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Journal articles on the topic 'Nmr hrmas'

Author: Grafiati

Published: 4 September 2022

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1

Valentini, Massimiliano, Mena Ritota, Caterina Cafiero, Sara Cozzolino, Liviana Leita, and Paolo Sequi. "The HRMAS-NMR tool in foodstuff characterisation." Magnetic Resonance in Chemistry 49 (December 2011): S121—S125. http://dx.doi.org/10.1002/mrc.2826.

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2

Martínez-Bisbal, M. Carmen, Vicent Esteve, Beatriz Martínez-Granados, and Bernardo Celda. "Magnetic Resonance Microscopy Contribution to Interpret High-Resolution Magic Angle Spinning Metabolomic Data of Human Tumor Tissue." Journal of Biomedicine and Biotechnology 2011 (2011): 1–8. http://dx.doi.org/10.1155/2011/763684.

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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.

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3

Lippens, Guy, Maryse Bourdonneau, Christophe Dhalluin, et al. "Study of Compounds Attached to Solid Supports Using High Resolution Magic Angle Spinning NMR." Current Organic Chemistry 3, no. 2 (1999): 147–69. http://dx.doi.org/10.2174/1385272803666220131194702.

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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.

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4

Ben Sellem, D., K. Elbayed, A. Neuville, et al. "Metabolomic Characterization of Ovarian Epithelial Carcinomas by HRMAS-NMR Spectroscopy." Journal of Oncology 2011 (2011): 1–9. http://dx.doi.org/10.1155/2011/174019.

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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.

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5

Ritota, Mena, Lorena Casciani, Sebastiana Failla, and Massimiliano Valentini. "HRMAS-NMR spectroscopy and multivariate analysis meat characterisation." Meat Science 92, no. 4 (2012): 754–61. http://dx.doi.org/10.1016/j.meatsci.2012.06.034.

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6

Metelo, Ana M., Nuria Arias-Ramos, Pilar Lopez-Larrubia, and M. Margarida C. A. Castro. "Metabolic effects of VO(dmpp)2 – an ex vivo1H-HRMAS NMR study to unveil its pharmacological properties." New Journal of Chemistry 43, no. 45 (2019): 17841–49. http://dx.doi.org/10.1039/c9nj02491c.

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7

Weng, JianXiang, Isabella H. Muti, Anya B. Zhong, et al. "A Nuclear Magnetic Resonance Spectroscopy Method in Characterization of Blood Metabolomics for Alzheimer’s Disease." Metabolites 12, no. 2 (2022): 181. http://dx.doi.org/10.3390/metabo12020181.

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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.

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8

Stenman, Katarina, Izabella Surowiec, Henrik Antti, et al. "Detection of Local Prostate Metabolites by Hrmas Nmr Spectroscopy: A Comparative Study of Human and Rat Prostate Tissues." Magnetic Resonance Insights 4 (January 2010): MRI.S6028. http://dx.doi.org/10.4137/mri.s6028.

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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.

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9

Castejón, David, Palmira Villa, Marta M. Calvo, Guillermo Santa-María, Marta Herraiz, and Antonio Herrera. "1H-HRMAS NMR study of smoked Atlantic salmon (Salmo salar)." Magnetic Resonance in Chemistry 48, no. 9 (2010): 693–703. http://dx.doi.org/10.1002/mrc.2652.

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10

Füzesi, Mark V., Isabella H. Muti, Yannick Berker, et al. "High Resolution Magic Angle Spinning Proton NMR Study of Alzheimer’s Disease with Mouse Models." Metabolites 12, no. 3 (2022): 253. http://dx.doi.org/10.3390/metabo12030253.

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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.

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11

Imperiale, Alessio, Karim Elbayed, François-Marie Moussallieh, et al. "Metabolomic profile of the adrenal gland: from physiology to pathological conditions." Endocrine-Related Cancer 20, no. 5 (2013): 705–16. http://dx.doi.org/10.1530/erc-13-0232.

