Label-free metabolic optical biomarkers track stem cell fate transition in real time.

Tracking stem cell fate transition is crucial for understanding their development and optimizing biomanufacturing. Destructive single-cell methods provide a pseudotemporal landscape of stem cell differentiation but cannot monitor stem cell fate in real time. We established a metabolic optical metric using label-free fluorescence lifetime imaging microscopy (FLIM), feature extraction and machine learning-assisted analysis, for real-time cell fate tracking. From a library of 205 metabolic optical biomarker (MOB) features, we identified 56 associated with hematopoietic stem cell (HSC) differentiation. These features collectively describe HSC fate transition and detect its bifurcate lineage choice. We further derived a MOB score measuring the "metabolic stemness" of single cells and distinguishing their division patterns. This score reveals a distinct role of asymmetric division in rescuing stem cells with compromised metabolic stemness and a unique mechanism of PI3K inhibition in promoting ex vivo HSC maintenance. MOB profiling is a powerful tool for tracking stem cell fate transition and improving their biomanufacturing from a single-cell perspective.

Optical and MRI Multimodal Tracing of Stem Cells In Vivo.

Stem cell therapy has shown great clinical potential in oncology, injury, inflammation, and cardiovascular disease. However, due to the technical limitations of the in vivo visualization of transplanted stem cells, the therapeutic mechanisms and biosafety of stem cells in vivo are poorly defined, which limits the speed of clinical translation. The commonly used methods for the in vivo tracing of stem cells currently include optical imaging, magnetic resonance imaging (MRI), and nuclear medicine imaging. However, nuclear medicine imaging involves radioactive materials, MRI has low resolution at the cellular level, and optical imaging has poor tissue penetration in vivo. It is difficult for a single imaging method to simultaneously achieve the high penetration, high resolution, and noninvasiveness needed for in vivo imaging. However, multimodal imaging combines the advantages of different imaging modalities to determine the fate of stem cells in vivo in a multidimensional way. This review provides an overview of various multimodal imaging technologies and labeling methods commonly used for tracing stem cells, including optical imaging, MRI, and the combination of the two, while explaining the principles involved, comparing the advantages and disadvantages of different combination schemes, and discussing the challenges and prospects of human stem cell tracking techniques.

Automated tracking of cell migration in phase contrast images with CellTraxx.

The ability of cells to move and migrate is required during development, but also in the adult in processes such as wound healing and immune responses. In addition, cancer cells exploit the cells' ability to migrate and invade to spread into nearby tissue and eventually metastasize. The majority of cancer deaths are caused by metastasis and the process of cell migration is therefore intensively studied. A common way to study cell migration is to observe cells through an optical microscope and record their movements over time. However, segmenting and tracking moving cells in phase contrast time-lapse video sequences is a challenging task. Several tools to track the velocity of migrating cells have been developed. Unfortunately, most of the automated tools are made for fluorescence images even though unlabelled cells are often preferred to avoid phototoxicity. Consequently, researchers are constrained with laborious manual tracking tools using ImageJ or similar software. We have therefore developed a freely available, user-friendly, automated tracking tool called CellTraxx. This software makes it easy to measure the velocity and directness of migrating cells in phase contrast images. Here, we demonstrate that our tool efficiently recognizes and tracks unlabelled cells of different morphologies and sizes (HeLa, RPE1, MDA-MB-231, HT1080, U2OS, PC-3) in several types of cell migration assays (random migration, wound healing and cells embedded in collagen). We also provide a detailed protocol and download instructions for CellTraxx.

Instant processing of large-scale image data with FACT, a real-time cell segmentation and tracking algorithm.

Quantifying cellular characteristics from a large heterogeneous population is essential to identify rare, disease-driving cells. A recent development in the combination of high-throughput screening microscopy with single-cell profiling provides an unprecedented opportunity to decipher disease-driving phenotypes. Accurately and instantly processing large amounts of image data, however, remains a technical challenge when an analysis output is required minutes after data acquisition. Here, we present fast and accurate real-time cell tracking (FACT). FACT can segment ∼20,000 cells in an average of 2.5 s (1.9-93.5 times faster than the state of the art). It can export quantifiable features minutes after data acquisition (independent of the number of acquired image frames) with an average of 90%-96% precision. We apply FACT to identify directionally migrating glioblastoma cells with 96% precision and irregular cell lineages from a 24 h movie with an average F1 score of 0.91.

ALFI: Cell cycle phenotype annotations of label-free time-lapse imaging data from cultured human cells.

