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1) Griffin J.L., Castro C. NMR-Based Metabolomics in Cardiac Research. NMR-Based Metabolomics. Methods in Molecular Biology (2019)

2) Zhichao X, Changrong G, Guanghong Z, Wangang Z, Guozhou L. 1H NMR-based metabolic characterization of Chinese Wuding chicken meat,
Food Chemistry(2019)

3) Duan, X., Zhang, T., Ou, L. et al. 1H NMR-based metabolomic study of metabolic profiling for the urine of kidney stone patients Urolithiasis (2019).

4) Uddin, G.M., Zhang, L., Shah, S. et al. Impaired branched chain amino acid oxidation contributes to cardiac insulin resistance in heart failure. Cardiovasc Diabetol (2019)

5) Le Gresley A, R. Peron J. A semi-automatic approach to the characterisation of dark chocolate by Nuclear Magnetic Resonance and multivariate analysis. Food Chemistry (2019)

6) Le Gresley A, Broadberry G, Robertson C, R. Peron J, Robinson J, O’Leary S. Application of pure shift and diffusion NMR for the characterisation of crude and processed pyrolysis oil. Journal of Analytical and Applied Pyrolysis (2019)

7) Palma, P.F.S., Bock, C., Silva, T.S. et al. STC1 and PTHrP Modify Carbohydrate and Lipid Metabolism in Liver of a Teleost Fish. Sci Rep 9, 723 (2019)

8) Jung Eun Lee, Sin Soo Jeun, Se Hoon Kim, Chang Young Yoo, Hyeon-Man Baek, Seung Ho Yang, Metabolic profiling of human gliomas assessed with NMR, Journal of Clinical Neuroscience (2019)

9) Zhong Y, Shi J, Zheng Z, Azher Nawaz M, Chen C, Cheng F, Kong Q, Bie Z, Huang Y, NMR-based fruit metabonomic analysis of watermelon grafted onto different rootstocks under two potassium levels, Scientia Horticulturae (2019)

10) Oliphant, K., Parreira, V.R., Cochrane, K. et al. Drivers of human gut microbial community assembly: coadaptation, determinism and stochasticity. ISME J (2019)

11) Montes-Grajales, D.; Esturau-Escofet, N.; Esquivel, B.; Martinez-Romero, E. Exo-Metabolites of Phaseolus vulgaris-Nodulating Rhizobial Strains. Metabolites 2019, 9, 105.

12) Mongan AM, Lynam-Lennon N, Doyle SL, et al. Visceral Adipose Tissue Modulates Radiosensitivity in Oesophageal Adenocarcinoma. Int J Med Sci. (2019)

13) T. Cappello, M. Maisano, A. Giannetto, A. Natalotto, V. Parrino, A. Mauceri & N. Spanò Pen shell Pinna nobilis L. (Mollusca: Bivalvia) from different peculiar environments: adaptive mechanisms of osmoregulation and neurotransmission, The European Zoological Journal(2019)

14) López‐Garrido, L, Bañuelos‐Hernández, AE, Pérez‐Hernández, E, et al. Metabolic profiling of serum in patients with cartilage tumours using 1H‐NMR spectroscopy: A pilot study. Magn Reson Chem. (2019)

15) Zhu, C.; Vitali, B.; Donders, G.; Parolin, C.; Li, Y.; Laghi, L. Univariate Statistical Analysis as a Guide to 1H-NMR Spectra Signal Assignment by Visual Inspection. Metabolites (2019) 9, 15.

16) Campbell J, Werkhoven S, Harrison J. Metabolomics of anoxia tolerance in Drosophila melanogaster: evidence against substrate limitation and for roles of protective metabolites and paralytic hypometabolism American Journal of Physiology-Regulatory, Integrative and Comparative Physiology (2019)

17) Xing, Y., Zhang, W., Zhao, H., Shen, Z., Liang, W., Zhou, J. ... Tang, S. Multi organ assessment via a 9.4 Tesla MRS evaluation of metabolites during the embryonic development of cleft palate induced by dexamethasone. Molecular Medicine Reports(2019)

18) Foroutan A., Goldansaz S.A., Lipfert M., Wishart D.S. Protocols for NMR Analysis in Livestock Metabolomics. In: Bhattacharya S. (eds) Metabolomics. Methods in Molecular Biology(2019)

19) Dubey, D, Chaurasia, S, Guleria, A, et al. Metabolite assignment of ultrafiltered synovial fluid extracted from knee joints of reactive arthritis patients using high resolution NMR spectroscopy. Magn Reson Chem. (2019)

