Cell fate simulation reveals cancer cell features in the tumor microenvironment.

To elucidate the dynamic evolution of cancer cell characteristics within the tumor microenvironment (TME), we developed an integrative approach combining single-cell tracking, cell fate simulation, and three-dimensional (3D) TME modeling. We began our investigation by analyzing the spatiotemporal behavior of individual cancer cells in cultured pancreatic (MiaPaCa2) and cervical (HeLa) cancer cell lines, with a focus on the α2-6 sialic acid (α2-6Sia) modification on glycans, which is associated with cell stemness. Our findings revealed that MiaPaCa2 cells exhibited significantly higher levels of α2-6Sia modification, correlating with enhanced reproductive capabilities, whereas HeLa cells showed less prevalence of this modification. To accommodate the in vivo variability of α2-6Sia levels, we employed a cell fate simulation algorithm that digitally generates cell populations based on our observed data while varying the level of sialylation, thereby simulating cell growth patterns. Subsequently, we performed a 3D TME simulation with these deduced cell populations, considering the microenvironment that could impact cancer cell growth. Immune cell landscape information derived from 193 cervical and 172 pancreatic cancer cases was used to estimate the degree of the positive or negative impact. Our analysis suggests that the deduced cells generated based on the characteristics of MiaPaCa2 cells are less influenced by the immune cell landscape within the TME compared to those of HeLa cells, highlighting that the fate of cancer cells is shaped by both the surrounding immune landscape and the intrinsic characteristics of the cancer cells.

Precise Serial Microregistration Enables Quantitative Microscopy Imaging Tracking of Human Skin Cells In Vivo.

We developed an automated microregistration method that enables repeated in vivo skin microscopy imaging of the same tissue microlocation and specific cells over a long period of days and weeks with unprecedented precision. Applying this method in conjunction with an in vivo multimodality multiphoton microscope, the behavior of human skin cells such as cell proliferation, melanin upward migration, blood flow dynamics, and epidermal thickness adaptation can be recorded over time, facilitating quantitative cellular dynamics analysis. We demonstrated the usefulness of this method in a skin biology study by successfully monitoring skin cellular responses for a period of two weeks following an acute exposure to ultraviolet light.

The development of an automated microscope image tracking and analysis system.

Microscopy image analysis plays a crucial role in understanding cellular behavior and uncovering important insights in various biological and medical research domains. Tracking cells within the time-lapse microscopy images is a fundamental technique that enables the study of cell dynamics, interactions, and migration. While manual cell tracking is possible, it is time-consuming and prone to subjective biases that impact results. In order to solve this issue, we sought to create an automated software solution, named cell analyzer, which is able to track cells within microscopy images with minimal input required from the user. The program of cell analyzer was written in Python utilizing the open source computer vision (OpenCV) library and featured a graphical user interface that makes it easy for users to access. The functions of all codes were verified through closeness, area, centroid, contrast, variance, and cell tracking test. Cell analyzer primarily utilizes image preprocessing and edge detection techniques to isolate cell boundaries for detection and analysis. It uniquely recorded the area, displacement, speed, size, and direction of detected cell objects and visualized the data collected automatically for fast analysis. Our cell analyzer provides an easy-to-use tool through a graphical user interface for tracking cell motion and analyzing quantitative cell images.

Methods and computational tools to study eukaryotic cell migration in vitro.

Cellular movement is essential for many vital biological functions where it plays a pivotal role both at the single cell level, such as during division or differentiation, and at the macroscopic level within tissues, where coordinated migration is crucial for proper morphogenesis. It also has an impact on various pathological processes, one for all, cancer spreading. Cell migration is a complex phenomenon and diverse experimental methods have been developed aimed at dissecting and analysing its distinct facets independently. In parallel, corresponding analytical procedures and tools have been devised to gain deep insight and interpret experimental results. Here we review established experimental techniques designed to investigate specific aspects of cell migration and present a broad collection of historical as well as cutting-edge computational tools used in quantitative analysis of cell motion.

