We report development and characterization of cell-engineered nanovesicles made from mesenchymal stem cells (MSCNVs), which have more than 300 times higher productivity than natural extracellular vesicles (EVs). MSCNVs had similar morphological characteristics to MSCEVs but have molecular characteristics that more resemble MSCs than MSCEVs. In vitro MSCNV treatment increased the proliferation and migration of primary skin fibroblasts and showed better effects than treatment using natural MSCEVs. Quantitative real-time PCR analysis showed increased expression of growth factors in MSCNV-treated skin fibroblasts. Intraperitoneal injection of MSCNVs into syngeneic mice induced mild local inflammation, which resulted in recruitment of immune cells to the injection site. In vivo MSCNV treatment of a mouse skin wound accelerated its healing; this acceleration by MSCNVs may occur by promoting blood vessel formation at the wound site. These results indicate the promise of MSCNVs as agents for regenerative medicine.

Amphiphilic polyethyleneimine derivatives (amPEIs) were synthesized and used to encapsulate dozens of quantum dots (QDs). The QD-amPEI composite was ∼100 nm in hydrodynamic diameter and had the slightly positive outer surface that suited well for cellular internalization. The QD-amPEI showed very efficient QD cellular labeling with the labeled cell fluorescence intensity more than 10 times higher than conventional techniques such as Lipofectamine-assisted QD delivery. QD-amPEI was optimal for maximal intracellular QD delivery by the large QD payload and the rapid endocytosis kinetics. QD-amPEI platform technology was demonstrated for gene delivery, cell-specific labeling, and ratiometric oxygen sensing. Our QD-amPEI platform has two partitions: positive outer surface and hydrophobic inside pocket. The outer positive surface was further exploited for gene delivery and targeting. Co-delivery of QDs and GFP silencing RNAs was successfully demonstrated by assembling siRNAs to the outer surfaces, which showed the transfection efficiency an order of magnitude higher than conventional gene transfections. Hyaluronic acids were tethered onto the QD-amPEI for cell-specific targeted labeling which showed the specific-to-nonspecific signal ratio over 100. The inside hydrophobic compartment was further applied for cohosting oxygen sensing phosphorescence Ru dyes along with QDs. The QD-Ru-amPEI oxygen probe showed accurate and reversible oxygen sensing capability by the ratiometric photoluminescence signals, which was successfully applied to cellular and spheroid models.

Multiphoton microscopy (MPM) is a nonlinear fluorescence microscopic technique widely used for cellular imaging of thick tissues and live animals in biological studies. However, MPM application to human tissues is limited by weak endogenous fluorescence in tissue and cytotoxicity of exogenous probes. Herein, we describe the applications of moxifloxacin, an FDA-approved antibiotic, as a cell-labeling agent for MPM. Moxifloxacin has bright intrinsic multiphoton fluorescence, good tissue penetration and high intracellular concentration. MPM with moxifloxacin was demonstrated in various cell lines, and animal tissues of cornea, skin, small intestine and bladder. Clinical application is promising since imaging based on moxifloxacin labeling could be 10 times faster than imaging based on endogenous fluorescence.

Volumetric imaging by fluorescence microscopy is often limited by anisotropic spatial resolution, in which the axial resolution is inferior to the lateral resolution. To address this problem, we present a deep-learning-enabled unsupervised super-resolution technique that enhances anisotropic images in volumetric fluorescence microscopy. In contrast to the existing deep learning approaches that require matched high-resolution target images, our method greatly reduces the effort to be put into practice as the training of a network requires only a single 3D image stack, without a priori knowledge of the image formation process, registration of training data, or separate acquisition of target data. This is achieved based on the optimal transport-driven cycle-consistent generative adversarial network that learns from an unpaired matching between high-resolution 2D images in the lateral image plane and low-resolution 2D images in other planes. Using fluorescence confocal microscopy and light-sheet microscopy, we demonstrate that the trained network not only enhances axial resolution but also restores suppressed visual details between the imaging planes and removes imaging artifacts.

Abstract:Inflammation is a non-specific immune response to injury intended to protect biological tissue from harmful stimuli such as pathogens, irritants, and damaged cells. In vivo optical tissue imaging has been used to provide spatial and dynamic characteristics of inflammation within the tissue. In this paper, we report in vivo visualization of inflammation in the skin at both cellular and physiological levels by using a combination of label-free two-photon microscopy (TPM) and optical coherence tomography (OCT). Skin inflammation was induced by topically applying lipopolysaccharide (LPS) on the mouse ear. Temporal OCT imaging visualized tissue swelling, vasodilation, and increased capillary density 30 min and 1 hour after application. TPM imaging showed immune cell migration within the inflamed skin. Combined OCT and TPM was applied to obtain complementary information from each modality in the same region of interest. The information provided by each modality were consistent with previous reports about the characteristics of inflammation. Therefore, the combination of OCT and TPM holds potential for studying inflammation of the skin.