A5031276133- Mass Spectrometry Techniques and Applications
- Metabolomics and Mass Spectrometry Studies
- Advanced Proteomics Techniques and Applications
- Intracerebral and Subarachnoid Hemorrhage Research
- Neurosurgical Procedures and Complications
- Isotope Analysis in Ecology
- Analytical Chemistry and Chromatography
- Ion-surface interactions and analysis
- Vascular Malformations Diagnosis and Treatment
- Acute Ischemic Stroke Management
- 3D Printing in Biomedical Research
- Machine Learning in Bioinformatics
- Intracranial Aneurysms: Treatment and Complications
- Alzheimer's disease research and treatments
University Hospital Heidelberg
2016-2024
Heidelberg University
2016-2024
Mannheim University of Applied Sciences
2020-2024
University Medical Centre Mannheim
2021-2024
German Cancer Research Center
2016-2019
ABC/2 is still widely accepted for volume estimations in spontaneous intracerebral hemorrhage (ICH) despite known limitations, which potentially accounts controversial outcome-study results. The aim of this study was to establish and validate an automatic segmentation algorithm, allowing quick accurate quantification ICH. A algorithm implementing first- second-order statistics, texture, threshold features trained on manual segmentations with a random-forest methodology. Quantitative data the...
Abstract Mass spectrometry imaging vows to enable simultaneous spatially resolved investigation of hundreds metabolites in tissues, but it primarily relies on traditional ion images for non-data-driven metabolite visualization and analysis. The rendering interpretation neither considers nonlinearities the resolving power mass spectrometers nor does yet evaluate statistical significance differential spatial abundance. Here, we outline computational framework moleculaR (...
MALDI mass spectrometry imaging (MSI) enables label-free, spatially resolved analysis of a wide range analytes in tissue sections. Quantitative MSI datasets is typically performed on single pixels or manually assigned regions interest (ROIs). However, many sparse, small objects such as Alzheimer's disease (AD) brain deposits amyloid peptides called plaques are neither nor ROIs. Here, we propose new approach to facilitate the comparative computational evaluation plaque-like by MSI: fast...
Mass spectrometry imaging (MSI) is a label-free analysis method for resolving bio-molecules or pharmaceuticals in the spatial domain. It offers unique perspectives examination of entire organs other tissue specimens. Owing to increasing capabilities modern MSI devices, use 3D and multi-modal becomes feasible routine applications-resulting hundreds gigabytes data. To fully leverage such acquisitions, interactive tools image reconstruction, visualization, are required, which preferably should...
Abstract Summary Python is the most commonly used language for deep learning (DL). Existing packages mass spectrometry imaging (MSI) data are not optimized DL tasks. We, therefore, introduce pyM2aia, a package MSI analysis with focus on memory-efficient handling, processing and convenient data-access applications. pyM2aia provides interfaces to its parent application M2aia, which offers interactive capabilities exploring annotating in imzML format. utilizes image input output routines,...
Abstract Three-dimensional (3D) human cell culture models have emerged as a key technology for personalized medicine and phenotypic compound screening in more disease-like in-vitro systems. Mass spectrometry imaging (MSI) is one of the most versatile label-free techniques that enables simultaneous generation spatial maps multiple relevant molecules these 3D-models. Here, we present an integrated platform 3D-MSI 3D-cell cultures comprising 3D-printed metal casting molds freezing embedding, MS...
We provide 10 consecutive brain slices of an APP NL-G-F mouse model [1], imaging both lipid and peptide features. The objective use-case described in the following is to demonstrate applicability M²aia v2021.01.01 [2,3] for mono- multi-modal 3D image reconstructions by showing how embed information into structural context three dimensions using M²aia. To mono-modal reconstruction, all dataset are loaded used slice-wise reconstruction stack. For 3D-reconstruction, will be pair-wise registered...
