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    Linear and non-linear optical imaging of cancer cells with silicon nanoparticles
    (Basel : Molecular Diversity Preservation International (MDPI), 2016) Tolstik, Elen; Osminkina, Liubov A.; Akimov, Denis; Gongalsky, Maksim B.; Kudryavtsev, Andrew A.; Timoshenko, Victor Yu.; Heintzmann, Rainer; Sivakov, Vladimir; Popp, Jürgen
    New approaches for visualisation of silicon nanoparticles (SiNPs) in cancer cells are realised by means of the linear and nonlinear optics in vitro. Aqueous colloidal solutions of SiNPs with sizes of about 10–40 nm obtained by ultrasound grinding of silicon nanowires were introduced into breast cancer cells (MCF-7 cell line). Further, the time-varying nanoparticles enclosed in cell structures were visualised by high-resolution structured illumination microscopy (HR-SIM) and micro-Raman spectroscopy. Additionally, the nonlinear optical methods of two-photon excited fluorescence (TPEF) and coherent anti-Stokes Raman scattering (CARS) with infrared laser excitation were applied to study the localisation of SiNPs in cells. Advantages of the nonlinear methods, such as rapid imaging, which prevents cells from overheating and larger penetration depth compared to the single-photon excited HR-SIM, are discussed. The obtained results reveal new perspectives of the multimodal visualisation and precise detection of the uptake of biodegradable non-toxic SiNPs by cancer cells and they are discussed in view of future applications for the optical diagnostics of cancer tumours.
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    A Machine Learning-Based Raman Spectroscopic Assay for the Identification of Burkholderia mallei and Related Species
    (Basel : MDPI, 2019) Silge, Anja; Moawad, Amira A.; Bocklitz, Thomas; Fischer, Katja; Rösch, Petra; Roesler, Uwe; Elschner, Mandy C.; Popp, Jürgen; Neubauer, Heinrich
    Burkholderia (B.) mallei, the causative agent of glanders, and B. pseudomallei, the causative agent of melioidosis in humans and animals, are genetically closely related. The high infectious potential of both organisms, their serological cross-reactivity, and similar clinical symptoms in human and animals make the differentiation from each other and other Burkholderia species challenging. The increased resistance against many antibiotics implies the need for fast and robust identification methods. The use of Raman microspectroscopy in microbial diagnostic has the potential for rapid and reliable identification. Single bacterial cells are directly probed and a broad range of phenotypic information is recorded, which is subsequently analyzed by machine learning methods. Burkholderia were handled under biosafety level 1 (BSL 1) conditions after heat inactivation. The clusters of the spectral phenotypes and the diagnostic relevance of the Burkholderia spp. were considered for an advanced hierarchical machine learning approach. The strain panel for training involved 12 B. mallei, 13 B. pseudomallei and 11 other Burkholderia spp. type strains. The combination of top- and sub-level classifier identified the mallei-complex with high sensitivities (>95%). The reliable identification of unknown B. mallei and B. pseudomallei strains highlighted the robustness of the machine learning-based Raman spectroscopic assay. © 2019 by the authors
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    Direct raman spectroscopic measurements of biological nitrogen fixation under natural conditions: An analytical approach for studying nitrogenase activity
    (Columbus, Ohio : American Chemical Society, 2016) Jochum, Tobias; Fastnacht, Agnes; Trumbore, Susan E.; Popp, Jürgen; Frosch, Torsten
    Biological N2 fixation is a major input of bioavailable nitrogen, which represents the most frequent factor limiting the agricultural production throughout the world. Especially, the symbiotic association between legumes and Rhizobium bacteria can provide substantial amounts of nitrogen (N) and reduce the need for industrial fertilizers. Despite its importance in the global N cycle, rates of biological nitrogen fixation have proven difficult to quantify. In this work, we propose and demonstrate a simple analytical approach to measure biological N2 fixation rates directly without a proxy or isotopic labeling. We determined a mean N2 fixation rate of 78 ± 5 μmol N2 (g dry weight nodule)-1 h-1 of a Medicago sativa-Rhizobium consortium by continuously analyzing the amount of atmospheric N2 in static environmental chambers with Raman gas spectroscopy. By simultaneously analyzing the CO2 uptake and photosynthetic plant activity, we think that a minimum CO2 mixing ratio might be needed for natural N2 fixation and only used the time interval above this minimum CO2 mixing ratio for N2 fixation rate calculations. The proposed approach relies only on noninvasive measurements of the gas phase and, given its simplicity, indicates the potential to estimate biological nitrogen fixation of legume symbioses not only in laboratory experiments. The same methods can presumably also be used to detect N2 fluxes by denitrification from ecosystems to the atmosphere. (Figure Presented).