The evolution of spectral flow cytometry

Nonparametric empirical Bayes biomarker imputation and estimation

Biomarkers are often measured in bulk to diagnose patients, monitor patient conditions, and research novel drug pathways. The measurement of these biomarkers often suffers from detection limits that result in missing and untrustworthy measurements. Frequently, missing biomarkers are imputed so that down-stream analysis can be conducted with modern statistical methods that cannot normally handle data subject to informative censoring. This work develops an empirical Bayesg $$ g $$ -modeling method for imputing and denoising biomarker measurements. We establish superior estimation properties compared to popular methods in simulations and with real data, providing the useful biomarker measurement estimations for down-stream analysis.

Cancer organoids 2.0: modelling the complexity of the tumour immune microenvironment

The development of neoplasia involves a complex and continuous interplay between malignantly transformed cells and the tumour microenvironment (TME). Cancer immunotherapies targeting the immune TME have been increasingly validated in clinical trials but response rates vary substantially between tumour histologies and are often transient, idiosyncratic and confounded by resistance. Faithful experimental models of the patient-specific tumour immune microenvironment, capable of recapitulating tumour biology and immunotherapy effects, would greatly improve patient selection, target identification and definition of resistance mechanisms for immuno-oncology therapeutics. In this Review, we discuss currently available and rapidly evolving 3D tumour organoid models that capture important immune features of the TME. We highlight diverse opportunities for organoid-based investigations of tumour immunity, drug development and precision medicine.

Closing Editorial: Immunophenotyping in Autoimmune Diseases and Cancer 3.0

The mammalian immune system is a Janus-faced network of well-coordinated highly specialized cells and biomolecules [...].

Within- and between-subject biological variation estimates for the enumeration of lymphocyte deep immunophenotyping and monocyte subsets

OBJECTIVES

This study aimed to deliver biological variation (BV) estimates for 25 types of lymphocyte subpopulations subjected to deep immunophenotyping (memory T/B cells, regulatory T cells, etc.) and classical, intermediate, and nonclassical monocyte subsets based on the full spectrum flow cytometry (FS-FCM) and a Biological Variation Data Critical Appraisal Checklist (BIVAC) design.

METHODS

Samples were collected biweekly from 60 healthy Chinese adults over 10 consecutive two-week periods. Each sample was measured in duplicate within a single run for lymphocyte deep immunophenotyping and monocyte subset determination using FS-FCM, including the percentage (%) and absolute count (cells/μL). After trend adjustment, a Bayesian model was applied to deliver the within-subject BV (CVI) and between-subject BV (CVG) estimates with 95 % credibility intervals.

RESULTS

Enumeration (% and cells/μL) for 25 types of lymphocyte deep immunophenotyping and three types of monocyte subset percentages showed considerable variability in terms of CVI and CVG. CVI ranged from 4.23 to 47.47 %. Additionally, CVG ranged between 10.32 and 101.30 %, except for CD4+ effector memory T cells re-expressing CD45RA. No significant differences were found between males and females for CVI and CVG estimates. Nevertheless, the CVGs of PD-1+ T cells (%) may be higher in females than males. Based on the desired analytical performance specification, the maximum allowable imprecision immune parameter was the CD8+PD-1+ T cell (cells/μL), with 23.7 %.

CONCLUSIONS

This is the first study delivering BV estimates for 25 types of lymphocyte subpopulations subjected to deep immunophenotyping, along with classical, intermediate, and nonclassical monocyte subsets, using FS-FCM and adhering to the BIVAC design.

Lessons Learned From Ocular Graft versus Host Disease: An Ocular Surface Inflammatory Disease of Known Time of Onset

