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- ItemFLIm 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, JürgenBiomaterials 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.
- ItemA Review on Data Fusion of Multidimensional Medical and Biomedical Data(Basel : MDPI, 2022) Azam, Kazi Sultana Farhana; Ryabchykov, Oleg; Bocklitz, ThomasData 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.
- ItemModified 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, ThomasRaman 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
- ItemCorrelation 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, UteBiofilm-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.
- ItemComparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study(Columbus, Ohio : American Chemical Society, 2020) Guo S.; Beleites C.; Neugebauer U.; Abalde-Cela S.; Afseth N.K.; Alsamad F.; Anand S.; Araujo-Andrade C.; Aškrabić S.; Avci E.; Baia M.; Baranska M.; Baria E.; Batista De Carvalho L.A.E.; De Bettignies P.; Bonifacio A.; Bonnier F.; Brauchle E.M.; Byrne H.J.; Chourpa I.; Cicchi R.; Cuisinier F.; Culha M.; Dahms M.; David C.; Duponchel L.; Duraipandian S.; El-Mashtoly S.F.; Ellis D.I.; Eppe G.; Falgayrac G.; Gamulin O.; Gardner B.; Gardner P.; Gerwert K.; Giamarellos-Bourboulis E.J.; Gizurarson S.; Gnyba M.; Goodacre R.; Grysan P.; Guntinas-Lichius O.; Helgadottir H.; Grošev V.M.; Kendall C.; Kiselev R.; Kölbach M.; Krafft C.; Krishnamoorthy S.; Kubryck P.; Lendl B.; Loza-Alvarez P.; Lyng F.M.; Machill S.; Malherbe C.; Marro M.; Marques M.P.M.; Matuszyk E.; Morasso C.F.; Moreau M.; Muhamadali H.; Mussi V.; Notingher I.; Pacia M.Z.; Pavone F.S.; Penel G.; Petersen D.; Piot O.; Rau J.V.; Richter M.; Rybarczyk M.K.; Salehi H.; Schenke-Layland K.; Schlücker S.; Schosserer M.; Schütze K.; Sergo V.; Sinjab F.; Smulko J.; Sockalingum G.D.; Stiebing C.; Stone N.; Untereiner V.; Vanna R.; Wieland K.; Popp J.; Bocklitz T.The variable configuration of Raman spectroscopic platforms is one of the major obstacles in establishing Raman spectroscopy as a valuable physicochemical method within real-world scenarios such as clinical diagnostics. For such real world applications like diagnostic classification, the models should ideally be usable to predict data from different setups. Whether it is done by training a rugged model with data from many setups or by a primary-replica strategy where models are developed on a 'primary' setup and the test data are generated on 'replicate' setups, this is only possible if the Raman spectra from different setups are consistent, reproducible, and comparable. However, Raman spectra can be highly sensitive to the measurement conditions, and they change from setup to setup even if the same samples are measured. Although increasingly recognized as an issue, the dependence of the Raman spectra on the instrumental configuration is far from being fully understood and great effort is needed to address the resulting spectral variations and to correct for them. To make the severity of the situation clear, we present a round robin experiment investigating the comparability of 35 Raman spectroscopic devices with different configurations in 15 institutes within seven European countries from the COST (European Cooperation in Science and Technology) action Raman4clinics. The experiment was developed in a fashion that allows various instrumental configurations ranging from highly confocal setups to fibre-optic based systems with different excitation wavelengths. We illustrate the spectral variations caused by the instrumental configurations from the perspectives of peak shifts, intensity variations, peak widths, and noise levels. We conclude this contribution with recommendations that may help to improve the inter-laboratory studies. © 2020 American Chemical Society.
- ItemApplication of molecular SERS nanosensors: where we stand and where we are headed towards?(Berlin ; Heidelberg : Springer, 2020) Jahn I.J.; Mühlig A.; Cialla-May D.Molecular specific and highly sensitive detection is the driving force of the surface-enhanced Raman spectroscopy (SERS) community. The technique opens the window to the undisturbed monitoring of cellular processes in situ or to the quantification of small molecular species that do not deliver Raman signals. The smart design of molecular SERS nanosensors makes it possible to indirectly but specifically detect, e.g. reactive oxygen species, carbon monoxide or potentially toxic metal ions. Detection schemes evolved over the years from simple metallic colloidal nanoparticles functionalized with sensing molecules that show uncontrolled aggregation to complex nanostructures with magnetic properties making the analysis of complex environmental samples possible. The present article gives the readership an overview of the present research advancements in the field of molecular SERS sensors, highlighting future trends. © 2020, The Author(s).
