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Author: Neugebauer, Ute × End date: 2024 × Start date: 2020 × DDC: 540 × DDC: 570 × Has files: Yes × WGL Institute: IPHT ×

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Now showing 1 - 4 of 4
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    Label-Free Characterization of Macrophage Polarization Using Raman Spectroscopy
    (Basel : Molecular Diversity Preservation International (MDPI), 2023) Naumann, Max; Arend, Natalie; Guliev, Rustam R.; Kretzer, Christian; Rubio, Ignacio; Werz, Oliver; Neugebauer, Ute
    Macrophages are important cells of the innate immune system that play many different roles in host defense, a fact that is reflected by their polarization into many distinct subtypes. Depending on their function and phenotype, macrophages can be grossly classified into classically activated macrophages (pro-inflammatory M1 cells), alternatively activated macrophages (anti-inflammatory M2 cells), and non-activated cells (resting M0 cells). A fast, label-free and non-destructive characterization of macrophage phenotypes could be of importance for studying the contribution of the various subtypes to numerous pathologies. In this work, single cell Raman spectroscopic imaging was applied to visualize the characteristic phenotype as well as to discriminate between different human macrophage phenotypes without any label and in a non-destructive manner. Macrophages were derived by differentiation of peripheral blood monocytes of human healthy donors and differently treated to yield M0, M1 and M2 phenotypes, as confirmed by marker analysis using flow cytometry and fluorescence imaging. Raman images of chemically fixed cells of those three macrophage phenotypes were processed using chemometric methods of unmixing (N-FINDR) and discrimination (PCA-LDA). The discrimination models were validated using leave-one donor-out cross-validation. The results show that Raman imaging is able to discriminate between pro- and anti-inflammatory macrophage phenotypes with high accuracy in a non-invasive, non-destructive and label-free manner. The spectral differences observed can be explained by the biochemical characteristics of the different phenotypes.
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    Biochemical Analysis of Leukocytes after In Vitro and In Vivo Activation with Bacterial and Fungal Pathogens Using Raman Spectroscopy
    (Basel : MDPI, 2021) Pistiki, Aikaterini; Ramoji, Anuradha; Ryabchykov, Oleg; Thomas-Rueddel, Daniel; Press, Adrian T.; Makarewicz, Oliwia; Giamarellos-Bourboulis, Evangelos J.; Bauer, Michael; Bocklitz, Thomas; Popp, Juergen; Neugebauer, Ute
    Biochemical information from activated leukocytes provide valuable diagnostic information. In this study, Raman spectroscopy was applied as a label-free analytical technique to characterize the activation pattern of leukocyte subpopulations in an in vitro infection model. Neutrophils, monocytes, and lymphocytes were isolated from healthy volunteers and stimulated with heat-inactivated clinical isolates of Candida albicans, Staphylococcus aureus, and Klebsiella pneumoniae. Binary classification models could identify the presence of infection for monocytes and lymphocytes, classify the type of infection as bacterial or fungal for neutrophils, monocytes, and lymphocytes and distinguish the cause of infection as Gram-negative or Gram-positive bacteria in the monocyte subpopulation. Changes in single-cell Raman spectra, upon leukocyte stimulation, can be explained with biochemical changes due to the leukocyte’s specific reaction to each type of pathogen. Raman spectra of leukocytes from the in vitro infection model were compared with spectra from leukocytes of patients with infection (DRKS-ID: DRKS00006265) with the same pathogen groups, and a good agreement was revealed. Our study elucidates the potential of Raman spectroscopy-based single-cell analysis for the differentiation of circulating leukocyte subtypes and identification of the infection by probing the molecular phenotype of those cells.
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    Vibrational Spectroscopic Investigation of Blood Plasma and Serum by Drop Coating Deposition for Clinical Application
    (Basel : Molecular Diversity Preservation International (MDPI), 2021) Huang, Jing; Ali, Nairveen; Quansah, Elsie; Guo, Shuxia; Noutsias, Michel; Meyer-Zedler, Tobias; Bocklitz, Thomas; Popp, Jürgen; Neugebauer, Ute; Ramoji, Anuradha
    In recent decades, vibrational spectroscopic methods such as Raman and FT-IR spectroscopy are widely applied to investigate plasma and serum samples. These methods are combined with drop coating deposition techniques to pre-concentrate the biomolecules in the dried droplet to improve the detected vibrational signal. However, most often encountered challenge is the inhomogeneous redistribution of biomolecules due to the coffee-ring effect. In this study, the variation in biomolecule distribution within the dried-sample droplet has been investigated using Raman and FT-IR spectroscopy and fluorescence lifetime imaging method. The plasma-sample from healthy donors were investigated to show the spectral differences between the inner and outer-ring region of the dried-sample droplet. Further, the preferred location of deposition of the most abundant protein albumin in the blood during the drying process of the plasma has been illustrated by using deuterated albumin. Subsequently, two patients with different cardiac-related diseases were investigated exemplarily to illustrate the variation in the pattern of plasma and serum biomolecule distribution during the drying process and its impact on patient-stratification. The study shows that a uniform sampling position of the droplet, both at the inner and the outer ring, is necessary for thorough clinical characterization of the patient’s plasma and serum sample using vibrational spectroscopy.
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    3-Step flow focusing enables multidirectional imaging of bioparticles for imaging flow cytometry
    (Cambridge : RSC, 2020) Kleiber, Andreas; Ramoji, Anuradha; Mayer, Günter; Neugebauer, Ute; Popp, Jürgen; Henkel, Thomas
    Multidirectional imaging flow cytometry (mIFC) extends conventional imaging flow cytometry (IFC) for the image-based measurement of 3D-geometrical features of particles. The innovative core is a flow rotation unit in which a vertical sample lamella is incrementally rotated by 90 degrees into a horizontal lamella. The required multidirectional views are generated by guiding all particles at a controllable shear flow position of the parabolic velocity profile of the capillary slit detection chamber. All particles pass the detection chamber in a two-dimensional sheet under controlled rotation while each particle is imaged multiple times. This generates new options for automated particle analysis. In an experimental application, we used our system for the accurate classification of 15 species of pollen based on 3D-morphological information. We demonstrate how the combination of multi directional imaging with advanced machine learning algorithms can improve the accuracy of automated bio-particle classification. As an additional benefit, we significantly decrease the number of false positives in the classification of foreign particles,i.e.those elements which do not belong to one of the trained classes by the 3D-extension of the classification algorithm. © The Royal Society of Chemistry 2020.