DSpace :: Browsing by Author "Schmitt, Michael"

Browsing by Author "Schmitt, Michael"

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Bessel beam CARS of axially structured samples
([London] : Macmillan Publishers Limited, part of Springer Nature, 2015) Heuke, Sandro; Zheng, Juanjuan; Akimov, Denis; Heintzmann, Rainer; Schmitt, Michael; Popp, Jürgen
We report about a Bessel beam CARS approach for axial profiling of multi-layer structures. This study presents an experimental implementation for the generation of CARS by Bessel beam excitation using only passive optical elements. Furthermore, an analytical expression is provided describing the generated anti-Stokes field by a homogeneous sample. Based on the concept of coherent transfer functions, the underling resolving power of axially structured geometries is investigated. It is found that through the non-linearity of the CARS process in combination with the folded illumination geometry continuous phase-matching is achieved starting from homogeneous samples up to spatial sample frequencies at twice of the pumping electric field wave. The experimental and analytical findings are modeled by the implementation of the Debye Integral and scalar Green function approach. Finally, the goal of reconstructing an axially layered sample is demonstrated on the basis of the numerically simulated modulus and phase of the anti-Stokes far-field radiation pattern.
Beyond 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, Jürgen
Assessing 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.
Biochemical Characterization of Mouse Retina of an Alzheimer's Disease Model by Raman Spectroscopy
(Washington, DC : ACS Publications, 2020) Stiebing, Clara; Jahn, Izabella J.; Schmitt, Michael; Keijzer, Nanda; Kleemann, Robert; Kiliaan, Amanda J.; Drexler, Wolfgang; Leitgeb, Rainer A.; Popp, Jürgen
The presence of biomarkers characteristic for Alzheimer's disease in the retina is a controversial topic. Raman spectroscopy offers information on the biochemical composition of tissues. Thus, it could give valuable insight into the diagnostic value of retinal analysis. Within the present study, retinas of a double transgenic mouse model, that expresses a chimeric mouse/human amyloid precursor protein and a mutant form of human presenilin 1, and corresponding control group were subjected to ex vivo Raman imaging. The Raman data recorded on cross sections of whole eyes highlight the layered structure of the retina in a label-free manner. Based on the Raman information obtained from en face mounted retina samples, a discrimination between healthy and Alzheimer's disease retinal tissue can be done with an accuracy of 85.9%. For this a partial least squares-linear discriminant analysis was applied. Therefore, although no macromolecular changes in form of, i.e., amyloid beta plaques, can be noticed based on Raman spectroscopy, subtle biochemical changes happening in the retina could lead to Alzheimer's disease identification. ©
Comparison of hyperspectral coherent Raman scattering microscopies for biomedical applications
(College Park : American Institute of Physics, 2018) Bocklitz, Thomas W.; Meyer, Tobias; Schmitt, Michael; Rimke, Ingo; Hoffmann, Franziska; von Eggeling, Ferdinand; Ernst, G.; Guntinas-Lichius, Orlando; Popp, Jürgen
Raman scattering based imaging represents a very powerful optical tool for biomedical diagnostics. Different Raman signatures obtained by distinct tissue structures and disease induced changes provoke sophisticated analysis of the hyperspectral Raman datasets. While the analysis of linear Raman spectroscopic tissue data is quite established, the evaluation of hyperspectral nonlinear Raman data has not yet been evaluated in great detail. The two most common nonlinear Raman methods are CARS (coherent anti-Stokes Raman scattering) and SRS (stimulated Raman scattering) spectroscopy. Specifically the linear concentration dependence of SRS as compared to the quadratic dependence of CARS has fostered the application of SRS tissue imaging. Here, we applied spectral processing to hyperspectral SRS and CARS data for tissue characterization. We could demonstrate for the first time that similar cluster distributions can be obtained for multispectral CARS and SRS data but that clustering is based on different spectral features due to interference effects in CARS and the different concentration dependence of CARS and SRS. It is shown that a direct combination of CARS and SRS data does not improve the clustering results.