- ItemIsolation of bacteria from artificial bronchoalveolar lavage fluid using density gradient centrifugation and their accessibility by Raman spectroscopy(Berlin [u.a.] : Springer, 2021) Wichmann, Christina; Rösch, Petra; Popp, JürgenRaman spectroscopy is an analytical method to identify medical samples of bacteria. Because Raman spectroscopy detects the biochemical properties of a cell, there are many factors that can influence and modify the Raman spectra of bacteria. One possible influence is a proper method for isolation of the bacteria. Medical samples in particular never occur in purified form, so a Raman-compatible isolation method is needed which does not affect the bacteria and thus the resulting spectra. In this study, we present a Raman-compatible method for isolation of bacteria from bronchoalveolar lavage (BAL) fluid using density gradient centrifugation. In addition to measuring the bacteria from a patient sample, the yield and the spectral influence of the isolation on the bacteria were investigated. Bacteria isolated from BAL fluid show additional peaks in comparison to pure culture bacteria, which can be attributed to components in the BAL sample. The isolation gradient itself has no effect on the spectra, and with a yield of 63% and 78%, the method is suitable for isolation of low concentrations of bacteria from a complex matrix. Graphical abstract.
- ItemMonitoring the thermally induced transition from sp3-hybridized into sp2-hybridized carbons(Amsterdam [u.a.] : Elsevier Science, 2021) Schüpfer, Dominique B.; Badaczewski, Felix; Peilstöcker, Jan; Guerra-Castro, Juan Manuel; Shim, Hwirim; Firoozabadi, Saleh; Beyer, Andreas; Volz, Kerstin; Presser, Volker; Heiliger, Christian; Smarsly, Bernd; Klar, Peter J.The preparation of carbons for technical applications is typically based on a treatment of a precursor, which is transformed into the carbon phase with the desired structural properties. During such treatment the material passes through several different structural stages, for example, starting from precursor molecules via an amorphous phase into crystalline-like phases. While the structure of non-graphitic and graphitic carbon has been well studied, the transformation stages from molecular to amorphous and non-graphitic carbon are still not fully understood. Disordered carbon often contains a mixture of sp3-, sp2-and sp1-hybridized bonds, whose analysis is difficult to interpret. We systematically address this issue by studying the transformation of purely sp3-hybridized carbons, that is, nanodiamond and adamantane, into sp2-hybridized non-graphitic and graphitic carbon. The precursor materials are thermally treated at different temperatures and the transformation stages are monitored. We employ Raman spectroscopy, WAXS and TEM to characterize the structural changes. We correlate the intensities and positions of the Raman bands with the lateral crystallite size La estimated by WAXS analysis. The behavior of the D and G Raman bands characteristic for sp2-type material formed by transforming the sp3-hybridized precursors into non-graphitic and graphitic carbon agrees well with that observed using sp2-structured precursors.
- ItemChemical Imaging of Mixed Metal Oxide Catalysts for Propylene Oxidation: From Model Binary Systems to Complex Multicomponent Systems(Weinheim : Wiley-VCH, 2021) Sprenger, Paul; Stehle, Matthias; Gaur, Abhijeet; Weiß, Jana; Brueckner, Dennis; Zhang, Yi; Garrevoet, Jan; Suuronen, Jussi‐Petteri; Thomann, Michael; Fischer, Achim; Grunwaldt, Jan‐Dierk; Sheppard, Thomas L.Industrially-applied mixed metal oxide catalysts often possess an ensemble of structural components with complementary functions. Characterisation of these hierarchical systems is challenging, particularly moving from binary to quaternary systems. Here a quaternary Bi−Mo−Co−Fe oxide catalyst showing significantly greater activity than binary Bi−Mo oxides for selective propylene oxidation to acrolein was studied with chemical imaging techniques from the microscale to nanoscale. Conventional techniques like XRD and Raman spectroscopy could only distinguish a small number of components. Spatially-resolved characterisation provided a clearer picture of metal oxide phase composition, starting from elemental distribution by SEM-EDX and spatially-resolved mapping of metal oxide components by 2D Raman spectroscopy. This was extended to 3D using multiscale hard X-ray tomography with fluorescence, phase, and diffraction contrast. The identification and co-localisation of phases in 2D and 3D can assist in rationalising catalytic performance during propylene oxidation, based on studies of model, binary, or ternary catalyst systems in literature. This approach is generally applicable and attractive for characterisation of complex mixed metal oxide systems. © 2021 The Authors. ChemCatChem published by Wiley-VCH GmbH