ABSTRACT

The ocular surface inflammatory disorders (OSIDs) comprise a group of conditions characterized by persistent inflammation of the ocular surface and adnexal tissues. Systemic autoimmune diseases and hypersensitivity reactions cause them, and, if left untreated, can result in severe inflammatory dry eye, corneal damage, and vision loss. Ocular graft-versus-host disease (oGVHD) forms part of the ocular surface inflammatory disease umbrella. It is a condition occurring after allogeneic hematopoietic stem cell or bone marrow transplantation, usually in chronic graft-versus-host disease. oGVHD can virtually affect any ocular adnexal tissue, especially the meibomian glands, and cause persistent inflammation, tissue fibrosis, and subsequent chronic, severe dry eye disease. Among the OSIDs, oGVHD has the particularity that it has a "time zero," meaning we know when the disease started. As such, preclinical models have leveraged this to investigate the molecular mechanisms involved in the damage oGVHD causes to the ocular surface. In oGVHD, establishing a "time zero" allows for predicting the clinical course and establishing adequate treatment. This is also possible because the inflammatory infiltration occurs in ocular surface tissues, which are readily accessible. Using oGVHD, we might be able to understand the immune response mechanisms in other OSIDs better (i.e., Sjögren syndrome, Stevens-Johnson syndrome, among others). This review presents an up-to-date overview of the pathogenesis, clinical presentation, and treatment of oGVHD. In addition, we will discuss the value of the "time zero" concept in the study of oGVHD.

Characterization of Human B Cell Hematological Malignancies Using Protein-Based Approaches

The maturation of B cells is a complex, multi-step process. During B cell differentiation, errors can occur, leading to the emergence of aberrant versions of B cells that, finally, constitute a malignant tumor. These B cell malignancies are classified into three main groups: leukemias, myelomas, and lymphomas, the latter being the most heterogeneous type. Since their discovery, multiple biological studies have been performed to characterize these diseases, aiming to define their specific features and determine potential biomarkers for diagnosis, stratification, and prognosis. The rise of advanced -omics approaches has significantly contributed to this end. Notably, proteomics strategies appear as promising tools to comprehensively profile the final molecular effector of these cells. In this narrative review, we first introduce the main B cell malignancies together with the most relevant proteomics approaches. Then, we describe the core studies conducted in the field and their main findings and, finally, we evaluate the advantages and drawbacks of flow cytometry, mass cytometry, and mass spectrometry for the profiling of human B cell disorders.

B cells and the stressed brain: emerging evidence of neuroimmune interactions in the context of psychosocial stress and major depression

The immune system has emerged as a key regulator of central nervous system (CNS) function in health and in disease. Importantly, improved understanding of immune contributions to mood disorders has provided novel opportunities for the treatment of debilitating stress-related mental health conditions such as major depressive disorder (MDD). Yet, the impact to, and involvement of, B lymphocytes in the response to stress is not well-understood, leaving a fundamental gap in our knowledge underlying the immune theory of depression. Several emerging clinical and preclinical findings highlight pronounced consequences for B cells in stress and MDD and may indicate key roles for B cells in modulating mood. This review will describe the clinical and foundational observations implicating B cell-psychological stress interactions, discuss potential mechanisms by which B cells may impact brain function in the context of stress and mood disorders, describe research tools that support the investigation of their neurobiological impacts, and highlight remaining research questions. The goal here is for this discussion to illuminate both the scope and limitations of our current understanding regarding the role of B cells, stress, mood, and depression.

Spectral flow cytometry: Fundamentals and future impact

Spectral flow cytometry has emerged as a significant player in the cytometry marketplace, with the potential for rapid growth. Despite a slow start, the technology has made significant strides in advancing various areas of single-cell analysis utilized by the scientific community. The integration of spectral cytometry into clinical laboratories and diagnostic processes is currently underway and is expected to garner a significant level of widespread acceptance in the near future. However, incorporating a new methodological approach into existing research programs can lead to misunderstandings or even misuse. This chapter offers an introductory yet comprehensive explanation of the scientific principles that form the foundation of spectral cytometry. Specifically, it delves into the unmixing processes that are utilized for data analysis. This overview is designed for those who are new to the field and seeking an informative guide to this exciting emerging technology.