20) Kim M, Kim I, Sung H, Nam M, Kim Y, Kyung D, Seong J, Hwang G. Metabolic dysfunction following weight regain compared to initial weight gain in a high-fat diet-induced obese mouse model. The Journal of Nutritional Biochemistry (2019)

21) Cheng, SC., Chen, K., Chiu, CY. et al. Metabolomic biomarkers in cervicovaginal fluid for detecting endometrial cancer through nuclear magnetic resonance spectroscopy
Metabolomics (2019)

22) Deyssenroth, M.A., Colicino, E., Curtin, P. et al. Quantitative methods for metabolomic analyses evaluated in the Children’s Health Exposure Analysis Resource (CHEAR). J Expo Sci Environ Epidemiol (2019)

23) Santiago G, Contreras J, Camargo M, Vallejo L. NMR-based metabonomic approach reveals changes in the urinary and fecal metabolome caused by resveratrol. Journal of Pharmaceutical and Biomedical Analysis (2019)

24) Wagner, L.; Gómez-Requeni, P.; Moazzami, A.A.; Lundh, T.; Vidakovic, A.; Langeland, M.; Kiessling, A.; Pickova, J. 1H NMR-Based Metabolomics and Lipid Analyses Revealed the Effect of Dietary Replacement of Microbial Extracts or Mussel Meal with Fish Meal to Arctic Charr (Salvelinus alpinus). Fishes (2019)

25) Lipfert M., Rout M.K., Berjanskii M., Wishart D.S. Automated Tools for the Analysis of 1D-NMR and 2D-NMR Spectra. In: Gowda G., Raftery D. (eds) NMR-Based Metabolomics. Methods in Molecular Biology(2019)

26) Fernando T, Sawala A, Bailey A, Gould A, Driscoll P. An Improved Method for Measuring Absolute Metabolite Concentrations in Small Biofluid or Tissue Samples. Journal of Proteome Research (2019)

27) Yousf, S., Sardesai, D.M., Mathew, A.B. et al. Metabolic signatures suggest o-phosphocholine to UDP-N-acetylglucosamine ratio as a potential biomarker for high-glucose and/or palmitate exposure in pancreatic β-cells Metabolomics (2019)

28) Choi, Y.Y., Lee, S.J., Lee, Y.J. et al. In vitro and in situ evaluation of Undaria pinnatifida as a feed ingredient for ruminants. J Appl Phycol (2019).

29) Wang X, Shao Z, Zhang Y, Vu T, Wu Z, Xu J, Deng M. A 1H NMR based study of hemolymph metabonomics in different resistant silkworms, Bombyx mori (Lepidotera), after BmNPV inoculation. Journal of Insect Physiology (2019)

30) Kostidis, S, Bank, JR, Soonawala, D, et al. Urinary metabolites predict prolonged duration of delayed graft function in DCD kidney transplant recipients. Am J Transplant. (2019)

31) Armbruster, M., Rist, M., Seifert, S. et al. Metabolite profiles evaluated, according to sex, do not predict resting energy expenditure and lean body mass in healthy non-obese subjects Eur J Nutr (2019)

32) Chen M, Zheng H, Xu M, Zhao L, Zhang Q, Song J, Zhao Z, Lu S, Weng Q, Wu X, Yang W, Fan X, Gao H, Ji J. Changes in hepatic metabolic profile during the evolution of STZ-induced diabetic rats via an 1H NMR-based metabonomic investigation. Biosci Rep (2019)

33) Liu S, Wang G, Xiao Z, Pu Y, Ge C, Liao G. 1H-NMR-based water-soluble low molecular weight compound characterization and free fatty acid composition of five kinds of Yunnan dry-cured hams. LWT (2019)

34) Bowman C, Alpergin E, Ellis J, Wolfgang M. Loss of ACOT7 potentiates seizures and metabolic dysfunction American Journal of Physiology-Endocrinology and Metabolism (2019).

35) Yoon, D. Choi, B.-R. Kim, Y.-C.; Oh, S.M.; Kim, H.-G.; Kim, J.-U.; Baek, N.-I.; Kim, S.; Lee, D.Y. Comparative Analysis of Panax ginseng Berries from Seven Cultivars Using UPLC-QTOF/MS and NMR-Based Metabolic Profiling. Biomolecules (2019)

36) Miller, C.N., Panagos, C.G., Mosedale, W.R.T. et al. NMR metabolomics reveals effects of Cryptosporidium infections on host cell metabolome. Gut Pathog (2019)

37) Mulukutla B, Mitchell J, Geoffroy P, Harrington C, Krishnan M, Kalomeris T, Morris C, Zhang L, Pegman P, Hiller G. Metabolic engineering of Chinese hamster ovary cells towards reduced biosynthesis and accumulation of novel growth inhibitors in fed-batch cultures.Metabolic Engineering (2019)

