Search Results
A Machine Learning-Based Raman Spectroscopic Assay for the Identification of Burkholderia mallei and Related Species
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
In situ Raman spectroscopy on silicon nanowire anodes integrated in lithium ion batteries
2019, Krause, A., Tkacheva, O., Omar, A., Langklotz, U., Giebeler, L., Dörfler, S., Fauth, F., Mikolajick, T., Weber, W.M.
Rapid decay of silicon anodes during lithiation poses a significant challenge in application of silicon as an anode material in lithium ion batteries. In situ Raman spectroscopy is a powerful method to study the relationship between structural and electrochemical data during electrode cycling and to allow the observation of amorphous as well as liquid and transient species in a battery cell. Herein, we present in situ Raman spectroscopy on high capacity electrode using uncoated and carbon-coated silicon nanowires during first lithiation and delithiation cycle in an optimized lithium ion battery setup and complement the results with operando X-ray reflection diffraction measurements. During lithiation, we were able to detect a new Raman signal at 1859 cm−1 especially on uncoated silicon nanowires. The detailed in situ Raman measurement of the first lithiation/delithiation cycle allowed to differentiate between morphology changes of the electrode as well as interphase formation from electrolyte components.
Elucidating the chemistry behind the reduction of graphene oxide using a green approach with polydopamine
2019, Silva, Cláudia, Simon, Frank, Friedel, Peter, Pötschke, Petra, Zimmerer, Cordelia
A new approach using X-ray photoelectron spectroscopy (XPS) was employed to give insight into the reduction of graphene oxide (GO) using a green approach with polydopamine (PDA). In this approach, the number of carbon atoms bonded to OH and to nitrogen in PDA is considered and compared to the total intensity of the signal resulting from OH groups in polydopamine-reduced graphene oxide (PDA-GO) to show the reduction. For this purpose, GO and PDA-GO with different times of reduction were prepared and characterized by Raman Spectroscopy and XPS. The PDA layer was removed to prepare reduced graphene oxide (RGO) and the effect of all chemical treatments on the thermal and electrical properties of the materials was studied. The results show that the complete reduction of the OH groups in GO occurred after 180 min of reaction. It was also concluded that Raman spectroscopy is not well suited to determine if the reduction and restoration of the sp2 structure occurred. Moreover, a significant change in the thermal stability was not observed with the chemical treatments. Finally, the electrical powder conductivity decreased after reduction with PDA, increasing again after its removal. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
Application of High-Throughput Screening Raman Spectroscopy (HTS-RS) for Label-Free Identification and Molecular Characterization of Pollen
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.
Counterfeit and substandard test of the antimalarial tablet Riamet® by means of Raman hyperspectral multicomponent analysis
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.
Recent advances in nano-photonic techniques for pharmaceutical drug monitoring with emphasis on Raman spectroscopy
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.
Automatic spike correction using UNIFIT 2020
2019, Hesse, Ronald, Bundesmann, Carsten, Denecke, Reinhard
The improvement of the software UNIFIT 2020 from an analysis processing software for photoelectron spectroscopy (XPS) only to a powerful tool for XPS, Auger electron spectroscopy (AES), X-ray absorption spectroscopy (XAS), and Raman spectroscopy requires new additional programme routines. Particularly, the implementation of the analysis of Raman spectra needs a well-working automatic spike correction. The application of the modified discrete Laplace operator method allows for a perfect localization and correction of the spikes and finally a successful peak fit of the spectra. The theoretical basis is described. Test spectra allow for the evaluation of the presented method. A comparison of the original and spike-corrected real measurements demonstrates the high quality of the method used.