Detecting and tracking multiple moving objects in a video is a challenging task. For living cells, the task becomes even more arduous as cells change their morphology over time, can partially overlap, and mitosis leads to new cells. Differently from fluorescence microscopy, label-free techniques can be easily applied to almost all cell lines, reducing sample preparation complexity and phototoxicity. In this study, we present ALFI, a dataset of images and annotations for label-free microscopy, made publicly available to the scientific community, that notably extends the current panorama of expertly labeled data for detection and tracking of cultured living nontransformed and cancer human cells. It consists of 29 time-lapse image sequences from HeLa, U2OS, and hTERT RPE-1 cells under different experimental conditions, acquired by differential interference contrast microscopy, for a total of 237.9 hours. It contains various annotations (pixel-wise segmentation masks, object-wise bounding boxes, tracking information). The dataset is useful for testing and comparing methods for identifying interphase and mitotic events and reconstructing their lineage, and for discriminating different cellular phenotypes.

Characterization of chimeric antigen receptor modified T cells expressing scFv-IL-13Rα2 after radiolabeling with 89Zirconium oxine for PET imaging.

BACKGROUND: Chimeric antigen receptor (CAR) T cell therapy is an exciting cell-based cancer immunotherapy. Unfortunately, CAR-T cell therapy is associated with serious toxicities such as cytokine release syndrome (CRS) and neurotoxicity. The mechanism of these serious adverse events (SAEs) and how homing, distribution and retention of CAR-T cells contribute to toxicities is not fully understood. Enabling in vitro methods to allow meaningful, sensitive in vivo biodistribution studies is needed to better understand CAR-T cell disposition and its relationship to both effectiveness and safety of these products. METHODS: To determine if radiolabelling of CAR-T cells could support positron emission tomography (PET)-based biodistribution studies, we labeled IL-13Rα2 targeting scFv-IL-13Rα2-CAR-T cells (CAR-T cells) with 89Zirconium-oxine (89Zr-oxine) and characterized and compared their product attributes with non-labeled CAR-T cells. The 89Zr-oxine labeling conditions were optimized for incubation time, temperature, and use of serum for labeling. In addition, T cell subtype characterization and product attributes of radiolabeled CAR-T cells were studied to assess their overall quality including cell viability, proliferation, phenotype markers of T-cell activation and exhaustion, cytolytic activity and release of interferon-γ upon co-culture with IL-13Rα2 expressing glioma cells. RESULTS: We observed that radiolabeling of CAR-T cells with 89Zr-oxine is quick, efficient, and radioactivity is retained in the cells for at least 8 days with minimal loss. Also, viability of radiolabeled CAR-T cells and subtypes such as CD4 + , CD8 + and scFV-IL-13Rα2 transgene positive T cell population were characterized and found similar to that of unlabeled cells as determined by TUNEL assay, caspase 3/7 enzyme and granzyme B activity assay. Moreover, there were no significant changes in T cell activation (CD24, CD44, CD69 and IFN-γ) or T cell exhaustion (PD-1, LAG-3 and TIM3) markers expression between radiolabeled and unlabeled CAR-T cells. In chemotaxis assays, migratory capability of radiolabeled CAR-T cells to IL-13Rα2Fc was similar to that of non-labeled cells. CONCLUSIONS: Importantly, radiolabeling has minimal impact on biological product attributes including potency of CAR-T cells towards IL-13Rα2 positive tumor cells but not IL-13Rα2 negative cells as measured by cytolytic activity and release of IFN-γ. Thus, IL-13Rα2 targeting CAR-T cells radiolabeled with 89Zr-oxine retain critical product attributes and suggest 89Zr-oxine radiolabeling of CAR-T cells may facilitate biodistribution and tissue trafficking studies in vivo using PET.

MegaPro, a clinically translatable nanoparticle for in vivo tracking of stem cell implants in pig cartilage defects.