38) Zainal B, Ding P, Ismail I, Saari N. 1H NMR metabolomics profiling unveils the compositional changes of hydro-cooled rockmelon (Cucumis melo L. reticulatus cv glamour) during storage related to in vitro antioxidant activity. Scientia Horticulturae(2019)

39) Mickiewicz B., Hyndman M.E., Vogel H.J. Metabolite Profiling of Clinical Cancer Biofluid Samples by NMR Spectroscopy. In: Haznadar M. (eds) Cancer Metabolism. Methods in Molecular Biology (2019)

40) Söder, J., Höglund, K., Dicksved, J. et al. Plasma metabolomics reveals lower carnitine concentrations in overweight Labrador Retriever dogs. Acta Vet Scand (2019)

41) Muhammed H, Kumar D, Dubey D, Kumar S, Chaurasia S, Guleria A, Majumder S, Singh R, Agarwal V, Misra R, Metabolomics analysis revealed significantly higher synovial Phe/Tyr ratio in reactive arthritis and undifferentiated spondyloarthropathy, Rheumatology (2019)

42) Xiao, Z. , Luo, Y. , Wang, G. , Ge, C. , Zhou, G. , Zhang, W. and Liao, G. (2019), 1H‐NMR‐based water‐soluble low molecular weight compound characterization and fatty acid composition of boiled Wuding chicken during processing. J. Sci. Food Agric. (2019)

43) Wei, Y, Liang, M, Xu, H, Zheng, K. Taurine alone or in combination with fish protein hydrolysate affects growth performance, taurine transport and metabolism in juvenile turbot (Scophthalmus maximus L.). Aquacult Nutr. (2019)

44) Gu J, Su F, Hong P, Zhang Q, Zhao M. 1H NMR-based metabolomic analysis of nine organophosphate flame retardants metabolic disturbance in Hep G2 cell line. Science of The Total Environment (2019)

45) Joesten, W.C. & Kennedy, RANCM: a new ranking scheme for assigning confidence levels to metabolite assignments in NMR-based metabolomics studies. M.A. Metabolomics (2019)

46) McGuire, J.L., DePasquale, E.A.K., Watanabe, M. et al. Chronic Dysregulation of Cortical and Metabolism After Experimental Traumatic Brain Injury
Mol Neurobiol (2019)

47) Lim, Y.; Song, T.-J.; Hwang, W.; Kim, J.Y.; Lee, D.; Kim, Y.-J.; Kwon, O. Synergistic Effects of Sanghuang–Danshen Bioactives on Arterial Stiffness in a Randomized Clinical Trial of Healthy Smokers: An Integrative Approach to in silico Network Analysis. Nutrients (2019)

48) Connolly, S., Dona, A., Wilkinson-White, L. et al. Relationship of the blood metabolome to subsequent carcass traits at slaughter in feedlot Wagyu crossbred steers. Sci Rep (2019)

49) Ghanbari R, Pathmasiri W, McRitchie S, Stewart D, Etemadi A, Abnet C, Pollock J, Malekzadeh R, Sumner S. Metabolomics Analysis of Opiate Abusers from Golestan Cohort Study (GCS) The FASEB Journal (2019)

50) Bezabeh T., Capati A., Ijare O.B. (2019) NMR-Based Urinary Metabolomics Applications. In: Gowda G., Raftery D. (eds) NMR-Based Metabolomics. Methods in Molecular Biology (2019)

51) Chiu, C‐Y, Cheng, M‐L, Chiang, M‐H, et al. Gut microbial‐derived butyrate is inversely associated with IgE responses to allergens in childhood asthma. Pediatr Allergy Immunol. (2019)

52) Rocculi P, Cevoli C, Tappi S, Genovese J, Urbinati E, Picone G, Fabbri A, Capozzi F, Dalla Rosa M. Freshness assessment of European hake (Merluccius merluccius) through the evaluation of eye chromatic and morphological characteristics. Food Research International (2019)

53) Zhu, C.; Li, C.; Wang, Y.; Laghi, L. Characterization of Yak Common Biofluids Metabolome by Means of Proton Nuclear Magnetic Resonance Spectroscopy. Metabolites (2019)

54) Lindqvist H, Gjertsson I, Andersson S, Calder P, Bärebring L. Influence of blue mussel (Mytilus edulis) intake on fatty acid composition in erythrocytes and plasma phospholipids and serum metabolites in women with rheumatoid arthritis. Prostaglandins, Leukotrienes and Essential Fatty Acids (2019)

55) Rautureau G, Palama T, Canard I, Mirande C, Chatellier S, van Belkum A, Elena-Herrmann B. Discrimination of Escherichia coli and Shigella spp. by Nuclear Magnetic Resonance Based Metabolomic Characterization of Culture Media. ACS Infectious Diseases (2019)