M²aia [1,2] is able to apply dimensionality reduction methods 2D/3D MSI images. To demonstrate the DR we load a single peptide brain slice MS image, select multiple ion images and start PCA t-SNE. Example data available [3]. [1] https://github.com/jtfcordes/m2aia [2] (RRID:SCR_019324): applications for interactive analysis in MITK [3] Cordes J; Enzlein T; Marsching C; Hinze M; Engelhardt S; Hopf Wolf I (2021): Supporting "M²aia - Interactive, fast memory efficient of 2D 3D multi-modal mass...
An N-glycan MALDI-MSI dataset (treated and untreated sections) [1,2] is preprocessed in M²aia [3,4], resulting an intermediate result the form of a combined continuous centroid-imzML file. In this protocol, M²aia-based processing steps are demonstrated. Finally, used for further analysis [5]. [1] Gustafsson et al. 2018; Data Brief [2] 2018: PRIDE repository; N-linked glycan page [3] https://github.com/jtfcordes/m2aia (GitHub) [4] (RRID:SCR_019324): MSI applications interactive MITK [5]...
Abstract Mass spectrometry imaging (MSI) vows to enable simultaneous spatially-resolved investigation of hundreds metabolites in tissue sections, but it still relies on poorly defined ion images for data interpretation. Here, we outline moleculaR , a computational framework R, that introduces systematic probabilistic mapping and point-for-point statistical testing MSI. Beyond statistics, allows arithmetic operations within the same MS image thereby, instance, analysis visualization complex...
An N-glycan MALDI-MSI dataset (treated and untreated sections) [1,2] is preprocessed in M²aia [3], resulting an intermediate result the form of a combined continuous centroid-imzML file. In this protocol, M²aia-based processing steps are demonstrated. [1] Gustafsson et al. 2018; Data Brief [2] 2018: PRIDE repository; N-linked glycan page [3] (RRID:SCR_019324): MSI applications for interactive analysis MITK
We provide 10 consecutive brain slices of an APP NL-G-F mouse model [1], imaging both lipid and peptide features. The objective use-case described in the following is to demonstrate applicability M²aia v2021.01.01 [2,3] for mono- multi-modal 3D image reconstructions by showing how embed information into structural context three dimensions using M²aia. To mono-modal reconstruction, all dataset are loaded used slice-wise reconstruction stack. For 3D-reconstruction, will be pair-wise registered...
M²aia is able to apply dimensionality reduction methods 2D/3D MSI images. To demonstrate the DR we load a single peptide brain slice MS image, select multiple peaks from peak list and start PCA t-SNE.
An N-glycan MALDI-MSI dataset (treated and untreated sections) [1,2] is preprocessed in M²aia [3], resulting an intermediate result the form of a combined continuous centroid-imzML file. In this protocol, M²aia-based processing steps are demonstrated. [1] Gustafsson et al. 2018; Data Brief [2] 2018: PRIDE repository; N-Glycane data set page [3] (RRID:SCR_019324): MSI applications for interactive analysis MITK
An N-glycan MALDI-MSI dataset (treated and untreated sections) [1,2] is preprocessed in M²aia [3], resulting an intermediate result the form of a combined continuous centroid-imzML file. In this protocol, M²aia-based processing steps are demonstrated. [1] Gustafsson et al. 2018; Data Brief [2] 2018: PRIDE repository; N-Glycane data set page [3] (RRID:SCR_019324): MSI applications for interactive analysis MITK
Mass spectrometry imaging (MSI) vows to enable simultaneous spatially-resolved investigation of hundreds metabolites in tissue sections, but it still relies on poorly defined ion images for data interpretation. Here, we outline moleculaR , a computational framework ( https://github.com/CeMOS-Mannheim/moleculaR ) that introduces probabilistic mapping and point-for-point statistical testing tissue. It enables collective molecular projections consequently milieus, lipid pathways or user-defined...
An N-glycan MALDI-MSI dataset (treated and untreated sections) [1,2] is preprocessed in M²aia [3], resulting an intermediate result the form of a combined continuous centroid-imzML file. In this protocol, M²aia-based processing steps are demonstrated. [1] Gustafsson et al. 2018; Data Brief [2] 2018: PRIDE repository; N-Glycane data set page [3] (RRID:SCR_019324): MSI applications for interactive analysis MITK