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- ItemSemantic segmentation of non-linear multimodal images for disease grading of inflammatory bowel disease: A segnet-based application([Sétubal] : SCITEPRESS - Science and Technology Publications Lda., 2019) Pradhan, Pranita; Meyer, Tobias; Vieth, Michael; Stallmach, Andreas; Waldner, Maximilian; Schmitt, Michael; Popp, Juergen; Bocklitz, Thomas; De Marsico, Maria; Sanniti di Baja, Gabriella; Fred, AnaNon-linear multimodal imaging, the combination of coherent anti-stokes Raman scattering (CARS), two-photon excited fluorescence (TPEF) and second harmonic generation (SHG), has shown its potential to assist the diagnosis of different inflammatory bowel diseases (IBDs). This label-free imaging technique can support the ‘gold-standard’ techniques such as colonoscopy and histopathology to ensure an IBD diagnosis in clinical environment. Moreover, non-linear multimodal imaging can measure biomolecular changes in different tissue regions such as crypt and mucosa region, which serve as a predictive marker for IBD severity. To achieve a real-time assessment of IBD severity, an automatic segmentation of the crypt and mucosa regions is needed. In this paper, we semantically segment the crypt and mucosa region using a deep neural network. We utilized the SegNet architecture (Badrinarayanan et al., 2015) and compared its results with a classical machine learning approach. Our trained SegNet mod el achieved an overall F1 score of 0.75. This model outperformed the classical machine learning approach for the segmentation of the crypt and mucosa region in our study.
- ItemBeyond endoscopic assessment in inflammatory bowel disease: real-time histology of disease activity by non-linear multimodal imaging(London : Nature Publishing Group, 2016) Chernavskaia, Olga; Heuke, Sandro; Vieth, Michael; Friedrich, Oliver; Schürmann, Sebastian; Atreya, Raja; Stallmach, Andreas; Neurath, Markus F.; Waldner, Maximilian; Petersen, Iver; Schmitt, Michael; Bocklitz, Thomas; Popp, JürgenAssessing disease activity is a prerequisite for an adequate treatment of inflammatory bowel diseases (IBD) such as Crohn’s disease and ulcerative colitis. In addition to endoscopic mucosal healing, histologic remission poses a promising end-point of IBD therapy. However, evaluating histological remission harbors the risk for complications due to the acquisition of biopsies and results in a delay of diagnosis because of tissue processing procedures. In this regard, non-linear multimodal imaging techniques might serve as an unparalleled technique that allows the real-time evaluation of microscopic IBD activity in the endoscopy unit. In this study, tissue sections were investigated using the non-linear multimodal microscopy combination of coherent anti-Stokes Raman scattering (CARS), two-photon excited auto fluorescence (TPEF) and second-harmonic generation (SHG). After the measurement a gold-standard assessment of histological indexes was carried out based on a conventional H&E stain. Subsequently, various geometry and intensity related features were extracted from the multimodal images. An optimized feature set was utilized to predict histological index levels based on a linear classifier. Based on the automated prediction, the diagnosis time interval is decreased. Therefore, non-linear multimodal imaging may provide a real-time diagnosis of IBD activity suited to assist clinical decision making within the endoscopy unit.
- ItemSingle cell analysis in native tissue: Quantification of the retinoid content of hepatic stellate cells([London] : Macmillan Publishers Limited, part of Springer Nature, 2016) Galler, Kerstin; Requardt, Robert Pascal; Glaser, Uwe; Markwart, Robby; Bocklitz, Thomas; Bauer, Michael; Popp, Jürgen; Neugebauer, UteHepatic stellate cells (HSCs) are retinoid storing cells in the liver: The retinoid content of those cells changes depending on nutrition and stress level. There are also differences with regard to a HSC’s anatomical position in the liver. Up to now, retinoid levels were only accessible from bulk measurements of tissue homogenates or cell extracts. Unfortunately, they do not account for the intercellular variability. Herein, Raman spectroscopy relying on excitation by the minimally destructive wavelength 785 nm is introduced for the assessment of the retinoid state of single HSCs in freshly isolated, unprocessed murine liver lobes. A quantitative estimation of the cellular retinoid content is derived. Implications of the retinoid content on hepatic health state are reported. The Raman-based results are integrated with histological assessments of the tissue samples. This spectroscopic approach enables single cell analysis regarding an important cellular feature in unharmed tissue.
