermann Thomas, Patricia Clerc, Michel Frederich, and Anne Gauvin-Bialecki. "A Chemotaxonomic Study of 11 Species of the Genus Psiadia Endemic to La Reunion by 1H NMR and GC-MS Based Metabolomic Approach." In Chemistry for a Clean and Healthy Planet, 139–52. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20283-5_9.

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Conference papers on the topic "1H-NMR metabolomics"

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Fanizzi, Francesco Paolo, Chiara Roberta Girelli, Francesca Calò, Federica Angilè, Laura Del Coco, Paride Papadia, Andrea Biagianti, Daniele Barbini, and Lucia Mazzi. "1H NMR–metabolomics for PDO and PGI EVOOs Assessment." In Virtual 2020 AOCS Annual Meeting & Expo. American Oil Chemists' Society (AOCS), 2020. http://dx.doi.org/10.21748/am20.2.

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Acevedo-Acevedo, Suehelay, Douglas C. Millar, and Sean P. Palecek. "Abstract 3481: Elucidating the metabolic crosstalk between lymphatic endothelial cells and breast cancer using 1H NMR metabolomics." In Proceedings: AACR Annual Meeting 2018; April 14-18, 2018; Chicago, IL. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1538-7445.am2018-3481.

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Hashim, Noor Haslinda Noor, Jalifah Latip, and Alfi Khatib. "Metabolite profiling of Clinacanthus nutans leaves extracts obtained from different drying methods by 1H NMR-based metabolomics." In THE 2016 UKM FST POSTGRADUATE COLLOQUIUM: Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2016 Postgraduate Colloquium. Author(s), 2016. http://dx.doi.org/10.1063/1.4966753.

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Ślusarczyk, S., J. JaŘpińska, Ł. Pecio, A. Stochmal, E. Gille, and A. Matkowski. "Diversity of diterpenoids and polyphenols in Salvia glutinosa L. analyzed using targeted metabolomics based on LC-qTOF-MS and 1H-NMR." In GA 2017 – Book of Abstracts. Georg Thieme Verlag KG, 2017. http://dx.doi.org/10.1055/s-0037-1608183.

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Mickiewicz, Beata, Hector R. Wong, Hans J. Vogel, and Brent W. Winston. "Metabolomic Profiling Of Serum Samples By 1H NMR Spectroscopy As A Novel Approach For Diagnosis Of Pediatric Septic Shock." In American Thoracic Society 2012 International Conference, May 18-23, 2012 • San Francisco, California. American Thoracic Society, 2012. http://dx.doi.org/10.1164/ajrccm-conference.2012.185.1_meetingabstracts.a4911.

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