Application of Mass Cytometry Platforms to Solid Organ Transplantation

Transplantation serves as the cornerstone of treatment for patients with end-stage organ disease. The prevalence of complications, such as allograft rejection, infection, and malignancies, underscores the need to dissect the complex interactions of the immune system at the single-cell level. In this review, we discuss studies using mass cytometry or cytometry by time-of-flight, a cutting-edge technology enabling the characterization of immune populations and cell-to-cell interactions in granular detail. We review the application of mass cytometry in human and experimental animal studies in the context of transplantation, uncovering invaluable contributions of the tool to understanding rejection and other transplant-related complications. We discuss recent innovations that have the potential to streamline and standardize mass cytometry workflows for application to multisite clinical trials. Additionally, we introduce imaging mass cytometry, a technique that couples the power of mass cytometry with spatial context, thereby mapping cellular interactions within tissue microenvironments. The synergistic integration of mass cytometry and imaging mass cytometry data with other omics data sets and high-dimensional data platforms to further define immune dynamics is discussed. In conclusion, mass cytometry technologies, when integrated with other tools and data, shed light on the intricate landscape of the immune response in transplantation. This approach holds significant potential for enhancing patient outcomes by advancing our understanding and facilitating the development of new diagnostics and therapeutics.

Systems biology of B cells in COVID-19

The integration of multi-'omic datasets into complex systems-wide assessments has become a mainstay in immunologic investigation. This focus on high-dimensional data collection and analysis was on full display in the investigation of COVID-19, the respiratory illness resulting from infection by the novel coronavirus SARS-CoV-2. Particularly in the area of B cell biology, tremendous efforts in both cellular and serologic investigation have resulted in an increasingly detailed mapping of the coordinated effector, memory, and antibody secreting cell responses that underpin the development of humoral immunity in response to primary viral infection. Further, the rapid development and deployment of effective vaccines has allowed for the assessment of developing memory responses across a wide variety of immune contexts, including in patients with compromised immune function. The result has been a period of rapid gains in the understanding of B cell biology unrestricted to the study of COVID-19. Here, we outline the systems-level technologies that have been routinely implemented in these investigations throughout the pandemic, and discuss how their use has led to clear and applicable gains in pursuance of the amelioration of human infectious disease and beyond.

Validation of Artificial Intelligence (AI)-Assisted Flow Cytometry Analysis for Immunological Disorders

Flow cytometry is a vital diagnostic tool for hematologic and immunologic disorders, but manual analysis is prone to variation and time-consuming. Over the last decade, artificial intelligence (AI) has advanced significantly. In this study, we developed and validated an AI-assisted flow cytometry workflow using 379 clinical cases from 2021, employing a 3-tube, 10-color flow panel with 21 antibodies for primary immunodeficiency diseases and related immunological disorders. The AI software (DeepFlow™, version 2.1.1) is fully automated, reducing analysis time to under 5 min per case. It interacts with hematopatholoists for manual gating adjustments when necessary. Using proprietary multidimensional density-phenotype coupling algorithm, the AI model accurately classifies and enumerates T, B, and NK cells, along with important immune cell subsets, including CD4+ helper T cells, CD8+ cytotoxic T cells, CD3+/CD4-/CD8- double-negative T cells, and class-switched or non-switched B cells. Compared to manual analysis with hematopathologist-determined lymphocyte subset percentages as the gold standard, the AI model exhibited a strong correlation (r > 0.9) across lymphocyte subsets. This study highlights the accuracy and efficiency of AI-assisted flow cytometry in diagnosing immunological disorders in a clinical setting, providing a transformative approach within a concise timeframe.

Laser Sources for Traditional and Spectral Flow Cytometry

Lasers for light scattering measurement and fluorescence excitation are essential components of all flow cytometers. Flow cytometers now typically rely on multiple laser wavelengths allowing excitation of a constantly increasing variety of fluorescent probes. The expanding use of spectral flow cytometry to increase the magnitude of multiparametric analysis is also changing the significance of laser choice in cytometry. In this chapter, we review the lasers available for flow cytometry and provide guidance in choosing laser wavelengths and characteristics to best match the needs of modern cell analysis by both conventional and spectral cytometry. We also discuss the recent advances in laser technology as the push to expand the palette of laser wavelength for cytometry continues.