Fiber-array-based Raman hyperspectral imaging for simultaneous chemical selective monitoring of particle size and shape of active ingredients in analgesic tablets
2019, Frosch, Timea, Wyrwich, Elisabeth, Yan, Di, Popp, Jürgen, Frosch, Torsten
The particle shape, size and distribution of active pharmaceutical ingredients (API) are relevant quality indicators of pharmaceutical tablets due to their high impact on the manufacturing process. Furthermore, the bioavailability of the APIs from the dosage form depends largely on these characteristics. Routinely, particle size and shape are only analyzed in the powder form, without regard to the effect of the formulation procedure on the particle characteristics. The monitoring of these parameters improves the understanding of the process; therefore, higher quality and better control over the biopharmaceutical profile can be ensured. A new fiber-array-based Raman hyperspectral imaging technique is presented for direct simultaneous in-situ monitoring of three different active pharmaceutical ingredients- acetylsalicylic acid, acetaminophen and caffeine- in analgesic tablets. This novel method enables a chemically selective, noninvasive assessment of the distribution of the active ingredients down to 1 µm spatial resolution. The occurrence of spherical and needle-like particles, as well as agglomerations and the respective particle size ranges, were rapidly determined for two commercially available analgesic tablet types. Subtle differences were observed in comparison between these two tablets. Higher amounts of acetaminophen were visible, more needle-shaped and bigger acetylsalicylic acid particles, and a higher incidence of bigger agglomerations were found in one of the analgesic tablets.
Vertical aerosol distribution in the southern hemispheric midlatitudes as observed with lidar in Punta Arenas, Chile (53.2° and 70.9° W), during ALPACA
2019, Foth, Andreas, Kanitz, Thomas, Engelmann, Ronny, Baars, Holger, Radenz, Martin, Seifert, Patric, Barja, Boris, Fromm, Michael, Kalesse, Heike, Ansmann, Albert
Within this publication, lidar observations of the vertical aerosol distribution above Punta Arenas, Chile (53.2 S and 70.9 W), which have been performed with the Raman lidar PollyXT from December 2009 to April 2010, are presented. Pristine marine aerosol conditions related to the prevailing westerly circulation dominated the measurements. Lofted aerosol layers could only be observed eight times during the whole measurement period. Two case studies are presented showing long-range transport of smoke from biomass burning in Australia and regionally transported dust from the Patagonian Desert, respectively. The aerosol sources are identified by trajectory analyses with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and FLEXible PARTicle dispersion model (FLEXPART). However, seven of the eight analysed cases with lofted layers show an aerosol optical thickness of less than 0.05. From the lidar observations, a mean planetary boundary layer (PBL) top height of 1150 350m was determined. An analysis of particle backscatter coefficients confirms that the majority of the aerosol is attributed to the PBL, while the free troposphere is characterized by a very low background aerosol concentration. The ground-based lidar observations at 532 and 1064 nm are supplemented by the Aerosol Robotic Network (AERONET) Sun photometers and the space-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The averaged aerosol optical thickness (AOT) determined by CALIOP was 0:02 0:01 in Punta Arenas from 2009 to 2010. © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.
New perspectives for viability studies with high-content analysis Raman spectroscopy (HCA-RS)
2019, Mondol, Abdullah S., Töpfer, Natalie, Rüger, Jan, Neugebauer, Ute, Popp, Jürgen, Schie, Iwan W.
Raman spectroscopy has been widely used in clinical and molecular biological studies, providing high chemical specificity without the necessity of labels and with little-to-no sample preparation. However, currently performed Raman-based studies of eukaryotic cells are still very laborious and time-consuming, resulting in a low number of sampled cells and questionable statistical validations. Furthermore, the approach requires a trained specialist to perform and analyze the experiments, rendering the method less attractive for most laboratories. In this work, we present a new high-content analysis Raman spectroscopy (HCA-RS) platform that overcomes the current challenges of conventional Raman spectroscopy implementations. HCA-RS allows sampling of a large number of cells under different physiological conditions without any user interaction. The performance of the approach is successfully demonstrated by the development of a Raman-based cell viability assay, i.e., the effect of doxorubicin concentration on monocytic THP-1 cells. A statistical model, principal component analysis combined with support vector machine (PCA-SVM), was found to successfully predict the percentage of viable cells in a mixed population and is in good agreement to results obtained by a standard cell viability assay. This study demonstrates the potential of Raman spectroscopy as a standard high-throughput tool for clinical and biological applications.