56) Tóth, L; Urbach, K; Klika, K D; H-M, Lorenz; Carvalho, R A; et al. P175 Comparative metabolomic and lipidomic analysis of serum samples from patients with seronegative rheumatoid arthritis and psoriatic arthritis Annals of the Rheumatic Diseases (2019)

57) Maulidiani M, Abas F, Rudiyanto R, Abdullah N, Azlan A, Lajis N. Application of quantitative spectral deconvolution of 1H NMR (qsd-NMR) in the simultaneous quantitative determination of creatinine and metformin in the human urine. Analytical Methods (2019)

58) Hajirezaee S, Rafieepour A, Shafiei S. A NMR-based metabonomic study on the ameliorating effects of Ginkgo biloba extract in rainbow trout, Oncorhynchus mykiss exposed to organophosphate pesticide, diazinon. Aquaculture(2019)

59) Peroulis, N., Androutsopoulos, V.P., Notas, G. et al. Significant metabolic improvement by a water extract of olives: Animal and human evidence Eur J Nutr (2019)

60) Lee, S.Y., Mediani, A., Ismail, I.S. et al. Antioxidants and α-glucosidase inhibitors from Neptunia oleracea fractions using 1H NMR-based metabolomics approach and UHPLC-MS/MS analysis. BMC Complement Altern Med (2019)

61) van Wyk A.S., van Staden E.M., Nel W.A.J., Prinsloo G. The feasibility of bridge-grafting to restore the flow of sucrose in girdled Ocotea bullata and Curtisia dentata medicinal trees. South African Journal of Botany (2019)

62) Mayengbam S, Mickiewicz B, Trottier S, Mu C, Wright D, Reimer R, Vogel H, Shearer J. Distinct Gut Microbiota and Serum Metabolites in Response to Weight Loss Induced by Either Dairy or Exercise in a Rodent Model of Obesity. Journal of Proteome Research (2019)

63) Yoon, D.; Choi, B.-R.; Ma, S.; Lee, J.W.; Jo, I.-H.; Lee, Y.-S.; Kim, G.-S.; Kim, S.; Lee, D.Y. Metabolomics for Age Discrimination of Ginseng Using a Multiplex Approach to HR-MAS NMR Spectroscopy, UPLC–QTOF/MS, and GC × GC–TOF/MS. Molecules (2019)

64) Lorén, C.E.; Dahl, C.P.; Do, L.; Almaas, V.M.; Geiran, O.R.; Mörner, S.; Hellman, U. Low Molecular Mass Myocardial Hyaluronan in Human Hypertrophic Cardiomyopathy. Cells (2019)

65) Khandelwal P, Andersen H, Romick-Rosendale L, Taggart C, Watanabe M, Lane A, Dandoy C, Lake K, Litts B, Morrow A, Lee M, Haslam D, Davies S. A Pilot Study of Human Milk to Reduce Intestinal Inflammation After Bone Marrow Transplant Breastfeeding Medicine (2019)

66) LeVatte M, Lipfert M, Zheng J, Wishart D. A fast, sensitive, single-step colorimetric dipstick assay for quantifying ascorbic acid in urine. Analytical Biochemistry (2019)

67) chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. (2019)

68) Mora-Ortiz, M., Nuñez Ramos, P., Oregioni, A. et al. NMR metabolomics identifies over 60 biomarkers associated with Type II Diabetes impairment in db/db mice Metabolomics (2019)

69) Awin T, Mediani A, Maulidiani M, Leong S, Faudzi S, Shaari K, Abas F. Phytochemical and bioactivity alterations of Curcuma species harvested at different growth stages by NMR-based metabolomics. Journal of Food Composition and Analysis (2019)

70) Raja V, Salsaa M, Joshi A, Li Y, van Roermund C, Saadat N, Lazcano P, Schmidtke M, Hüttemann M, Gupta S, Wanders R, Greenberg M. Cardiolipin-deficient cells depend on anaplerotic pathways to ameliorate defective TCA cycle function. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids (2019)

71) Bermingham K, Brennan L, Segurado R, Barron R, Gibney E, Ryan M, Gibney M, O’Sullivan A. Exploring Covariation between Traditional Markers of Metabolic Health and the Plasma Metabolomic Profile: A Classic Twin Design. Journal of Proteome Research (2019)

72) Inserte J, Aluja D, Barba I, Ruiz-Meana M, Miró E, Poncelas M, Vilardosa U, Castellano J, Garcia-Dorado D. High-fat diet improves tolerance to myocardial ischemia by delaying normalization of intracellular PH at reperfusion. Journal of Molecular and Cellular Cardiology (2019)

73) Labaki, W.W., Gu, T., Murray, S. et al. Serum amino acid concentrations and clinical outcomes in smokers: SPIROMICS metabolomics study. Sci Rep (2019)

74) Kim, H. C., Ko, Y. J., Kim, M., Choe, J., Yong, H. I., & Jo, C. Optimization of 1D 1H Quantitative NMR (Nuclear Magnetic Resonance) Conditions for Polar Metabolites in Meat. Food science of animal resources (2019).