Computational tissue staining of non-linear multimodal imaging using supervised and unsupervised deep learning
(Washington, DC : OSA, 2021) Pradhan, Pranita; Meyer, Tobias; Vieth, Michael; Stallmach, Andreas; Waldner, Maximilian; Schmitt, Michael; Popp, Juergen; Bocklitz, Thomas
Hematoxylin and Eosin (H&E) staining is the 'gold-standard' method in histopathology. However, standard H&E staining of high-quality tissue sections requires long sample preparation times including sample embedding, which restricts its application for 'real-time' disease diagnosis. Due to this reason, a label-free alternative technique like non-linear multimodal (NLM) imaging, which is the combination of three non-linear optical modalities including coherent anti-Stokes Raman scattering, two-photon excitation fluorescence and second-harmonic generation, is proposed in this work. To correlate the information of the NLM images with H&E images, this work proposes computational staining of NLM images using deep learning models in a supervised and an unsupervised approach. In the supervised and the unsupervised approach, conditional generative adversarial networks (CGANs) and cycle conditional generative adversarial networks (cycle CGANs) are used, respectively. Both CGAN and cycle CGAN models generate pseudo H&E images, which are quantitatively analyzed based on mean squared error, structure similarity index and color shading similarity index. The mean of the three metrics calculated for the computationally generated H&E images indicate significant performance. Thus, utilizing CGAN and cycle CGAN models for computational staining is beneficial for diagnostic applications without performing a laboratory-based staining procedure. To the author's best knowledge, it is the first time that NLM images are computationally stained to H&E images using GANs in an unsupervised manner.
FLIM data analysis based on Laguerre polynomial decomposition and machine-learning
(Bellingham, Wash. : SPIE, 2021) Guo, Shuxia; Silge, Anja; Bae, Hyeonsoo; Tolstik, Tatiana; Meyer, Tobias; Matziolis, Georg; Schmitt, Michael; Popp, Jürgen; Bocklitz, Thomas
Significance: The potential of fluorescence lifetime imaging microscopy (FLIM) is recently being recognized, especially in biological studies. However, FLIM does not directly measure the lifetimes, rather it records the fluorescence decay traces. The lifetimes and/or abundances have to be estimated from these traces during the phase of data processing. To precisely estimate these parameters is challenging and requires a well-designed computer program. Conventionally employed methods, which are based on curve fitting, are computationally expensive and limited in performance especially for highly noisy FLIM data. The graphical analysis, while free of fit, requires calibration samples for a quantitative analysis. Aim: We propose to extract the lifetimes and abundances directly from the decay traces through machine learning (ML). Approach: The ML-based approach was verified with simulated testing data in which the lifetimes and abundances were known exactly. Thereafter, we compared its performance with the commercial software SPCImage based on datasets measured from biological samples on a time-correlated single photon counting system. We reconstructed the decay traces using the lifetime and abundance values estimated by ML and SPCImage methods and utilized the root-mean-squared-error (RMSE) as marker. Results: The RMSE, which represents the difference between the reconstructed and measured decay traces, was observed to be lower for ML than for SPCImage. In addition, we could demonstrate with a three-component analysis the high potential and flexibility of the ML method to deal with more than two lifetime components.