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In this study, we i) assessed the metabolic profile of the normal adrenal cortex and medulla of adult human subjects by means of1H-high-resolution magic-angle spinning nuclear magnetic resonance (HRMAS NMR) spectroscopy; ii) compared the biochemical profile of adenoma (Ad), adrenal cortical carcinoma (ACC), and pheochromocytoma (PCC) samples with that of healthy adrenal tissue samples; and iii) investigated the metabolic differences between ACCs and Ads as well as between ACCs and PCCs. Sixty-six tissue samples (13 adrenal cortical tissue, eight medullary tissue, 13 Ad, 12 ACC, and 20 PCC samples) were analyzed. Adrenaline and noradrenaline were undetectable in cortical samples representing the metabolic signature of the tissue derived from neural crest. Similarity between the metabolic profile of Ads and that of the normal adrenal cortex was shown. Inversely, ACC samples clearly made up a detached group exhibiting the typical stigmata of neoplastic tissue such as choline-containing compounds, biochemical markers of anaerobic processes, and increased glycolysis. Significantly higher levels of lactate, acetate, and total choline-containing compounds played a major role in the differentiation of ACCs from Ads. Moreover, the high fatty acid content of ACCs contributed to the cluster identification of ACCs. Of the 14 sporadic PCC samples, 12 exhibited predominant or exclusive noradrenaline secretion. The noradrenaline:adrenaline ratio was inverted in the normal medullary tissue samples. Multiple endocrine neoplasia type 2- and NF1-related PCC samples exhibited both adrenaline and noradrenaline secretion. In the von Hippel–Lindau disease-related PCC samples, only noradrenaline secretion was detected by HRMAS NMR spectroscopy. This study is one of the first applications of metabolomics to adrenal pathophysiology and it is the largest study to report HRMAS NMR data related to the adrenal cortex and adrenal cortical tumors.

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12

Thieme, Karena, Gernot Zech, Horst Kunz, Hans Wolfgang Spiess, and Ingo Schnell. "Dipolar Recoupling in NOESY-Type1H−1H NMR Experiments under HRMAS Conditions." Organic Letters 4, no. 9 (2002): 1559–62. http://dx.doi.org/10.1021/ol025782a.

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13

Posset, Tobias, Johannes Guenther, Jacqueline Pope, Thomas Oeser, and Janet Blümel. "Immobilized Sonogashira catalyst systems: new insights by multinuclear HRMAS NMR studies." Chemical Communications 47, no. 7 (2011): 2059. http://dx.doi.org/10.1039/c0cc04194g.

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14

Ferro, Monica, Franca Castiglione, Carlo Punta, et al. "Anomalous diffusion of Ibuprofen in cyclodextrin nanosponge hydrogels: an HRMAS NMR study." Beilstein Journal of Organic Chemistry 10 (November 19, 2014): 2715–23. http://dx.doi.org/10.3762/bjoc.10.286.

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Ibuprofen sodium salt (IP) was encapsulated in cyclodextrin nanosponges (CDNS) obtained by cross-linking of β-cyclodextrin with ethylenediaminetetraacetic acid dianhydride (EDTAn) in two different preparations: CDNSEDTA 1:4 and 1:8, where the 1:n notation indicates the CD to EDTAn molar ratio. The entrapment of IP was achieved by swelling the two polymers with a 0.27 M solution of IP in D2O, leading to colourless, homogeneous hydrogels loaded with IP. The molecular environment and the transport properties of IP in the hydrogels were studied by high resolution magic angle spinning (HRMAS) NMR spectroscopy. The mean square displacement (MSD) of IP in the gels was obtained by a pulsed field gradient spin echo (PGSE) NMR pulse sequence at different observation times t d. The MSD is proportional to the observation time elevated to a scaling factor α. The α values define the normal Gaussian random motion (α = 1), or the anomalous diffusion (α < 1, subdiffusion, α > 1 superdiffusion). The experimental data here reported point out that IP undergoes subdiffusive regime in CDNSEDTA 1:4, while a slightly superdiffusive behaviour is observed in CDNSEDTA 1:8. The transition between the two dynamic regimes is triggered by the polymer structure. CDNSEDTA 1:4 is characterized by a nanoporous structure able to induce confinement effects on IP, thus causing subdiffusive random motion. CDNSEDTA 1:8 is characterized not only by nanopores, but also by dangling EDTA groups ending with ionized COO− groups. The negative potential provided by such groups to the polymer backbone is responsible for the acceleration effects on the IP anion thus leading to the superdiffusive behaviour observed. These results point out that HRMAS NMR spectroscopy is a powerful direct method for the assessment of the transport properties of a drug encapsulated in polymeric scaffolds. The diffusion properties of IP in CDNS can be modulated by suitable polymer synthesis; this finding opens the possibility to design suitable systems for drug delivery with predictable and desired drug release properties.