75) Lohr, K.E., Khattri, R.B., Guingab-Cagmat, J. et al. Metabolomic profiles differ among unique genotypes of a threatened Caribbean coral. Sci Rep (2019)

76) Niemuth J, Harms C, Stoskopf M. Sea Turtle Tears: A Novel, Minimally Invasive Sampling Method for 1H-NMR Metabolomics Investigations with Cold Stun Syndrome as a Case Study. Journal of Wildlife Diseases (2019)

77) Carlucci, C., Jones, C.S., Oliphant, K. et al. Effects of defined gut microbial ecosystem components on virulence determinants of Clostridioides difficile. Sci Rep (2019)

78) Gao H, Jiang Q, Ji H, Ning J, Li C, Zheng H. Type 1 diabetes induces cognitive dysfunction in rats associated with alterations of the gut microbiome and metabolomes in serum and hippocampus. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease (2019)

79) Mayengbam S, Virtanen H, Hittel DS, Elliott C, Reimer RA, Vogel HJ, et al. Metabolic consequences of discretionary fortified beverage consumption containing excessive vitamin B levels in adolescents. PLoS ONE 14(1(2019)

80) Mendoza D, Arias J, Cuaspud O, Esturau-Escofet N, Hernández-Espino C, Rodríguez de San Miguel E, Arias M. 1H-NMR-based metabolomic of plant cell suspension cultures of Thevetia peruviana treated with salicylic acid and methyl jasmonate. Industrial Crops and Products (2019)

81) Metrulas, L. K., McNeil, C., Slupsky, C. M., and Bamforth, C. W. The application of metabolomics to ascertain the significance of prolonged maturation in the production of lager‐style beers, J. Inst. Brew. (2019)

82) Lindqvist H, Rådjursöga M, Malmodin D, Winkvist A, Ellegård L. Serum metabolite profiles of habitual diet: evaluation by 1H-nuclear magnetic resonance analysis, The American Journal of Clinical Nutrition, Volume (2019)

83) Chen L, Wu J, Li Z, Liu Q, Zhao X, Yang H. Metabolomic analysis of energy regulated germination and sprouting of organic mung bean (Vigna radiata) using NMR spectroscopy. Food Chemistry. (2019)

84) Shao X, He J, Liang R, Lu Y, Shi Y, Wang Y, Zheng X, Zhang S, Wang T. Mortality, growth and metabolic responses by 1H-NMR-based metabolomics of earthworms to sodium selenite exposure in soils. Ecotoxicology and Environmental Safety (2019)

85) M. Urpi-Sarda, E. Almanza-Aguilera, R. Llorach, R. Vázquez-Fresno, R. Estruch, D. Corella, J.V. Sorli, F. Carmona, A. Sanchez-Pla, J. Salas-Salvadó, C. Andres-Lacueva. Non-targeted metabolomic biomarkers and metabotypes of type 2 diabetes: A cross-sectional study of PREDIMED trial participants. Diabetes & Metabolism (2019).

86) Ahmed N, Kidane B, Wang L, Qing G, Tan L, Buduhan G, Srinathan S, Aliani M. Non-invasive exploration of metabolic profile of lung cancer with Magnetic Resonance Spectroscopy and Mass Spectrometry. Contemporary Clinical Trials Communications (2019).

87) R. Caricato, M.E. Giordano, T. Schettino, M. Maisano, A. Mauceri, A. Giannetto, T. Cappello, V. Parrino, S. Ancora, I. Caliani, N. Bianchi, C. Leonzio, G. Mancini, S. Cappello, S. Fasulo, M.G. Lionetto. Carbonic anhydrase integrated into a multimarker approach for the detection of the stress status induced by pollution exposure in Mytilus galloprovincialis: A field case study. Science of The Total Environment (2019)

88) Abed-Elmdoust A, Rahimi R, Farahmand H, Amiri B, Mirvaghefi A, Rafiee G. Droplet vitrification versus straw cryopreservation for spermatozoa banking in Persian sturgeon (Acipenser persicus) from metabolite point of view. Theriogenology (2019)

