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Molecular Imaging Mass Spectrometry platform - Nexus of Aging and Disease - an imminent global threat. University of Antwerp

Inge Mertens
Molecular Imaging, Pathology, Radiotherapy & Oncology (MIPRO)
Mass spectrometry imaging (MSI) is especially developed for the identification of biomolecules in a manner that retains cytological and histological patterning. This novel technical process, abbreviated to MALDI-MSI represents an interesting and extremely productive intersection between mass spectrometric and imaging platforms. Therefore, the postdoc is bridging 3 University of Antwerp CORE facilities (Center for Proteomics, Bio-Imaging lab and ...

MALDI Mass Spectrometry Imaging (MALDI-MSI): Bridging proteomics and imaging. University of Antwerp

Stuart Maudsley
Center for Oncological Research (CORE), Global Health Institute (GHI), Institutional Research Unit, Molecular Imaging, Pathology, Radiotherapy & Oncology (MIPRO), Laboratory of cell biology and histology, Proteinchemistry, proteomics and epigenetic signalling(PPES), Biomolecular & Analytical Mass Spectrometry (BAMS), Systemic Physiological and Ecotoxicological Research (SPHERE), Translational Neurobiology
The instrument acquired in this project is a matrix assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometer capable of mass spectrometry imaging (MSI). This technique is especially developed for the identification of biomolecules in a manner that retains cytological and histological patterning. This novel technical process, abbreviated to MALDI-MSI represents an interesting and extremely productive intersection between ...

Method development for multi-modal imaging mass spectrometry (LA-ICP-MS and MALDI-MS): fusing elemental with molecular information to gain insight into hypoxia-driven processes in cancer Ghent University

Frank Vanhaecke
Department of Chemistry

Tumor hypoxia is one of the hallmarks of cancer and has turned into a central issue in cancer treatment since it is associated with malignant tumor progression, resistance to therapy and increased metastatic spread. To date, many aspects of hypoxia-induced changes in tumors remain to be elucidated. This drives the need to develop multi-modal imaging workflows for discovering and identifying key biomolecules in the heterogeneous tumor ...

Advanced 2D and 3D chemical imaging using laser ablation ICP - mass spectrometry (LA-ICP-MS) and complementary multimodal techniques via image fusion Ghent University

Frank Vanhaecke
Department of Chemistry, Department of Analytical chemistry

Laser ablation-ICP-mass spectrometry (LA-ICP-MS) can be used for visualizing the distribution of (trace) elements across any solid material with high spatial resolution. The recent development of low-dispersion LA cells has provided gains in throughput and sensitivity of 2-3 orders of magnitude compared to conventional cells. The project focuses on development of methodologies for high-resolution 2D & 3D imaging of samples of a wide range ...

Chemical Imaging of Biological Systems by Mass Spectrometry Imaging-enhanced Coherent Raman Scattering Microscopy KU Leuven

Johan Swinnen
Laboratory of Lipid Metabolism and Cancer
The functioning of biological systems is made possible through intricate interactions between cells that make up the tissues and the interplay between diverse classes of molecules that make up the cells. Dysregulation of this ecosystem typically leads to disease. Recent advances in spatial omics approaches have enabled a detailed mapping of the molecular composition of tissues with retention of spatial information. One of the emerging ...

Manifold Learning for Visualization, Prioritization, and Data Fusion of Mass Spectrometry Imaging Data KU Leuven

Bart De Moor
Laboratory of Protein Phosphorylation and Proteomics, Dynamical Systems, Signal Processing and Data Analytics (STADIUS), ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics

Mass Spectrometry Imaging (MSI) is a powerful molecular imaging technology that can detect the spatial distribution of molecules in a tissue section. Because MSI does not require any a priori labeling, the technique has become very popular for the explorative comparison of metabolites, lipids, peptides and proteins between various tissue regions. Since it has been shown that tumor heterogeneity plays an important role in tumor biology, it has ...

Computational Mass Spectrometry Imaging of Amyloid Plaque Populations in the Brains of Non-Demented and Alzheimer's Disease Patients KU Leuven

Lucia Chavez Gutierrez
Laboratory of Proteolytic Mechanisms in Neurodegeneration (VIB-KU Leuven)

γ-Secretase activity is involved in multiple physiological processes and plays a key role in Alzheimer’s disease (AD) pathogenesis. AD-causing mutations in Presenilin (PSEN1/2) (the catalytic core of γ-secretase) and the Amyloid Precursor Protein (APP) consistently reduce the number of γ-secretase cleavages on the APP C99 substrate, leading to production of longer amyloidogenic Aβ peptides. The pathogenic mutant effect points at the shift in ...

Dimensionality reduction of mass spectrometry imaging with deep learning KU Leuven

Bart De Moor
Dynamical Systems, Signal Processing and Data Analytics (STADIUS), Electrical Engineering (ESAT), Kulak Kortrijk Campus
The spatial distribution of molecules in tissues can be measured using a technique called Mass Spectrometry Imaging (MSI). A single MSI experiment results in a large amount of data, such that efficient algorithms are required to analyse the results. Multiple MSI experiments will be conducted and analysed to detect temporal patterns using advanced deep learning techniques. These methods can be applied to get a better understanding of cancer ...

Machine learning for Mass Spectrometry Imaging KU Leuven

Bart De Moor
Dynamical Systems, Signal Processing and Data Analytics (STADIUS)

A mass spectrometry imaging experiment results in very large, high dimensional data sets that are not easily analysed. This data contains an enormous amount of diverse information about all kinds of diseases, treatments and so on. Using machine learning techniques we want to find new insights from this data. We also want to find more efficient analysing methods for this type of data.