Добірка наукової літератури з теми "Nmr hrmas"

HRMAS NMR is considered a valuable technique to obtain detailed metabolic profile of unprocessed tissues. To properly interpret the HRMAS metabolomic results, detailed information of the actual state of the sample inside the rotor is needed. MRM (Magnetic Resonance Microscopy) was applied for obtaining structural and spatially localized metabolic information of the samples inside the HRMAS rotors. The tissue was observed stuck to the rotor wall under the effect of HRMAS spinning. MRM spectroscopy showed a transference of metabolites from the tissue to the medium. The sample shape and the metabolite transfer after HRMAS indicated that tissue had undergone alterations and it can not be strictly considered as intact. This must be considered when HRMAS is used for metabolic tissue characterization, and it is expected to be highly dependent on the manipulation of the sample. The localized spectroscopic information of MRM reveals the biochemical compartmentalization on tissue samples hidden in the HRMAS spectrum.

This article presents an overview of high resolution magic angle spinning (HRMAS) NMR applied to solid phase synthesis. The different interactions existing in such samples are described and analyzed with respect to their effect on the linewidth of the sample. The critical element leading to the relatively narrow linewidth observed in such compounds using HRMAS is shown to be the averaging of the magnetic susceptibility differences at the resin bead I solvent interface. The hardware required to record such spectra is described with an emphasis on probe technology. Applications of HRMAS to a tetrapeptide, an organic molecule and a polymer are presented here.

Objectives. The objectives of the present study are to determine if a metabolomic study by HRMAS-NMR can (i) discriminate between different histological types of epithelial ovarian carcinomas and healthy ovarian tissue, (ii) generate statistical models capable of classifying borderline tumors and (iii) establish a potential relationship with patient's survival or response to chemotherapy.Methods. 36 human epithelial ovarian tumor biopsies and 3 healthy ovarian tissues were studied using1H HRMAS NMR spectroscopy and multivariate statistical analysis.Results. The results presented in this study demonstrate that the three histological types of epithelial ovarian carcinomas present an effective metabolic pattern difference. Furthermore, a metabolic signature specific of serous (N-acetyl-aspartate) and mucinous (N-acetyl-lysine) carcinomas was found. The statistical models generated in this study are able to predict borderline tumors characterized by an intermediate metabolic pattern similar to the normal ovarian tissue. Finally and importantly, the statistical model of serous carcinomas provided good predictions of both patient's survival rates and the patient's response to chemotherapy.Conclusions. Despite the small number of samples used in this study, the results indicate that metabolomic analysis of intact tissues by HRMAS-NMR is a promising technique which might be applicable to the therapeutic management of patients.

There is currently a crucial need for improved diagnostic techniques and targeted treatment methods for Alzheimer’s disease (AD), a disease which impacts millions of elderly individuals each year. Metabolomic analysis has been proposed as a potential methodology to better investigate and understand the progression of this disease. In this report, we present our AD metabolomics results measured with high resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) on human blood plasma samples obtained from AD and non-AD subjects. Our study centers on developments of AD and non-AD metabolomics differentiating models with procedures of quality assurance (QA) and quality control (QC) through pooled samples. Our findings suggest that analysis of blood plasma samples using HRMAS NMR has the potential to differentiate between diseased and healthy subjects, which has important clinical implications for future improvements in AD diagnosis methodologies.

The use of magnetic resonance spectroscopy (MRS) for the detection of in-vivo metabolic perturbations is increasing in popularity in Prostate Cancer (PCa) research on both humans and rodent models. However, there are distinct metabolic differences between species and prostate areas; a fact making general conclusions about PCa difficult. Here, we use High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) spectroscopy to provide tissue specific identification of metabolites and their relative ratios; information useful in providing insight into the biochemical pathways of the prostate. As our NMR-based approach reveals, human and rat prostate tissues have different metabolic signatures as reflected in numerous key metabolites, including citrate and choline compounds, but also aspartate, lysine, taurine, glutamate, glutamine, creatine and inositol. In general, distribution of these metabolites is not only highly dependent on the species (human versus rat), but also on the location (lobe/zone) in the prostate tissue and the sample pathology; an observation making HRMAS NMR of intact tissue samples a promising method for extracting differences and common features in various experimental prostate cancer models.