89) Falegan, O.S.; Arnold Egloff, S.A.; Zijlstra, A.; Hyndman, M.E.; Vogel, H.J. Urinary Metabolomics Validates Metabolic Differentiation Between Renal Cell Carcinoma Stages and Reveals a Unique Metabolic Profile for Oncocytomas. Metabolites (2019)

90) Arora, N., Kumari, P., Kumar, A. et al. Delineating the molecular responses of a halotolerant microalga using integrated omics approach to identify genetic engineering targets for enhanced TAG production. Biotechnol Biofuels (2019)

91) Madrid-Gambin F, Garcia-Aloy M, Vázquez-Fresno R, Vegas-Lozano E, Sánchez-Pla A, Misawa K, Hase T, Shimotoyodome A, Andres-Lacueva C. Metabolic Signature of a Functional High-Catechin Tea after Acute and Sustained Consumption in Healthy Volunteers through 1H NMR Based Metabolomics Analysis of Urine. Journal of Agricultural and Food Chemistry (2019)

92) Awin T, Buzgaia N, Ghafar S, Mediani A, Faudzi S, Maulidiani M, Shaari K, Abas F. Identification of nitric oxide inhibitory compounds from the rhizome of Curcuma xanthorrhiza. Food Bioscience (2019)

93) Rohweder B, Lehmann G, Eichner N, Polen T, Rajendran C, Ruperti F, Linde M, Treiber T, Jung O, Dettmer K, Meister G, Bott M, Gronwald W, Sterner R. Library Selection with a Randomized Repertoire of (βα)8-Barrel Enzymes Results in Unexpected Induction of Gene Expression. Biochemistry (2019)

94) Kim K, Lee S, Chun B, Jeong S, Jeon C. Tetragenococcus halophilus MJ4 as a starter culture for repressing biogenic amine (cadaverine) formation during saeu-jeot (salted shrimp) fermentation. Food Microbiology (2019)

95) Thomaidou A, Chatziioannou A, Deda O, Benaki D, Gika H, Mikros E, Agakidis C, Raikos N, Theodoridis G, Sarafidis K. A pilot case-control study of urine metabolomics in preterm neonates with necrotizing enterocolitis. Journal of Chromatography (2019)

96) Alborghetti MR, Correa MEP, Whangbo J, Shi X, Aricetti JA, Silva AA, Miranda ECM, Sforca ML, Caldana C, Gerszten RE, Ritz J, Zeri ACM. Clinical Metabolomics Identifies Blood Serum Branched Chain Amino Acids as Potential Predictive Biomarkers for Chronic Graft vs. Host Disease. Front. Oncol. (2019)

97) Rahimi, R., Farahmand, H., Mirvaghefi, A. et al. 1H NMR metabolic profiling of the cryopreserved spermatozoa of the wild endangered Persian sturgeon (Acipenser persicus) with the use of beta-cyclodextrin as an external cryoprotectant. Fish Physiol Biochem (2019)

98) Ahmed, S, Dubey, D, Chowdhury, A, et al. Nuclear magnetic resonance‐based metabolomics reveals similar metabolomics profiles in undifferentiated peripheral spondyloarthritis and reactive arthritis. Int J Rheum Dis. (2019)

99) Rajasinghe, L.D.; Hutchings, M.; Gupta, S.V. Delta-Tocotrienol Modulates Glutamine Dependence by Inhibiting ASCT2 and LAT1 Transporters in Non-Small Cell Lung Cancer (NSCLC) Cells: A Metabolomic Approach. Metabolites (2019)

100) An, J.N., Hyeon, J.S., Jung, Y. et al. Urinary myo-inositol is associated with the clinical outcome in focal segmental glomerulosclerosis. Sci Rep (2019)

101) Osadnik T, Osadnik K, Pawlas N, et al. Metabolic and genetic profiling of young adults with and without a family history of premature coronary heart disease (MAGNETIC). Study design and methodology. Arch Med Sci. (2019)

102) Liu, Z., Triba, M.N., Amathieu, R. et al. Nuclear magnetic resonance-based serum metabolomic analysis reveals different disease evolution profiles between septic shock survivors and non-survivors. Crit Care 23 (2019)

103) Gu, J, Shu, D, Su, F, Xie, Y, Liang, X. Analysis of metabolome changes in the HepG2 cells of apatinib treatment by using the NMR‐based metabolomics. J Cell Biochem. (2019)

104) Park J, Gim S, Jeon J, Kim M, Choi J, Lee J. Chemical profiles and antioxidant properties of roasted rice hull extracts in bulk oil and oil-in-water emulsion. Food Chemistry (2019)

105) Chiu C, Cheng M, Wong K, Lai S, Chiang M, Tsai M, Lin G. Metabolomics Reveals Anaerobic Bacterial Fermentation and Hypoxanthine Accumulation for Fibrinous Pleural Effusions in Children with Pneumonia. Journal of Proteome Research (2019)