In Vivo PET Imaging of 89Zr-Labeled Natural Killer Cells and the Modulating Effects of a Therapeutic Antibody.

Natural killer (NK) cells can kill cancer cells via antibody-dependent cell-mediated cytotoxicity (ADCC): a tumor-associated IgG antibody binds to the Fcγ receptor CD16 on NK cells via the antibody Fc region and activates the cytotoxic functions of the NK cell. Here, we used PET imaging to assess NK cell migration to human epidermal growth factor receptor 2 (HER2)-positive HCC1954 breast tumors, examining the influence of HER2-targeted trastuzumab antibody treatment on NK cell tumor accumulation. Methods: Human NK cells from healthy donors were expanded ex vivo and labeled with [89Zr]Zr-oxine. In vitro experiments compared the phenotypic markers, viability, proliferation, migration, degranulation, and ADCC behaviors of both labeled (89Zr-NK) and unlabeled NK cells. Female mice bearing orthotopic human breast HCC1954 tumors were administered 89Zr-NK cells alongside trastuzumab treatment or a sham treatment and then scanned using PET/CT imaging over 7 d. Flow cytometry and γ-counting were used to analyze the presence of 89Zr-NK cells in liver and spleen tissues. Results: 89Zr cell radiolabeling yields measured 42.2% ± 8.0%. At an average specific activity of 16.7 ± 4.7 kBq/106 cells, 89Zr-NK cells retained phenotypic and functional characteristics including CD56 and CD16 expression, viability, migration, degranulation, and ADCC capabilities. In vivo PET/CT studies indicated predominant accumulation of 89Zr-NK cells in the liver and spleen. Ex vivo analyses of liver and spleen tissues indicated that the administered human 89Zr-NK cells retained their radioactivity in vivo and that 89Zr did not transfer to cells of murine soft tissues, thus validating this 89Zr PET method for NK cell tracking. Notably, 89Zr-NK cells migrated to HER2-positive tumors, both with and without trastuzumab treatment. Trastuzumab treatment was associated with an increased 89Zr-NK cell signal at days 1 and 3 after injection. Conclusion: In vitro, 89Zr-NK cells maintained key cellular and cytotoxic functions. In vivo, 89Zr-NK cells trafficked to HER2-postive tumors, with trastuzumab treatment correlating with enhanced 89Zr-NK infiltration. This study demonstrates the feasibility of using PET to image 89Zr-NK cell infiltration into solid tumors.

Immune Cell-Based Microrobots for Remote Magnetic Actuation, Antitumor Activity, and Medical Imaging.

Translating medical microrobots into clinics requires tracking, localization, and performing assigned medical tasks at target locations, which can only happen when appropriate design, actuation mechanisms, and medical imaging systems are integrated into a single microrobot. Despite this, these parameters are not fully considered when designing macrophage-based microrobots. This study presents living macrophage-based microrobots that combine macrophages with magnetic Janus particles coated with FePt nanofilm for magnetic steering and medical imaging and bacterial lipopolysaccharides for stimulating macrophages in a tumor-killing state. The macrophage-based microrobots combine wireless magnetic actuation, tracking with medical imaging techniques, and antitumor abilities. These microrobots are imaged under magnetic resonance imaging and optoacoustic imaging in soft-tissue-mimicking phantoms and ex vivo conditions. Magnetic actuation and real-time imaging of microrobots are demonstrated under static and physiologically relevant flow conditions using optoacoustic imaging. Further, macrophage-based microrobots are magnetically steered toward urinary bladder tumor spheroids and imaged with a handheld optoacoustic device, where the microrobots significantly reduce the viability of tumor spheroids. The proposed approach demonstrates the proof-of-concept feasibility of integrating macrophage-based microrobots into clinic imaging modalities for cancer targeting and intervention, and can also be implemented for various other medical applications.

Digital in-line holographic microscopy for label-free identification and tracking of biological cells.

