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Now showing 1 - 10 of 75
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    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. ©
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    Rapid isolation and identification of pneumonia associated pathogens from sputum samples combining an innovative sample preparation strategy and array-based detection
    (Washington : American Chemical Society, 2019) Pahlow, Susanne; Lehniger, Lydia; Hentschel, Stefanie; Seise, Barbara; Braun, Sascha D.; Ehricht, Ralf; Berg, Albrecht; Popp, Jürgen; Weber, Karina
    With this study, an innovative and convenient enrichment and detection strategy for eight clinically relevant pneumonia pathogens, namely, Acinetobacter baumannii, Escherichia coli, Haemophilus influenzae, Klebsiella pneumoniae, Moraxella catarrhalis, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae is introduced. Bacteria were isolated from sputum samples with amine-modified particles exploiting pH-dependent electrostatic interactions between bacteria and the functionalized particle surface. Following this, an asymmetric polymerase chain reaction as well as subsequent stringent array-based hybridization with specific complementary capture probes were performed. Finally, results were visualized by an enzyme-induced silver nanoparticle deposition, providing stable endpoint signals and consequently an easy detection possibility. The assay was optimized using spiked samples of artificial sputum with different strains of the abovementioned bacterial species. Furthermore, actual patient sputum samples with S. pneumoniae were successfully analyzed. The presented approach offers great potential for the urgent need of a fast, specific, and reliable isolation and identification platform for important pneumonia pathogens, covering the complete process chain from sample preparation up to array-based detection within only 4 h.With this study, an innovative and convenient enrichment and detection strategy for eight clinically relevant pneumonia pathogens, namely, Acinetobacter baumannii, Escherichia coli, Haemophilus influenzae, Klebsiella pneumoniae, Moraxella catarrhalis, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae is introduced. Bacteria were isolated from sputum samples with amine-modified particles exploiting pH-dependent electrostatic interactions between bacteria and the functionalized particle surface. Following this, an asymmetric polymerase chain reaction as well as subsequent stringent array-based hybridization with specific complementary capture probes were performed. Finally, results were visualized by an enzyme-induced silver nanoparticle deposition, providing stable endpoint signals and consequently an easy detection possibility. The assay was optimized using spiked samples of artificial sputum with different strains of the abovementioned bacterial species. Furthermore, actual patient sputum samples with S. pneumoniae were successfully analyzed. The presented approach offers great potential for the urgent need of a fast, specific, and reliable isolation and identification platform for important pneumonia pathogens, covering the complete process chain from sample preparation up to array-based detection within only 4 h.
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    Rapid Colorimetric Detection of Pseudomonas aeruginosa in Clinical Isolates Using a Magnetic Nanoparticle Biosensor
    (Washington, DC : ACS Publications, 2019) Alhogail, Sahar; Suaifan, Ghadeer A.R.Y; Bikker, Floris J.; Kaman, Wendy E.; Weber, Karina; Cialla-May, Dana; Popp, Jürgen; Zourob, Mohammed M.
    A rapid, sensitive, and specific colorimetric biosensor based on the use of magnetic nanoparticles (MNPs) was designed for the detection of Pseudomonas aeruginosa in clinical samples. The biosensing platform was based on the measurement of P. aeruginosa proteolytic activity using a specific protease substrate. At the N-terminus, this substrate was covalently bound to MNPs and was linked to a gold sensor surface via cystine at the C-terminus of the substrates. The golden sensor appears black to naked eyes because of the coverage of the MNPs. However, upon proteolysis, the cleaved peptide–MNP moieties will be attracted by an external magnet, revealing the golden color of the sensor surface, which can be observed by the naked eye. In vitro, the biosensor was able to detect specifically and quantitatively the presence of P. aeruginosa with a detection limit of 102 cfu/mL in less than 1 min. The colorimetric biosensor was used to test its ability to detect in situ P. aeruginosa in clinical isolates from patients. This biochip is anticipated to be useful as a rapid point-of-care device for the diagnosis of P. aeruginosa-related infections.
