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- ItemThe Bouguer-Beer-Lambert Law: Shining Light on the Obscure(Weinheim : Wiley-VCH Verl., 2020) Mayerhöfer, Thomas G.; Pahlow, Susanne; Popp, JürgenThe Beer-Lambert law is unquestionably the most important law in optical spectroscopy and indispensable for the qualitative and quantitative interpretation of spectroscopic data. As such, every spectroscopist should know its limits and potential pitfalls, arising from its application, by heart. It is the goal of this work to review these limits and pitfalls, as well as to provide solutions and explanations to guide the reader. This guidance will allow a deeper understanding of spectral features, which cannot be explained by the Beer-Lambert law, because they arise from electromagnetic effects/the wave nature of light. Those features include band shifts and intensity changes based exclusively upon optical conditions, i. e. the method chosen to record the spectra, the substrate and the form of the sample. As such, the review will be an essential tool towards a full understanding of optical spectra and their quantitative interpretation based not only on oscillator positions, but also on their strengths and damping constants.
- ItemNovel Biobased Self-Healing Ionomers Derived from Itaconic Acid Derivates(Weinheim : Wiley-VCH, 2021) Meurer, Josefine; Hniopek, Julian; Dahlke, Jan; Schmitt, Michael; Popp, Jürgen; Zechel, Stefan; Hager, Martin D.This article presents novel biobased ionomers featuring self-healing abilities. These smart materials are synthesized from itaconic acid derivates. Large quantities of itaconic acid can be produced from diverse biomass like corn, rice, and others. This study presents a comprehensive investigation of their thermal and mechanical properties via differential scanning calorimetry (DSC), thermo gravimetric analysis (TGA), and FT-Raman and FT-IR measurements as well as dynamic mechanic analysis. Within all these measurements, different kinds of structure-property relationships could be derived from these measurements. For example, the proportion of ionic groups enormously influences the self-healing efficiency. The investigation of the self-healing abilities reveals healing efficiencies up to 99% in 2 h at 90 °C for the itaconic acid based ionomer with the lowest ionic content. © 2020 The Authors. Macromolecular Rapid Communications published by Wiley-VCH GmbH
- ItemStealth Effect of Short Polyoxazolines in Graft Copolymers: Minor Changes of Backbone End Group Determine Liver Cell-Type Specificity(Washington, DC : ACS Publications, 2021) Muljajew, Irina; Huschke, Sophie; Ramoji, Anuradha; Cseresnyés, Zoltán; Hoeppener, Stephanie; Nischang, Ivo; Foo, Wanling; Popp, Jürgen; Figge, Marc Thilo; Weber, Christine; Bauer, Michael; Schubert, Ulrich S.; Press, Adrian T.Dye-loaded micelles of 10 nm diameter formed from amphiphilic graft copolymers composed of a hydrophobic poly(methyl methacrylate) backbone and hydrophilic poly(2-ethyl-2-oxazoline) side chains with a degree of polymerization of 15 were investigated concerning their cellular interaction and uptake in vitro as well as their interaction with local and circulating cells of the reticuloendothelial system in the liver by intravital microscopy. Despite the high molar mass of the individual macromolecules (Mn ≈ 20 kg mol-1), backbone end group modification by attachment of a hydrophilic anionic fluorescent probe strongly affected the in vivo performance. To understand these effects, the end group was additionally modified by the attachment of four methacrylic acid repeating units. Although various micelles appeared similar in dynamic light scattering and cryo-transmission electron microscopy, changes in the micelles were evident from principal component analysis of the Raman spectra. Whereas an efficient stealth effect was found for micelles formed from polymers with anionically charged or thiol end groups, a hydrophobic end group altered the micelles' structure sufficiently to adapt cell-type specificity and stealth properties in the liver. © 2021 The Authors. Published by American Chemical Society.
- ItemBiochemical 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, JürgenThe 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. ©
- 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
- ItemOnline investigation of respiratory quotients in Pinus sylvestris and Picea abies during drought and shading by means of cavity-enhanced Raman multi-gas spectrometry(Cambridge : Soc., 2015) Hanf, Stefan; Fischer, Sarah; Hartmann, Henrik; Keiner, Robert; Trumbore, Susan; Popp, Jürgen; Frosch, TorstenPhotosynthesis and respiration are major components of the plant carbon balance. During stress, like drought, carbohydrate supply from photosynthesis is reduced and the Krebs cycle respiration must be fueled with other stored carbon compounds. However, the dynamics of storage use are still unknown. The respiratory quotient (RQ, CO2 released per O2 consumed during respiration) is an excellent indicator of the nature of the respiration substrate. In plant science, however, online RQ measurements have been challenging or even impossible so far due to very small gas exchange fluxes during respiration. Here we apply cavity-enhanced multi-gas Raman spectrometry (CERS) for online in situ RQ measurements in drought-tolerant pine (Pinus sylvestris [L.]) and drought-intolerant spruce (Picea abies [L. H. Karst]). Two different treatments, drought and shading, were applied to reduce photosynthesis and force dependency on stored substrates. Changes in respiration rates and RQ values were continuously monitored over periods of several days with low levels of variance. The results show that both species switched from COH-dominated respiration (RQ = 1.0) to a mixture of substrates during shading (RQ = 0.77–0.81), while during drought only pine did so (RQ = 0.75). The gas phase measurements were complemented by concentration measurements of non-structural carbohydrates and lipids. These first results suggest a physiological explanation for greater drought tolerance in pine. CERS was proven as powerful technique for non-consumptive and precise real-time monitoring of respiration rates and respirational quotients for the investigation of plant metabolism under drought stress conditions that are predicted to increase with future climate change.