- ItemA 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, HeinrichBurkholderia (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
- ItemIn situ spectroelectrochemical and theoretical study on the oxidation of a 4H-imidazole-ruthenium dye adsorbed on nanocrystalline TiO2 thin film electrodes(Cambridge : RSC Publ., 2015) Zhang, Ying; Kupfer, Stephan; Zedler, Linda; Schindler, Julian; Bocklitz, Thomas; Guthmuller, Julien; Rau, Sven; Dietzek, BenjaminTerpyridine 4H-imidazole-ruthenium(II) complexes are considered promising candidates for use as sensitizers in dye sensitized solar cells (DSSCs) by displaying broad absorption in the visible range, where the dominant absorption features are due to metal-to-ligand charge transfer (MLCT) transitions. The ruthenium(III) intermediates resulting from photoinduced MLCT transitions are essential intermediates in the photoredox-cycle of the DSSC. However, their photophysics is much less studied compared to the ruthenium(II) parent systems. To this end, the structural alterations accompanying one-electron oxidation of the RuIm dye series (including a non-carboxylic RuIm precursor, and, carboxylic RuImCOO in solution and anchored to a nanocrystalline TiO2 film) are investigated via in situ experimental and theoretical UV-Vis absorption and resonance Raman (RR) spectroelectrochemistry. The excellent agreement between the experimental and the TDDFT spectra derived in this work allows for an in-depth assignment of UV-Vis and RR spectral features of the dyes. A concordant pronounced wavelength dependence with respect to the charge transfer character has been observed for the model system RuIm, and both RuImCOO in solution and attached on the TiO2 surface. Excitation at long wavelengths leads to the population of ligand-to-metal charge transfer states, i.e. photoreduction of the central ruthenium(III) ion, while high-energy excitation features an intra-ligand charge transfer state localized on the 4H-imidazole moiety. Therefore, these 4H-imidazole ruthenium complexes investigated here are potential multi-photoelectron donors. One electron is donated from MLCT states, and additionally, the 4H-imidazole ligand reveals electron-donating character with a significant contribution to the excited states of the ruthenium(III) complexes upon blue-light irradiation.
- ItemSpatial resolution of tip-enhanced Raman spectroscopy – DFT assessment of the chemical effect(Cambridge : RSC Publ., 2016) Latorre, Federico; Kupfer, Stephan; Bocklitz, Thomas; Kinzel, Daniel; Trautmann, Steffen; Gräfe, Stefanie; Deckert, VolkerExperimental evidence of extremely high spatial resolution of tip-enhanced Raman scattering (TERS) has been recently demonstrated. Here, we present a full quantum chemical description (at the density functional level of theory) of the non-resonant chemical effects on the Raman spectrum of an adenine molecule mapped by a tip, modeled as a single silver atom or a small silver cluster. We show pronounced changes in the Raman pattern and its intensities depending on the conformation of the nanoparticle–substrate system, concluding that the spatial resolution of the chemical contribution of TERS can be in the sub-nm range.
- ItemA manual and an automatic TERS based virus discrimination(Cambridge : RSC Publ., 2015) Olschewski, Konstanze; Kämmer, Evelyn; Stöckel, Stephan; Bocklitz, Thomas; Deckert-Gaudig, Tanja; Zell, Roland; Cialla-May, Dana; Weber, Karina; Deckert, Volker; Popp, JürgenRapid techniques for virus identification are more relevant today than ever. Conventional virus detection and identification strategies generally rest upon various microbiological methods and genomic approaches, which are not suited for the analysis of single virus particles. In contrast, the highly sensitive spectroscopic technique tip-enhanced Raman spectroscopy (TERS) allows the characterisation of biological nano-structures like virions on a single-particle level. In this study, the feasibility of TERS in combination with chemometrics to discriminate two pathogenic viruses, Varicella-zoster virus (VZV) and Porcine teschovirus (PTV), was investigated. In a first step, chemometric methods transformed the spectral data in such a way that a rapid visual discrimination of the two examined viruses was enabled. In a further step, these methods were utilised to perform an automatic quality rating of the measured spectra. Spectra that passed this test were eventually used to calculate a classification model, through which a successful discrimination of the two viral species based on TERS spectra of single virus particles was also realised with a classification accuracy of 91%.