106) Amin A, Mostafa H, Arif N, Kader M, Hay Y. Metabolomics profiling and pathway analysis of human plasma and urine reveal further insights into the multifactorial nature of coronary artery disease. Clinica Chimica Acta (2019)

107) Panthi R, Sundekilde U, Kelly A, Hennessy D, Kilcawley K, Mannion D, Fenelon M, Sheehan J. Influence of herd diet on the metabolome of Maasdam cheeses. Food Research International (2019)

108) Ruan L, Li M, Xing Y, Hong W, Chen C, Chen J, Xu H, Zhao W, Wang J. Hepatotoxicity and hepatoprotection of Polygonum multiflorum Thund. as two sides of the same biological coin. Journal of Ethnopharmacology. (2019)

109) Roth TL, Switzer A, Watanabe-Chailland M, et al. Reduced Gut Microbiome Diversity and Metabolome Differences in Rhinoceros Species at Risk for Iron Overload Disorder. Front Microbiol. (2019)

110) Giskeødegård G, Andreassen T, Bertilsson H, Tessem M, Bathen T. The effect of sampling procedures and day-to-day variations in metabolomics studies of biofluids. Analytica Chimica Acta (2019)

111) Li M, Feng X, Ba D, Chen C, Ruan L, Xing Y, Chen L, Zhong G, Wang J. Hepatoprotection of Herpetospermum caudigerum Wall. against CCl4-induced liver fibrosis on rats. Journal of Ethnopharmacology (2019)

112) Forsgård R, Marrachelli V, Lindén J, Frias R, Collado M, Korpela R, Monleon D, Spillmann T, Österlund P. Two-Week Aflibercept or Erlotinib Administration Does Not Induce Changes in Intestinal Morphology in Male Sprague–Dawley Rats But Aflibercept Affects Serum and Urine Metabolic Profiles. Translational Oncology (2019)

113) Ríos-Reina R, Callejón R, Savorani F, Amigo J, Cocchi M. Data fusion approaches in spectroscopic characterization and classification of PDO wine vinegars. Talanta (2019)

114) Da Costa, M., Cônsolo, N., Silva, J., Buarque, V., Padilla, A., Coutinho, I., . . . Saran Netto, A. (n.d.). Performance, carcass traits and serum metabolomic profile of Nellore males with different genetic potential for post-weaning growth. Animal (2019)

115) Stec D, Henry C, Stec D E, Voziyan P. Changes in urinary metabolome related to body fat involve intermediates of choline processing by gut microbiota. Heliyon (2019)

116) Alinaghi, M.; Jiang, P.-P.; Brunse, A.; Sangild, P.T.; Bertram, H.C. Rapid Cerebral Metabolic Shift during Neonatal Sepsis Is Attenuated by Enteral Colostrum Supplementation in Preterm Pigs. Metabolites (2019)

117) Chen C, Fu Y, Li M, Ruan L, Xu H, Chen J, Zhao W, Meng H, Xing Y, Hong W, Wang J. Nuclear magnetic resonance-based metabolomics approach to evaluate preventive and therapeutic effects of Gastrodia elata Blume on chronic atrophic gastritis. Journal of Pharmaceutical and Biomedical Analysis (2019)

118) O’Brien, K.A., Atkinson, R.A., Richardson, L. et al. Metabolomic and lipidomic plasma profile changes in human participants ascending to Everest Base Camp. Sci Rep 9 (2019)

119) Mora-Ortiz, M., Trichard, M., Oregioni, A. et al. Thanatometabolomics: introducing NMR-based metabolomics to identify metabolic biomarkers of the time of death. Metabolomics (2019)

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Case Studies

The case studies below showcase various studies that were performed using Chenomx technology and services.


Analyzing the Metabolic Effects of Acetaminophen


Developing Biomarkers for Adverse Drug Responses


Pathways From Serological Metabolite Profiles

Acetaminophen is the most common identifiable cause of acute liver failure, and is an excellent model compound for studying liver toxicity. Acetaminophen toxicity has thus become a very active area of research. Identifying and quantifying metabolites associated with acetaminophen toxicity is an integral part of this research, and Chenomx is uniquely equipped to extract this information from biofluid samples.

Drug-induced liver injury is the leading reason that drug candidates fail. Identifying a suite of toxicity biomarkers for use in preclinical screening of drug candidates will allow drugs with harmful side effects to be identified earlier. Biomarkers that can be used to monitor or stage diseases will also offer insight into the net metabolic effect of a drug and can provide information for developing new drugs or adjusting treatment. Chenomx software offers powerful tools to aid in identifying these biomarkers.