- ItemAssessment of shifted excitation Raman difference spectroscopy in highly fluorescent biological samples(Cambridge : Soc., 2021) Korinth, Florian; Shaik, Tanveer Ahmed; Popp, Jürgen; Krafft, ChristophShifted excitation Raman difference spectroscopy (SERDS) can be used as an instrumental baseline correction technique to retrieve Raman bands in highly fluorescent samples. Genipin (GE) cross-linked equine pericardium (EP) was used as a model system since a blue pigment is formed upon cross-linking, which results in a strong fluorescent background in the Raman spectra. EP was cross-linked with 0.25% GE solution for 0.5 h, 2 h, 4 h, 6 h, 12 h, and 24 h, and compared with corresponding untreated EP. Raman spectra were collected with three different excitation wavelengths. For the assessment of the SERDS technique, the preprocessed SERDS spectra of two excitation wavelengths (784 nm-786 nm) were compared with the mathematical baseline-corrected Raman spectra at 785 nm excitation using extended multiplicative signal correction, rubberband, the sensitive nonlinear iterative peak and polynomial fitting algorithms. Whereas each baseline correction gave poor quality spectra beyond 6 h GE crosslinking with wave-like artefacts, the SERDS technique resulted in difference spectra, that gave superior reconstructed spectra with clear collagen and resonance enhanced GE pigment bands with lower standard deviation. Key for this progress was an advanced difference optimization approach that is described here. Furthermore, the results of the SERDS technique were independent of the intensity calibration because the system transfer response was compensated by calculating the difference spectrum. We conclude that this SERDS strategy can be transferred to Raman studies on biological and non-biological samples with a strong fluorescence background at 785 nm and also shorter excitation wavelengths which benefit from more intense scattering intensities and higher quantum efficiencies of CCD detectors. This journal is
- ItemUse of polymers as wavenumber calibration standards in deep-UVRR(Amsterdam [u.a.] : Elsevier Science, 2022) Pistiki, Aikaterini; Ryabchykov, Oleg; Bocklitz, Thomas W.; Rösch, Petra; Popp, JürgenDeep-UV resonance Raman spectroscopy (UVRR) allows the classification of bacterial species with high accuracy and is a promising tool to be developed for clinical application. For this attempt, the optimization of the wavenumber calibration is required to correct the overtime changes of the Raman setup. In the present study, different polymers were investigated as potential calibration agents. The ones with many sharp bands within the spectral range 400–1900 cm−1 were selected and used for wavenumber calibration of bacterial spectra. Classification models were built using a training cross-validation dataset that was then evaluated with an independent test dataset obtained after 4 months. Without calibration, the training cross-validation dataset provided an accuracy for differentiation above 99 % that dropped to 51.2 % after test evaluation. Applying the test evaluation with PET and Teflon calibration allowed correct assignment of all spectra of Gram-positive isolates. Calibration with PS and PEI leads to misclassifications that could be overcome with majority voting. Concerning the very closely related and similar in genome and cell biochemistry Enterobacteriaceae species, all spectra of the training cross-validation dataset were correctly classified but were misclassified in test evaluation. These results show the importance of selecting the most suitable calibration agent in the classification of bacterial species and help in the optimization of the deep-UVRR technique.
- ItemRevealing the Chemical Composition of Birch Pollen Grains by Raman Spectroscopic Imaging(Basel : Molecular Diversity Preservation International (MDPI), 2022) Stiebing, Clara; Post, Nele; Schindler, Claudia; Göhrig, Bianca; Lux, Harald; Popp, Jürgen; Heutelbeck, Astrid; Schie, Iwan W.The investigation of the biochemical composition of pollen grains is of the utmost interest for several environmental aspects, such as their allergenic potential and their changes in growth conditions due to climatic factors. In order to fully understand the composition of pollen grains, not only is an in-depth analysis of their molecular components necessary but also spatial information of, e.g., the thickness of the outer shell, should be recorded. However, there is a lack of studies using molecular imaging methods for a spatially resolved biochemical composition on a single-grain level. In this study, Raman spectroscopy was implemented as an analytical tool to investigate birch pollen by imaging single pollen grains and analyzing their spectral profiles. The imaging modality allowed us to reveal the layered structure of pollen grains based on the biochemical information of the recorded Raman spectra. Seven different birch pollen species collected at two different locations in Germany were investigated and compared. Using chemometric algorithms such as hierarchical cluster analysis and multiple-curve resolution, several components of the grain wall, such as sporopollenin, as well as the inner core presenting high starch concentrations, were identified and quantified. Differences in the concentrations of, e.g., sporopollenin, lipids and proteins in the pollen species at the two different collection sites were found, and are discussed in connection with germination and other growth processes.
- ItemTowards on-site testing of Phytophthora species(Cambridge : RSC Publ., 2014) Schwenkbier, Lydia; Pollok, Sibyll; König, Stephan; Urban, Matthias; Werres, Sabine; Cialla-May, Dana; Weber, Karina; Popp, JürgenRapid detection and accurate identification of plant pathogens in the field is an ongoing challenge. In this study, we report for the first time on the development of a helicase-dependent isothermal amplification (HDA) in combination with on-chip hybridization for the detection of selected Phytophthora species. The HDA approach allows efficient amplification of the yeast GTP-binding protein (Ypt1) target gene region at one constant temperature in a miniaturized heating device. The assay's specificity was determined by on-chip DNA hybridization and subsequent silver nanoparticle deposition. The silver deposits serve as stable endpoint signals that enable the visual as well as the electrical readout. Our promising results point to the direction of a near future on-site application of the combined techniques for a reliable detection of Phytophthora species.