Imaging the invisible—Bioorthogonal Raman probes for imaging of cells and tissues
(Weinheim [u.a.] : Wiley-VCH, 2020) Azemtsop Matanfack, Georgette; Rüger, Jan; Stiebing, Clara; Schmitt, Michael; Popp, Jürgen
A revolutionary avenue for vibrational imaging with super-multiplexing capability can be seen in the recent development of Raman-active bioortogonal tags or labels. These tags and isotopic labels represent groups of chemically inert and small modifications, which can be introduced to any biomolecule of interest and then supplied to single cells or entire organisms. Recent developments in the field of spontaneous Raman spectroscopy and stimulated Raman spectroscopy in combination with targeted imaging of biomolecules within living systems are the main focus of this review. After having introduced common strategies for bioorthogonal labeling, we present applications thereof for profiling of resistance patterns in bacterial cells, investigations of pharmaceutical drug-cell interactions in eukaryotic cells and cancer diagnosis in whole tissue samples. Ultimately, this approach proves to be a flexible and robust tool for in vivo imaging on several length scales and provides comparable information as fluorescence-based imaging without the need of bulky fluorescent tags. © 2020 The Authors. Journal of Biophotonics published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
In vivo coherent anti-Stokes Raman scattering microscopy reveals vitamin A distribution in the liver
(Weinheim : Wiley-VCH-Verl., 2021) Rodewald, Marko; Bae, Hyeonsoo; Huschke, Sophie; Meyer-Zedler, Tobias; Schmitt, Michael; Press, Adrian Tibor; Schubert, Stephanie; Bauer, Michael; Popp, Juergen
Here we present a microscope setup for coherent anti-Stokes Raman scattering (CARS) imaging, devised to specifically address the challenges of in vivo experiments. We exemplify its capabilities by demonstrating how CARS microscopy can be used to identify vitamin A (VA) accumulations in the liver of a living mouse, marking the positions of hepatic stellate cells (HSCs). HSCs are the main source of extracellular matrix protein after hepatic injury and are therefore the main target of novel nanomedical strategies in the development of a treatment for liver fibrosis. Their role in the VA metabolism makes them an ideal target for a CARS-based approach as they store most of the body's VA, a class of compounds sharing a retinyl group as a structural motive, a moiety that is well known for its exceptionally high Raman cross section of the C=C stretching vibration of the conjugated backbone.
Intestinal epithelial barrier integrity investigated by label-free techniques in ulcerative colitis patients
([London] : Macmillan Publishers Limited, part of Springer Nature, 2023) Quansah, Elsie; Gardey, Elena; Ramoji, Anuradha; Meyer-Zedler, Tobias; Goehrig, Bianca; Heutelbeck, Astrid; Hoeppener, Stephanie; Schmitt, Michael; Waldner, Maximillian; Stallmach, Andreas; Popp, Jürgen
The intestinal epithelial barrier, among other compartments such as the mucosal immune system, contributes to the maintenance of intestinal homeostasis. Therefore, any disturbance within the epithelial layer could lead to intestinal permeability and promote mucosal inflammation. Considering that disintegration of the intestinal epithelial barrier is a key element in the etiology of ulcerative colitis, further assessment of barrier integrity could contribute to a better understanding of the role of epithelial barrier defects in ulcerative colitis (UC), one major form of chronic inflammatory bowel disease. Herein, we employ fast, non-destructive, and label-free non-linear methods, namely coherent anti-Stokes Raman scattering (CARS), second harmonic generation (SHG), two-photon excited fluorescence (TPEF), and two-photon fluorescence lifetime imaging (2P-FLIM), to assess the morpho-chemical contributions leading to the dysfunction of the epithelial barrier. For the first time, the formation of epithelial barrier gaps was directly visualized, without sophisticated data analysis procedures, by the 3D analysis of the colonic mucosa from severely inflamed UC patients. The results were compared with histopathological and immunofluorescence images and validated using transmission electron microscopy (TEM) to indicate structural alterations of the apical junction complex as the underlying cause for the formation of the epithelial barrier gaps. Our findings suggest the potential advantage of non-linear multimodal imaging is to give precise, detailed, and direct visualization of the epithelial barrier in the gastrointestinal tract, which can be combined with a fiber probe for future endomicroscopy measurements during real-time in vivo imaging.
