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Now showing 1 - 10 of 19
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    Evaluation of shifted excitation Raman difference spectroscopy and comparison to computational background correction methods applied to biochemical Raman spectra
    (Basel : MDPI, 2017) Cordero, Eliana; Korinth, Florian; Stiebing, Clara; Krafft, Christoph; Schie, Iwan W.; Popp, Jürgen
    Raman spectroscopy provides label-free biochemical information from tissue samples without complicated sample preparation. The clinical capability of Raman spectroscopy has been demonstrated in a wide range of in vitro and in vivo applications. However, a challenge for in vivo applications is the simultaneous excitation of auto-fluorescence in the majority of tissues of interest, such as liver, bladder, brain, and others. Raman bands are then superimposed on a fluorescence background, which can be several orders of magnitude larger than the Raman signal. To eliminate the disturbing fluorescence background, several approaches are available. Among instrumentational methods shifted excitation Raman difference spectroscopy (SERDS) has been widely applied and studied. Similarly, computational techniques, for instance extended multiplicative scatter correction (EMSC), have also been employed to remove undesired background contributions. Here, we present a theoretical and experimental evaluation and comparison of fluorescence background removal approaches for Raman spectra based on SERDS and EMSC.
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    Counterfeit and substandard test of the antimalarial tablet Riamet® by means of Raman hyperspectral multicomponent analysis
    (Basel : MDPI, 2019) Frosch, Timea; Wyrwich, Elisabeth; Yan, Di; Domes, Christian; Domes, Robert; Popp, Jürgen; Frosch, Torsten
    The fight against counterfeit pharmaceuticals is a global issue of utmost importance, as failed medication results in millions of deaths every year. Particularly affected are antimalarial tablets. A very important issue is the identification of substandard tablets that do not contain the nominal amounts of the active pharmaceutical ingredient (API), and the differentiation between genuine products and products without any active ingredient or with a false active ingredient. This work presents a novel approach based on fiber-array based Raman hyperspectral imaging to qualify and quantify the antimalarial APIs lumefantrine and artemether directly and non-invasively in a tablet in a time-efficient way. The investigations were carried out with the antimalarial tablet Riamet® and self-made model tablets, which were used as examples of counterfeits and substandard. Partial least-squares regression modeling and density functional theory calculations were carried out for quantification of lumefantrine and artemether and for spectral band assignment. The most prominent differentiating vibrational signatures of the APIs were presented.
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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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    Noise Sources and Requirements for Confocal Raman Spectrometers in Biosensor Applications
    (Basel : MDPI, 2021) Jahn, Izabella J.; Grjasnow, Alexej; John, Henry; Weber, Karina; Popp, Jürgen; Hauswald, Walter
    Raman spectroscopy probes the biochemical composition of samples in a non-destructive, non-invasive and label-free fashion yielding specific information on a molecular level. Nevertheless, the Raman effect is very weak. The detection of all inelastically scattered photons with highest efficiency is therefore crucial as well as the identification of all noise sources present in the system. Here we provide a study for performance comparison and assessment of different spectrometers for confocal Raman spectroscopy in biosensor applications. A low-cost, home-built Raman spectrometer with a complementary metal-oxide-semiconductor (CMOS) camera, a middle price-class mini charge-coupled device (CCD) Raman spectrometer and a laboratory grade confocal Raman system with a deeply cooled CCD detector are compared. It is often overlooked that the sample itself is the most important “optical” component in a Raman spectrometer and its properties contribute most significantly to the signal-to-noise ratio. For this purpose, different representative samples: a crystalline silicon wafer, a polypropylene sample and E. coli bacteria were measured under similar conditions using the three confocal Raman spectrometers. We show that biosensor applications do not in every case profit from the most expensive equipment. Finally, a small Raman database of three different bacteria species is set up with the middle price-class mini CCD Raman spectrometer in order to demonstrate the potential of a compact setup for pathogen discrimination.
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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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    Assessment of Advanced Oxidation Processes Using Zebrafish in a Non-Forced Exposure System: A Proof of Concept
    (Basel : MDPI, 2021) Cabascango, Tamia; Ortiz, Karol; Sandoval Pauker, Christian; Espinoza Pavón, Isabel; Ramoji, Anuradha; Popp, Jürgen; Pérez, Jady; Pinto, C. Miguel; Rivera-Parra, José Luis; Muñoz-Bisesti, Florinella; Aldás, María Belén; Araújo, Cristiano V. M.; Vargas Jentzsch, Paul
    Water bodies and aquatic ecosystems are threatened by discharges of industrial waters. Ecotoxicological effects of components occurring in untreated and treated wastewaters are often not considered. The use of a linear, multi-compartmented, non-forced, static system constructed with PET bottles is proposed for the quality assessment of treated waters, to deal with such limitations. Two synthetic waters, one simulating wastewater from the textile industry and the other one simulating wastewater from the cassava starch industry, were prepared and treated by homogeneous Fenton process and heterogeneous photocatalysis, respectively. Untreated and treated synthetic waters and their dilutions were placed into compartments of the non-forced exposure system, in which zebrafish (Danio rerio), the indicator organism, could select the environment of its preference. Basic physical–chemical and chemical parameters of untreated and treated synthetic waters were measured. The preference and avoidance responses allowed verification of whether or not the quality of the water was improved due to the treatment. The results of these assays can be a complement to conventional parameters of water quality.