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15

Cheng, Leo L., Anya B. Zhong, Isabella H. Muti, et al. "Abstract 2322: Multiplatform metabolomics studies of human cancers with NMR and mass spectrometry imaging." Cancer Research 82, no. 12_Supplement (2022): 2322. http://dx.doi.org/10.1158/1538-7445.am2022-2322.

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Abstract Unfortunately, at present, there is no single technique that possesses all the characteristics needed to be considered an ideal global metabolite profiling tool. Thus, the use of multiple analytical platforms, such as combining the strengths of Mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), for metabolic profiling can maximize coverage and generate more global metabolomic profiles. In this study, we demonstrate the utilities of the combined NMR and MSI multiplatform in our metabolomics results on human prostate and lung cancers. Statistical data on the natural history of prostate cancer (PCa) show that &gt;70% of patients diagnosed by PSA screening will likely experience indolent disease with little impact on well-being. For about 17% of newly PSA-diagnosed patients, however, aggressive PCa proliferation ensues, truncating life expectancy. At present, no reliable clinical test can differentiate between these two groups. Using HRMAS 1HNMR followed by quantitative histology, we showed statistically significant correlations between concentrations of Spm and the amount of histologically-benign epithelial (Hb Epi) prostatic cells and glands in human cancerous prostates. However, as above discussed that using HRMAS NMR alone we cannot prove that Spm was indeed generated or resided in the Hb Epi cells. Nevertheless, using MALDI MSI, we were able to locate Spm (m/z: 203.223 ± 0.001Da) onto Hb Epi, where spermine on the PCa lesions appeared below detection limits. From these maps, for the first time, we could visualize and confirm the differential localizations of Spm in prostates. This proof of Sym relationship to prostate pathologies and its proposed PCa inhibitory effects may support further studies that are critical in differentiating aggressive from indolent PCa for disease evaluations and patient personalized treatment strategies. To search for such screening metabolomics biomarkers in lung cancer, we used HRMAS NMR to analyze 93 pairs of human LuCa tissue and serum samples, and 29 healthy human sera. A number of potential metabolite candidates capable to differentiate LuCa characteristics were identified, including glutamate, lipids, alanine, glycerylphosphorylcholine, glutamine, phosphorylcholine, etc. This list can be further expanded by analyzing metabolite composition in the serum of cancer patients and control healthy subjects using LC-MS, which offers a dramatic increase in sensitivity compared to HRMAS NMR and, therefore, is better suited for the biomarker discovery. In addition to acquiring high-resolution mass data, the high data acquisition rate allows the fragment ion mass spectra (MS/MS) to be generated for the most abundant ionic species in each chromatographic peak. This feature allows specific classes of tumor-attenuated metabolites to be identified based on the presence of unique structurally diagnostic fragment ions in MS/MS spectra. Citation Format: Leo L. Cheng, Anya B. Zhong, Isabella H. Muti, Stephen J. Eyles, Richard W. Vachet, Sylwia A. Stopka, Kristen N. Sikora, Cedric E. Bobst, Jeffrey N. Agar, Mari A. Mino-Kenudson, Chin-Lee Wu, David C. Christiani, Igor A. Kaltashov, Nathalie Y. Agar. Multiplatform metabolomics studies of human cancers with NMR and mass spectrometry imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2322.

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16

Brenna, Stefano, Tobias Posset, Julien Furrer, and Janet Blümel. "14N NMR and Two-Dimensional Suspension1H and13C HRMAS NMR Spectroscopy of Ionic Liquids Immobilized on Silica." Chemistry - A European Journal 12, no. 10 (2006): 2880–88. http://dx.doi.org/10.1002/chem.200501193.