Label-free multimodal imaging of infected Galleria mellonella larvae
([London] : Macmillan Publishers Limited, part of Springer Nature, 2022) Quansah, Elsie; Ramoji, Anuradha; Thieme, Lara; Mirza, Kamran; Goering, Bianca; Makarewicz, Oliwia; Heutelbeck, Astrid; Meyer-Zedler, Tobias; Pletz, Mathias W.; Schmitt, Michael; Popp, Jürgen
Non-linear imaging modalities have enabled us to obtain unique morpho-chemical insights into the tissue architecture of various biological model organisms in a label-free manner. However, these imaging techniques have so far not been applied to analyze the Galleria mellonella infection model. This study utilizes for the first time the strength of multimodal imaging techniques to explore infection-related changes in the Galleria mellonella larvae due to massive E. faecalis bacterial infection. Multimodal imaging techniques such as fluorescent lifetime imaging (FLIM), coherent anti-Stokes Raman scattering (CARS), two-photon excited fluorescence (TPEF), and second harmonic generation (SHG) were implemented in conjunction with histological HE images to analyze infection-associated tissue damage. The changes in the larvae in response to the infection, such as melanization, vacuolization, nodule formation, and hemocyte infiltration as a defense mechanism of insects against microbial pathogens, were visualized after Enterococcus faecalis was administered. Furthermore, multimodal imaging served for the analysis of implant-associated biofilm infections by visualizing biofilm adherence on medical stainless steel and ePTFE implants within the larvae. Our results suggest that infection-related changes as well as the integrity of the tissue of G. mellonella larvae can be studied with high morphological and chemical contrast in a label-free manner.
Multimodal Molecular Imaging and Identification of Bacterial Toxins Causing Mushroom Soft Rot and Cavity Disease
(Weinheim : Wiley-VCH, 2021) Dose, Benjamin; Thongkongkaew, Tawatchai; Zopf, David; Kim, Hak Joong; Bratovanov, Evgeni V.; García-Altares, María; Scherlach, Kirstin; Kumpfmüller, Jana; Ross, Claudia; Hermenau, Ron; Niehs, Sarah; Silge, Anja; Hniopek, Julian; Schmitt, Michael; Popp, Jürgen; Hertweck, Christian
Soft rot disease of edible mushrooms leads to rapid degeneration of fungal tissue and thus severely affects farming productivity worldwide. The bacterial mushroom pathogen Burkholderia gladioli pv. agaricicola has been identified as the cause. Yet, little is known about the molecular basis of the infection, the spatial distribution and the biological role of antifungal agents and toxins involved in this infectious disease. We combine genome mining, metabolic profiling, MALDI-Imaging and UV Raman spectroscopy, to detect, identify and visualize a complex of chemical mediators and toxins produced by the pathogen during the infection process, including toxoflavin, caryoynencin, and sinapigladioside. Furthermore, targeted gene knockouts and in vitro assays link antifungal agents to prevalent symptoms of soft rot, mushroom browning, and impaired mycelium growth. Comparisons of related pathogenic, mutualistic and environmental Burkholderia spp. indicate that the arsenal of antifungal agents may have paved the way for ancestral bacteria to colonize niches where frequent, antagonistic interactions with fungi occur. Our findings not only demonstrate the power of label-free, in vivo detection of polyyne virulence factors by Raman imaging, but may also inspire new approaches to disease control. © 2021 The Authors. ChemBioChem published by Wiley-VCH GmbH
Multimodal Nonlinear Microscopy for Therapy Monitoring of Cold Atmospheric Plasma Treatment
(Basel : MDPI, 2019) Meyer, Tobias; Bae, Hyeonsoo; Hasse, Sybille; Winter, Jörn; von Woedtke, Thomas; Schmitt, Michael; Weltmann, Klaus-Dieter; Popp, Jürgen
Here we report on a non-linear spectroscopic method for visualization of cold atmospheric plasma (CAP)-induced changes in tissue for reaching a new quality level of CAP application in medicine via online monitoring of wound or cancer treatment. A combination of coherent anti-Stokes Raman scattering (CARS), two-photon fluorescence lifetime imaging (2P-FLIM) and second harmonic generation (SHG) microscopy has been used for non-invasive and label-free detection of CAP-induced changes on human skin and mucosa samples. By correlation with histochemical staining, the observed local increase in fluorescence could be assigned to melanin. CARS and SHG prove the integrity of the tissue structure, visualize tissue morphology and composition. The influence of plasma effects by variation of plasma parameters e.g., duration of treatment, gas composition and plasma source has been evaluated. Overall quantitative spectroscopic markers could be identified for a direct monitoring of CAP-treated tissue areas, which is very important for translating CAPs into clinical routine.
