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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 View Research Article/Paper
Han, Xianlin. Lipidomics: Comprehensive Mass Spectrometry of Lipids. John Wiley & Sons, 2016 View Research Article/Paper
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. View Research Article/Paper
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. View Research Article/Paper
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. View Research Article/Paper
Glutathion, D. T. (2014). Deutscher Lebensmittelchemikertag 2013 in Braunschweig. Lebensmittelchemie, 68, 17-48. View Research Article/Paper
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. View Research Article/Paper
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. View Research Article/Paper
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. View Research Article/Paper
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. View Research Article/Paper
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. View Research Article/Paper
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. View Research Article/Paper
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. View Research Article/Paper
Bhattacharya, S.K. (2013). Recent advances in shotgun lipidomics and their implication for vision research and ophthalmology. Curr Eye Res, 38(4):417-427. View Research Article/Paper
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.
View Research Article/Paper
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. View Research Article/Paper
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.
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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. View Research Article/Paper
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. View Research Article/Paper



A high throughput informatics tool for identification and relative quantitation of lipids using data from LC-, MALDI-, Shotgun-, Mass Spectrometry Workflows

The main biological functions of lipids include energy storage, acting as structural components of cell membranes, and participating as important signaling molecules.

Comparative studies of complex lipid mixtures found in cells and tissues could potentially reveal lipid biomarkers. The presence of lipids in membranes is reflective of the physiological state of an organism at a given time. Targeted and non-targeted approaches based on chromatography and mass spectrometry are employed for such studies. Both the approaches involve identification and measurement of lipids in the samples.

The challenges with mass spectrometry based lipidomics are the chemical complexity and large range of concentration of thousands of lipid species that are present in biological samples. Moreover, identification of lipids requires sophisticated software since automated interpretation of lipid MS/MS spectra is more challenging as compared to other biopolymers such as DNA, carbohydrates or peptides since lipids show much less standardized fragment mass spectra. Each lipid class has its own fragmentation patterns as well as ionization efficiency.

High Throughput DIA Data Processing with Waters® UPLC® SONAR™ and Waters® UPLC® HDMSE along with Waters® TQ-S and Shimadzu LCMS 8060 are now supported!

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  • Robust Lipid Structure Database
  • Project Management and Data Visualization
  • High Throughput Lipid Structural Elucidation using MS, MS/MS and MSE Data
  • High Throughput DIA Data Processing- Waters® UPLC® SONAR™ and Waters® UPLC® HDMSE
  • LC MS and LC- MS/MS (DDA) High Throughput Data Processing
  • Multiplexed Precursor Ion Scan (PIS) and Neutral Loss Scan (NLS) Triple Quadrupole Mass Spectrometry Methods Based Lipid Profiling and Quantitation - Waters® TQ-S, Shimadzu LCMS 8060
  • Normalize Analyte Peaks Based on Peaks of the Internal Standards; either analytes, and the internal standards belong to same lipid class or an analyte and one of the internal standards have the "closest retention time"
  • MALDI-FT-ICR-MS Lipidomics Analysis
  • Mass Spectra Annotation with Identified Lipids
  • Generate Report

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