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Eva-Maria Patronas (geb. Klebermass)
Mag. pharm. Eva-Maria Patronas (geb. Klebermass)

Department of Biomedical Imaging and Image-guided Therapy (Division of Nuclear Medicine)
Position: PHD Student

T +43 1 40400 15570
eva-maria.patronas@meduniwien.ac.at

Keywords

Carbohydrate Metabolism; Diagnostic Imaging; Metabolism; Oncology; Positron-Emission Tomography

Research interests

My main research interest is the visualization and characterization of energy metabolism, especially carbohydrate metabolism, using PET tracers. Currently, I am focused on studying the metabolism of the radiotracer 2-[18F]FDG and its impact on PET imaging. In addition, I am interested in the pentose phosphate pathway and the development of new imaging probes targeting carbohydrate metabolism.

Techniques, methods & infrastructure

Techniques and Methods:

  • 2D and 3D cell culture
  • Analytical HPLC
  • Enzyme activity assays
  • Autoradiography
  • Western Blot
  • PCR
  • Immunohistochemistry
  • Small animal PET/CT


Infrastructure:

 Access to the Preclinical Imaging Laboratory (FELASA certificate).

Selected publications

  1. Klebermass, E.-M. et al. (2021) ‘If It Works, Don’t Touch It? A Cell-Based Approach to Studying 2-[18F]FDG Metabolism’, Pharmaceuticals, 14(9), p. 910. Available at: http://dx.doi.org/10.3390/ph14090910.
  2. Philippe, C., Klebermass E.M. et al. (2021) ‘Discovery of melanin‐concentrating hormone receptor 1 in brown adipose tissue’, Annals of the New York Academy of Sciences, 1494(1), pp. 70–86. Available at: http://dx.doi.org/10.1111/nyas.14563.
  3. Hana, C.A. et al. (2021) ‘Inhibition of Lipid Accumulation in Skeletal Muscle and Liver Cells: A Protective Mechanism of Bilirubin Against Diabetes Mellitus Type 2’, Frontiers in Pharmacology, 11. Available at: http://dx.doi.org/10.3389/fphar.2020.636533.
  4. Klebermass, E.-M. et al. (2022) ‘Autoradiography on deparaffinized tissue sections – A feasibility study with 68Ga-labeled PET-tracers’, Applied Radiation and Isotopes, 189, p. 110425. Available at: http://dx.doi.org/10.1016/j.apradiso.2022.110425.
  5. Sundar, L.K. et al. (2018) ‘Towards quantitative [18F]FDG-PET/MRI of the brain: Automated MR-driven calculation of an image-derived input function for the non-invasive determination of cerebral glucose metabolic rates’, Journal of Cerebral Blood Flow & Metabolism, 39(8), pp. 1516–1530. Available at: http://dx.doi.org/10.1177/0271678x18776820.