Nonresonant Raman spectroscopy of isolated human retina samples complying with laser safety regulations for in vivo measurements
(Bellingham, Wash. : SPIE, 2019) Stiebing, Clara; Schie, Iwan W.; Knorr, Florian; Schmitt, Michael; Keijzer, Nanda; Kleemann, Robert; Jahn, Izabella J.; Jahn, Martin; Kiliaan, Amanda J.; Ginner, Laurin; Lichtenegger, Antonia; Drexler, Wolfgang; Leitgeb, Rainer A.; Popp, Jürgen
Retinal diseases, such as age-related macular degeneration, are leading causes of vision impairment, increasing in incidence worldwide due to an aging society. If diagnosed early, most cases could be prevented. In contrast to standard ophthalmic diagnostic tools, Raman spectroscopy can provide a comprehensive overview of the biochemical composition of the retina in a label-free manner. A proof of concept study of the applicability of nonresonant Raman spectroscopy for retinal investigations is presented. Raman imaging provides valuable insights into the molecular composition of an isolated ex vivo human retina sample by probing the entire molecular fingerprint, i.e., the lipid, protein, carotenoid, and nucleic acid content. The results are compared to morphological information obtained by optical coherence tomography of the sample. The challenges of in vivo Raman studies due to laser safety limitations and predefined optical parameters given by the eye itself are explored. An in-house built setup simulating the optical pathway in the human eye was developed and used to demonstrate that even under laser safety regulations and the above-mentioned optical restrictions, Raman spectra of isolated ex vivo human retinas can be recorded. The results strongly support that in vivo studies using nonresonant Raman spectroscopy are feasible and that these studies provide comprehensive molecular information of the human retina. © The Authors. Published by SPIE.
Novel Biobased Self-Healing Ionomers Derived from Itaconic Acid Derivates
(Weinheim : Wiley-VCH, 2021) Meurer, Josefine; Hniopek, Julian; Dahlke, Jan; Schmitt, Michael; Popp, Jürgen; Zechel, Stefan; Hager, Martin D.
This article presents novel biobased ionomers featuring self-healing abilities. These smart materials are synthesized from itaconic acid derivates. Large quantities of itaconic acid can be produced from diverse biomass like corn, rice, and others. This study presents a comprehensive investigation of their thermal and mechanical properties via differential scanning calorimetry (DSC), thermo gravimetric analysis (TGA), and FT-Raman and FT-IR measurements as well as dynamic mechanic analysis. Within all these measurements, different kinds of structure-property relationships could be derived from these measurements. For example, the proportion of ionic groups enormously influences the self-healing efficiency. The investigation of the self-healing abilities reveals healing efficiencies up to 99% in 2 h at 90 °C for the itaconic acid based ionomer with the lowest ionic content. © 2020 The Authors. Macromolecular Rapid Communications published by Wiley-VCH GmbH
Photophysics of Anionic Bis(4H-imidazolato)CuI Complexes
(Weinheim : Wiley-VCH, 2022) Seidler, Bianca; Tran, Jens H.; Hniopek, Julian; Traber, Philipp; Görls, Helmar; Gräfe, Stefanie; Schmitt, Michael; Popp, Jürgen; Schulz, Martin; Dietzek‐Ivanšić, Benjamin
In this paper, the photophysical behavior of four panchromatically absorbing, homoleptic bis(4H-imidazolato)CuI complexes, with a systematic variation in the electron-withdrawing properties of the imidazolate ligand, were studied by wavelength-dependent time-resolved femtosecond transient absorption spectroscopy. Excitation at 400, 480, and 630 nm populates metal-to-ligand charge transfer, intraligand charge transfer, and mixed-character singlet states. The pump wavelength-dependent transient absorption data were analyzed by a recently established 2D correlation approach. Data analysis revealed that all excitation conditions yield similar excited-state dynamics. Key to the excited-state relaxation is fast, sub-picosecond pseudo-Jahn-Teller distortion, which is accompanied by the relocalization of electron density onto a single ligand from the initially delocalized state at Franck-Condon geometry. Subsequent intersystem crossing to the triplet manifold is followed by a sub-100 ps decay to the ground state. The fast, nonradiative decay is rationalized by the low triplet-state energy as found by DFT calculations, which suggest perspective treatment at the strong coupling limit of the energy gap law.
