@article{VottelerCarvajalBerrioPudlasetal.2012,
  author    = {Votteler, Miriam and Carvajal Berrio, Daniel A. and Pudlas, Marieke and Walles, Heike and Schenke-Layland, Katja},
  title     = {Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy},
  series = {Journal of Visual Expression},
  volume    = {63},
  journal   = {Journal of Visual Expression},
  number    = {e3977},
  doi       = {10.3791/3977},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-124569},
  year      = {2012},
  abstract  = {Non-destructive, non-contact and label-free technologies to monitor cell and tissue cultures are needed in the field of biomedical research.1-5 However, currently available routine methods require processing steps and alter sample integrity. Raman spectroscopy is a fast method that enables the measurement of biological samples without the need for further processing steps. This laser-based technology detects the inelastic scattering of monochromatic light.6 As every chemical vibration is assigned to a specific Raman band (wavenumber in cm-1), each biological sample features a typical spectral pattern due to their inherent biochemical composition.7-9 Within Raman spectra, the peak intensities correlate with the amount of the present molecular bonds.1 Similarities and differences of the spectral data sets can be detected by employing a multivariate analysis (e.g. principal component analysis (PCA)).10 Here, we perform Raman spectroscopy of living cells and native tissues. Cells are either seeded on glass bottom dishes or kept in suspension under normal cell culture conditions (37 °C, 5\% CO2) before measurement. Native tissues are dissected and stored in phosphate buffered saline (PBS) at 4 °C prior measurements. Depending on our experimental set up, we then either focused on the cell nucleus or extracellular matrix (ECM) proteins such as elastin and collagen. For all studies, a minimum of 30 cells or 30 random points of interest within the ECM are measured. Data processing steps included background subtraction and normalization.},
  language  = {en}
}
@article{MeyerGerhardHartmannLodesetal.2021,
  author    = {Meyer, Till Jasper and Gerhard-Hartmann, Elena and Lodes, Nina and Scherzad, Agmal and Hagen, Rudolf and Steinke, Maria and Hackenberg, Stephan},
  title     = {Pilot study on the value of Raman spectroscopy in the entity assignment of salivary gland tumors},
  series = {PLoS One},
  volume    = {16},
  journal   = {PLoS One},
  number    = {9},
  doi       = {10.1371/journal.pone.0257470},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-264736},
  year      = {2021},
  abstract  = {Background The entity assignment of salivary gland tumors (SGT) based on histomorphology can be challenging. Raman spectroscopy has been applied to analyze differences in the molecular composition of tissues. The aim of this study was to evaluate the suitability of RS for entity assignment in SGT. Methods Raman data were collected in deparaffinized sections of pleomorphic adenomas (PA) and adenoid cystic carcinomas (ACC). Multivariate data and chemometric analysis were completed using the Unscrambler software. Results The Raman spectra detected in ACC samples were mostly assigned to nucleic acids, lipids, and amides. In a principal component-based linear discriminant analysis (LDA) 18 of 20 tumor samples were classified correctly. Conclusion In this proof of concept study, we show that a reliable SGT diagnosis based on LDA algorithm appears possible, despite variations in the entity-specific mean spectra. However, a standardized workflow for tissue sample preparation, measurement setup, and chemometric algorithms is essential to get reliable results.},
  language  = {en}
}