Rationale: Efficient labeling methods for mesenchymal stem cells (MSCs) are crucial for tracking and understanding their behavior in regenerative medicine applications, particularly in cartilage defects. MegaPro nanoparticles have emerged as a potential alternative to ferumoxytol nanoparticles for this purpose. Methods: In this study, we employed mechanoporation to develop an efficient labeling method for MSCs using MegaPro nanoparticles and compared their effectiveness with ferumoxytol nanoparticles in tracking MSCs and chondrogenic pellets. Pig MSCs were labeled with both nanoparticles using a custom-made microfluidic device, and their characteristics were analyzed using various imaging and spectroscopy techniques. The viability and differentiation capacity of labeled MSCs were also assessed. Labeled MSCs and chondrogenic pellets were implanted into pig knee joints and monitored using MRI and histological analysis. Results: MegaPro-labeled MSCs demonstrated shorter T2 relaxation times, higher iron content, and greater nanoparticle uptake compared to ferumoxytol-labeled MSCs, without significantly affecting their viability and differentiation capacity. Post-implantation, MegaPro-labeled MSCs and chondrogenic pellets displayed a strong hypointense signal on MRI with considerably shorter T2* relaxation times compared to adjacent cartilage. The hypointense signal of both MegaPro- and ferumoxytol-labeled chondrogenic pellets decreased over time. Histological evaluations showed regenerated defect areas and proteoglycan formation with no significant differences between the labeled groups. Conclusion: Our study demonstrates that mechanoporation with MegaPro nanoparticles enables efficient MSC labeling without affecting viability or differentiation. MegaPro-labeled cells show enhanced MRI tracking compared to ferumoxytol-labeled cells, emphasizing their potential in clinical stem cell therapies for cartilage defects.

Dual Magnetic Particle Imaging and Akaluc Bioluminescence Imaging for Tracking Cancer Cell Metastasis.

Magnetic particle imaging (MPI) provides hotspot tracking and direct quantification of superparamagnetic iron oxide nanoparticle (SPIO)-labelled cells. Bioluminescence imaging (BLI) with the luciferase reporter gene Akaluc can provide complementary information on cell viability. Thus, we explored combining these technologies to provide a more holistic view of cancer cell fate in mice. Akaluc-expressing 4T1Br5 cells were labelled with the SPIO Synomag-D and injected into the mammary fat pads (MFP) of four nude mice. BLI was performed on days 0, 6 and 13, and MPI was performed on days 1, 8 and 14. Ex vivo histology and fluorescence microscopy of MFP and a potential metastatic site was conducted. The BLI signal in the MFP increased significantly from day 0 to day 13 (p < 0.05), mirroring tumor growth. The MPI signal significantly decreased from day 1 to day 14 (p < 0.05) due to SPIO dilution in proliferating cells. Both modalities detected secondary metastases; however, they were visualized in different anatomical regions. Akaluc BLI complemented MPI cell tracking, allowing for longitudinal measures of cell viability and sensitive detection of distant metastases at different locations. We predict this multimodal imaging approach will help to evaluate novel therapeutics and give a better understanding of metastatic mechanisms.

Biocompatible Iron Oxide Nanoring-Labeled Mesenchymal Stem Cells: An Innovative Magnetothermal Approach for Cell Tracking and Targeted Stroke Therapy.

Labeling stem cells with magnetic nanoparticles is a promising technique for in vivo tracking and magnetic targeting of transplanted stem cells, which is critical for improving the therapeutic efficacy of cell therapy. However, conventional endocytic labeling with relatively poor labeling efficiency and a short labeling lifetime has hindered the implementation of these innovative enhancements in stem-cell-mediated regenerative medicine. Herein, we describe an advanced magnetothermal approach to label mesenchymal stem cells (MSCs) efficiently by local induction of heat-enhanced membrane permeability for magnetic resonance imaging (MRI) tracking and targeted therapy of stroke, where biocompatible γ-phase, ferrimagnetic vortex-domain iron oxide nanorings (γ-FVIOs) with superior magnetoresponsive properties were used as a tracer. This approach facilitates a safe and efficient labeling of γ-FVIOs as high as 150 pg of Fe per cell without affecting the MSCs proliferation and differentiation, which is 3.44-fold higher than that by endocytosis labeling. Such a high labeling efficiency not only enables the ultrasensitive magnetic resonance imaging (MRI) detection of sub-10 cells and long-term tracking of transplanted MSCs over 10 weeks but also endows transplanted MSCs with a magnetic manipulation ability in vivo. A proof-of-concept study using a rat stroke model showed that the labeled MSCs facilitated MRI tracking and magnetic targeting for efficient replacement therapy with a significantly reduced dosage of 5 × 104 transplanted cells. The findings in this study have demonstrated the great potential of the magnetothermal approach as an efficient labeling technique for future clinical usage.

Segmentation, tracking and cell cycle analysis of live-cell imaging data with Cell-ACDC.