A polyyne toxin produced by an antagonistic bacterium blinds and lyses a Chlamydomonad alga
(Washington, DC : National Acad. of Sciences, 2021) Hotter, Vivien; Zopf, David; Kim, Hak Joong; Silge, Anja; Schmitt, Michael; Aiyar, Prasad; Fleck, Johanna; Matthäus, Christian; Hniopek, Julian; Yan, Qing; Loper, Joyce; Sasso, Severin; Hertweck, Christian; Popp, Jürgen; Mittag, Maria
Algae are key contributors to global carbon fixation and form the basis of many food webs. In nature, their growth is often supported or suppressed by microorganisms. The bacterium Pseudomonas protegens Pf-5 arrests the growth of the green unicellular alga Chlamydomonas reinhardtii, deflagellates the alga by the cyclic lipopeptide orfamide A, and alters its morphology [P. Aiyar et al., Nat. Commun. 8, 1756 (2017)]. Using a combination of Raman microspectroscopy, genome mining, and mutational analysis, we discovered a polyyne toxin, protegencin, which is secreted by P. protegens, penetrates the algal cells, and causes destruction of the carotenoids of their primitive visual system, the eyespot. Together with secreted orfamide A, protegencin thus prevents the phototactic behavior of C. reinhardtii. A mutant of P. protegens deficient in protegencin production does not affect growth or eyespot carotenoids of C. reinhardtii. Protegencin acts in a direct and destructive way by lysing and killing the algal cells. The toxic effect of protegencin is also observed in an eyeless mutant and with the colony-forming Chlorophyte alga Gonium pectorale. These data reveal a two-pronged molecular strategy involving a cyclic lipopeptide and a conjugated tetrayne used by bacteria to attack select Chlamydomonad algae. In conjunction with the bloom-forming activity of several chlorophytes and the presence of the protegencin gene cluster in over 50 different Pseudomonas genomes [A. J. Mullins et al., bioRxiv [Preprint] (2021). https://www.biorxiv.org/content/10.1101/2021.03.05.433886v1 (Accessed 17 April 2021)], these data are highly relevant to ecological interactions between Chlorophyte algae and Pseudomonadales bacteria.
Pseudo-HE images derived from CARS/TPEF/SHG multimodal imaging in combination with Raman-spectroscopy as a pathological screening tool
(London : BioMed Central, 2016) Bocklitz, Thomas W.; Salah, Firas Subhi; Vogler, Nadine; Heuke, Sandro; Chernavskaia, Olga; Schmidt, Carsten; Waldner, Maximilian J.; Greten, Florian R.; Bräuer, Rolf; Schmitt, Michael; Stallmach, Andreas; Petersen, Iver; Popp, Jürgen
Due to the steadily increasing number of cancer patients worldwide the early diagnosis and treatment of cancer is a major field of research. The diagnosis of cancer is mostly performed by an experienced pathologist via the visual inspection of histo-pathological stained tissue sections. To save valuable time, low quality cryosections are frequently analyzed with diagnostic accuracies that are below those of high quality embedded tissue sections. Thus, alternative means have to be found that enable for fast and accurate diagnosis as the basis of following clinical decision making.