Metabolomic data sets obtained using Chenomx NMR Suite often require additional analysis to place them in proper context. The GeneGo pathway analysis platform can help establish this context. In this note, we present an example analysis using serological metabolic profiles from Chenomx NMR Suite, known inflammatory markers from prior studies of the K/BxN mouse model and the GeneGo platform to generate a mechanistic hypothesis for the K/BxN mouse model.

Application Notes


Accurate CSI Quantification for Targeted Profiling

Accurately quantifying metabolites using targeted profiling in Chenomx NMR Suite requires using a chemical shape and shift indicator (CSI) of known concentration. As a result, the accuracy of the CSI concentration has a significant influence on quantification accuracy using this technique. Measuring ratios of the CSI peak area with that of a second, commercially available standard under optimal acquisition conditions offers a simple method of accurately measuring the concentration of the CSI.

 Optimizing Spectra for Metabolomics

Chenomx Processor allows you to work with NMR spectra from a variety of sources, helping you apply phasing and baseline correction through manual and semi-automated tools, and offering advanced lineshape correction through reference deconvolution. Processor also allows you to define chemical shape indicator (CSI) parameters and determine sample pH via indicator compounds. These are necessary prerequisites to analyzing your spectra with Chenomx Profiler.

Sample Types

Targeted Profiling of Common Metabolites in Saliva

Saliva is an excellent biofluid for analysis by targeted profiling. It is easily collected by individuals with minimal training, using noninvasive techniques. Targeted profiling of saliva samples can provide identification and quantification of many of the small molecule metabolites commonly found in saliva, and may allow the development of simple screening procedures for a variety of diseases. In this note we present a list of common metabolites found in human saliva, and techniques for targeted profiling of saliva spectra with Chenomx NMR Suite.

Metabolites in Blood Serum and Plasma

Blood serum and plasma are biofluids that are increasingly important in NMR-based metabolomics analysis. In this note we discuss several approaches to the analysis of serum using Chenomx NMR Suite, focusing on relaxation-edited NMR (CPMG) and physical separation of protein and metabolites using ultrafiltration. The CPMG method is simpler to apply, but the spectra are easier to analyze when protein is removed from a sample.


Targeted Profiling of Common Metabolites in Urine

Urine is a readily-collected, information-rich biofluid that can provide insight into the metabolic state of an organism. As a result, urine is often a focus in metabolomics investigations using NMR and MRI spectroscopy, in both diagnostic and monitoring applications. Targeted profiling is a powerful tool that can drive such studies, providing direct identification and quantification of a variety of metabolites. In this note we present a list of common metabolites found in many NMR spectra of human urine and several strategies for approaching targeted profiling of such spectra with Chenomx NMR Suite.


Identifying Metabolites in Biofluids

In this note we present a rapid, efficient method for identifying metabolites in biofluid NMR spectra using targeted profiling. Conventional techniques for identifying and quantifying metabolites in such spectra are labor-intensive and error-prone, as positions and linewidths of peaks can vary widely with changes in pH and other solution matrix effects. The length of time and level of operator skill needed to analyze large numbers of these complex spectra are significant barriers to the widespread application of NMR in metabolomics.

Statistical Analysis

Statistical Analysis of Targeted Profiling Data

Analysis of 1H NMR spectra in metabolomics studies often requires multivariate pattern recognition techniques to extract meaningful results. Targeted profiling offers the ability to analyze spectra based directly on the identity and quantities of individual compounds. Profiles created using targeted profiling in Chenomx NMR Suite can be used as input in statistical software packages such as Umetrics SIMCA-P. Performing PCA on Chenomx targeted profiles yields information-rich results that allow rapid biological interpretation, since group separation can be directly correlated to variations in specific metabolite concentrations.

Correcting Lineshapes in NMR Spectra

In this note we present a method for removing lineshape distortions from nuclear magnetic resonance (NMR) spectra prior to more detailed analysis. Reference deconvolution is a method of reconstructing an ideal spectrum by removing lineshape distortions caused by field inhomogeneity. Applying reference deconvolution has been found to improve the quality of fit of a spectrum using targeted profiling in Chenomx NMR Suite. However, successful application of reference deconvolution to a spectrum requires some preprocessing and the presence of an appropriate reference peak.


Statistical Analysis of Spectral Binning Data

Analysis of 1H NMR spectra in metabolomics studies often requires multivariate pattern recognition techniques to extract meaningful results. Spectral binning is an effective data reduction technique commonly used to prepare spectra for multivariate analysis. Spectral binning output from the Profiler module of Chenomx NMR Suite can readily be analyzed with multivariate analysis software packages like Umetrics SIMCA-P.