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17

Lancelot, Nathalie, Karim Elbayed, Jésus Raya, et al. "Characterization of the 310-Helix in Model Peptides by HRMAS NMR Spectroscopy." Chemistry - A European Journal 9, no. 6 (2003): 1317–23. http://dx.doi.org/10.1002/chem.200390151.

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18

Iqbal, Sajid, Francisco Rodríguez-LLansola, Beatriu Escuder, Juan F. Miravet, Ingrid Verbruggen, and Rudolph Willem. "HRMAS 1H NMR as a tool for the study of supramolecular gels." Soft Matter 6, no. 9 (2010): 1875. http://dx.doi.org/10.1039/b926785a.

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19

Cakmakci, Doruk, Emin Onur Karakaslar, Elisa Ruhland, et al. "Machine learning assisted intraoperative assessment of brain tumor margins using HRMAS NMR spectroscopy." PLOS Computational Biology 16, no. 11 (2020): e1008184. http://dx.doi.org/10.1371/journal.pcbi.1008184.

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Complete resection of the tumor is important for survival in glioma patients. Even if the gross total resection was achieved, left-over micro-scale tissue in the excision cavity risks recurrence. High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) technique can distinguish healthy and malign tissue efficiently using peak intensities of biomarker metabolites. The method is fast, sensitive and can work with small and unprocessed samples, which makes it a good fit for real-time analysis during surgery. However, only a targeted analysis for the existence of known tumor biomarkers can be made and this requires a technician with chemistry background, and a pathologist with knowledge on tumor metabolism to be present during surgery. Here, we show that we can accurately perform this analysis in real-time and can analyze the full spectrum in an untargeted fashion using machine learning. We work on a new and large HRMAS NMR dataset of glioma and control samples (n = 565), which are also labeled with a quantitative pathology analysis. Our results show that a random forest based approach can distinguish samples with tumor cells and controls accurately and effectively with a median AUC of 85.6% and AUPR of 93.4%. We also show that we can further distinguish benign and malignant samples with a median AUC of 87.1% and AUPR of 96.1%. We analyze the feature (peak) importance for classification to interpret the results of the classifier. We validate that known malignancy biomarkers such as creatine and 2-hydroxyglutarate play an important role in distinguishing tumor and normal cells and suggest new biomarker regions. The code is released at http://github.com/ciceklab/HRMAS_NC.

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20

Sizun, C., J. Raya, A. Intasiri, A. Boos, and K. Elbayed. "Investigation of the surfactants in CTAB-templated mesoporous silica by 1H HRMAS NMR." Microporous and Mesoporous Materials 66, no. 1 (2003): 27–36. http://dx.doi.org/10.1016/j.micromeso.2003.08.023.

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21

Li, Wei. "Multidimensional HRMAS NMR: a platform for in vivo studies using intact bacterial cells." Analyst 131, no. 7 (2006): 777. http://dx.doi.org/10.1039/b605110c.

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22

Rousselot-Pailley, Pierre, Christophe Boutillon, Jean-Michel Wieruszeski, and Guy Lippens. "HRMAS NMR observation of ?-sheet secondary structure on a water swollen solid support." Journal of Peptide Science 9, no. 1 (2003): 47–53. http://dx.doi.org/10.1002/psc.431.

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23

Huhn, Stephen D., Christina M. Szabo, Jerome H. Gass, and Adriana E. Manzi. "Metabolic profiling of normal and hypertensive rat kidney tissues by hrMAS-NMR spectroscopy." Analytical and Bioanalytical Chemistry 378, no. 6 (2004): 1511–19. http://dx.doi.org/10.1007/s00216-003-2477-x.

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24

Steiner, Annabel, Stefan Andreas Schmidt, Cara Sophie Fellmann, et al. "Ex Vivo High-Resolution Magic Angle Spinning (HRMAS) 1H NMR Spectroscopy for Early Prostate Cancer Detection." Cancers 14, no. 9 (2022): 2162. http://dx.doi.org/10.3390/cancers14092162.