Digital in-line holographic microscopy (DIHM) is a non-invasive, real-time, label-free technique that captures three-dimensional (3D) positional, orientational, and morphological information from digital holographic images of living biological cells. Unlike conventional microscopies, the DIHM technique enables precise measurements of dynamic behaviors exhibited by living cells within a 3D volume. This review outlines the fundamental principles and comprehensive digital image processing procedures employed in DIHM-based cell tracking methods. In addition, recent applications of DIHM technique for label-free identification and digital tracking of various motile biological cells, including human blood cells, spermatozoa, diseased cells, and unicellular microorganisms, are thoroughly examined. Leveraging artificial intelligence has significantly enhanced both the speed and accuracy of digital image processing for cell tracking and identification. The quantitative data on cell morphology and dynamics captured by DIHM can effectively elucidate the underlying mechanisms governing various microbial behaviors and contribute to the accumulation of diagnostic databases and the development of clinical treatments.

Growth phase-dependent ribonucleic acid production dynamics.

Transcriptional events play a crucial role in major cellular processes that specify the activity of an individual cells and influences cell population behavior in response to environment. Active (ON) and an inactive (OFF) states controls the transcriptional burst. Yet, the mechanism and kinetics of ON/OFF-state across the different growth phases of Escherichia coli remains elusive. Here, we have used a single mRNA detection method in live-cells to comprehend the ON/OFF mechanism of the first transcriptional (TF) and consecutive events (TC) controlled by lactose promoters, Plac and Plac/ara1. We determined that the duration of TF ON/OFF has different modes, exhibiting a close to inverse behavior to that of TC ON/OFF. Dynamics of ON/OFF states in fast and slow-dividing cells were affected by the promoter region during the initiation of transcription. Period of TF ON-state defines the behavior of TC by altering the number and the frequency of mRNAs formed. Furthermore, we have shown that delayed OFF-time in TF affects the dynamics of TC in both states, which is mainly determined by the upstream promoter region. Furthermore, using elongation arrest experiments, we independently validate that mRNA noise in TC is governed by the delayed OFF-period in TF. We have identified the position of the regulatory regions that plays a crucial role in noise (Fano) modulation. Taken together, our results suggest that the dynamics of the first transcriptional event, TF, pre-defines the diversity of the population.

SC-Track: a robust cell-tracking algorithm for generating accurate single-cell lineages from diverse cell segmentations.

Computational analysis of fluorescent timelapse microscopy images at the single-cell level is a powerful approach to study cellular changes that dictate important cell fate decisions. Core to this approach is the need to generate reliable cell segmentations and classifications necessary for accurate quantitative analysis. Deep learning-based convolutional neural networks (CNNs) have emerged as a promising solution to these challenges. However, current CNNs are prone to produce noisy cell segmentations and classifications, which is a significant barrier to constructing accurate single-cell lineages. To address this, we developed a novel algorithm called Single Cell Track (SC-Track), which employs a hierarchical probabilistic cache cascade model based on biological observations of cell division and movement dynamics. Our results show that SC-Track performs better than a panel of publicly available cell trackers on a diverse set of cell segmentation types. This cell-tracking performance was achieved without any parameter adjustments, making SC-Track an excellent generalized algorithm that can maintain robust cell-tracking performance in varying cell segmentation qualities, cell morphological appearances and imaging conditions. Furthermore, SC-Track is equipped with a cell class correction function to improve the accuracy of cell classifications in multiclass cell segmentation time series. These features together make SC-Track a robust cell-tracking algorithm that works well with noisy cell instance segmentation and classification predictions from CNNs to generate accurate single-cell lineages and classifications.

Probing cell proliferation: Considerations for dye selection.

