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Surface-enhanced Raman scattering (SERS) has been extensively applied to detect complex analytes due to its ability to enhance the fingerprint signals of molecules around nanostructured metallic surfaces. Thus, it is essential to design SERS-active nanostructures with abundant electromagnetic hotspots in a probed volume according to the dimensions of the analytes, as the analytes must be located in their hotspots for maximum signal enhancement. Herein, we demonstrate a simple method for detecting robust SERS signals from multi-scaled bioanalytes, regardless of their dimensions in the liquid state, through a photothermally driven co-assembly with colloidal plasmonic nanoparticles as signal enhancers. Under resonant light illumination, plasmonic nanoparticles and analytes in the solution quickly assemble at the focused surface area by convective movements induced by the photothermal heating of the plasmonic nanoparticles without any surface modification. Such collective assemblies of plasmonic nanoparticles and analytes were optimized by varying the optical density and surface charge of the nanoparticles, the viscosity of the solvent, and the light illumination time to maximize the SERS signals. Using these light-induced co-assemblies, the intrinsic SERS signals of small biomolecules can be detected down to nanomolar concentrations based on their fingerprint spectra. Furthermore, large-sized biomarkers, such as viruses and exosomes, were successfully detected without labels, and the complexity of the collected spectra was statistically analyzed using t-distributed stochastic neighbor embedding combined with support vector machine (t-SNE + SVM). The proposed method is expected to provide a robust and convenient method to sensitively detect biologically and environmentally relevant analytes at multiple scales in liquid samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Stem cell-based therapies have recently emerged to treat various incurable diseases and disorders. Types of stem cell-derived cells and their functions should be intensively analyzed before therapy. However, current pre-treatment steps for biological analysis are mostly destructive. Here, we report a novel optical method that enables ultra-fast and label-free characterization of cells, eliminating invasive, destructive steps. The technique, referred to as "autofluorescence-Raman mapping integration (ARMI)" analysis uses cell autofluorescence (AF) to reveal cellular morphology and cytosolic microstructures, while Raman mapping allows site-specific intensive analysis of target molecules, which enables ultra-fast identification of cell types. We used human mesenchymal stem cells (MSCs) as a model and induced adipogenesis. Lipid droplets in cells appeared as "blanks" in three-dimensional AF images and site-specific Raman mapping guided by AF identified the structure and components of the CH 2 stretch. Adipogenesis could be rapidly and precisely analyzed, not only for the same batch but also for different batches. Therefore, the developed tool is highly useful for the accurate screening of stem cell differentiation and implementation in biomedical and clinical applications., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Terahertz (THz) imaging technology has shown significant potential for use in biomedical imaging owing to its non-ionizing characteristics by its low photon energy and its ultrabroadband spectral comparability with many molecular vibrational resonances. However, despite the significant advantage of being able to identify bio-materials in label-free configurations, most meaningful signals are buried by huge water absorption, thus it is very difficult to distinguish them using the small differences in optical constants at THz regime, limiting the practical application of this technology. Here, we demonstrate advanced THz imaging with enhanced color contrast by the use of THz field that is localized and enhanced by a nanometer-scale slot array. THz images of a biological specimen, such as mouse brain tissue and fingerprint, on a nano-slot array-based metamaterial sensing chip, which is elaborately fabricated in large-area, show a higher contrast and clearer boundary information in reflectance without any labeling. A reliable numerical solution to find accurate optical constants using THz nano-slot resonance for the quantitative analysis of target bio-specimens is also introduced. Finally, the precise optical properties of real bio-samples and atlas information are provided for specific areas where amyloid beta proteins, known to cause dementia, have accumulated in a mouse brain., (Copyright © 2020 Elsevier B.V. All rights reserved.)

A label-free, non-dispruptive, and real-time analytical device to monitor the dynamic features of biomolecules and their interactions with neighboring molecules is an essential prerequisite for biochip- and diagonostic assays. To explore one of the central questions on the lipid-lipid interactions in the course of the liquid-ordered (l o ) domain formation, called rafts, we developed a method of reconstituting continuous but spatially heterogeneous lipid membrane platforms with molayer-bilayer juntions (MBJs) that enable to form the l o domains in a spatiotemporally controlled manner. This allows us to detect the time-lapse dynamics of the lipid-lipid interactions during raft formation and resultant membrane phase changes together with the raft-associated receptor-ligand binding through the surface plasmon resonance (SPR). For cross-validation, using epifluorescence microscopy, we demonstrated the underlying mechanisms for raft formations that the infiltration of cholesterols into the sphingolipid-enriched domains plays a crucial roles in the membrane phase-separation. Our membrane platform, being capable of monitoring dynamic interactions among lipids and performing the systematic optical analysis, will unveil physiological roles of cholesterols in a variety of biological events., (Copyright © 2019 Elsevier B.V. All rights reserved.)