Raman imaging of changes in the polysaccharides distribution in the cell wall during apple fruit development and senescence
(Berlin ; Heidelberg : Springer, 2016) Szymańska-Chargot, Monika; Chylińska, Monika; Pieczywek, Piotr M.; Rösch, Petra; Schmitt, Michael; Popp, Jürgen; Zdunek, Artur
Main conclusion Du ring on-tree ripening, the pectin distribution changed from polydispersed in cell wall to cumulated in cell wall corners. During apple storage, the pectin distribution returned to evenly dispersed along the cell wall. The plant cell wall influences the texture properties of fruit tissue for example apples become softer during ripening and postharvest storage. This softening process is believed to be mainly connected with changes in the cell wall composition due to polysaccharides undergoing an enzymatic degradation. These changes in polysaccharides are currently mainly investigated via chemical analysis or monoclonal labeling. Here, we propose the application of Raman microscopy for evaluating the changes in the polysaccharide distribution in the cell wall of apples during both ripening and postharvest storage. The apples were harvested 1 month and 2 weeks before optimal harvest date as well as at the optimal harvest date. The apples harvested at optimal harvest date were stored for 3 months. The Raman maps, as well as the chemical analysis were obtained for each harvest date and after 1, 2 and 3 months of storage, respectively. The analysis of the Raman maps showed that the pectins in the middle lamella and primary cell wall undergo a degradation. The changes in cellulose and hemicellulose were less pronounced. These findings were confirmed by the chemical analysis results. During development changes of pectins from a polydispersed form in the cell walls to a cumulated form in cell wall corners could be observed. In contrast after 3 months of apple storage we could observe an substantial pectin decrease. The obtained results demonstrate that Raman chemical imaging might be a very useful tool for a first identification of compositional changes in plant tissue during their development. The great advantage Raman microspectroscopy offers is the simultaneous localization and identification of polysaccharides within the cell wall and plant tissue.
A rigid coherent anti-Stokes Raman scattering endoscope with high resolution and a large field of view
(College Park : American Institute of Physics, 2018) Zirak, P.; Matz, Gregor; Messerschmidt, Bernhard; Meyer, Tobias; Schmitt, Michael; Popp, Jürgen; Uckermann, Ortrud; Galli, R.; Kirsch, Matthias; Winterhalder, M.J.; Zumbusch, A.
Nonlinear optical endoscopy is an attractive technique for biomedical imaging since it promises to give access to high resolution imaging in vivo. Among the various techniques used for endoscopic contrast generation, coherent anti-Stokes Raman scattering (CARS) is especially interesting. CARS endoscopy allows molecule specific imaging of unlabeled samples. In this contribution, we describe the design, implementation, and experimental characterization of a rigid, compact CARS endoscope with a spatial resolution of 750 nm over a field of view of roughly 250 μm. Omission of the relay optics and use of a gradient index lens specifically designed for this application allow one to realize these specifications in an endoscopic unit which is 2.2 mm wide over a length of 187 mm, making clinical applications during surgical interventions possible. Multimodal use of the endoscope is demonstrated with images of samples with neurosurgical relevance.Nonlinear optical endoscopy is an attractive technique for biomedical imaging since it promises to give access to high resolution imaging in vivo. Among the various techniques used for endoscopic contrast generation, coherent anti-Stokes Raman scattering (CARS) is especially interesting. CARS endoscopy allows molecule specific imaging of unlabeled samples. In this contribution, we describe the design, implementation, and experimental characterization of a rigid, compact CARS endoscope with a spatial resolution of 750 nm over a field of view of roughly 250 μm. Omission of the relay optics and use of a gradient index lens specifically designed for this application allow one to realize these specifications in an endoscopic unit which is 2.2 mm wide over a length of 187 mm, making clinical applications during surgical interventions possible. Multimodal use of the endoscope is demonstrated with images of samples with neurosurgical relevance.
Semantic 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, Ana
Non-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.

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