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    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.
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    TopUp SERS substrates with integrated internal standard
    (Basel : MDPI, 2018) Patze, Sophie; Hübner, Uwe; Weber, Karina; Cialla-May, Dana; Popp, Jürgen
    Surface-enhanced Raman spectroscopy (SERS) is known as a molecular-specific and highly sensitive method. In order to enable the routine application of SERS, powerful SERS substrates are of great importance. Within this manuscript, a TopUp SERS substrate is introduced which is fabricated by a top-down process based on microstructuring as well as a bottom-up generation of silver nanostructures. The Raman signal of the support material acts as an internal standard in order to improve the quantification capabilities. The analyte molecule coverage of sulfamethoxazole on the surface of the nanostructures is characterized by the SERS signal evolution fitted by a Langmuir–Freundlich isotherm.
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    Wide Field Spectral Imaging with Shifted Excitation Raman Difference Spectroscopy Using the Nod and Shuffle Technique
    (Basel : MDPI, 2020) Korinth, Florian; Schmälzlin, Elmar; Stiebing, Clara; Urrutia, Tanya; Micheva, Genoveva; Sandin, Christer; Müller, André; Maiwald, Martin; Sumpf, Bernd; Krafft, Christoph; Tränkle, Günther; Roth, Martin M; Popp, Jürgen
    Wide field Raman imaging using the integral field spectroscopy approach was used as a fast, one shot imaging method for the simultaneous collection of all spectra composing a Raman image. For the suppression of autofluorescence and background signals such as room light, shifted excitation Raman difference spectroscopy (SERDS) was applied to remove background artifacts in Raman spectra. To reduce acquisition times in wide field SERDS imaging, we adapted the nod and shuffle technique from astrophysics and implemented it into a wide field SERDS imaging setup. In our adapted version, the nod corresponds to the change in excitation wavelength, whereas the shuffle corresponds to the shifting of charges up and down on a Charge-Coupled Device (CCD) chip synchronous to the change in excitation wavelength. We coupled this improved wide field SERDS imaging setup to diode lasers with 784.4/785.5 and 457.7/458.9 nm excitation and applied it to samples such as paracetamol and aspirin tablets, polystyrene and polymethyl methacrylate beads, as well as pork meat using multiple accumulations with acquisition times in the range of 50 to 200 ms. The results tackle two main challenges of SERDS imaging: gradual photobleaching changes the autofluorescence background, and multiple readouts of CCD detector prolong the acquisition time.
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    Application of High-Throughput Screening Raman Spectroscopy (HTS-RS) for Label-Free Identification and Molecular Characterization of Pollen
    (Basel : MDPI, 2019) Mondol, Abdullah S.; Patel, Milind D.; Rüger, Jan; Stiebing, Clara; Kleiber, Andreas; Henkel, Thomas; Popp, Jürgen; Schie, Iwan W.
    Pollen studies play a critical role in various fields of science. In the last couple of decades, replacement of manual identification of pollen by image-based methods using pollen morphological features was a great leap forward, but challenges for pollen with similar morphology remain, and additional approaches are required. Spectroscopy approaches for identification of pollen, such as Raman spectroscopy has potential benefits over traditional methods, due to the investigation of the intrinsic molecular composition of a sample. However, current Raman-based characterization of pollen is complex and time-consuming, resulting in low throughput and limiting the statistical significance of the acquired data. Previously demonstrated high-throughput screening Raman spectroscopy (HTS-RS) eliminates the complexity as well as human interaction by incorporation full automation of the data acquisition process. Here, we present a customization of HTS-RS for pollen identification, enabling sampling of a large number of pollen in comparison to other state-of-the-art Raman pollen investigations. We show that using Raman spectra we are able to provide a preliminary estimation of pollen types based on growth habits using hierarchical cluster analysis (HCA) as well as good taxonomy of 37 different Pollen using principal component analysis-support vector machine (PCA-SVM) with good accuracy even for the pollen specimens sharing similar morphological features. Our results suggest that HTS-RS platform meets the demands for automated pollen detection making it an alternative method for research concerning pollen.