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search.filters.applied.f.access: openAccess × Author: Popp, J. × End date: 2019 × Start date: 2010 × Type: Text × Publisher: Basel : MDPI AG × WGL Institute: IPHT ×

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    Raman imaging with a fiber-coupled multichannel spectrograph
    (Basel : MDPI AG, 2014) Schmälzlin, E.; Moralejo, B.; Rutowska, M.; Monreal-Ibero, A.; Sandin, C.; Tarcea, N.; Popp, J.; Roth, M.M.
    Until now, spatially resolved Raman Spectroscopy has required to scan a sample under investigation in a time-consuming step-by-step procedure. Here, we present a technique that allows the capture of an entire Raman image with only one single exposure. The Raman scattering arising from the sample was collected with a fiber-coupled high-performance astronomy spectrograph. The probe head consisting of an array of 20 × 20 multimode fibers was linked to the camera port of a microscope. To demonstrate the high potential of this new concept, Raman images of reference samples were recorded. Entire chemical maps were received without the need for a scanning procedure.
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    Raman-spectroscopy based cell identification on a microhole array chip
    (Basel : MDPI AG, 2014) Neugebauer, U.; Kurz, C.; Bocklitz, T.; Berger, T.; Velten, T.; Clement, J.H.; Krafft, C.; Popp, J.
    Circulating tumor cells (CTCs) from blood of cancer patients are valuable prognostic markers and enable monitoring responses to therapy. The extremely low number of CTCs makes their isolation and characterization a major technological challenge. For label-free cell identification a novel combination of Raman spectroscopy with a microhole array platform is described that is expected to support high-throughput and multiplex analyses. Raman spectra were registered from regularly arranged cells on the chip with low background noise from the silicon nitride chip membrane. A classification model was trained to distinguish leukocytes from myeloblasts (OCI-AML3) and breast cancer cells (MCF-7 and BT-20). The model was validated by Raman spectra of a mixed cell population. The high spectral quality, low destructivity and high classification accuracy suggests that this approach is promising for Raman activated cell sorting.