@article{BechtSchollmayerMonakhovaetal.2021, author = {Becht, Alexander and Schollmayer, Curd and Monakhova, Yulia and Holzgrabe, Ulrike}, title = {Tracing the origin of paracetamol tablets by near-infrared, mid-infrared, and nuclear magnetic resonance spectroscopy using principal component analysis and linear discriminant analysis}, series = {Analytical and Bioanalytical Chemistry}, volume = {413}, journal = {Analytical and Bioanalytical Chemistry}, number = {11}, doi = {10.1007/s00216-021-03249-z}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-265400}, pages = {3107-3118}, year = {2021}, abstract = {Most drugs are no longer produced in their own countries by the pharmaceutical companies, but by contract manufacturers or at manufacturing sites in countries that can produce more cheaply. This not only makes it difficult to trace them back but also leaves room for criminal organizations to fake them unnoticed. For these reasons, it is becoming increasingly difficult to determine the exact origin of drugs. The goal of this work was to investigate how exactly this is possible by using different spectroscopic methods like nuclear magnetic resonance and near- and mid-infrared spectroscopy in combination with multivariate data analysis. As an example, 56 out of 64 different paracetamol preparations, collected from 19 countries around the world, were chosen to investigate whether it is possible to determine the pharmaceutical company, manufacturing site, or country of origin. By means of suitable pre-processing of the spectra and the different information contained in each method, principal component analysis was able to evaluate manufacturing relationships between individual companies and to differentiate between production sites or formulations. Linear discriminant analysis showed different results depending on the spectral method and purpose. For all spectroscopic methods, it was found that the classification of the preparations to their manufacturer achieves better results than the classification to their pharmaceutical company. The best results were obtained with nuclear magnetic resonance and near-infrared data, with 94.6\%/99.6\% and 98.7/100\% of the spectra of the preparations correctly assigned to their pharmaceutical company or manufacturer.}, language = {en} } @article{StefanakisBasslerWalczuchetal.2023, author = {Stefanakis, Mona and Bassler, Miriam C. and Walczuch, Tobias R. and Gerhard-Hartmann, Elena and Youssef, Almoatazbellah and Scherzad, Agmal and St{\"o}th, Manuel Bernd and Ostertag, Edwin and Hagen, Rudolf and Steinke, Maria R. and Hackenberg, Stephan and Brecht, Marc and Meyer, Till Jasper}, title = {The impact of tissue preparation on salivary gland tumors investigated by Fourier-transform infrared microspectroscopy}, series = {Journal of Clinical Medicine}, volume = {12}, journal = {Journal of Clinical Medicine}, number = {2}, issn = {2077-0383}, doi = {10.3390/jcm12020569}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-304887}, year = {2023}, abstract = {Due to the wide variety of benign and malignant salivary gland tumors, classification and malignant behavior determination based on histomorphological criteria can be difficult and sometimes impossible. Spectroscopical procedures can acquire molecular biological information without destroying the tissue within the measurement processes. Since several tissue preparation procedures exist, our study investigated the impact of these preparations on the chemical composition of healthy and tumorous salivary gland tissue by Fourier-transform infrared (FTIR) microspectroscopy. Sequential tissue cross-sections were prepared from native, formalin-fixed and formalin-fixed paraffin-embedded (FFPE) tissue and analyzed. The FFPE cross-sections were dewaxed and remeasured. By using principal component analysis (PCA) combined with a discriminant analysis (DA), robust models for the distinction of sample preparations were built individually for each parotid tissue type. As a result, the PCA-DA model evaluation showed a high similarity between native and formalin-fixed tissues based on their chemical composition. Thus, formalin-fixed tissues are highly representative of the native samples and facilitate a transfer from scientific laboratory analysis into the clinical routine due to their robust nature. Furthermore, the dewaxing of the cross-sections entails the loss of molecular information. Our study successfully demonstrated how FTIR microspectroscopy can be used as a powerful tool within existing clinical workflows.}, language = {en} } @article{StrubeBlossBrownSpaetheetal.2015, author = {Strube-Bloss, Martin F. and Brown, Austin and Spaethe, Johannes and Schmitt, Thomas and R{\"o}ssler, Wolfgang}, title = {Extracting the Behaviorally Relevant Stimulus: Unique Neural Representation of Farnesol, a Component of the Recruitment Pheromone of Bombus terrestris}, series = {PLoS One}, volume = {10}, journal = {PLoS One}, number = {9}, doi = {10.1371/journal.pone.0137413}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-125875}, pages = {e0137413}, year = {2015}, abstract = {To trigger innate behavior, sensory neural networks are pre-tuned to extract biologically relevant stimuli. Many male-female or insect-plant interactions depend on this phenomenon. Especially communication among individuals within social groups depends on innate behaviors. One example is the efficient recruitment of nest mates by successful bumblebee foragers. Returning foragers release a recruitment pheromone in the nest while they perform a 'dance' behavior to activate unemployed nest mates. A major component of this pheromone is the sesquiterpenoid farnesol. How farnesol is processed and perceived by the olfactory system, has not yet been identified. It is much likely that processing farnesol involves an innate mechanism for the extraction of relevant information to trigger a fast and reliable behavioral response. To test this hypothesis, we used population response analyses of 100 antennal lobe (AL) neurons recorded in alive bumblebee workers under repeated stimulation with four behaviorally different, but chemically related odorants (geraniol, citronellol, citronellal and farnesol). The analysis identified a unique neural representation of the recruitment pheromone component compared to the other odorants that are predominantly emitted by flowers. The farnesol induced population activity in the AL allowed a reliable separation of farnesol from all other chemically related odor stimuli we tested. We conclude that the farnesol induced population activity may reflect a predetermined representation within the AL-neural network allowing efficient and fast extraction of a behaviorally relevant stimulus. Furthermore, the results show that population response analyses of multiple single AL-units may provide a powerful tool to identify distinct representations of behaviorally relevant odors.}, language = {en} } @article{BasslerKnoblichGerhardHartmannetal.2023, author = {Bassler, Miriam C. and Knoblich, Mona and Gerhard-Hartmann, Elena and Mukherjee, Ashutosh and Youssef, Almoatazbellah and Hagen, Rudolf and Haug, Lukas and Goncalves, Miguel and Scherzad, Agmal and St{\"o}th, Manuel and Ostertag, Edwin and Steinke, Maria and Brecht, Marc and Hackenberg, Stephan and Meyer, Till Jasper}, title = {Differentiation of salivary gland and salivary gland tumor tissue via Raman imaging combined with multivariate data analysis}, series = {Diagnostics}, volume = {14}, journal = {Diagnostics}, number = {1}, issn = {2075-4418}, doi = {10.3390/diagnostics14010092}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-355558}, year = {2023}, abstract = {Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90\% and validated by predicting model-unknown Raman spectra, of which 93\% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.}, language = {en} }