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    Deep learning-based classification of blue light cystoscopy imaging during transurethral resection of bladder tumors
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Ali, Nairveen; Bolenz, Christian; Todenhöfer, Tilman; Stenzel, Arnulf; Deetmar, Peer; Kriegmair, Martin; Knoll, Thomas; Porubsky, Stefan; Hartmann, Arndt; Popp, Jürgen; Kriegmair, Maximilian C.; Bocklitz, Thomas
    Bladder cancer is one of the top 10 frequently occurring cancers and leads to most cancer deaths worldwide. Recently, blue light (BL) cystoscopy-based photodynamic diagnosis was introduced as a unique technology to enhance the detection of bladder cancer, particularly for the detection of flat and small lesions. Here, we aim to demonstrate a BL image-based artificial intelligence (AI) diagnostic platform using 216 BL images, that were acquired in four different urological departments and pathologically identified with respect to cancer malignancy, invasiveness, and grading. Thereafter, four pre-trained convolution neural networks were utilized to predict image malignancy, invasiveness, and grading. The results indicated that the classification sensitivity and specificity of malignant lesions are 95.77% and 87.84%, while the mean sensitivity and mean specificity of tumor invasiveness are 88% and 96.56%, respectively. This small multicenter clinical study clearly shows the potential of AI based classification of BL images allowing for better treatment decisions and potentially higher detection rates.
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    Autofluorescence lifetime augmented reality as a means for real-time robotic surgery guidance in human patients
    (Berlin : Nature Publishing, 2019) Gorpas, Dimitris; Phipps, Jennifer E.; Bec, Julien; Ma, Dinglong; Dochow, Sebastian; Yankelevich, Diego R.; Sorger, Jonathan; Popp, Jürgen; Bewley, Arnaud Fassett; Gandour-Edwards, Regina F.; Marcu, Laura; Farwell, D. Gregory
    Due to loss of tactile feedback the assessment of tumor margins during robotic surgery is based only on visual inspection, which is neither significantly sensitive nor specific. Here we demonstrate time-resolved fluorescence spectroscopy (TRFS) as a novel technique to complement the visual inspection of oral cancers during transoral robotic surgery (TORS) in real-time and without the need for exogenous contrast agents. TRFS enables identification of cancerous tissue by its distinct autofluorescence signature that is associated with the alteration of tissue structure and biochemical profile. A prototype TRFS instrument was integrated synergistically with the da Vinci Surgical robot and the combined system was validated in swine and human patients. Label-free and real-time assessment and visualization of tissue biochemical features during robotic surgery procedure, as demonstrated here, not only has the potential to improve the intraoperative decision making during TORS but also other robotic procedures without modification of conventional clinical protocols.
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    Morpho-molecular signal correlation between optical coherence tomography and Raman spectroscopy for superior image interpretation and clinical diagnosis
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Schie, Iwan W.; Placzek, Fabian; Knorr, Florian; Cordero, Eliana; Wurster, Lara M.; Hermann, Gregers G.; Mogensen, Karin; Hasselager, Thomas; Drexler, Wolfgang; Popp, Jürgen; Leitgeb, Rainer A.
    The combination of manifold optical imaging modalities resulting in multimodal optical systems allows to discover a larger number of biomarkers than using a single modality. The goal of multimodal imaging systems is to increase the diagnostic performance through the combination of complementary modalities, e.g. optical coherence tomography (OCT) and Raman spectroscopy (RS). The physical signal origins of OCT and RS are distinctly different, i.e. in OCT it is elastic back scattering of photons, due to a change in refractive index, while in RS it is the inelastic scattering between photons and molecules. Despite those diverse characteristics both modalities are also linked via scattering properties and molecular composition of tissue. Here, we investigate for the first time the relation of co-registered OCT and RS signals of human bladder tissue, to demonstrate that the signals of these complementary modalities are inherently intertwined, enabling a direct but more importantly improved interpretation and better understanding of the other modality. This work demonstrates that the benefit for using two complementary imaging approaches is, not only the increased diagnostic value, but the increased information and better understanding of the signal origins of both modalities. This evaluation confirms the advantages for using multimodal imaging systems and also paves the way for significant further improved understanding and clinically interpretation of both modalities in the future.
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    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.
