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.

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.

2020, Cordero, Eliana, Rüger, Jan, Marti, Dominik, Mondol, Abdullah S., Hasselager, Thomas, Mogensen, Karin, Hermann, Gregers G., Popp, Jürgen, Schie, Iwan W.

Existing approaches for early-stage bladder tumor diagnosis largely depend on invasive and time-consuming procedures, resulting in hospitalization, bleeding, bladder perforation, infection and other health risks for the patient. The reduction of current risk factors, while maintaining or even improving the diagnostic precision, is an underlying factor in clinical instrumentation research. For example, for clinic surveillance of patients with a history of noninvasive bladder tumors real-time tumor diagnosis can enable immediate laser-based removal of tumors using flexible cystoscopes in the outpatient clinic. Therefore, novel diagnostic modalities are required that can provide real-time in vivo tumor diagnosis. Raman spectroscopy provides biochemical information of tissue samples ex vivo and in vivo and without the need for complicated sample preparation and staining procedures. For the past decade there has been a rise in applications to diagnose and characterize early cancer in different organs, such as in head and neck, colon and stomach, but also different pathologies, for example, inflammation and atherosclerotic plaques. Bladder pathology has also been studied but only with little attention to aspects that can influence the diagnosis, such as tissue heterogeneity, data preprocessing and model development. The present study presents a clinical investigative study on bladder biopsies to characterize the tumor grading ex vivo, using a compact fiber probe-based imaging Raman system, as a crucial step towards in vivo Raman endoscopy. Furthermore, this study presents an evaluation of the tissue heterogeneity of highly fluorescent bladder tissues, and the multivariate statistical analysis for discrimination between nontumor tissue, and low- and high-grade tumor. © 2019 The Authors. Journal of Biophotonics published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

2019, Frosch, Timea, Knebl, Andreas, Frosch, Torsten

Innovations in Raman spectroscopic techniques provide a potential solution to current problems in pharmaceutical drug monitoring. This review aims to summarize the recent advances in the field. The developments of novel plasmonic nanoparticles continuously push the limits of Raman spectroscopic detection. In surface-enhanced Raman spectroscopy (SERS), these particles are used for the strong local enhancement of Raman signals from pharmaceutical drugs. SERS is increasingly applied for forensic trace detection and for therapeutic drug monitoring. In combination with spatially offset Raman spectroscopy, further application fields could be addressed, e.g. in situ pharmaceutical quality testing through the packaging. Raman optical activity, which enables the thorough analysis of specific chiral properties of drugs, can also be combined with SERS for signal enhancement. Besides SERS, micro- and nano-structured optical hollow fibers enable a versatile approach for Raman signal enhancement of pharmaceuticals. Within the fiber, the volume of interaction between drug molecules and laser light is increased compared with conventional methods. Advances in fiber-enhanced Raman spectroscopy point at the high potential for continuous online drug monitoring in clinical therapeutic diagnosis. Furthermore, fiber-array based non-invasive Raman spectroscopic chemical imaging of tablets might find application in the detection of substandard and counterfeit drugs. The discussed techniques are promising and might soon find widespread application for the detection and monitoring of drugs in various fields.

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).

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

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

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.

2020, Götz, Theresa, Dahms, Marcel, Kirchhoff, Johanna, Beleites, Claudia, Glaser, Uwe, Bohnert, Jürgen A., Pletz, Mathias W., Popp, Jürgen, Schlattmann, Peter, Neugebauer, Ute

A Raman-based, strain-independent, semi-automated method is presented that allows the rapid (<3 hours) determination of antibiotic susceptibility of bacterial pathogens isolated from clinical samples. Applying a priori knowledge about the mode of action of the respective antibiotic, we identified characteristic Raman marker bands in the spectrum and calculated batch-wise weighted sum scores from standardized Raman intensity differences between spectra of antibiotic exposed and nonexposed samples of the same strains. The lead substances for three relevant antibiotic classes (fluoroquinolone ciprofloxacin, third-generation cephalosporin cefotaxime, ureidopenicillin piperacillin) against multidrug-resistant Gram-negative bacteria (MRGN) revealed a high sensitivity and specificity for the susceptibility testing of two Escherichia coli laboratory strains and 12 clinical isolates. The method benefits from the parallel incubation of control and treated samples, which reduces the variance due to alterations in cultivation conditions and the standardization of differences between batches leading to long-term comparability of Raman measurements. © 2020 The Authors. Journal of Biophotonics published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

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