BACKGROUND: High-throughput live-cell imaging is a powerful tool to study dynamic cellular processes in single cells but creates a bottleneck at the stage of data analysis, due to the large amount of data generated and limitations of analytical pipelines. Recent progress on deep learning dramatically improved cell segmentation and tracking. Nevertheless, manual data validation and correction is typically still required and tools spanning the complete range of image analysis are still needed. RESULTS: We present Cell-ACDC, an open-source user-friendly GUI-based framework written in Python, for segmentation, tracking and cell cycle annotations. We included state-of-the-art deep learning models for single-cell segmentation of mammalian and yeast cells alongside cell tracking methods and an intuitive, semi-automated workflow for cell cycle annotation of single cells. Using Cell-ACDC, we found that mTOR activity in hematopoietic stem cells is largely independent of cell volume. By contrast, smaller cells exhibit higher p38 activity, consistent with a role of p38 in regulation of cell size. Additionally, we show that, in S. cerevisiae, histone Htb1 concentrations decrease with replicative age. CONCLUSIONS: Cell-ACDC provides a framework for the application of state-of-the-art deep learning models to the analysis of live cell imaging data without programming knowledge. Furthermore, it allows for visualization and correction of segmentation and tracking errors as well as annotation of cell cycle stages. We embedded several smart algorithms that make the correction and annotation process fast and intuitive. Finally, the open-source and modularized nature of Cell-ACDC will enable simple and fast integration of new deep learning-based and traditional methods for cell segmentation, tracking, and downstream image analysis. Source code: https://github.com/SchmollerLab/Cell_ACDC.

Ferromagnetic Vortex Iron Oxide Nanorings Modified with Integrin ß1 Antibody for Targeted MRI Tracking of Human Mesenchymal Stem Cells.

Mesenchymal stem cells (MSCs) have demonstrated great potential for tissue engineering and regenerative medicine applications. Noninvasive and real-term tracking of transplanted MSCs in vivo is crucial for studying the distribution and migration of MSCs, and their role in tissue injury repair. This study reports on the use of ferrimagnetic vortex iron oxide (FVIO) nanorings modified with anti-human integrin ß1 for specific recognition and magnetic resonance imaging (MRI) tracking of human MSCs (hMSCs). Integrin ß1 is highly expressed at all stem cell proliferation and differentiation stages. Therefore, the anti-integrin ß1 antibody (Ab) introduced in FVIO targets integrin ß1, thus enabling FVIO to target stem cells at any stage. This is unlike the traditional MRI-based monitoring of transplanted stem cells, which usually requires pre-labeling the stem cells with tracers before injection. Because of the ability to recognize hMSCs, the Ab-modified FVIO nanotracers (FVIO-Ab) have the advantage of not requiring pre-labeling before stem cell transplantation. Furthermore, the FVIO-Ab nanotracers have high T*2 contrast resulting from the unique magnetic properties of FVIO which can improve the MRI tracking efficiency of stem cells. This work may provide a new way for stem cell labeling and in vivo MRI tracking, thus reducing the risks associated with stem cell transplantation and promoting clinical translation.

Multicolor strategies for investigating clonal expansion and tissue plasticity.

Understanding the generation of complexity in living organisms requires the use of lineage tracing tools at a multicellular scale. In this review, we describe the different multicolor strategies focusing on mouse models expressing several fluorescent reporter proteins, generated by classical (MADM, Brainbow and its multiple derivatives) or acute (StarTrack, CLoNe, MAGIC Markers, iOn, viral vectors) transgenesis. After detailing the multi-reporter genetic strategies that serve as a basis for the establishment of these multicolor mouse models, we briefly mention other animal and cellular models (zebrafish, chicken, drosophila, iPSC) that also rely on these constructs. Then, we highlight practical applications of multicolor mouse models to better understand organogenesis at single progenitor scale (clonal analyses) in the brain and briefly in several other tissues (intestine, skin, vascular, hematopoietic and immune systems). In addition, we detail the critical contribution of multicolor fate mapping strategies in apprehending the fine cellular choreography underlying tissue morphogenesis in several models with a particular focus on brain cytoarchitecture in health and diseases. Finally, we present the latest technological advances in multichannel and in-depth imaging, and automated analyses that enable to better exploit the large amount of data generated from multicolored tissues.

LIM Tracker: a software package for cell tracking and analysis with advanced interactivity.