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The aim of our study was to assess ex vivo HRMAS (high-resolution magic angle spinning) 1H NMR spectroscopy as a diagnostic tool for early PCa detection by testing whether metabolomic alterations in prostate biopsy samples can predict future PCa diagnosis. In a primary prospective study (04/2006–10/2018), fresh biopsy samples of 351 prostate biopsy patients were NMR spectroscopically analyzed (Bruker 14.1 Tesla, Billerica, MA, USA) and histopathologically evaluated. Three groups of 16 patients were compared: group 1 and 2 represented patients whose NMR scanned biopsy was histobenign, but patients in group 1 were diagnosed with cancer before the end of the study period, whereas patients in group 2 remained histobenign. Group 3 included cancer patients. Single-metabolite concentrations and metabolomic profiles were not only able to separate histobenign and malignant prostate tissue but also to differentiate between samples of histobenign patients who received a PCa diagnosis in the following years and those who remained histobenign. Our results support the hypothesis that metabolomic alterations significantly precede histologically visible changes, making metabolomic information highly beneficial for early PCa detection. Thanks to its predictive power, metabolomic information can be very valuable for the individualization of PCa active surveillance strategies.

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Steiner, Annabel, Stefan Andreas Schmidt, Cara Sophie Fellmann, et al. "Ex Vivo High-Resolution Magic Angle Spinning (HRMAS) 1H NMR Spectroscopy for Early Prostate Cancer Detection." Cancers 14, no. 9 (2022): 2162. http://dx.doi.org/10.3390/cancers14092162.

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The aim of our study was to assess ex vivo HRMAS (high-resolution magic angle spinning) 1H NMR spectroscopy as a diagnostic tool for early PCa detection by testing whether metabolomic alterations in prostate biopsy samples can predict future PCa diagnosis. In a primary prospective study (04/2006–10/2018), fresh biopsy samples of 351 prostate biopsy patients were NMR spectroscopically analyzed (Bruker 14.1 Tesla, Billerica, MA, USA) and histopathologically evaluated. Three groups of 16 patients were compared: group 1 and 2 represented patients whose NMR scanned biopsy was histobenign, but patients in group 1 were diagnosed with cancer before the end of the study period, whereas patients in group 2 remained histobenign. Group 3 included cancer patients. Single-metabolite concentrations and metabolomic profiles were not only able to separate histobenign and malignant prostate tissue but also to differentiate between samples of histobenign patients who received a PCa diagnosis in the following years and those who remained histobenign. Our results support the hypothesis that metabolomic alterations significantly precede histologically visible changes, making metabolomic information highly beneficial for early PCa detection. Thanks to its predictive power, metabolomic information can be very valuable for the individualization of PCa active surveillance strategies.

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26

Ritota, M., S. Cozzolino, S. Marconi, P. Sequi, M. Valentini, and F. Marini. "METABOLIC PROFILING OF SWEET PEPPER (CAPSICUM ANNUUM L.) BY MEANS OF HRMAS-NMR SPECTROSCOPY." Acta Horticulturae, no. 932 (May 2012): 279–84. http://dx.doi.org/10.17660/actahortic.2012.932.40.

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27

Le Lann, K., N. Kervarec, C. E. Payri, E. Deslandes, and V. Stiger-Pouvreau. "Discrimination of allied species within the genus Turbinaria (Fucales, Phaeophyceae) using HRMAS NMR spectroscopy." Talanta 74, no. 4 (2008): 1079–83. http://dx.doi.org/10.1016/j.talanta.2007.08.021.

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Kandasamy, Sujatha, Jayeon Yoo, Jeonghee Yun, Han Byul Kang, Kuk-Hwan Seol, and Jun-Sang Ham. "1H HRMAS-NMR based metabolic fingerprints for discrimination of cheeses based on sensory qualities." Saudi Journal of Biological Sciences 27, no. 6 (2020): 1446–61. http://dx.doi.org/10.1016/j.sjbs.2020.04.043.

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Händel, Heidi, Elke Gesele, Klaus Gottschall, and Klaus Albert. "Application of HRMAS 1H NMR Spectroscopy To Investigate Interactions between Ligands and Synthetic Receptors." Angewandte Chemie International Edition 42, no. 4 (2003): 438–42. http://dx.doi.org/10.1002/anie.200390133.