Alzheimer’s disease (AD) is a crippling condition that affects millions of elderly adults each year, yet there remains a serious need for improved methods of diagnosis. Metabolomic analysis has been proposed as a potential methodology to better investigate and understand the progression of this disease; however, studies of human brain tissue metabolomics are challenging, due to sample limitations and ethical considerations. Comprehensive comparisons of imaging measurements in animal models to identify similarities and differences between aging- and AD-associated metabolic changes should thus be tested and validated for future human non-invasive studies. In this paper, we present the results of our highresolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) studies of AD and wild-type (WT) mouse models, based on animal age, brain regions, including cortex vs. hippocampus, and disease status. Our findings suggest the ability of HRMAS NMR to differentiate between AD and WT mice using brain metabolomics, which potentially can be implemented in in vivo evaluations.

A few abnormal cells found in a small piece of prostate tissue are most consequential for a man’s future. The prevalence of prostate cancer (PCa) is increasing globally. The main instigating factor for this cancer is not yet known, but it appears to be the consequence of many variables such as an increasingly older population, more frequent PSA-testing, and factors involving lifestyle. Prostate cancer screening, as an equivalent for breast cancer screening, has been suggested but unfortunately there are no accurate diagnostic tools available for this type of screening. The reason for this is simply that the prostate is one of the most difficult organs to diagnose and, consequently, PCa screening would generate far too many false-positive and false-negative results.  The prostate is not easily accessible as it is deeply-seated in the male pelvic area, wrapped around the urethra and surrounded by sensitive vital organs.  Furthermore, PCa is frequently multi-focal, and the cancer cells have a tendency of assimilating among normal cells and, thus, do not always form solid lumps.  Therefore, prostate tumors are often not felt by digital rectal examination (DRE) or identified by imaging.  The PSA-test is not reliable as it is more prostate-specific than cancer-specific.  Due to increasing prostate awareness, more early-stage and locally confined PCa are being detected. This is saving lives, although there is a high risk of over treatment and unnecessary side-effects.  The increased detection of PCa requires sophisticated diagnostic methods and highly skilled clinicians who can discern between indolent and aggressive cancers.  The current “gold-standard” for PCa diagnosis is biopsy grading by pathologists using the Gleason score system, which is a difficult task.  Therefore, innovative methods to improve the precision of prostate diagnosis, by increased biopsy sensitivity and tumor localization, are of essence. In light of these difficulties, the metabolomic approach using 1D and 2D high-resolution magic angle spinning (HRMAS) NMR spectroscopy combined with histopathology on intact prostatectomy specimens was evaluated in this research project.  The non-destructive nature of HRMAS NMR enables spectroscopic analysis of intact tissue samples with consecutive histological examinations under light microscope. Metabolomics aids in the unraveling and the discovery of organ-specific endogenous metabolites that have the potential to be reliable indicators of organ function and viability, extrinsic and intrinsic perturbations, as well as valuable markers for treatment response. The results may, therefore, be applied clinically to characterize an organ by utilizing biomarkers that have the capacity to distinguish between disease and health. The aim was to characterize the human and the rat prostate in terms of its intermediary metabolism, which I show here to differ between species and anatomical regions.  Furthermore, the aim is to seek the verification of HRMAS NMR derived metabolites which are known to be a part of the prostate metabolome such as, citrate, choline, and the polyamines which were performed, but also the identification of metabolites not previously identified as part of the local prostate metabolism, such as Omega-6, which was detected in tumors.  The extended aim was to elucidate novel bio-markers with clinical potential. In this study, the common phyto-nutrient, inositol, which appears to possess protective properties, was identified as being a potentially important PCa bio-marker for the distinction between the more indolent Gleason score 6 and the more aggressive Gleason score 7 in non-malignant prostate tissues with tumors elsewhere in the organ. Further studies in this area of PCa research are therefore warranted.