Cell tracking is one of the most critical tools for time-lapse image analysis to observe cell behavior and cell lineages over a long period of time. However, the accompanying graphical user interfaces are often difficult to use and do not incorporate seamless manual correction, data analysis tools, or simple training set design tools if it is machine learning based. In this paper, we introduce our cell tracking software "LIM Tracker". This software has a conventional tracking function consisting of recognition processing and link processing, a sequential search-type tracking function based on pattern matching, and a manual tracking function. LIM Tracker enables the seamless use of these functions. In addition, the system incorporates a highly interactive and interlocking data visualization method, which displays analysis result in real time, making it possible to flexibly correct the data and reduce the burden of tracking work. Moreover, recognition functions with deep learning (DL) are also available, which can be used for a wide range of targets including stain-free images. LIM Tracker allows researchers to track living objects with good usability and high versatility for various targets. We present a tracking case study based on fluorescence microscopy images (NRK-52E/EKAREV-NLS cells or MCF-10A/H2B-iRFP-P2A-mScarlet-I-hGem-P2A-PIP-NLS-mNeonGreen cells) and phase contrast microscopy images (Glioblastoma-astrocytoma U373 cells). LIM Tracker is implemented as a plugin for ImageJ/Fiji. The software can be downloaded from https://github.com/LIMT34/LIM-Tracker .

Magnetic particle imaging: tracer development and the biomedical applications of a radiation-free, sensitive, and quantitative imaging modality.

Magnetic particle imaging (MPI) is an emerging tracer-based modality that enables real-time three-dimensional imaging of the non-linear magnetisation produced by superparamagnetic iron oxide nanoparticles (SPIONs), in the presence of an external oscillating magnetic field. As a technique, it produces highly sensitive radiation-free tomographic images with absolute quantitation. Coupled with a high contrast, as well as zero signal attenuation at-depth, there are essentially no limitations to where that can be imaged within the body. These characteristics enable various biomedical applications of clinical interest. In the opening sections of this review, the principles of image generation are introduced, along with a detailed comparison of the fundamental properties of this technique with other common imaging modalities. The main feature is a presentation on the up-to-date literature for the development of SPIONs tailored for improved imaging performance, and developments in the current and promising biomedical applications of this emerging technique, with a specific focus on theranostics, cell tracking and perfusion imaging. Finally, we will discuss recent progress in the clinical translation of MPI. As signal detection in MPI is almost entirely dependent on the properties of the SPION employed, this work emphasises the importance of tailoring the synthetic process to produce SPIONs demonstrating specific properties and how this impacts imaging in particular applications and MPI's overall performance.

Non-invasive cell-tracking methods for adoptive T cell therapies.

Adoptive T cell therapies (ACT) have demonstrated groundbreaking results in blood cancers and melanoma. Nevertheless, their significant cost, the occurrence of severe adverse events, and their poor performance in solid tumors are important hurdles hampering more widespread applicability. In vivo cell-tracking allows instantaneous and non-invasive monitoring of the distribution, tumor homing, persistence, and redistribution to other organs of infused T cells in patients. Furthermore, cell-tracking could aid in the clinical management of patients, allowing the detection of non-responders or severe adverse events at an early stage. This review provides a concise overview of the main principles and potential of cell-tracking, followed by a discussion of the clinically relevant labeling strategies and their application in ACT.

Visualizing stem cells in vivo using magnetic resonance imaging.

Stem cell (SC) therapies displayed encouraging efficacy and clinical outcome in various disorders. Despite this huge hype, clinical translation of SC therapy has been disheartening due to contradictory results from clinical trials. The ability to monitor migration and engraftment of cells in vivo represents an ideal strategy in cell therapy. Therefore, suitable imaging approach to track MSCs would allow understanding of migratory and homing efficiency, optimal route of delivery and engraftment of cells at targeted location. Hence, longitudinal tracking of SCs is crucial for the optimization of treatment parameters, leading to improved clinical outcome and translation. Magnetic resonance imaging (MRI) represents a suitable imaging modality to observe cells non-invasively and repeatedly. Tracking is achieved when cells are incubated prior to implantation with appropriate contrast agents (CA) or tracers which can then be detected in an MRI scan. This review explores and emphasizes the importance of monitoring the distribution and fate of SCs post-implantation using current contrast agents, such as positive CAs including paramagnetic metals (gadolinium), negative contrast agents such as superparamagnetic iron oxides and 19 F containing tracers, specifically for the in vivo tracking of MSCs using MRI. This article is categorized under: Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Emerging Technologies.

The sensitivity of magnetic particle imaging and fluorine-19 magnetic resonance imaging for cell tracking.

