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    FLIm and raman spectroscopy for investigating biochemical changes of bovine pericardium upon genipin cross-linking
    (Basel : MDPI, 2020) Shaik, Tanveer Ahmed; Alfonso-Garcia, Alba; Richter, Martin; Korinth, Florian; Krafft, Christoph; Marcu, Laura; Popp, Jürgen
    Biomaterials used in tissue engineering and regenerative medicine applications benefit from longitudinal monitoring in a non-destructive manner. Label-free imaging based on fluorescence lifetime imaging (FLIm) and Raman spectroscopy were used to monitor the degree of genipin (GE) cross-linking of antigen-removed bovine pericardium (ARBP) at three incubation time points (0.5, 1.0, and 2.5 h). Fluorescence lifetime decreased and the emission spectrum redshifted compared to that of uncross-linked ARBP. The Raman signature of GE-ARBP was resonance-enhanced due to the GE cross-linker that generated new Raman bands at 1165, 1326, 1350, 1380, 1402, 1470, 1506, 1535, 1574, 1630, 1728, and 1741 cm-1. These were validated through density functional theory calculations as cross-linker-specific bands. A multivariate multiple regression model was developed to enhance the biochemical specificity of FLIm parameters fluorescence intensity ratio (R2 = 0.92) and lifetime (R2 = 0.94)) with Raman spectral results. FLIm and Raman spectroscopy detected biochemical changes occurring in the collagenous tissue during the cross-linking process that were characterized by the formation of a blue pigment which affected the tissue fluorescence and scattering properties. In conclusion, FLIm parameters and Raman spectroscopy were used to monitor the degree of cross-linking non-destructively. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
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    A Review on Data Fusion of Multidimensional Medical and Biomedical Data
    (Basel : MDPI, 2022) Azam, Kazi Sultana Farhana; Ryabchykov, Oleg; Bocklitz, Thomas
    Data fusion aims to provide a more accurate description of a sample than any one source of data alone. At the same time, data fusion minimizes the uncertainty of the results by combining data from multiple sources. Both aim to improve the characterization of samples and might improve clinical diagnosis and prognosis. In this paper, we present an overview of the advances achieved over the last decades in data fusion approaches in the context of the medical and biomedical fields. We collected approaches for interpreting multiple sources of data in different combinations: image to image, image to biomarker, spectra to image, spectra to spectra, spectra to biomarker, and others. We found that the most prevalent combination is the image-to-image fusion and that most data fusion approaches were applied together with deep learning or machine learning methods.
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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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    Modified PCA and PLS: Towards a better classification in Raman spectroscopy–based biological applications
    (New York, NY : Wiley Interscience, 2020) Guo, Shuxia; Rösch, Petra; Popp, Jürgen; Bocklitz, Thomas
    Raman spectra of biological samples often exhibit variations originating from changes of spectrometers, measurement conditions, and cultivation conditions. Such unwanted variations make a classification extremely challenging, especially if they are more significant compared with the differences between groups to be separated. A classifier is prone to such unwanted variations (ie, intragroup variations) and can fail to learn the patterns that can help separate different groups (ie, intergroup differences). This often leads to a poor generalization performance and a degraded transferability of the trained model. A natural solution is to separate the intragroup variations from the intergroup differences and build the classifier based on merely the latter information, for example, by a well-designed feature extraction. This forms the idea of this contribution. Herein, we modified two commonly applied feature extraction approaches, principal component analysis (PCA) and partial least squares (PLS), in order to extract merely the features representing the intergroup differences. Both of the methods were verified with two Raman spectral datasets measured from bacterial cultures and colon tissues of mice, respectively. In comparison to ordinary PCA and PLS, the modified PCA was able to improve the prediction on the testing data that bears significant difference to the training data, while the modified PLS could help avoid overfitting and lead to a more stable classification. © 2019 The Authors. Journal of Chemometrics published by John Wiley & Sons Ltd
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    Elucidating the chemistry behind the reduction of graphene oxide using a green approach with polydopamine
    (Basel : MDPI, 2019) Silva, Cláudia; Simon, Frank; Friedel, Peter; Pötschke, Petra; Zimmerer, Cordelia
    A new approach using X-ray photoelectron spectroscopy (XPS) was employed to give insight into the reduction of graphene oxide (GO) using a green approach with polydopamine (PDA). In this approach, the number of carbon atoms bonded to OH and to nitrogen in PDA is considered and compared to the total intensity of the signal resulting from OH groups in polydopamine-reduced graphene oxide (PDA-GO) to show the reduction. For this purpose, GO and PDA-GO with different times of reduction were prepared and characterized by Raman Spectroscopy and XPS. The PDA layer was removed to prepare reduced graphene oxide (RGO) and the effect of all chemical treatments on the thermal and electrical properties of the materials was studied. The results show that the complete reduction of the OH groups in GO occurred after 180 min of reaction. It was also concluded that Raman spectroscopy is not well suited to determine if the reduction and restoration of the sp2 structure occurred. Moreover, a significant change in the thermal stability was not observed with the chemical treatments. Finally, the electrical powder conductivity decreased after reduction with PDA, increasing again after its removal. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
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    Probing Oxide Reduction and Phase Transformations at the Au-TiO2 Interface by Vibrational Spectroscopy
    (Bussum : Baltzer, 2017-8-17) Pougin, Anna; Lüken, Alexander; Klinkhammer, Christina; Hiltrop, Dennis; Kauer, Max; Tölle, Katharina; Havenith-Newen, Martina; Morgenstern, Karina; Grünert, Wolfgang; Muhler, Martin; Strunk, Jennifer
    By a combination of FT-NIR Raman spectroscopy, infrared spectroscopy of CO adsorption under ultrahigh vacuum conditions (UHV-IR) and Raman spectroscopy in the line scanning mode the formation of a reduced titania phase in a commercial Au/TiO2 catalyst and in freshly prepared Au/anatase catalysts was detected. The reduced phase, formed at the Au-TiO2 interface, can serve as nucleation point for the formation of stoichiometric rutile. TinO2n−1 Magnéli phases, structurally resembling the rutile phase, might be involved in this process. The formation of the reduced phase and the rutilization process is clearly linked to the presence of gold nanoparticles and it does not proceed under similar conditions with the pure titania sample. Phase transformations might be both thermally or light induced, however, the colloidal deposition synthesis of the Au/TiO2 catalysts is clearly ruled out as cause for the formation of the reduced phase.