Le cancer est la première cause de morbi-mortalité dans le monde. La recherche de biomarqueurs diagnostiques, pronostiques et prédictives de la réponse aux traitements est capitale dans l’amélioration de la prise en charge de ce fléau mondial. Nous avons choisi une technique récente qui est la spectroscopie RMN HRMAS et des méthodes d’analyse statistique robustes (PCA et PLS-DA), afin d’établir les profils métaboliques des cancers épithéliaux de l’ovaire et des cancers mammaires. Nous avons établi, après un rappel théorique de la spectroscopie RMN HRMAS, un état d’art des applications médicales de cette technique, notamment gynécologiques chez la femme et urogénitales chez l’homme. Nous avons décrit les différentes étapes de la démarche établie pour l’analyse spectrale : préparation de l’échantillon tissulaire, acquisition RMN et analyse statistique. Nous avons montré que cette technique, permettant une analyse rapide (20 min) et non destructive d’échantillons tissulaires intacts, est applicable à la prise en charge thérapeutique des patientes atteintes de carcinomes ovariens et mammaires. Elle a permis, dans le cas des cancers de l’ovaire, de caractériser métaboliquement les trois types histologiques (séreux, endométrioïdes et mucineux) et le tissu ovarien sain, de générer des modèles statistiques permettant de classer les tumeurs borderline et de prédire la survie des patientes et la réponse à la chimiothérapie. Dans le cas des cancers du sein, elle a permis de discriminer métaboliquement les carcinomes mammaires, les fibroadénomes et le tissu sain et d’étudier métaboliquement les différents indicateurs histologiques des ces carcinomes. Nous projetons de confirmer ces résultats préliminaires très encourageants sur une plus grande cohorte<br>Cancer is the leading cause of morbidity and mortality worldwide. The search for diagnostic, prognostic and predictive biomarkers of response to treatment is crucial in improving the management of this global scourge. We chose a new technique that is HRMAS NMR spectroscopy and robust statistical analysis methods (PCA and PLS-DA), to establish the metabolic profiles ofepithelial ovarian and breast cancers. We have determined, after a theoretical reminder of HRMAS NMR spectroscopy, a state of the art including medical applications of this technique, mainly gynecological in woman and uro-genital in man. We describe the different steps of the process established for spectral analysis : preparation of tissue sample, NMR acquisition and statistical analysis. We showed that this technique, allowing a rapid analysis (20 min) and non-destructive of intact tissue samples, is applicable to the therapeutic management of patients with breast and ovarian carcinomas. It has, in the case of ovarian cancer, characterize metabolically the three histological types (serous, endometrioid and mucinous) and healthy ovarian tissue, generate statistical models to classify borderline tumors and predict survival patients and response to chemotherapy. In the case of breast cancer, it could discriminate metabolically breast carcinomas, fibroadenomas and healthy tissue and study metabolically different histological indicators of these carcinomas. We plan to confirm these very encouraging preliminary results in a larger cohort

Background Prostate cancer (PCa) is the most frequently diagnosed malignant disease among adult males in the USA and the second leading cause of cancer deaths in men. Due to the lack of diagnostic tools that are able to differentiate highly malignant and aggressive cases from indolent tumors, overtreatment has become very common in the era of prostate specific antigen (PSA) screening. New diagnostic methods to determine biological status, malignancy, aggressiveness and extent of PCa are urgently needed. 1H High Resolution Magic Angle Spinning Nuclear Magnetic Resonance Spectroscopy (1H HRMAS MRS) can be used to establish PCa metabolomic profiles while preserving tissue architecture for subsequent histopathological analysis. Immunohistochemistry (IHC), as opposed to conventional histopathology methods, has the potential to provide objective, more accurate and quantitative knowledge of tissue pathology. This diagnostic- accuracy study sought to evaluate a novel approach to quantitatively identify metabolomic markers of PCa by exploring the potential of PCa immunomarkers to quantify metabolomic profiles established by 1H HRMAS MRS. Material and Methods 1H HRMAS MRS was performed on tissue samples of 51 prostate cancer patients using a 14.1 Tesla NMR spectrometer (BRUKER Biospin, Billerica, MA) with a rotor synchronized CPMG pulse sequence. Spectral intensities of 36 regions of interest were measured as integrals of curve fittings with Lorentzian-Gaussian line shapes. Immunohistochemistry (IHC) was carried out following the spectroscopy scan, using three prostate immunomarkers to identify cancerous and benign glands: P504S (Alpha-methylacyl-CoA-racemace), CK903 (high-molecular weight cytokeratin) and p63. The immunostaining quality following 1H HRMAS