[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

This article reviews some of the recent advances in Raman spectroscopy, in areas related to natural tissues and cell biology. It summarizes some of the most widely used peak frequencies and their assignments. The aim of this study is to prepare a database of molecular fingerprints, which will help researchers in defining the chemical structure of the biological tissues introducing most of the important peaks present in the natural tissues. In spite of applying different methods, there seems to be a considerable similarity in defining the peaks of identical areas of the spectra. As a result, it is believed that preparing a unique collection of the frequencies encountered in Raman spectroscopic studies can lead to significant improvements both in the quantity and quality of spectral data and their outcomes. This article is the first review of its kind to provide a precise database on the most important Raman characteristic peak frequencies for researchers aiming to analyze natural tissues by Raman ...

Raman spectroscopy of biological tissues

Current medical imaging technologies allow visualization of tissue anatomy in the human body at resolutions ranging from 100 micrometers to 1 millimeter. These technologies are generally not sensitive enough to detect early-stage tissue abnormalities associated with diseases such as cancer and atherosclerosis, which require micrometer-scale resolution. Here, optical coherence tomography was adapted to allow high-speed visualization of tissue in a living animal with a catheter-endoscope 1 millimeter in diameter. This method, referred to as "optical biopsy," was used to obtain cross-sectional images of the rabbit gastrointestinal and respiratory tracts at 10-micrometer resolution.

In Vivo Endoscopic Optical Biopsy with Optical Coherence Tomography

Since 2000, there has been an explosion of activity in the field of plasmon-enhanced Raman spectroscopy (PERS), including surface-enhanced Raman spectroscopy (SERS), tip-enhanced Raman spectroscopy (TERS) and shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS). In this Review, we explore the mechanism of PERS and discuss PERS hotspots — nanoscale regions with a strongly enhanced local electromagnetic field — that allow trace-molecule detection, biomolecule analysis and surface characterization of various materials. In particular, we discuss a new generation of hotspots that are generated from hybrid structures combining PERS-active nanostructures and probe materials, which feature a strong local electromagnetic field on the surface of the probe material. Enhancement of surface Raman signals up to five orders of magnitude can be obtained from materials that are weakly SERS active or SERS inactive. We provide a detailed overview of future research directions in the field of PERS, focusing on new PERS-active nanomaterials and nanostructures and the broad application prospect for materials science and technology. Assisted by rationally designed novel plasmonic nanostructures, surface-enhanced Raman spectroscopy has presented a new generation of analytical tools (that is, tip-enhanced Raman spectroscopy and shell-isolated nanoparticle-enhanced Raman spectroscopy) with an extremely high surface sensitivity, spatial resolution and broad application for materials science and technology.

Nanostructure-based plasmon-enhanced Raman spectroscopy for surface analysis of materials

Raman spectroscopy can be used to measure the chemical composition of a sample, which can in turn be used to extract biological information. Many materials have characteristic Raman spectra, which means that Raman spectroscopy has proven to be an effective analytical approach in geology, semiconductor, materials and polymer science fields. The application of Raman spectroscopy and microscopy within biology is rapidly increasing because it can provide chemical and compositional information, but it does not typically suffer from interference from water molecules. Analysis does not conventionally require extensive sample preparation; biochemical and structural information can usually be obtained without labeling. In this protocol, we aim to standardize and bring together multiple experimental approaches from key leaders in the field for obtaining Raman spectra using a microspectrometer. As examples of the range of biological samples that can be analyzed, we provide instructions for acquiring Raman spectra, maps and images for fresh plant tissue, formalin-fixed and fresh frozen mammalian tissue, fixed cells and biofluids. We explore a robust approach for sample preparation, instrumentation, acquisition parameters and data processing. By using this approach, we expect that a typical Raman experiment can be performed by a nonspecialist user to generate high-quality data for biological materials analysis.

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Using Raman spectroscopy to characterize biological materials

Near infrared Raman spectra of human brain lipids.

Sample size planning for classification models.

Infrared (IR) and Raman spectroscopy are emerging biophotonic tools to recognize various diseases. The current review gives an overview of the experimental techniques, data-classification algorithms and applications to assess soft tissues, hard tissues and body fluids. The methodology section presents the principles to combine vibrational spectroscopy with microscopy, lateral information and fiber-optic probes. A crucial step is the classification of spectral data by a variety of algorithms. We discuss unsupervised algorithms such as cluster analysis or principal component analysis and supervised algorithms such as linear discriminant analysis, soft independent modeling of class analogies, artificial neural networks support vector machines, Bayesian classification, partial least-squares regression and ensemble methods. The selected topics include tumors of epithelial tissue, brain tumors, prion diseases, bone diseases, atherosclerosis, kidney stones and gallstones, skin tumors, diabetes and osteoarthritis.

Disease recognition by infrared and Raman spectroscopy.

Raman spectroscopy has been recognized to be a powerful tool to study cells and tissues because the method provides molecular information without external markers such as stains or radioactive labels. To overcome the disadvantage of low signal intensities from most biomolecules, enhancement effects are utilized. A non-linear variant of Raman spectroscopy called coherent anti-Stokes Raman spectroscopy (CARS) belongs to the most promising techniques because it combines signal enhancement due to the coherent nature of the process with further advantages such as directional emission, narrow spectral bandwidth and no disturbing interference with autofluorescence. This review describes briefly the principles of the methods and summarizes applications to cells and tissues that are expected to gain significance in the future such as the combination with imaging approaches, microscopy, optical traps and fiber-optic probes.

Raman and CARS microspectroscopy of cells and tissues.

Raman spectroscopy has been recognized to be a powerful tool for label-free discrimination of cells. Sampling methods are under development to utilize the unique capabilities to identify cells in body fluids such as saliva, urine or blood. The current study applied optical traps in combination with Raman spectroscopy to acquire spectra of single cells in microfluidic glass channels. Optical traps were realized by two 1070 nm single mode fibre lasers. Microflows were controlled by a syringe pump system. A novel microfluidic glass chip was designed to inject single cells, modify the flow speed, accommodate the laser fibres and sort cells after Raman based identification. Whereas the integrated microchip setup used 514 nm for excitation of Raman spectra, a quartz capillary setup excited spectra with 785 nm laser wavelength. Classification models were trained using linear discriminant analysis to differentiate erythrocytes, leukocytes, acute myeloid leukaemia cells (OCI-AML3), and breast tumour cells BT-20 and MCF-7 with accuracies that are comparable with previous Raman experiments of dried cells and fixed cells in a Petri dish. Implementation into microfluidic environments enables a high degree of automation that is required to improve the throughput of the approach for Raman activated cell sorting.

Christoph Krafft

Papers

Near infrared Raman spectra of human brain lipids.

Sample size planning for classification models.

Disease recognition by infrared and Raman spectroscopy.

Raman and CARS microspectroscopy of cells and tissues.

Tumour cell identification by means of Raman spectroscopy in combination with optical traps and microfluidic environments