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Citations & Reviews

Ningombam, S.M., Shulaev, V., 2022. Bioinformatics in Lipidomics: Automating Large-Scale LC-MS-Based Untargeted Lipidomics Profiling with SimLipid Software. Methods Mol. Biol., 2396, 197-214.
Pakiet, A., Sikora, K., Kobiela, J., Rostkowska, O., Mika, A. and Sledzinski, T., 2021. Alterations in complex lipids in tumor tissue of patients with colorectal cancer. Lipids in health and disease, 20(1), pp.1-11.
Vasilopoulou, C.G., Sulek, K., Brunner, A.D., Meitei, N.S., Schweiger-Hufnagel, U., Meyer, S.W., Barsch, A., Mann, M. and Meier, F., 2020. Trapped ion mobility spectrometry and PASEF enable in-depth lipidomics from minimal sample amounts. Nature Communications, 11(1), pp.1-11.
Haler, J. R., Sisley, E., Diaz, Y. C., Meitei, S., Cooper, H. J., & Fernandez-Lima, F. (2019). Workflow for Fast Lipid Tissue Screening using LESA-FT-ICR-MS. Analytical Methods, 2019, 11, 2385-2395.
Meitei, N.S. (October 12, 2018). A Faster Way to Quantitatively Profile the Lipidome. Technology Networks.
Kothalawala, N., Mudalige, T. K., Sisco, P., Linder, S. W. (2018). Novel analytical methods to assess the chemical and physical properties of liposomes. Journal of Chromatography B, 1091, 14–20.
Rajanayake, K. K., Taylor, W. R., & Isailovic, D. (2016). The comparison of glycosphingolipids isolated from an epithelial ovarian cancer cell line and a nontumorigenic epithelial ovarian cell line using MALDI-MS and MALDI-MS/MS. Carbohydrate Research. In Press, doi:10.1016/j.carres.2016.05.006.
Han, Xianlin. Lipidomics: Comprehensive Mass Spectrometry of Lipids. John Wiley & Sons, 2016.
Cordeiro, F. B., Cataldi, T. R., da Costa, L. D. V. T., de Lima, C. B., Stevanato, J., Zylbersztejn, D. S., Ferreira, C.R., Eberlin, M.N., Cedenho, A.P., & Turco, E. G. L. (2014). Follicular fluid lipid fingerprinting from women with PCOS and hyper response during IVF treatment. Journal of assisted reproduction and genetics. doi:10.1007/s10815-014-0375-0.
Gueugneau, M., Coudy-Gandilhon, C., Théron, L., Meunier, B., Barboiron, C., Combaret, L., Taillandier, D., Polge, C., Attaix, D., Picard, B., Verney, J., Roche, F., Féasson, L., Barthélémy, J.C., & Béchet, D. (2014). Skeletal Muscle Lipid Content and Oxidative Activity in Relation to Muscle Fiber Type in Aging and Metabolic Syndrome. J Gerontol A Biol Sci Med Sci, glu086. doi: 10.1093/gerona/glu086.
Kang, Y. P., Lee, W. J., Hong, J. Y., Lee, S. B., Park, J. H., Kim, D., Park, S., Park, C.S., Park, S.W., & Kwon, S. W. (2014). Novel approach for analysis of Bronchoalveolar Lavage Fluid (BALF) using HPLC-QTOF-MS-based lipidomics: Lipid levels in asthmatics and corticosteroid-treated asthmatic patients. J. Proteome Res, 13 (9), 3919–3929.
Glutathion, D. T. (2014). Deutscher Lebensmittelchemikertag 2013 in Braunschweig. Lebensmittelchemie, 68, 17-48.
Edwards, G., Aribindi, K., Guerra, Y., Lee, R. K., & Bhattacharya, S. K. (2014). Phospholipid profiles of control and glaucomatous human aqueous humor. Biochimie, 101, 232-247.