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Palomino-Schätzlein, Martina, Maria Micaela Molina-Navarro, Marta Tormos-Pérez, Susana Rodríguez-Navarro, and Antonio Pineda-Lucena. "Optimised protocols for the metabolic profiling of S. cerevisiae by 1H-NMR and HRMAS spectroscopy." Analytical and Bioanalytical Chemistry 405, no. 26 (2013): 8431–41. http://dx.doi.org/10.1007/s00216-013-7271-9.

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Shintu, Laetitia, Stefano Caldarelli, and Mylène Campredon. "HRMAS NMR spectroscopy combined with chemometrics as an alternative analytical tool to control cigarette authenticity." Analytical and Bioanalytical Chemistry 405, no. 28 (2013): 9093–100. http://dx.doi.org/10.1007/s00216-013-7354-7.

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32

Rainaldi, Mario, Nathalie Lancelot, Karim Elbayed та ін. "Conformational analysis by HRMAS NMR spectroscopy of resin-bound homo-peptides from Cα-methyl-leucine". Org. Biomol. Chem. 1, № 11 (2003): 1835–37. http://dx.doi.org/10.1039/b303193d.

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Ritota, Mena, Lorena Casciani, and Massimiliano Valentini. "PGI chicory (Cichorium intybus L.) traceability by means of HRMAS-NMR spectroscopy: a preliminary study." Journal of the Science of Food and Agriculture 93, no. 7 (2012): 1665–72. http://dx.doi.org/10.1002/jsfa.5947.

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Stenman, Katarina, Pär Stattin, Hans Stenlund, Katrine Riklund, Gerhard Gröbner, and Anders Bergh. "H HRMAS NMR Derived Bio-markers Related to Tumor Grade, Tumor Cell Fraction, and Cell Proliferation in Prostate Tissue Samples." Biomarker Insights 6 (January 2011): BMI.S6794. http://dx.doi.org/10.4137/bmi.s6794.

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A high-resolution magic angle spinning NMR spectroscopic approach is presented for evaluating the occurrence, amount and aggressiveness of cancer in human prostate tissue samples. Using this technique, key metabolites in malignant and non-malignant samples (n = 149) were identified, and patterns of their relative abundance were analyzed by multivariate statistical methods. Ratios of various metabolites – including (glycerophophorylcholine + phosphorylcholine)/creatine, myo-inositol/scyllo-inositol, scyllo-inositol/creatine, choline/creatine, and citrate/creatine – correlated with: i) for non-malignant tissue samples, the distance to the nearest tumor and its Gleason score and; ii) the fraction of tumor cells present in the sample; and iii) tumor cell proliferation (Ki67 labelling index). This NMR-based approach allows the extraction of information that could be useful for developing novel diagnostic methods for prostate cancer.

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35

Mazzei, Pierluigi, and Alessandro Piccolo. "1H HRMAS-NMR metabolomic to assess quality and traceability of mozzarella cheese from Campania buffalo milk." Food Chemistry 132, no. 3 (2012): 1620–27. http://dx.doi.org/10.1016/j.foodchem.2011.11.142.

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36

Fauvelle, F., F. Dorandeu, P. Carpentier, et al. "Changes in mouse brain metabolism following a convulsive dose of soman: A proton HRMAS NMR study." Toxicology 267, no. 1-3 (2010): 99–111. http://dx.doi.org/10.1016/j.tox.2009.10.026.

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Poschalko, Alexander, Nathalie Lancelot, Julien Marin, et al. "DEUSS: A Perdeuterated Poly(oxyethylene)-Based Resin for Improving HRMAS NMR Studies of Solid-Supported Molecules." Chemistry - A European Journal 10, no. 18 (2004): 4532–37. http://dx.doi.org/10.1002/chem.200400373.

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Valente, Ana P., Fábio C. L. Almeida, Clovis R. Nakaie, Shirley Schreier, Edson Crusca, and Eduardo M. Cilli. "Study of the effect of the peptide loading and solvent system in SPPS by HRMAS-NMR." Journal of Peptide Science 11, no. 9 (2005): 556–63. http://dx.doi.org/10.1002/psc.659.