Broadly speaking, cell tracking dyes are fluorescent compounds that bind stably to components on or within the cells so the fate of the labeled cells can be followed. Their staining should be bright and homogeneous without affecting cell function. For purposes of monitoring cell proliferation, each time a cell divides the intensity of cell tracking dye should diminish equally between daughter cells. These dyes can be grouped into two different classes. Protein reactive dyes label cells by reacting covalently but non-selectively with intracellular proteins. Carboxyfluorescein diacetate succinimidyl ester (CFSE) is the prototypic general protein label. Membrane intercalating dyes label cells by partitioning non-selectively and non-covalently within the plasma membrane. The PKH membrane dyes are examples of lipophilic compounds whose chemistry allows for their retention within biological membranes without affecting cellular growth, viability, or proliferation when used properly. Here we provide considerations based for labeling cell lines and peripheral blood mononuclear cells using both classes of dyes. Examples from optimization experiments are presented along with critical aspects of the staining procedures to help mitigate common risks. Of note, we present data where a logarithmically growing cell line is labeled with both a protein dye and a membrane tracking dye to compare dye loss rates over 6days. We found that dual stained cells paralleled dye loss of the corresponding single stained cells. The decrease in fluorescence intensity by protein reactive dyes, however, was more rapid than that with the membrane reactive dyes, indicating the presence of additional division-independent dye loss.

Deep Learning-Based Cell Tracking in Deforming Organs and Moving Animals.

Cell tracking is an essential step in extracting cellular signals from moving cells, which is vital for understanding the mechanisms underlying various biological functions and processes, particularly in organs such as the brain and heart. However, cells in living organisms often exhibit extensive and complex movements caused by organ deformation and whole-body motion. These movements pose a challenge in obtaining high-quality time-lapse cell images and tracking the intricate cell movements in the captured images. Recent advances in deep learning techniques provide powerful tools for detecting cells in low-quality images with densely packed cell populations, as well as estimating cell positions for cells undergoing large nonrigid movements. This chapter introduces the challenges of cell tracking in deforming organs and moving animals, outlines the solutions to these challenges, and presents a detailed protocol for data preparation, as well as for performing cell segmentation and tracking using the latest version of 3DeeCellTracker. This protocol is expected to enable researchers to gain deeper insights into organ dynamics and biological processes.

Extracellular vesicles promote migration despite BRAF inhibitor treatment in malignant melanoma cells.

Extracellular vesicles (EVs) constitute a vital component of intercellular communication, exerting significant influence on metastasis formation and drug resistance mechanisms. Malignant melanoma (MM) is one of the deadliest forms of skin cancers, because of its high metastatic potential and often acquired resistance to oncotherapies. The prevalence of BRAF mutations in MM underscores the importance of BRAF-targeted therapies, such as vemurafenib and dabrafenib, alone or in combination with the MEK inhibitor, trametinib. This study aimed to elucidate the involvement of EVs in MM progression and ascertain whether EV-mediated metastasis promotion persists during single agent BRAF (vemurafenib, dabrafenib), or MEK (trametinib) and combined BRAF/MEK (dabrafenib/trametinib) inhibition.Using five pairs of syngeneic melanoma cell lines, we assessed the impact of EVs - isolated from their respective supernatants - on melanoma cell proliferation and migration. Cell viability and spheroid growth assays were employed to evaluate proliferation, while migration was analyzed through mean squared displacement (MSD) and total traveled distance (TTD) measurements derived from video microscopy and single-cell tracking.Our results indicate that while EV treatments had remarkable promoting effect on cell migration, they exerted only a modest effect on cell proliferation and spheroid growth. Notably, EVs demonstrated the ability to mitigate the inhibitory effects of BRAF inhibitors, albeit they were ineffective against a MEK inhibitor and the combination of BRAF/MEK inhibitors. In summary, our findings contribute to the understanding of the intricate role played by EVs in tumor progression, metastasis, and drug resistance in MM.

Indocyanine Green-Labeled Platelets for Survival and Recovery Studies.