Magnetic particle imaging (MPI) and fluorine-19 (19F) MRI produce images which allow for quantification of labeled cells. MPI is an emerging instrument for cell tracking, which is expected to have superior sensitivity compared to 19F MRI. Our objective is to assess the cellular sensitivity of MPI and 19F MRI for detection of mesenchymal stem cells (MSC) and breast cancer cells. Cells were labeled with ferucarbotran or perfluoropolyether, for imaging on a preclinical MPI system or 3 Tesla clinical MRI, respectively. Using the same imaging time, as few as 4000 MSC (76 ng iron) and 8000 breast cancer cells (74 ng iron) were reliably detected with MPI, and 256,000 MSC (9.01 × 1016 19F atoms) were detected with 19F MRI, with SNR > 5. MPI has the potential to be more sensitive than 19F MRI for cell tracking. In vivo sensitivity with MPI and 19F MRI was evaluated by imaging MSC that were administered by different routes. In vivo imaging revealed reduced sensitivity compared to ex vivo cell pellets of the same cell number. We attribute reduced MPI and 19F MRI cell detection in vivo to the effect of cell dispersion among other factors, which are described.

Tracking of Oral and Craniofacial Stem Cells in Tissue Development, Regeneration, and Diseases.

PURPOSE OF REVIEW: The craniofacial region hosts a variety of stem cells, all isolated from different sources of bone and cartilage. However, despite scientific advancements, their role in tissue development and regeneration is not entirely understood. The goal of this review is to discuss recent advances in stem cell tracking methods and how these can be advantageously used to understand oro-facial tissue development and regeneration. RECENT FINDINGS: Stem cell tracking methods have gained importance in recent times, mainly with the introduction of several molecular imaging techniques, like optical imaging, computed tomography, magnetic resonance imaging, and ultrasound. Labelling of stem cells, assisted by these imaging techniques, has proven to be useful in establishing stem cell lineage for regenerative therapy of the oro-facial tissue complex. Novel labelling methods complementing imaging techniques have been pivotal in understanding craniofacial tissue development and regeneration. These stem cell tracking methods have the potential to facilitate the development of innovative cell-based therapies.

Tracking of human embryonic stem cell-derived mesenchymal stem cells in premature ovarian failure model mice.

Premature ovarian failure (POF) is defined by amenorrhea, hypoestrogenism, elevated gonadotropin levels, and infertility. Chemotherapeutic agents are the most gonadotoxic agents that lead to POF. Although some previous studies have presented that mesenchymal stem cells (MSCs) transplantation could rescue the ovary function of POF animal models through the paracrine pathway, these mechanisms require further investigation. However, mechanisms of embryonic stem cell-derived MSCs (ES-MSCs) therapeutic effects on POF animal models have not been fully investigated yet. This study aimed to evaluate the migration and distribution of ES-MSCs in a model of chemotherapy-induced POF. Female mice received intraperitoneal injections of cyclophosphamide (Cy) to induce POF. Then, MSCs were labeled with green fluorescent protein (GFP) in vitro and injected intravenously into POF mice, and the distribution of MSCs was dynamically monitored at 1 week after transplantation. We harvested the lungs, liver, spleen, ovaries, heart, and kidneys 1 week after transplantation. The sections of these tissues were observed under the fluorescent microscope. More than 70% MSCs were successfully labeled with GFP at 72 h after labeling. MSCs were uniformly distributed in multiple organs and tissues including lungs, liver, spleen, ovaries, heart, and kidneys of POF mice. In mice, at 1week after intravenous transplantation, GFP labeled ES-MSCs were observed in the lungs, liver, spleen, ovaries, heart, and kidneys of POF mice, and the number of GFP labeled ES-MSCs in lungs, ovaries, and heart were higher than that in the spleen, kidneys, and liver. Our results revealed intravenously implanted ES-MSCs could migrate into the various tissues in chemotherapy-induced damaged POF mice.

MRI-Based and Histologically Verified 3D Modeling of Spatial Distribution of Intra-Arterially Transplanted Cells in Rat Brain.

Visualization of transplanted stem cells in the brain is an important issue in the study of the mechanisms of their therapeutic action. MRI allowing visualization of single transplanted cells previously labeled with superparamagnetic iron oxide particles is among the most informative methods of non-invasive intravital imaging. Verification of MRI data using pathomorphological examination at the microscopic level helps to avoid errors in data interpretation. However, making serial sections of the whole brain and searching for transplanted cells under the microscope is laborious and time-consuming. We have developed a method for 3D modeling of the distribution of transplanted cells in the brain allowing navigating through various brain structures and identifying the areas of accumulation of transplanted cells, which significantly increases the efficiency and reduces the time of histological examination.