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Benahmed, Malika A., Karim Elbayed, François Daubeuf, Nicola Santelmo, Nelly Frossard, and Izzie J. Namer. "NMR HRMAS spectroscopy of lung biopsy samples: Comparison study between human, pig, rat, and mouse metabolomics." Magnetic Resonance in Medicine 71, no. 1 (2013): 35–43. http://dx.doi.org/10.1002/mrm.24658.

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Rabeson, H., F. Fauvelle, G. Testylier, et al. "Quantitation with QUEST of brain HRMAS-NMR signals: Application to metabolic disorders in experimental epileptic seizures." Magnetic Resonance in Medicine 59, no. 6 (2008): 1266–73. http://dx.doi.org/10.1002/mrm.21610.

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Villa, Palmira, David Castejón, Marta Herraiz, and Antonio Herrera. "1 H-HRMAS NMR study of cold smoked Atlantic salmon (Salmo salar ) treated with E-beam." Magnetic Resonance in Chemistry 51, no. 6 (2013): 350–57. http://dx.doi.org/10.1002/mrc.3957.

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Imperiale, Alessio, Karim Elbayed, François-Marie Moussallieh, et al. "Metabolomic pattern of childhood neuroblastoma obtained by 1H-high-resolution magic angle spinning (HRMAS) NMR spectroscopy." Pediatric Blood & Cancer 56, no. 1 (2010): 24–34. http://dx.doi.org/10.1002/pbc.22668.

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Rocha, Cláudia M., António S. Barros, Ana M. Gil, et al. "Metabolic Profiling of Human Lung Cancer Tissue by1H High Resolution Magic Angle Spinning (HRMAS) NMR Spectroscopy." Journal of Proteome Research 9, no. 1 (2010): 319–32. http://dx.doi.org/10.1021/pr9006574.

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Pope, J. C., T. Posset, N. Bhuvanesh, and J. Blümel. "The Palladium Component of an Immobilized Sonogashira Catalyst System: New Insights by Multinuclear HRMAS NMR Spectroscopy." Organometallics 33, no. 23 (2014): 6750–53. http://dx.doi.org/10.1021/om501162q.

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Pinoie, Vanja, Monique Biesemans, and Rudolph Willem. "Quantitative Tin Loading Determination of Supported Catalysts by119Sn HRMAS NMR using a Calibrated Internal Signal (ERETIC)." Organometallics 27, no. 15 (2008): 3633–34. http://dx.doi.org/10.1021/om800399x.

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Torregrossa, Liborio, Laetitia Shintu, Jima Nambiath Chandran, et al. "Toward the Reliable Diagnosis of Indeterminate Thyroid Lesions: A HRMAS NMR-Based Metabolomics Case of Study." Journal of Proteome Research 11, no. 6 (2012): 3317–25. http://dx.doi.org/10.1021/pr300105e.

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Mao, Hui, Donna Toufexis, Xiaoxia Wang, Agnès Lacreuse, and Shaoxiong Wu. "Changes of metabolite profile in kainic acid induced hippocampal injury in rats measured by HRMAS NMR." Experimental Brain Research 183, no. 4 (2007): 477–85. http://dx.doi.org/10.1007/s00221-007-1061-6.

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Ritota, Mena, Lorena Casciani, Bei-Zhong Han, et al. "Traceability of Italian garlic (Allium sativum L.) by means of HRMAS-NMR spectroscopy and multivariate data analysis." Food Chemistry 135, no. 2 (2012): 684–93. http://dx.doi.org/10.1016/j.foodchem.2012.05.032.

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Ruhl, Isaiah D., Elodie Salmon, and Patrick G. Hatcher. "Early diagenesis of Botryococcus braunii race A as determined by high resolution magic angle spinning (HRMAS) NMR." Organic Geochemistry 42, no. 1 (2011): 1–14. http://dx.doi.org/10.1016/j.orggeochem.2010.09.004.

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Culeddu, N., A. Solinas, M. Chessa, et al. "675 HIGH RESOLUTION-MAGIC ANGLE SPINNING (HRMAS)- NMR-BASED METABOLOMIC FINGERPRINTS OF EARLY AND RECURRENT HEPATOCELLULAR CARCINOMA." Journal of Hepatology 58 (April 2013): S274. http://dx.doi.org/10.1016/s0168-8278(13)60677-7.

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