MRS was evaluated and compared to unscanned sections of the same sample, to verify the stability and accessibility of the proposed immunomarkers. IHC images were automatically and quantitatively evaluated, using a quantitative image analysis program (QIAP), to determine the percentage of cancerous and benign epithelia in the tissue cross- sections. The results of the program were validated by a correlation with the results of a quantitative IHC review and quantitative conventional histopathology analysis performed by an experienced pathologist. Ultimately, spectral intensities and the cancer epithelium percentage, obtained from quantitative immunohistochemistry, were correlated in order to validate PCa metabolomic markers identified by 1H HRMAS MRS. Patient outcomes and incidence of recurrence were determined by retrospective review of medical records five years after initial surgery. Categories of recurrence were correlated to spectral intensities to explore potential metabolomic markers of recurrence in the cohort. Results Immunostainings with P504S and CK903 showed excellent staining quality and accessibility following 1H HRMAS MRS, suggesting these markers to be suitable for the presented quantitative approach to determine metabolomics profiles of PCa. In contrast, the quality of p63 IHC was impaired after previously performed spectroscopy. IHC using the immunomarkers P504S and CK903 on adjacent slides was found to present a feasible quantitative diagnostic method to distinguish between benign and cancerous conditions in prostate tissue. The cancer epithelium percentage as determined by QIAP showed a significant correlation to the results of quantitative IHC analysis performed by a pathologist (p &lt; 0.001), as well as to a quantitative conventional histopathology review (p = 0.001). The same was true for the benign epithelium percentage (p &lt; 0.001 and p = 0.0183), validating the presented approach. Two metabolomic regions showed a significant correlation between relative spectral intensities and the cancer epithelium percentage as determined by QIAP: 3.22 ppm (p = 0.015) and 2.68 ppm (p = 0.0144). The metabolites corresponding to these regions, phosphocholine and citrate, could be identified as metabolomic markers of PCa in the present cohort. 45 patients were followed for more than 12 months. Of these, 97.8% were still alive five years after initial surgery. 11 patients (24.4%) experienced a recurrence during the follow- up time. The categories of recurrence showed a correlation to the spectral intensities of two regions, 2.33 – 2.3 ppm (p = 0.0403) and 1.28 ppm (p = 0.0144), corresponding to the metabolites phosphocreatine and lipids. Conclusion This study introduces a method that allows an observer-independent, quantitative analysis of IHC to help establish metabolomic profiles and identify metabolomic markers of PCa from spectral intensities obtained with 1H HRMAS NMR Spectroscopy. The immunomarkers P504S and CK903 have been found suitable IHC analysis following 1H HRMAS MRS. A prospective in vivo application of PCa metabolite profiles and metabolomic markers determined by the presented method could serve as highly sensitive, non- invasive diagnostic tool. This observer- independent, computer- automated, quantitative analysis could help to distinguish highly aggressive tumors from low-malignant conditions, avoid overtreatment and reduce risks and complications for cancer patients in the future. Further studies are needed to verify the identified PCa metabolomic markers and to establish clinical applicability<br>Einführung Prostatakrebs ist eine häufigsten Krebserkrankungen in den USA und die zweithäufigste malignom- assoziierte Todesursache männlicher Patienten weltweit. Seit der Einführung des Prostata- spezifischen Antigen (PSA)- Screeningtests wird diese Krebsart in früheren Stadien diagnostiziert und therapiert, wodurch die Mortalitätsrate in den letzten Jahren deutlich reduziert werden konnte. Da moderne diagnostische Methoden bislang jedoch nicht ausreichend in der Lage sind, suffizient zwischen hochmalignen und weniger aggressiven Varianten dieses bösartigen Krebsleidens zu unterscheiden, werden häufig auch Patienten aggressiv therapiert, deren niedriggradiges Prostatakarzinom keine klinische Relevanz gehabt hätte. Es besteht daher ein großes wissenschaftliches Interesse an der Entwicklung neuer diagnostischer Methoden zur akkuraten Bestimmung von biologischem Status, Malignität, Aggressivität und Ausmaß einer Prostatakrebserkrankung. \\\\\\\"1H High Resolution Magic Angle Spinning Nuclear Magnetic Resonance Spectroscopy\\\\\\\" (1H HRMAS MRS) ist eine vielversprechende diagnostische Methode, welche es ermöglicht, metabolomische Profile von Prostatakrebs zu erstellen, ohne die Gewebsstruktur der analysierten Proben zu zerstören. Durch anschließende histopathologische Begutachtung lassen sich die erstellten Metabolitprofile validieren und evaluieren. Im Gegensatz zu konventionellen histopathologischen Methoden können durch immunhistochemische Verfahren dabei