Squeezed state in the hydrodynamic focusing regime for Escherichia coli bacteria detection

Flow cytometry is an essential technique in single particle analysis and cell sorting for further downstream diagnosis, exhibiting high-throughput and multiplexing capabilities for many biological and biomedical applications. Although many hydrodynamic focusing-based microfluidic cytometers have been demonstrated with reduced size and cost to adapt to point-of-care settings, the operating conditions are not characterized systematically. This study presents the flow transition process in the hydrodynamic focusing mechanism when the flow rate or the Reynolds number increases. The characteristics of flow fields and mass transport were studied under various operating conditions, including flow rates and microchannel heights. A transition from the squeezed focusing state to the over-squeezed anti-focusing state in the hydrodynamic focusing regime was observed when the Reynolds number increased above 30. Parametric studies illustrated that the focusing width increased with the Reynolds number but decreased with the microchannel height in the over-squeezed state. The microfluidic cytometric analyses using microbeads and E. coli show that the recovery rate was maintained by limiting the Reynolds number to 30. The detailed analysis of the flow transition will provide new insight into microfluidic cytometric analyses with a broad range of applications in food safety, water monitoring and healthcare sectors.

Multicompartmental analysis of the murine pulmonary immune response by spectral flow cytometry

Studies of pulmonary inflammation require unique considerations due to the complex structure and composition of the lungs. The lungs have multiple compartments and diverse immune cell populations, with inherently high autofluorescence, and are involved in the host response to pulmonary pathogens. We describe a protocol that accounts for these factors through a novel combination of methodologies-in vivo compartmental analysis and spectral flow cytometry with a broad panel of antibodies. In vivo compartmental analysis enables the precise localization of immune cells within the marginated vasculature, lung interstitium, nonlavageable airways, and lavageable airways of the lungs, as well as the pulmonary lymph nodes. Spectral flow cytometry with a broad panel of antibodies supports an unbiased exploratory approach to investigating diverse immune cell populations during pulmonary inflammation. Most importantly, spectral flow uses cellular autofluorescence to aid in the resolution and identification of immune cell populations. This methodology enables the acquisition of high-quality data compatible with informed gating and dimensionality reduction algorithms. In addition, our protocol emphasizes considerations for compartmentalization of the inflammatory response, spectral flow panel design, and autofluorescence spectra analysis. These methodologies are critical for increasing the rigor of pulmonary research. We apply this protocol for the precise characterization and localization of leukocytes in the pulmonary host response to influenza A virus in C57BL/6J mice. In particular, we demonstrate that this protocol improves the quantification and localization of alveolar macrophages within the airways. The methodology is modifiable and expandable to allow for further characterization of leukocyte populations of special interest.NEW & NOTEWORTHY We describe a novel combination of methodologies that incorporates dual in vivo compartmental analysis using intravascular and intratracheal CD45 labeling, a broad panel of antibodies for identifying lymphoid and nonlymphoid cells, and spectral flow cytometry that uses cellular autofluorescence to aid in resolving and identifying immune cell populations. This methodology allows precise localization of immune cells in the lavageable airways, nonlavageable airways, interstitial lung tissue, and marginated in the lung vasculature.

High-Throughput Single-Cell Analysis of Nanoparticle-Cell Interactions

Understanding nanoparticle-cell interactions at single-nanoparticle and single-cell resolutions is crucial to improving the design of next-generation nanoparticles for safer, more effective, and more efficient applications in nanomedicine. This review focuses on recent advances in the continuous high-throughput analysis of nanoparticle-cell interactions at the single-cell level. We highlight and discuss the current trends in continual flow high-throughput methods for analyzing single cells, such as advanced flow cytometry techniques and inductively coupled plasma mass spectrometry methods, as well as their intersection in the form of mass cytometry. This review further discusses the challenges and opportunities with current single-cell analysis approaches and provides proposed directions for innovation in the high-throughput analysis of nanoparticle-cell interactions.

Evolving Approach to Clinical Cytometry for Immunodeficiencies and Other Immune Disorders

Primary immunodeficiencies were initially identified on the basis of recurrent, severe or unusual infections. Subsequently, it was noted that these diseases can also manifest with autoimmunity, autoinflammation, allergy, lymphoproliferation and malignancy, hence a conceptual change and their renaming as inborn errors of immunity. Ongoing advances in flow cytometry provide the opportunity to expand or modify the utility and scope of existing laboratory tests in this field to mirror this conceptual change. Here we have used the B cell subset, variably known as CD21low B cells, age-associated B cells and T-bet+ B cells, as an example to demonstrate this possibility.

