東京大学 · 生化学・遺伝学・分子生物学
Jingwen Shou教授の研究室は、超分解能・多色同時イメージングを実現する新規光機能材料と光学技術の開発を柱としています。特に、刺激的ラマン散乱(SRS)を用いた高速・高感度なマルチモードイメージング技術や、光スイッチング可能なバイオプローブの開発により、生きた細胞内での分子動態を高時空間分解能で可視化することを目指しています。また、偏光制御を不要とする高速二重偏光SRS顕微鏡技術の開発により、分子配向や対称性の詳細な解析を可能にしています。
Figures are computed from collected data and may differ slightly.
Observing multiple molecular species simultaneously with high spatiotemporal resolution is crucial for comprehensive understanding of complex, dynamic, and heterogeneous biological systems. The recently reported super-multiplex optical imaging breaks the "color barrier" of fluorescence to achieve multiplexing number over six in living systems, while its temporal resolution is limited to several minutes mainly by slow color tuning. Herein, we report integrated stimulated Raman and fluorescence mi
Super-resolution vibrational microscopy is promising to increase the degree of multiplexing of nanometer-scale biological imaging because of the narrower spectral linewidth of molecular vibration compared to fluorescence. However, current techniques of super-resolution vibrational microscopy suffer from various limitations including the need for cell fixation, high power loading, or complicated detection schemes. Here, we present reversible saturable optical Raman transitions (RESORT) microscopy
Photoswitchable fluorescence is a powerful technique to realize super-resolution imaging, highlighting, and optical storage, while its multiplexing capability is limited. Raman scattering is attracting attention because it generates narrowband vibrational signatures, which are potentially useful for highly multiplexed detection of different constituents. Here, we demonstrate photoswitchable stimulated Raman scattering (SRS) spectroscopy and microscopy where narrowband vibrational signatures are
Polarized Raman spectroscopy and microscopy are known to enable the investigation of symmetry and orientation of molecular vibrational modes and to give additional spectroscopic signature. However, conventional Raman spectroscopy always requires prolonged exposure to ensure the satisfying signal-to-noise ratio, which impedes fast imaging. Here, we demonstrate dual-polarization hyperspectral stimulated Raman scattering microscopy with simultaneous accessibility of two polarized Raman images in or
Low-loss and broadband optics is important in optical measurement and imaging. Here, we design an axicon-based beam shaper for low-loss and broadband microscopic optics by numerically calculating the transmittance and focusing performance, assuming an application to stimulated Raman scattering (SRS) microscopy. Furthermore, we demonstrate the beam shaper equipped in an SRS microscope and confirm that the axicon-based optics increases transmittance without sacrificing spatial resolution or signal
Polarization-resolved stimulated Raman scattering spectroscopies and microscopies have been utilized to investigate the symmetry and orientation of molecular vibrational modes and to provide extra spectral signatures, while the polarization modulation introduced additional complexity and the successive measurement on different polarization states limits the imaging speed. Here we demonstrate dual-polarization hyperspectral stimulated Raman scattering microscopy which enables detailed imaging mea
We demonstrate a multispectral and multimodal microscopy which enables high-speed stimulated Raman and fluorescence imaging. Both the Raman wavenumber and the fluorescence detection wavelength of each frame can be tuned via high-speed galvanometer-driven optical filters.
Super-resolution vibrational microscopy is a promising tool to increase the degree of multiplexing of nanometer-scale biological imaging, because the spectral linewidth of molecular vibration is about 50 times narrower than that of fluorescence. However, current techniques of super-resolution vibrational microscopy still suffer from various limitations including the need for cell fixation, high power loading or complicated frequency-modulated detection schemes. Herein we utilize photoswitchable
Among various optical methods, fluorescence imaging has been the most widely exploited thanks to its superior sensitivity and specificity, but the resolvable colors are restricted to 2-5 colors because of the intrinsically broad and featureless spectra. Recently, this fluorescent “color barrier” was broken and super-multiplex optical imaging became possible taking advantage of well-designed Raman probes. However, the acquisition of the super-multiplex images is still relatively slow which impede
Here's a dataset for 'Super-resolution vibrational imaging based on photoswitchable Raman probe.'
Simultaneous localization of multiple cellular components related to the cellular activities, e.g. metabolism of small molecules, is not well understood due to the intrinsic limitations of fluorescence imaging technologies. The broad fluorescence emission often limits the available color number to ~4. Additionally, staining of small metabolic precursors is still difficult using fluorophores because the relatively large size of fluorophores will affect the regular metabolism of small molecules. H
Here's a dataset for 'Super-resolution vibrational imaging based on photoswitchable Raman probe.'
Here's a dataset for 'Super-resolution vibrational imaging based on photoswitchable Raman probe.'
In this paper,the exact penalty function theory of nonsmooth programming with both e-quality and inequality constraints(?)is discussed.The main results are the following:Suppose X is a compact set,the number of global optimal solution sets of the originalproblem is finite.Under appropriate restrictions,the global exact penalty function exists.Especially,a 1-1 correspondence between the solutions of the original problem and its exactpenalty function problem is set up.Two evaluation theorems for p
We present a fiber optical parametric oscillator incorporating wavelength-tunable pump pulses and an intracavity optical filter. A wide tuning range of 90 nm is achieved while keeping the repetition rate constant.
Open papers in the app to read, cite, and organize with AI.