Low-Background Tip-Enhanced Raman Spectroscopy Enabled by a Plasmon Thin-Film Waveguide Probe.

Tip-enhanced Raman spectroscopy (TERS) is a nano-optical approach to extract spatially resolved chemical information with nanometer precision. However, in the case of direct-illumination TERS, which is often employed in commercial TERS instruments, strong fluorescence or far-field Raman signals from the illuminated areas may be excited as a background. They may overwhelm the near-field TERS signal and dramatically decrease the near-field to far-field signal contrast of TERS spectra. It is still challenging for TERS to study the surface of fluorescent materials or a bulk sample that cannot be placed on an Au/Ag substrate. In this study, we developed an indirect-illumination TERS probe that allows a laser to be focused on a flat interface of a thin-film waveguide located far away from the region generating the TERS signal. Surface plasmon polaritons are generated stably on the waveguide and eventually accumulated at the tip apex, thereby producing a spatially and energetically confined hotspot to ensure stable and high-resolution TERS measurements with a low background. With this thin-film waveguide probe, TERS spectra with obvious contrast from a diamond plate can be acquired. Furthermore, the TERS technique based on this probe exhibits excellent TERS signal stability, a long lifetime, and good spatial resolution. This technique is expected to have commercial potential and enable further popularization and development of TERS technology as a powerful analytical method.

Transfer learning and wavelength selection method in NIR spectroscopy to predict glucose and lactate concentrations in culture media using VIP-Boruta.

Regression models are constructed to predict glucose and lactate concentrations from near-infrared spectra in culture media. The partial least-squares (PLS) regression technique is employed, and we investigate the improvement in the predictive ability of PLS models that can be achieved using wavelength selection and transfer learning. We combine Boruta, a nonlinear variable selection method based on random forests, with variable importance in projection (VIP) in PLS to produce the proposed variable selection method, VIP-Boruta. Furthermore, focusing on the situation where both culture medium samples and pseudo-culture medium samples can be used, we transfer pseudo media to culture media. Data analysis with an actual dataset of culture media and pseudo media confirms that VIP-Boruta can effectively select appropriate wavelengths and improves the prediction ability of PLS models, and that transfer learning with pseudo media enhances the predictive ability. The proposed method could reduce the prediction errors by about 61% for glucose and about 16% for lactate, compared to the traditional PLS model.

Glucose Monitoring in Cell Culture with Online Ultrasound-Assisted Near-Infrared Spectroscopy.

Near-infrared (NIR) spectroscopic analysis for suspensions often requires a pretreatment by dilution or filtering of suspended solids to maintain the sensitivity of the measurements. An online ultrasound-assisted spectroscopy (UAS) unit enabling pretreatment-free and noncontact analysis for bioprocessing is proposed and evaluated with a model suspension containing 3-µm-diameter polystyrene latex particles (PSLs) with the density of 5.1 × 108 counts/ml and Chinese hamster ovary (CHO) cell culture whose cell density was 3.2 × 107 cells/ml. The online UAS uses acoustic radiation force generated by ultrasonic standing waves. Suspended matter such as the PSLs and CHO cells can be localized at nodal planes in the suspensions by the acoustic radiation force. Hence, in the case of the online UAS, incoming light can pass through the suspensions more easily than that in the case of a conventional spectroscopy. Its effectiveness was evaluated by the predictive capability of a calibration model for glucose concentrations in the model suspensions and the CHO cell cultures. The calibration models were constructed by use of a partial least-squares regression (PLS-R) in the range of 4900-4200 cm-1 region after the pretreatment of second-order Savitzky-Golay filter. The calibration model built from the NIR spectra acquired with the online UAS could predict the glucose concentration in the CHO cell cultures with a measurement error of 0.6%. It was validated that the glucose concentrations in the flowing model suspension were able to be monitored by the online UAS with a measurement error of 8%. The newly developed online UAS for cell culture monitoring allows us to promote a wider use of NIR spectroscopy. For example, in the applications to the biopharmaceutical and cell-therapy industries, the online UAS enables simpler and easier monitoring of cell cultures because cleaning and sterilization of monitoring tools after cell culturing can be eliminated.