objektivere, akkuratere und quantifizierbare histopathologische Erkenntnisse gewonnen werden. Die vorliegende Studie präsentiert einen neuentwickelten diagnostischen Ansatz zur quantitativen Bestimmung von metabolomischen Markern von Prostatakrebs, basierend auf der Durchführung von 1H HRMAS NMR Spektroskopie und quantitativer Immunhistochemie. Material und Methoden Einundfünfzig Gewebsproben von Prostatakrebspatienten wurden mittels 1H HRMAS MRS an einem 14.1 T BRUKER NMR Spektrometer unter Einsatz einer CPMG-Pulssequenz untersucht. Spektrale Intensitäten in 36 Metabolitregionen wurden gemessen. Anschließend wurden die analysierten Gewebeproben mit drei Immunfärbemarkern für sowohl malignes (P504S, Alpha-methylacyl-CoA-racemase) als auch benignes (CK903, High-molecular weight cytokeratin, und p63) Prostatagewebe angefärbt und quantitativ mit Hilfe eines Bildanalyseprogramms (QIAP) ausgewertet. Die Anwendbarkeit und Auswertbarkeit der genannten Immunomarker nach Spektroskopie wurde evaluiert und mit der Färbungsqualität von nicht- gescannten Schnitten verglichen. Die Resultate der automatischen Auswertung durch QIAP konnten durch einen erfahrenen Pathologen in einer quantitativen Analyse der Immunfärbungen sowie konventioneller histologischer Färbungen derselben Gewebsproben validiert werden. Die spektralen Intensitäten aus den Messungen mit 1H HRMAS MRS wurden mit den korrespondierenden Ergebnissen der quantitativen Auswertung der Immunfärbungen korreliert, um metabolomische Marker von Prostatakrebs zu identifizieren. Der klinische Verlauf und die Rezidivrate der Patienten wurden 5 Jahre nach der initialen Prostatektomie retrospektiv bestimmt. Rezidivkategorien wurden erstellt und mit den bestimmten spektralen Intensitäten korreliert, um metabolomische Marker für das Auftreten von Prostatakrebsrezidiven zu identifizieren. Ergebnisse Die Immunfärbungen mit P504S und CK903 zeigten exzellente Qualität und Auswertbarkeit nach vorheriger 1H HRMAS MRS. Beide Marker eigneten sich zur Durchführung von quantitativer Immunhistochemie an spektroskopierten Gewebeproben. Im Gegensatz dazu war die Qualität der Immunfärbungen mit p63 nach Spektroskopie vermindert. Quantitative Immunfärbungen unter Einsatz der Immunmarker P504S und CK903 stellten eine praktikable diagnostische Methode dar, um zwischen malignen und benignem Prostatagewebe zu unterscheiden. Der Anteil von bösartig verändertem Prostatagewebe, bestimmt durch QIAP, korrelierte signifikant mit den Ergebnissen der quantitativen Analyse der Immunfärbungen durch den Pathologen (p &lt; 0.001), sowie mit der quantitativen Auswertung der konventionellen histopathologischen Färbung (p = 0.001). Ebenso ließ sich die Bestimmung des Anteils von benignem Gewebe mit QIAP zu den Ergebnissen der pathologischen Analyse korrelieren (p &lt; 0.001 und p = 0.0183). Für zwei metabolomische Regionen konnte ein signifikante Korrelation zwischen relativen spektralen Intensitäten, bestimmt mit 1H HRMAS NMR Spektroskopie, und dem Anteil von malignem Epithelium in derselben Gewebeprobe, ermittelt durch QIAP, festgestellt werden: 3.22 ppm (p = 0.015) und 2.68 ppm (p = 0.0144). Die zu diesen Regionen korrespondierenden Metaboliten, Phosphocholin und Zitrat, konnten als potentielle metabolomische Marker für Prostatakrebs identifiziert werden. Die retrospektiven Analyse der klinischen Daten der Patienten fünf Jahre nach Prostatektomie ergab eine Überlebensrate von 97.8%. Elf dieser Patienten (24.4%) erlitten ein Rezidiv ihrer Erkrankung. Die bestimmten Rezidivkategorien korrelierten signifikant mit zwei metabolomischen Regionen (2.33 – 2.3 ppm, p = 0.0403 und 1.28 ppm, p = 0.0144), welche zu den Metaboliten Phosphokreatin und Lipiden korrespondierten. Schlussfolgerung Die vorliegende Studie präsentiert einen diagnostischen Ansatz zur objektiven und quantitativen Bestimmung metabolomischer Marker von Prostatakrebs unter Verwendung von 1H HRMAS MRS und Immunhistochemie. P504S und CK903 eignen sich als Immunmarker für quantitative Immunfärbungen nach vorheriger Durchführung von 1H HRMAS MRS. Die Metaboliten Phosphocholin und Zitrat konnten in der vorliegenden Patientenkohorte als potentielle metabolomische Marker für Prostatakrebs identifiziert werden. Eine mögliche in vivo Anwendung der gefundenen metabolomischen Marker könnte als hochsensitives, objektives und nicht- invasives diagnostisches Werkzeug der Prostatakrebsdiagnostik dienen. Der vorliegende untersucherunabhängige, automatisierte und quantitative diagnostischer Ansatz hat das Potential, zwischen hochmalignen und weniger aggressiven Krebsfällen zu unterscheiden und somit unnötige Risiken und Komplikationen für Prostatakrebspatienten zu reduzieren. Weitere Untersuchungen sind notwendig, um die identifizierten metabolomischen Marker zu verifizieren und eine klinische Anwendung zu etablieren