Introduction: Before being implemented in daily clinical routine, new production strategies for platelet concentrates (PCs) must be validated for their efficacy. Besides in vitro testing, the establishment of new methods requires the labeling of platelets for in vivo studies of platelets' survival and recovery. Indocyanine green (ICG) is a Food and Drug Administration-approved near-infrared (NIR) fluorescent dye for diagnostic use in vivo, suitable for non-radioactive direct cell labeling of platelets. Methods: Platelets from PCs in storage solutions with different plasma concentrations were labeled with ICG up to concentrations of 200 µm. Whole blood (WB) was used as an ex vivo matrix to monitor the labeling stability of ICG-labeled platelets. The impact of labeling processes was assessed by the quantification of CD62P expression and PAC-1 binding as platelet function markers. Platelet aggregation was analyzed by light transmission aggregometry. ICG-labeling efficiency and stability of platelets were determined by flow cytometry. Results: Platelets from PCs could be successfully labeled with 10 µm ICG after 1 and 4 days of storage. The best labeling efficiency of 99.8% ± 0.1% (immediately after labeling) and 81% ± 6.2% (after 24 h incubation with WB) was achieved by plasma replacement by 100% platelet additive solution for the labeling process. Since the washing process slightly impaired platelet function, ICG labeling itself did not affect platelets. Immediately after the ICG-labeling process, plasma was re-added, resulting in a recovered platelet function. Conclusion: We developed a Good Manufacturing Practice compatible protocol for ICG fluorescent platelet labeling suitable for survival and recovery studies in vivo as a non-radioactive labeling alternative.

We developed a simple, reproducible method according to Good Manufacturing Practice guidelines for labeling of platelets from platelet concentrates (PCs) with indocyanine green (ICG) as a non-radioactive alternative. PCs are medicinal drugs that are transfused to prevent or treat bleeding. They consist of the blood cells' platelets which are responsible for clotting processes in the body. Manufacturing procedures of PCs are continuously refined, and for in vivo testing, these platelets have to be labeled to track and to distinguish them from proband's or patient's own cells. Radioactive labeling, for a long time the gold standard for cell labeling, is no longer accepted. ICG is a fluorescent dye approved by the drug authorities and already used for diagnostic purposes in humans. We used ICG to label platelets from PCs. With our method, we achieved a labeling efficiency of 99.8%. We used whole blood (WB) as an ex vivo matrix to monitor the labeling stability of ICG-labeled platelets. After the addition of ICG-labeled platelets to WB, the labeling efficiency decreased to 81% after 24 h. However, we were still able to distinguish the ICG-labeled platelets from the WB platelets. We could also show that platelet function was not impaired by the labeling processes. The good tolerance of ICG indicates a short path to clinical application in healthy volunteers and investigations of novel PC-manufacturing procedures. As a read-out system, flow cytometry systems equipped with NIR lasers and filters could offer the possibility of rapid visualization, cell tracking, re-isolation, and ex vivo studies.

In Vivo Microrheology Reveals Local Elastic and Plastic Responses Inside 3D Bacterial Biofilms.

Bacterial biofilms are highly abundant 3D living materials capable of performing complex biomechanical and biochemical functions, including programmable growth, self-repair, filtration, and bioproduction. Methods to measure internal mechanical properties of biofilms in vivo with spatial resolution on the cellular scale have been lacking. Here, thousands of cells are tracked inside living 3D biofilms of the bacterium Vibrio cholerae during and after the application of shear stress, for a wide range of stress amplitudes, periods, and biofilm sizes, which revealed anisotropic elastic and plastic responses of both cell displacements and cell reorientations. Using cellular tracking to infer parameters of a general mechanical model, spatially-resolved measurements of the elastic modulus inside the biofilm are obtained, which correlate with the spatial distribution of the polysaccharides within the biofilm matrix. The noninvasive microrheology and force-inference approach introduced here provides a general framework for studying mechanical properties with high spatial resolution in living materials.

Intracerebral transplantation of MRI-trackable autologous bone marrow stromal cells for patients with subacute ischemic stroke.

