Yong Guo

Fluorescence lifetime imaging (FLIM) has established itself as a pivotal tool for investigating biological processes within living cells. However, the extensive imaging duration necessary to accumulate sufficient photons for accurate fluorescence lifetime calculations poses a significant obstacle to achieving high-resolution monitoring of cellular dynamics. In this study, we introduce an image reconstruction method based on the edge-preserving interpolation method (EPIM), which transforms rapidly acquired low-resolution FLIM data into high-pixel images, thereby eliminating the need for extended acquisition times. Specifically, we decouple the grayscale image and the fluorescence lifetime matrix and perform an individual interpolation on each. Following the interpolation of the intensity image, we apply wavelet transformation and adjust the wavelet coefficients according to the image gradients. After the inverse transformation, the original image is obtained and subjected to noise reduction to complete the image reconstruction process. Subsequently, each pixel is pseudo-color-coded based on its intensity and lifetime, preserving both structural and temporal information. We evaluated the performance of the bicubic interpolation method and our image reconstruction approach on fluorescence microspheres and fixed-cell samples, demonstrating their effectiveness in enhancing the quality of lifetime images. By applying these techniques to live-cell imaging, we can successfully obtain high-pixel FLIM images at shortened intervals, facilitating the capture of rapid cellular events.

Volumetric imaging of a mouse brain in vivo with one-photon and two-photon ultralong anti-diffracting (UAD) beam illumination was performed. The three-dimensional (3D) structure of blood vessels in the mouse brain were mapped to a two-dimensional (2D) image. The speed of volumetric imaging was significantly improved due to the long focal length of the UAD beam. Comparing one-photon and two-photon UAD beam volumetric imaging, we found that the imaging depth of two-photon volumetric imaging (80 μm) is better than that of one-photon volumetric imaging (60 μm), and the signal-to-background ratio (SBR) of two-photon volumetric imaging is two times that of one-photon volumetric imaging. Therefore, we used two-photon UAD volumetric imaging to perform dynamic volumetric imaging of mouse brain blood vessels in vivo, and obtained the blood flow velocity.

Two-photon probes with broad absorption spectra are beneficial for multi-color two-photon microscopy imaging, which is one of the most powerful tools to study the dynamic processes of living cells. To achieve multi-color two-photon imaging, multiple lasers and detectors are usually required for excitation and signal collection, respectively. However, one makes the imaging system more complicated and costly. Here, we demonstrate a multi-color two-photon imaging method with a single-wavelength excitation by using a signal separation strategy. The method can effectively solve the problem of spectral crosstalk by selecting a suitable filter combination and applying image subtraction. The experimental results show that the two-color and three-color two-photon imaging are achieved with a single femtosecond laser. Furthermore, this method can also be combined with multi-photon imaging technology to reveal more information and interaction in thick biological tissues.

Although conventional fluorescence intensity imaging can be used to qualitatively study the drug toxicity of nanodrug carrier systems at the single-cell level, it has limitations for studying nanodrug transport across membranes. Fluorescence correlation spectroscopy (FCS) can provide quantitative information on nanodrug concentration and diffusion in a small area of the cell membrane; thus, it is an ideal tool for studying drug transport across the membrane. In this paper, the FCS method was used to measure the diffusion coefficients and concentrations of carbon dots (CDs), doxorubicin (DOX) and CDs-DOX composites in living cells (COS7 and U₂OS) for the first time. The drug concentration and diffusion coefficient in living cells determined by FCS measurements indicated that the CDs-DOX composite distinctively improved the transmembrane efficiency and rate of drug molecules, in accordance with the conclusions drawn from the fluorescence imaging results. Furthermore, the effects of pH values and ATP concentrations on drug transport across the membrane were also studied. Compared with free DOX under acidic conditions, the CDs-DOX complex has higher cellular uptake and better transmembrane efficacy in U₂OS cells. Additionally, high concentrations of ATP will cause negative changes in cell membrane permeability, which will hinder the transmembrane transport of CDs and DOX and delay the rapid diffusion of CDs-DOX. The results of this study show that the FCS method can be utilized as a powerful tool for studying the expansion and transport of nanodrugs in living cells, and might provide a new drug exploitation strategy for cancer treatment in vivo.

Stimulated emission depletion (STED) microscopy is a typical laser-scanning super-resolution imaging technology, the emergence of which has opened a new research window for studying the dynamic processes of live biological samples on a nanometer scale. According to the characteristics of STED, a high depletion power is required to obtain a high resolution. However, a high laser power can induce severe phototoxicity and photobleaching, which limits the applications for live cell imaging, especially in two-color STED super-resolution imaging. Therefore, we developed a low-power two-color STED super-resolution microscope with a single supercontinuum white-light laser. Using this system, we achieved low-power two-color super-resolution imaging based on digital enhancement technology. Lateral resolutions of 109 and 78 nm were obtained for mitochondria and microtubules in live cells, respectively, with 0.8 mW depletion power. These results highlight the great potential of the novel digitally enhanced two-color STED microscopy for long-term dynamic imaging of live cells.

The existence of aberrations has always been an important limiting factor in the imaging field. Especially in optical microscopy imaging, the accumulated aberration of the optical system and the biological samples distorts the wavefront on the focal plane, thereby reducing the imaging resolution. Here, we propose an adaptive optical aberration correction method based on convolutional neural network. By establishing the relationship between the Zernike polynomial and the distorted wavefront, with the help of the fast calculation advantage of an artificial intelligence neural network, the distorted wavefront information can be output in a short time for the reconstruction of the wavefront to achieve the purpose of improving imaging resolution. Experimental results show that this method can effectively compensate the aberrations introduced by the system, agarose and HeLa cells. After correcting, the point spread function restored the doughnut-shape, and the resolution of the HeLa cell image increased about 20%.