Le Cancer, l’une des pathologies les plus fréquentes au sein de la population, possède encore actuellement un taux de morbi-mortalité important tous sexes confondus, et ce malgré les importants progrès diagnostiques et thérapeutiques réalisés. D’un point de vue diagnostique, dans une approche dite de « Biologie de systèmes », en complément de l’étude anatomo- pathologique qui reste la référence, de nouvelles techniques ont été développées pour la caractérisation de profils métaboliques (Métabolomique) d’échantillons tissulaires pathologiques ou non, parmi lesquelles la Spectroscopie RMN HRMAS. Après un bref rappel théorique et avoir dressé le bilan des applications de cette technique en Cancérologie, nous avons exposé les différentes étapes du protocole à mettre en place afin d’envisager son implémentation dans un cadre hospitalier. L’ensemble des résultats présentés permettent d’envisager l’utilisation de cette technique en pratique clinique courante. Il faut néanmoins valider la robustesse des modèles statistiques élaborés et confirmer ces résultats sur de plus grandes cohortes d’échantillons. Des développements technologiques, analytiques et statistiques sont également nécessaires<br>Cancer, one of the most frequent pathologies among the population, has still an important morbidity-mortality rate all sex confounded, despite the important diagnostical and therapeutical progresses achieved. From a diagnostical point of view, in a so called “Systems Biology approach”, as a complement of the gold standard histopathological study, some new techniques have been developed for the characterization of metabolic profiles (Metabolomics) of tissular samples pathological or not, among which HRMAS NMR Spectroscopy. After some brief theoretical considerations and after reporting the applications of this technique in Cancerology, we exposed the different steps of the protocol to design in order to consider its implementation in a hospital set up. All the results presented allow considering the use of this technique in a clinical routine. Nevertheless, it is necessary to validate the robustness of the statistical models built and to confirm these results on much larger cohorts of samples. Some technical, analytical and statistical developments are also needed

From day to day, the role of HRMAS (High-Resolution Magic Angle Sinning) Nuclear Magnetic Resonance Spectroscopy (NMRS) in medical diagnosis is increasing. This technique enables setting up metabolite profiles of ex vivo pathological and healthy tissue. Automatic spectrum quantitation enables monitoring of diseases. However for several metabolites, the values of chemical shifts of proton groups may slightly differ according to the micro-environment in the tissue or cells, in particular to its pH. This hampers accurate estimation of the metabolite concentrations mainly when using quantitation algorithms based on a metabolite basis-set. The present word is devoted to the optimization of NMR metabolite basis set signals, particularly to the algorithms of chemical shift mismatch correction. Two sighal processing ("warping") methods were developed for simple and fast spectrum optimization : signal stretching/shrinking (resampling) and spectrum splitting. Then, another optimization method, QM-QUEST, coupling Quantrum Mechanical simulation and quantitation algorithms was implemented. The latter provides more robust fitting while limiting user involvement and respects the correct fingerprints of metabolites. Its efficiency is demonstrated by accurately quantitating signals from tissue samples of human brains with oligodendroglioma, obtained at 11.7 Tesla and spectra of cells acquired at 9.4T by HRMAS-NMR. As the necessity of fast NMR signal simulation based on quantum Mechanics is raised in the thesis, a part of the word is dedicated to an approximate method speeding-up the calculations. The algorithm based on spin-system fragmentation could become an important part of the QM-QUEST optimization method and will be implemented as an option of simulation in NMR-SCOPE, module of the jMRUI software package.

La transplantation pulmonaire est une alternative thérapeutique ultime dans de nombreuses maladies pulmonaires sévères, en particulier chez des patients atteints de mucoviscidose (Cystic Fibrosis) , de fibrose pulmonaire idiopathique (IPF idiopathie pulmonary fibrosis), delymphangioléiomyomatose (LAM) ou d'hypertension pulmonaire. Cependant, les besoins en greffe dépassent largement le nombre de transplantations pratiquées en France. Les causes de ce déséquilibre incluent un trop faible nombre de donneurs potentiels en raison de critères actuels pour l'acceptation du greffon qui sont restreints car les biomarqueurs biologiques de qualité et de viabilité du greffon n'ont pas été décrits à ce jour. L'une des possibilités d'augmenter le nombre de donneurs, est de mettre en évidence des biomarqueurs de la qualité du greffon et d'étendre les critères d'acceptabilité du greffon en permettant les prélèvements à partir de donneurs à coeur arrêté est une possibilité. Les prélèvements pulmonaires après arrêt cardiaque sont effectués, en clinique expérimentale chez l'homme, en Espagne depuis trois ans. Il existe dans ce pays une législation très favorable et surtout