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    Surface-Enhanced Raman Spectroscopy to Characterize Different Fractions of Extracellular Vesicles from Control and Prostate Cancer Patients
    (Basel : MDPI, 2021) Osei, Eric Boateng; Paniushkina, Liliia; Wilhelm, Konrad; Popp, Jürgen; Nazarenko, Irina; Krafft, Christoph
    Extracellular vesicles (EVs) are membrane-enclosed structures ranging in size from about 60 to 800 nm that are released by the cells into the extracellular space; they have attracted interest as easily available biomarkers for cancer diagnostics. In this study, EVs from plasma of control and prostate cancer patients were fractionated by differential centrifugation at 5000× g, 12,000× g and 120,000× g. The remaining supernatants were purified by ultrafiltration to produce EV-depleted free-circulating (fc) fractions. Spontaneous Raman and surface-enhanced Raman spectroscopy (SERS) at 785 nm excitation using silver nanoparticles (AgNPs) were employed as label-free techniques to collect fingerprint spectra and identify the fractions that best discriminate between control and cancer patients. SERS spectra from 10 µL droplets showed an enhanced Raman signature of EV-enriched fractions that were much more intense for cancer patients than controls. The Raman spectra of dehydrated pellets of EV-enriched fractions without AgNPs were dominated by spectral contributions of proteins and showed variations in S-S stretch, tryptophan and protein secondary structure bands between control and cancer fractions. We conclude that the AgNPs-mediated SERS effect strongly enhances Raman bands in EV-enriched fractions, and the fractions, EV12 and EV120 provide the best separation of cancer and control patients by Raman and SERS spectra.
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    Fiber-based SORS-SERDS system and chemometrics for the diagnostics and therapy monitoring of psoriasis inflammatory disease in vivo
    (Washington, DC : Optica, 2021-1-28) Schleusener, Johannes; Guo, Shuxia; Darvin, Maxim E.; Thiede, Gisela; Chernavskaia, Olga; Knorr, Florian; Lademann, Jürgen; Popp, Jürgen; Bocklitz, Thomas W.
    Psoriasis is considered a widespread dermatological disease that can strongly affect the quality of life. Currently, the treatment is continued until the skin surface appears clinically healed. However, lesions appearing normal may contain modifications in deeper layers. To terminate the treatment too early can highly increase the risk of relapses. Therefore, techniques are needed for a better knowledge of the treatment process, especially to detect the lesion modifications in deeper layers. In this study, we developed a fiber-based SORS-SERDS system in combination with machine learning algorithms to non-invasively determine the treatment efficiency of psoriasis. The system was designed to acquire Raman spectra from three different depths into the skin, which provide rich information about the skin modifications in deeper layers. This way, it is expected to prevent the occurrence of relapses in case of a too short treatment. The method was verified with a study of 24 patients upon their two visits: the data is acquired at the beginning of a standard treatment (visit 1) and four months afterwards (visit 2). A mean sensitivity of ≥85% was achieved to distinguish psoriasis from normal skin at visit 1. At visit 2, where the patients were healed according to the clinical appearance, the mean sensitivity was ≈65%.
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    Shape-Memory Metallopolymers Based on Two Orthogonal Metal–Ligand Interactions
    (Weinheim : Wiley-VCH, 2021) Meurer, Josefine; Hniopek, Julian; Bätz, Thomas; Zechel, Stefan; Enke, Marcel; Vitz, Jürgen; Schmitt, Michael; Popp, Jürgen; Hager, Martin D.; Schubert, Ulrich S.
    A new shape-memory polymer is presented, in which both the stable phase as well as the switching unit consist of two different metal complexes. Suitable metal ions, which simultaneously form labile complexes with histidine and stable ones with terpyridine ligands, are identified via isothermal titration calorimetry (ITC) measurements. Different copolymers are synthesized, which contain butyl methacrylate as the main monomer and the metal-binding ligands in the side chains. Zn(TFMS)2 and NiCl2 are utilized for the dual crosslinking, resulting in the formation of metallopolymer networks. The switching temperature can simply be tuned by changing the composition as well as by the choice of the metal ion. Strain fixity rates (about 99%) and very high strain recovery rates (up to 95%) are achieved and the mechanism is revealed using different techniques such as Raman spectroscopy. © 2021 The Authors. Advanced Materials published by Wiley-VCH GmbH