Nie, W., Yan, L., Lee, Y. H., Guha, C., Kurland, I. J., & Lu, H. (2014). Advanced mass spectrometry‐based multi‐omics technologies for exploring the pathogenesis of hepatocellular carcinoma. Mass Spectrometry Reviews. doi: 10.1002/mas.21439.
West, R. E., Marvin, R. K., Hensley, K., & Isailovic, D. (2014). Qualitative analysis of omega-3 fatty acid oxidation by desorption electrospray ionization-mass spectrometry (DESI-MS). Int J Mass Spectrom, 372, 29-38.
Camargo, M., Intasqui, P., de Lima, C. B., Montani, D. A., Nichi, M., Pilau, E. J., Gozzo, F.C., Lo Turco, E.G., & Bertolla, R. P. (2014). MALDI-TOF fingerprinting of seminal plasma lipids in the study of human male infertility. Lipids, 49(9), 943-956.
Kaur, P., Rizk, N., Ibrahim, S., Luo, Y., Younes, N., Perry, B., Dennis, K., Zirie, M., Luta, G., & Cheema, A.K. (2014). Quantitative metabolomic and lipidomic profiling reveals aberrant amino acid metabolism in type 2 diabetes. Mol Biosyst., 9(2):307-17.
Aribindi, K., Guerra, Y., Lee, R. K., & Bhattacharya S. K. (2013). Comparative phospholipid profiles of control and glaucomatous human trabecular meshwork. Invest Ophthalmol Vis Sci, 54(4):3037-3044.
Ghosh, S.P., Singh, R., Chakraborty, K., Kulkarni, S., Uppal, A., Luo, Y., Kaur, P., Pathak, R., Kumar, K.S., Hauer-Jensen, M., & Cheema, A.K. (2013). Metabolomic changes in gastrointestinal tissues after whole body radiation in a murine model. Mol Biosyst, 9(4):723-731.
Bhattacharya, S.K. (2013). Recent advances in shotgun lipidomics and their implication for vision research and ophthalmology. Curr Eye Res, 38(4):417-427.
Aribindi, K., Guerra, Y., Piqueras, M. D. C., Banta, J. T., Lee, R. K., & Bhattacharya, S. K. (2013). Cholesterol and glycosphingolipids of human trabecular meshwork and aqueous humor: comparative profiles from control and glaucomatous donors. Current eye research, 38(10), 1017-1026.
Wheelock, C.E., Goss, V.M., Balgoma, D., Nicholas, B., Brandsma, J., Skipp, P.J., Snowden, S., Burg, D., D'Amico, A., Horvath, I., Chaiboonchoe, A., Ahmed, H., Ballereau, S., Rossios, C., Chung, K.F., Montuschi, P., Fowler, S.J., Adcock, I.M., Postle, A.D., Dahlén, S.E., Rowe, A., Sterk, P.J., Auffray, C., Djukanovic, R., & U-BIOPRED Study Group. (2013). Application of 'omics technologies to biomarker discovery in inflammatory lung diseases. Eur Respir J, 42(3):802-825.
Chughtaia, S., Chughtaia, K., Cillero-Pastora, B., Kiss, A., Agrawal, P., MacAleesea, L., & Heeren, R.M.A. (2012). A multimodal mass spectrometry imaging approach for the study of musculoskeletal tissues. Int J Mass Spectrom, 325–327, 150–160.
Chansela, P., Goto-Inoue, N., Zaima, N., Hayasaka, T., & Sroyraya, M. et al. (2012) Composition and localization of lipids in Penaeus merguiensis ovaries during the ovarian maturation cycle as revealed by imaging mass spectrometry. PLoS ONE, 7(3): e33154.
Scherer, M., Leuthäuser-Jaschinski, K., Ecker, J., Schmitz, G., & Liebisch, G. (2010). A rapid and quantitative LC-MS/MS method to profile sphingolipids. J Lipid Res, 51(7):2001-2011.



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