une conscience collective qui rend le don d'organes extrêmement facilité. Il est donc essentiel d'optimiser l' utilisation de cette ressource. Pour cela, la mise en place de critères de validation de la qualité du greffon est une donnée clé pour palier à ce manque de transplantation pulmonaire. Les critères d'acceptabilité d'un greffon pulmonaires sont basés sur des données cliniques n'existant pas de biomarqueurs biologiques de qualité et de viabilité du greffon. Nous proposons ici l'utilisation de la métabolomique par spectroscopie en Résonance Magnétique Nucléaire à haute résolution par rotation à angle magique (RMN HRMAS) pour mettre en évidence des biomarqueurs de la qualité du greffon. La métabolomique par la spectroscopie RMN HRMAS, est une technique d'analyse rapide (20 minutes) et originale, caractérisée par l'analyse directe d'un tissu biologique intact sans nécessité d'extraction. Cette technique étudie les profils métaboliques dans le but de mettre en évidence des biomarqueurs métaboliques. La métabolomique a été largement utilisée dans des études en cancérologie pour la détermination de la malignité d'un tissu (Bertini 1. et coll. , Canser Res. 2012/ Griffin JL et coll ., Nat Rev Cancer, 2004/ Li M. et coll. , PLoSOne, 2011/ O'connell TM. Bioanalysis. 2012/ Ma Y. et coll. Mol Biol Rep. 2012). Cependant, très peu de publications dans la littérature s'intéressent au domaine de la transplantation et à la qualité du greffon (Rocha C. et coll. , Journal of Proteome Research, 2011/ RobertR. et coll. J Critical Ca re 2010/ Stenlund H. et coll., Chemometrics and Intelligent Laboratory Systems, 2009/ Du a rte F.L. et coll. , Anal.Chem.2005). Ce projet de thèse avait pour objectifs de :1. Etudier la faisabilité d'utiliser la métabolomique par la spectroscopie RMN HRMAS pour évaluer la qualité du greffon pulmonaire.2. Mettre en évidence de potentiels biomarqueurs de la qualité du greffon pulmonaire.3. Evaluer une éventuelle introduction de cette technique en pratique courante dans un environnement hospitalier. Pour répondre à ces objectifs, il a été entrepris :• Etudier les métabolomes pulmonaires de différentes espèces animales, puis de les comparer au métabolome du poumonhumain afin d'identifier le modèle expérimental le plus adapté à la transplantation pulmonaire.• Evaluer la qualité du greffon chez un modèle animal (porc Large White) pour la transplantation pulmonaire (modèle expérimental de préservation pulmonaire en in situ chez le donneur à coeur arrêté, modèle de perfusion pulmonaire en ex vivo sur machine ocs™).• Evaluer l'effet de la perfusion de deux solutions de conservation sur la qualité du greffon pulmonaire chez le porc<br>Lung transplantation is a therapeutic alternative in many severe pulmonary diseases, especially in patients suffering from CF (CysticFibrosis), idiopathie pulmonary fibrosis (IPF), lymphangioleiomyomatosis (LAM) or pulmonary hypertension . However, the need fortransplantation far outweighs the number of transplants performed in France. The causes of this imbalance include an insufficient number of potential donors because of the current criteria for the acceptance of the graft that are restricted as biomarkers of quality and viability of the graft have not been described so far.One of the possibilities to increase the donor pool is to identify biomarkers of the quality of the graft and expand the criteria foracceptability of the graft allowing withdrawals from non-heart-beating donors. The lung taking were performed after cardiac arrest inclinical trials carried out on humans for three years in Spain.lt is therefore essential to optimize the use of this resource. For this, the establishment of criteria for validating the quality of the graft isgiven a key to solve this problem of lung transplantation. The criteria for acceptability of a lung transplant are based on clinical data inabsence of biomarkers of quality and viability for the lung graft.We propose the use of the metabolomics by high-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HRMASNMR) to highlight potential biomarkers for the quality of the graft.The Metabolomics by NMR HRMAS spectroscopy is an original analytical technique characterized by a rapid analysis (20 minutes)performed on intact biopsy samples without extraction prior to analysis. This technique studies the metabolic profiles in arder to identifymetabolic biomarkers. Metabolomics has been widely used in studies in oncology for the determination of malignancy of a tissue (Bertini et al. , Canser Res. 2012/ Griffin JL et al., Nat Rev Cancer, 2004/ Li M. et al. , PLoS One, 2011/ O'connel! TM. Bioanalysis. 