BACKGROUND: Ischemic stroke is one of the leading causes of death and neurological disability worldwide, and stem cell therapy is highly expected to reverse the sequelae. This phase 1/2, first-in-human study evaluated the safety, feasibility, and monitoring of an intracerebral-transplanted magnetic resonance imaging (MRI)-trackable autologous bone marrow stromal cell (HUNS001-01) for patients with subacute ischemic stroke. METHODS: The study included adults with severe disability due to ischemic stroke. HUNS001-01 cultured with human platelet lysates and labeled with superparamagnetic iron oxide was stereotactically transplanted into the peri-infarct area 47-64 days after ischemic stroke onset (dose: 2 or 5 × 107 cells). Neurological and radiographic evaluations were performed throughout 1 year after cell transplantation. The trial was registered at UMIN Clinical Trial Registry (number UMIN000026130). FINDINGS: All seven patients who met the inclusion criteria successfully achieved cell expansion, underwent intracerebral transplantation, and completed 1 year of follow-up. No product-related adverse events were observed. The median National Institutes of Health Stroke Scale and modified Rankin scale scores before transplantation were 13 and 4, which showed improvements of 1-8 and 0-2, respectively. Cell tracking proved that the engrafted cells migrated toward the infarction border area 1-6 months after transplantation, and the quantitative susceptibility mapping revealed that cell signals at the migrated area constantly increased throughout the follow-up period up to 34% of that of the initial transplanted site. CONCLUSIONS: Intracerebral transplantation of HUNS001-01 was safe and well tolerated. Cell tracking shed light on the therapeutic mechanisms of intracerebral transplantation. FUNDING: This work was supported by the Japan Agency for Medical Research and Development (AMED; JP17bk0104045 and JP20bk0104011).

Longitudinal Magnetic Resonance Imaging Tracking of Transplanted Neural Progenitor Cells in the Spinal Cord Utilizing the Bright-Ferritin Mechanism.

Human neural progenitor cells (hNPCs) hold promise for treating spinal cord injury. Studies to date have focused on improving their regenerative potential and therapeutic effect. Equally important is ensuring successful delivery and engraftment of hNPCs at the injury site. Unfortunately, no current imaging solution for cell tracking is compatible with long-term monitoring in vivo. The objective of this study was to apply a novel bright-ferritin magnetic resonance imaging (MRI) mechanism to track hNPC transplants longitudinally and on demand in the rat spinal cord. We genetically modified hNPCs to stably overexpress human ferritin. Ferritin-overexpressing (FT) hNPCs labeled with 0.2 mM manganese provided significant T1-induced bright contrast on in vitro MRI, with no adverse effect on cell viability, morphology, proliferation, and differentiation. In vivo, 2 M cells were injected into the cervical spinal cord of Rowett nude rats. MRI employed T1-weighted acquisitions and T1 mapping on a 3 T scanner. Conventional short-term cell tracking was performed using exogenous Mn labeling prior to cell transplantation, which displayed transient bright contrast on MRI 1 day after cell transplantation and disappeared after 1 week. In contrast, long-term cell tracking using bright-ferritin allowed on-demand signal recall upon Mn supplementation and precise visualization of the surviving hNPC graft. In fact, this new cell tracking technology identified 7 weeks post-transplantation as the timepoint by which substantial hNPC integration occurred. Spatial distribution of hNPCs on MRI matched that on histology. In summary, bright-ferritin provides the first demonstration of long-term, on-demand, high-resolution, and specific tracking of hNPCs in the rat spinal cord.

Single-cell tracking as a tool for studying EMT-phenotypes.