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    Correlation of crystal violet biofilm test results of Staphylococcus aureus clinical isolates with Raman spectroscopic read-out
    (Chichester [u.a.] : Wiley, 2021) Ebert, Christina; Tuchscherr, Lorena; Unger, Nancy; Pöllath, Christine; Gladigau, Frederike; Popp, Jürgen; Löffler, Bettina; Neugebauer, Ute
    Biofilm-related infections occur quite frequently in hospital settings and require rapid diagnostic identification as they are recalcitrant to antibiotic therapy and make special treatment necessary. One of the standard microbiological in vitro tests is the crystal violet test. It indirectly determines the amount of biofilm by measuring the optical density (OD) of the crystal violet-stained biofilm matrix and cells. However, this test is quite time-consuming, as it requires bacterial cultivation up to several days. In this study, we correlate fast Raman spectroscopic read-out of clinical Staphylococcus aureus isolates from 47 patients with different disease background with their biofilm-forming characteristics. Included were low (OD < 10), medium (OD ≥ 10 and ≤20), and high (OD > 20) biofilm performers as determined by the crystal violet test. Raman spectroscopic analysis of the bacteria revealed most spectral differences between high and low biofilm performers in the fingerprint region between 750 and 1150 cm−1. Using partial least square regression (PLSR) analysis on the Raman spectra involving the three categories of biofilm formation, it was possible to obtain a slight linear correlation of the Raman spectra with the biofilm OD values. The PLSR loading coefficient highlighted spectral differences between high and low biofilm performers for Raman bands that represent nucleic acids, carbohydrates, and proteins. Our results point to a possible application of Raman spectroscopy as a fast prediction tool for biofilm formation of bacterial strains directly after isolation from the infected patient. This could help clinicians make timely and adapted therapeutic decision in future.
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    In situ Raman spectroscopy on silicon nanowire anodes integrated in lithium ion batteries
    (Pennington, NJ : Electrochemical Society Inc., 2019) Krause, A.; Tkacheva, O.; Omar, A.; Langklotz, U.; Giebeler, L.; Dörfler, S.; Fauth, F.; Mikolajick, T.; Weber, W.M.
    Rapid decay of silicon anodes during lithiation poses a significant challenge in application of silicon as an anode material in lithium ion batteries. In situ Raman spectroscopy is a powerful method to study the relationship between structural and electrochemical data during electrode cycling and to allow the observation of amorphous as well as liquid and transient species in a battery cell. Herein, we present in situ Raman spectroscopy on high capacity electrode using uncoated and carbon-coated silicon nanowires during first lithiation and delithiation cycle in an optimized lithium ion battery setup and complement the results with operando X-ray reflection diffraction measurements. During lithiation, we were able to detect a new Raman signal at 1859 cm−1 especially on uncoated silicon nanowires. The detailed in situ Raman measurement of the first lithiation/delithiation cycle allowed to differentiate between morphology changes of the electrode as well as interphase formation from electrolyte components.
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    Secondary Structure and Glycosylation of Mucus Glycoproteins by Raman Spectroscopies
    (Columbus, Ohio : American Chemical Society, 2016) Davies, Heather S.; Singh, Prabha; Deckert-Gaudig, Tanja; Deckert, Volker; Rousseau, Karine; Ridley, Caroline E.; Dowd, Sarah E.; Doig, Andrew J.; Pudney, Paul D. A.; Thornton, David J.; Blanch, Ewan W.
    The major structural components of protective mucus hydrogels on mucosal surfaces are the secreted polymeric gel-forming mucins. The very high molecular weight and extensive O-glycosylation of gel-forming mucins, which are key to their viscoelastic properties, create problems when studying mucins using conventional biochemical/structural techniques. Thus, key structural information, such as the secondary structure of the various mucin subdomains, and glycosylation patterns along individual molecules, remains to be elucidated. Here, we utilized Raman spectroscopy, Raman optical activity (ROA), circular dichroism (CD), and tip-enhanced Raman spectroscopy (TERS) to study the structure of the secreted polymeric gel-forming mucin MUC5B. ROA indicated that the protein backbone of MUC5B is dominated by unordered conformation, which was found to originate from the heavily glycosylated central mucin domain by isolation of MUC5B O-glycan-rich regions. In sharp contrast, recombinant proteins of the N-terminal region of MUC5B (D1-D2-D′-D3 domains, NT5B), C-terminal region of MUC5B (D4-B-C-CK domains, CT5B) and the Cys-domain (within the central mucin domain of MUC5B) were found to be dominated by the β-sheet. Using these findings, we employed TERS, which combines the chemical specificity of Raman spectroscopy with the spatial resolution of atomic force microscopy to study the secondary structure along 90 nm of an individual MUC5B molecule. Interestingly, the molecule was found to contain a large amount of α-helix/unordered structures and many signatures of glycosylation, pointing to a highly O-glycosylated region on the mucin.