2012/ Ma Y. et al. Mol Biol Rep. 2012). However, very few papers in the literature combine the use of the metabolomics NMR HRMAS and the assessment of the quality of the graft (Rocha C. et al. , Journal of Proteome Research, 2011/ Robert R. et al. J Critical Care 2010/ Stenlund H. et al, Chemometrics and Intelligent Laboratory Systems, 2009/ Duarte F.L. et al. , Anal. Chem. 2005).The purposes of this research work were:1. Studying the feasibility of using the metabolomics by NMR HRMAS for the assessment of the quality of the lung graft2. Assess the metabolome of the lung in degradation conditions and highlight potential biomarkers of the quality of the graft3. Assess the possible use of the metabolomics by NMR HRMAS as a tool in clinical practice within a hospital environment.To answer to these purposes we made experimental experiences as follows:- Studying the lung metabolome of various animal species, and compare them to the human metabolome to identify the most suitableexperimental model for lung transplantation.- Assessing the quality of the graft in an animal model (pig Large White) for lung transplantation (experimental model of lung preservation in situ in the case of non-heart-beating donor, lung model for an ex vivo perfusion using OCS ™ Machine)- Evaluating the effect of perfusion with two preservation solutions on the quality of lung graft in pig model

La spectroscopie RMN Haute Résolution en Rotation à l’Angle Magique (HRMAS) permet la caractérisation métabolomique tissulaire. Nous avons caractérisé par RMN HRMAS le profil métabolomique des glandes parathyroïdiennes hypersécrétantes. Celui de l’hyperparathyroïdie primaire (HPT1) a été comparé à celui des HPT rénales. Au sein des HPT1, la distinction a pu être faite entre pathologie uni- et multi-glandulaire. Le profil métabolomique du tissu pancréatique sain a été comparé à celui du tissu tumoral. Aussi, les patients longs/courts-survivants ont pu être distingués. La relation entre le phénotype métabolique et la survie des patients a été étudiée. Le profil métabolomique des TIPMP a été caractérisé. Les TIPMP non dégénérées et dégénérées ont été comparées. Le risque de dégénérescence a été corrélé au profil métabolomique. Nos résultats montrent que la spectroscopie RMN HRMAS est une technique prometteuse pour l’étude du profil métabolomique des HPT et des pathologies pancréatiques<br>High Resolution Magic Angle Spinning (HRMAS) NMR spectroscopy allows metabolomics of intact tissues. Metabolomics profiling of hyperfunctioning parathyroid glands were characterized were characterized by using HRMAS NMR spectroscopy. Primary hyperparathy- roidism (PHPT) was compared to renal HPT. Among PHPT, we distinguished single gland disease from multiple gland disease. Pancreatic parenchyma and adenocarcinoma were compared. Thus, long-term and short-term survival patients were distinguished. The relationship between the survival of patients and their metabolic phenotype was studied. Metabolomics profiling of IPMN was also examined. IPMN with no degeneration and de- generated IPMN were compared. Finally, the risk of degeneration was correlated with the metabolomics profile. Our results show that HRMAS NMR spectroscopy is a promising technique in view of studying metabolomic profiling of HPT and pancreatic diseases

Ces travaux de thèse portent sur l'analyse des mélanges réels et synthétiques complexes composés de petites molécules à l'aide de la RMN HRMAS. Dans une première partie, une approche RMN HRMAS basée sur l'analyse métabolomique en combinaison avec des techniques de reconnaissance des formes (PCA et O-PLS-DA) a été appliquée pour le diagnostic des lésions thyroïdiennes indéterminées et étudier également les effets biologiques négatifs des nanoparticules d'aluminium sur pseudomonas brassicacearum. Dans une seconde partie, nous avons étudié la RMN chromatographique en utilisant la silice comme matrice de support qui pourrait fournir une alternative rapide et complète de la LC pour la caractérisation de mélanges complexes. En outre, l'exigence de la suppression du signal dans l'extrait de plantes naturelles et d'hydrocarbures aromatiques conduit à l'élaboration d'une méthode rapide et précise en utilisant des polymères à empreintes moléculaires avec une excellente sélectivité. La sélectivité des polymères à empreintes moléculaires à travers la capture d'une cible moléculaire spécifique est exploitée ici pour éliminer efficacement les signaux RMN<br>This thesis work deals with the analysis of natural and synthetic complex mixtures composed of small molecules using HRMAS NMR. In a first part, an integrated HRMAS-NMR based metabolomic analysis in combination with pattern recognition techniques (PCA and O-PLS-DA) has been applied for the diagnosis of indeterminate thyroid lesions and also studied the potential adverse biological effects of aluminium nanoparticles on pseudomonas brassicacearum. In a second part we investigated that chromatographic NMR using silica as the matrix support could provide a quick alternative and complement to LC for the characterization of complex mixtures. In addition, requirement for signal suppression in natural plant extract and aromatic hydrocarbons led to the development of a rapid and accurate method using molecularly imprinted polymers with excellent selectivity. The selectivity of Molecularly Imprinted polymers towards capturing a specific molecular target is exploited here to efficiently remove NMR signals