This article demonstrates that label-free single-cell video tracking is a useful approach for in vitro studies of Epithelial-Mesenchymal Transition (EMT). EMT is a highly heterogeneous process, involved in wound healing, embryogenesis and cancer. The process promotes metastasis, and increased understanding can aid development of novel therapeutic strategies. The role of EMT-associated biomarkers depends on biological context, making it challenging to compare and interpret data from different studies. We demonstrate single-cell video tracking for comprehensive phenotype analysis. In this study we performed single-cell video tracking on 72-h long recordings. We quantified several behaviours at a single-cell level during induced EMT in MDA-MB-468 cells. This revealed notable variations in migration speed, with different dose-response patterns and varying distributions of speed. By registering cell morphologies during the recording, we determined preferred paths of morphological transitions. We also found a clear association between migration speed and cell morphology. We found elevated rates of cell death, diminished proliferation, and an increase in mitotic failures followed by re-fusion of sister-cells. The method allows tracking of phenotypes in cell lineages, which can be particularly useful in epigenetic studies. Sister-cells were found to have significant similarities in their speeds and morphologies, illustrating the heritability of these traits.

Short cell cycle duration is a phenotype of human epidermal stem cells.

BACKGROUND: A traditional view is that stem cells (SCs) divide slowly. Meanwhile, both embryonic and pluripotent SCs display a shorter cell cycle duration (CCD) in comparison to more committed progenitors (CPs). METHODS: We examined the in vitro proliferation and cycling behavior of somatic adult human cells using live cell imaging of passage zero keratinocytes and single-cell RNA sequencing. RESULTS: We found two populations of keratinocytes: those with short CCD and protracted near exponential growth, and those with long CCD and terminal differentiation. Applying the ergodic principle, the comparative numbers of cycling cells in S phase in an enriched population of SCs confirmed a shorter CCD than CPs. Further, analysis of single-cell RNA sequencing of cycling adult human keratinocyte SCs and CPs indicated a shortening of both G1 and G2M phases in the SC. CONCLUSIONS: Contrary to the pervasive paradigm, SCs progress through cell cycle more quickly than more differentiated dividing CPs. Thus, somatic human adult keratinocyte SCs may divide infrequently, but divide rapidly when they divide. Additionally, it was found that SC-like proliferation persisted in vitro.

Three-dimensional topology-based analysis segments volumetric and spatiotemporal fluorescence microscopy.

Image analysis techniques provide objective and reproducible statistics for interpreting microscopy data. At higher dimensions, three-dimensional (3D) volumetric and spatiotemporal data highlight additional properties and behaviors beyond the static 2D focal plane. However, increased dimensionality carries increased complexity, and existing techniques for general segmentation of 3D data are either primitive, or highly specialized to specific biological structures. Borrowing from the principles of 2D topological data analysis (TDA), we formulate a 3D segmentation algorithm that implements persistent homology to identify variations in image intensity. From this, we derive two separate variants applicable to spatial and spatiotemporal data, respectively. We demonstrate that this analysis yields both sensitive and specific results on simulated data and can distinguish prominent biological structures in fluorescence microscopy images, regardless of their shape. Furthermore, we highlight the efficacy of temporal TDA in tracking cell lineage and the frequency of cell and organelle replication.

Applications of Intravital Imaging in Cancer Immunotherapy.

Currently, immunotherapy is one of the most effective treatment strategies for cancer. However, the efficacy of any specific anti-tumor immunotherapy can vary based on the dynamic characteristics of immune cells, such as their rate of migration and cell-to-cell interactions. Therefore, understanding the dynamics among cells involved in the immune response can inform the optimization and improvement of existing immunotherapy strategies. In vivo imaging technologies use optical microscopy techniques to visualize the movement and behavior of cells in vivo, including cells involved in the immune response, thereby showing great potential for application in the field of cancer immunotherapy. In this review, we briefly introduce the technical aspects required for in vivo imaging, such as fluorescent protein labeling, the construction of transgenic mice, and various window chamber models. Then, we discuss the elucidation of new phenomena and mechanisms relating to tumor immunotherapy that has been made possible by the application of in vivo imaging technology. Specifically, in vivo imaging has supported the characterization of the movement of T cells during immune checkpoint inhibitor therapy and the kinetic analysis of dendritic cell migration in tumor vaccine therapy. Finally, we provide a perspective on the challenges and future research directions for the use of in vivo imaging technology in cancer immunotherapy.