2020 –

2020
  1. Pan, S., Hullar, M.A.J., Lai, L.A., Peng, H., May, D.H., Noble, W.S., Raftery, D., Navarro, S.L., Neuhouser, M.L., Lampe, P.D., Lampe, J.W., Chen, R. Gut Microbial Protein Expression in Response to Dietary Patterns in a Controlled Feeding Study: A Metaproteomic Approach. Microorganisms 8(3):379, 2020
  2. Deng, L., Guo, F., Cheng, K-K., Zhu, J., Gu, H., Raftery, D., Dong, J. Identifying Significant Metabolic Pathways Using Multi-Block Partial Least-Squares Analysis. J Proteome Res 19(5):1965-1974. 2020
  3. Liu, Y., Xu, X., Deng, L.,. Cheng, K., Xu, J., Raftery, D., Dong, J. A Novel Network Modelling for Metabolite Set Analysis: A Case Study on CRC Metabolomics. IEEE Access 8:106425-106436, 2020
  4. Zhang, X., Dong, J., Raftery, D. Five Easy Metrics of Data Quality for LC–MS-Based Global Metabolomics. Anal Chem. in press, 2020
  5. Meador, J.P., Bettcher, L.F., Ellenberger, M.C., Senn, T.D. Metabolomic profiling for juvenile Chinook salmon exposed to contaminants of emerging concern. Science Total Environ. 747:141097, 2020
  6. Navarro, S.L., Levy, L., Curtis, K.R., Elkon, I., Kahsai, O.J., Ammar, H.S., Randolph, T.W., Hong, N.N., Carnevale Neto, F., Raftery, D., Chapkin, R.S. Effect of a flaxseed lignan intervention on circulating bile acids in a placebo-controlled randomized, crossover trial. Nutrients, 12(6):1837, 2020
  7. Jin, K., Wilson, K.A., Beck, J.N., Nelson, C.S., Brownridge III, G.W., Harrison, B.R., Djukovic, D., Raftery, D., Brem, R.B., Yu, S., Drton, M. Genetic and metabolomic architecture of variation in diet restriction-mediated lifespan extension in Drosophila. PLoS genetics. 16(7):e1008835, 2020.
  8. Kamp, J.K., Cain, K.C., Utleg, A., Burr, R.L., Raftery, D., Luna, R.A., Shulman, R.J., Heitkemper, M.M. Bile acids and microbiome among individuals with irritable bowel syndrome and healthy volunteers. Biol Res. Nurs. in press, 2020.
  9. Harrison, B.R., Wang, L., Gajda, E., Hoffman, E.V., Chung, B.Y., Pletcher, S.D., Raftery, D., Promislow, D.E.L. The metabolome as a link in the genotype-phenotype map for peroxide resistance in the fruit fly, Drosophila melanogaster. BMC Genomics 21: 341, 2020.
  10. Johnson, S.C., Kayser, E.-B., Bornstein, R., Stokes, J., Bitto, A., Park, K.Y., Pan, A., Sun, G., Raftery, D., Kaeberlein, M., Sedensky, M.M., Morgan, P.G. Regional metabolic signatures in the Ndufs4(KO) mouse brain implicate defective glutamate/α-ketoglutarate metabolism in mitochondrial disease. Mol. Genet. Metab. 130(2):118-132, 2020.
  11. Utzschneider, K.M., Johnson, T.N., Breymeyer, K.L., Bettcher, L., Raftery, D., Newton, K.M., Neuhouser, M.L. Small changes in glucose variability induced by low and high glycemic index diets are not associated with changes in β-cell function in adults with pre-diabetes. J Diabetes Complications. 34(8):107586,  2020.
  12. Ioannou, G.N., Nagana Gowda, G.A., Djukovic, D., Raftery, D. Distinguishing NASH histological severity using a multiplatform metabolomics approach. Metabolites. 10(4):E168, 2020. PMID: 32344559.
  13. Djukovic, D., Raftery, D., Nagana Gowda, G.A. Chapter 16 – Mass spectrometry and NMR spectroscopy based quantitative metabolomics, in Proteomic and Metabolomic Approaches to Biomarker Discovery (Second Edition), Editor(s): Issaq, H. J., Veenstra, T. D. Academic Press, 289-311, 2020. doi: 10.1016/B978-0-12-818607-7.00016-5.
  14. Hanson, A.J., Banks, W.A., Bettcher, L.F., Pepin, R., Raftery, D., Craft, S. Cerebrospinal fluid lipidomics: effects of an intravenous triglyceride infusion and apoE status, Metabolomics. 16(1):6 , 2020. PMID: 31832778.
  15. Ritterhoff, J., Young, S., Villet, O., Shao, D., Carnevale Neto, F., Bettcher, L.F., Hsu, Y.A., Kolwicz, S.C., Raftery, D., Tian, R. Metabolic Remodeling Promotes Cardiac Hypertrophy by Directing Glucose to Aspartate Biosynthesis, Circ Res. 126(2):182-196, 2020. PMID: 31709908.