In this article, we report the use of randomly structured light illumination for chemical imaging of molecular distribution based on Raman microscopy with improved image resolution. Random structured basis images generated from temporal and spectral characteristics of the measured Raman signatures were superposed to perform structured illumination microscopy (SIM) with the blind-SIM algorithm. For experimental validation, Raman signatures corresponding to Rhodamine 6G (R6G) in the waveband of 730-760 nm and Raman shift in the range of 1096-1634 cm-1 were extracted and reconstructed to build images of R6G. The results confirm improved image resolution using the concept and hints at super-resolution by almost twice better than the diffraction-limit.
In this study, we investigated plasmonic field localization with trapezoidal nanopatterns under normal incident light excitation to find optimum structures for sensing and imaging. A finite element method was used to calculate the fundamental characteristics of the localized surface plasmon with varied trapezoidal nanopatterns. First, we describe how to localize the plasmonic fields on the trapezoidal patterns and then report our results from the investigation of the optimum properties of the nanopatterns for maximized field intensity. Initially, we expected that maximized field localization would lead to enhancement of the sensing sensitivity or imaging resolution in plasmon-based sensing and imaging systems. However, more interestingly, we found a field cancellation effect under specific modality conditions through the simulation. Thus, we thoroughly investigated the principle of the effect and extracted the modality conditions that induced field cancellation. In addition, specific modality conditions of nanopatterns that could be fabricated with conventional lithographic methods were numerically determined. Then, the field cancellation effect was experimentally verified using scanning nearfield optical microscopy. The results indicate that trapezoidal nanopatterns bring about enhanced field localization at the shaper edge of nanopatterns than do conventional rectangular nanopatterns and that plasmonic field cancellation can be observed under specific modality conditions of nanopatterns, even for conventional rectangular nanopatterns. Thus, it is suggested that careful fabrication and maintenance are needed to obtain strong plasmonic localization. Finally, the feasibility of providing a novel sensing platform using the field cancellation effect is suggested.
Lobarstin is a metabolite occurring from the Antarctic lichen Stereocaulon alpnum. Human glioblastoma is highly resistant to chemotherapy with temozolomide. Lobarstin was examined for its effect on glioblastoma.Temozolomide-resistant T98G cells were subjected to toxicity test with temozolomide and/or lobarstin. DNA damage and recovery was assessed by the alkaline comet assay and expression of DNA repair genes was examined by RT-PCR and western blot analysis.Lobarstin alone at 40 μM was toxic against T98G, but had no effect in primary human fibroblasts. Co-treatment of lobarstin with temozolomide yielded enhanced toxicity. Temozolomide-alone or with lobarstin co-treatment gave similar extent of DNA damage. However, the recovery was reduced in co-treated cells. Expression of DNA repair genes, O(6)-methylguanine-DNA methyltransferase, poly(ADP-ribose) polymerase 1 and ligase 3 were reduced in lobarstin-treated cells.Enhanced sensitivity to temozolomide by lobarstin co-treatment may be attributed to reduced DNA repair.
In this work, we explore the use of machine learning for constructing the leakage radiation characteristics of the bright-field images of nanoislands from surface plasmon polariton based on the plasmonic random nanosubstrate. The leakage radiation refers to a leaky wave of surface plasmon polariton (SPP) modes through a dielectric substrate which has drawn interest due to its possibility of direct visualization and analysis of SPP propagation. A fast-learning two-layer neural network has been deployed to learn and predict the relationship between the leakage radiation characteristics and the bright-field images of nanoislands utilizing a limited number of training samples. The proposed learning framework is expected to significantly simplify the process of leaky radiation image construction without the need of sophisticated equipment. Moreover, a wide range of application extensions can be anticipated for the proposed image-to-image prediction.
We demonstrated gold nanodimer arrays could improve the signal-to-noise ratio (SNR) of fluorescence correlation spectroscopy (FCS). In this research, we explore the feasibility of plasmon-enhanced FCS for biomolecular study using a nanodimer array whose gap size was 18 nm. Fluorescence nanobead with a diameter of 40 nm was first examined to verify if gold nanodimer arrays can enhance SNR of fluorescence and scattering intensities. We emphasize that plasmon-enhanced FCS can improve the precision for analyzing the dynamics of the particle by combining scattering characteristics of nanodimer arrays to surface plasmon resonance imaging technique. We have also observed the fluorescence enhancement and plasmon scattering in the movement of lysosome in HEK293 cells. It was found that we could measure diffusion properties such as diffusion coefficients and anomalous exponents with a low standard deviation.
We investigated super-localized measurement of molecular distribution at cell membrane with surface plasmon localization. The plasmonic nanostructures could improve the precision of optical measurement over diffraction-limited microscopy techniques.
This work describes extreme light localization for intracellular molecular imaging and sensing with a high signal-to-noise ratio and precision. We explore localization techniques by which achievable resolution may be customized for subcellular dynamics of molecular complexes. We have also conducted plasmon-enhanced fluorescence correlation spectroscopy of cellular organelles with improved precision. The approach was extended to switching-based light localization to circumvent the diffraction limit and to use random disordered composite metallic islands for improved structured light microscopy. Extreme light localization also proves useful for enhancing Raman microscopy. Localization-based super-resolved Raman microscopy and techniques in combination with structured illumination will be discussed.
We investigate label-free measurement of molecular distribution by super-resolved Raman microscopy using surface plasmon (SP) localization. Localized SP was formed with plasmonic nanopost arrays (PNAs) for measurement of the molecular distribution in HeLa cells. Compared with conventional Raman microscopy on gold thin films, PNAs induce a localized near-field, which allows for the enhancement of the peak signal-to-noise ratio by as much as 4.5 dB in the Raman shifts. Super-resolved distributions of aromatic amino acids and lipids (C-C stretching and C-H2 twist mode) as targets in HeLa cells were obtained after image reconstruction. Results show almost 4-fold improvement on average in the lateral precision over conventional diffraction-limited Raman microscopy images. Combined with axial imaging in an evanescent field, the results suggest an improvement in optical resolution due to superlocalized light volume by more than an order of magnitude over that of conventional diffraction-limited Raman microscopy.
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