Flow Cytometry: The Next Revolution

Unmasking the subtleties of the immune system requires both a comprehensive knowledge base and the ability to interrogate that system with intimate sensitivity. That task, to a considerable extent, has been handled by an iterative expansion in flow cytometry methods, both in technological capability and also in accompanying advances in informatics. As the field of fluorescence-based cytomics matured, it reached a technological barrier at around 30 parameter analyses, which stalled the field until spectral flow cytometry created a fundamental transformation that will likely lead to the potential of 100 simultaneous parameter analyses within a few years. The simultaneous advance in informatics has now become a watershed moment for the field as it competes with mature systematic approaches such as genomics and proteomics, allowing cytomics to take a seat at the multi-omics table. In addition, recent technological advances try to combine the speed of flow systems with other detection methods, in addition to fluorescence alone, which will make flow-based instruments even more indispensable in any biological laboratory. This paper outlines current approaches in cell analysis and detection methods, discusses traditional and microfluidic sorting approaches as well as next-generation instruments, and provides an early look at future opportunities that are likely to arise.

Full spectrum flow cytometry in the clinical laboratory

Contemporary full spectrum or "spectral" flow cytometry is a recently developed technology that allows for high-dimensional flow cytometric analyses of cells and particles in suspension. This single-cell technology has gained popularity in research settings because it can conservatively detect 35 or more antigens simultaneously in a single-tube assay format. Recently, spectral flow cytometry has obtained regulatory approval for use as an in vitro diagnostic device in China and Europe, enabling use of this technology in some clinical flow cytometry laboratories. The purpose of this review is to describe the basic principles of conventional and spectral flow cytometry, contrasting these two technologies. To illustrate the analytic power of spectral flow cytometry, we provide an example of spectral flow cytometry data analyses and the use of a machine learning algorithm to harvest the vast amount of information contained within large spectral flow cytometry datasets. Finally, we discuss the advantages of spectral flow cytometry adoption in clinical laboratories and preliminary studies comparing the performance of this technology relative to conventional flow cytometers that are currently used in clinical laboratory environments.

Extensive flow cytometric immunophenotyping of human PBMC incorporating detection of chemokine receptors, cytokines and tetramers

Characterization of immune cells is essential to advance our understanding of immunology and flow cytometry is an important tool in this context. Addressing both cellular phenotype and antigen-specific functional responses of the same cells is valuable to achieve a more integrated understanding of immune cell behavior and maximizes information obtained from precious samples. Until recently, panel size was limiting, resulting in panels generally focused on either deep immunophenotyping or functional readouts. Ongoing developments in the field of (spectral) flow cytometry have made panels of 30⁺ markers more accessible, opening up possibilities for advanced integrated analyses. Here, we optimized immune phenotyping by co-detection of markers covering chemokine receptors, cytokines and specific T cell/peptide tetramer interaction using a 32-color panel. Such panels enable integrated analysis of cellular phenotypes and markers assessing the quality of immune responses and will contribute to our understanding of the immune system.

Development of Spectral Nano-Flow Cytometry for High-Throughput Multiparameter Analysis of Individual Biological Nanoparticles

Correlated analysis of multiple biochemical parameters at the single-particle level and in a high-throughput manner is essential for insights into the diversity and functions of biological nanoparticles (BNPs), such as bacteria and subcellular organelles. To meet this challenge, we developed a highly sensitive spectral nano-flow cytometer (S-nFCM) by integrating a spectral recording module to a laboratory-built nFCM that is 4-6 orders of magnitude more sensitive in side scattering detection and 1-2 orders of magnitude more sensitive in fluorescence detection than conventional flow cytometers. An electron-multiplying charge-coupled device (EMCCD) was used to acquire the full fluorescence spectra of single BNPs upon holographic grating dispersion. Up to 10,000 spectra can be collected in 1 min with 2.1 nm resolution. The precision, linearity, and sensitivity were examined. Complete discernment of single influenza viruses against the background signal, discrimination of different strains of marine cyanobacteria in a mixed sample based on their spectral properties of natural fluorescence, classification of bacterial categories exhibiting different patterns of antigen expression, and multiparameter analysis of single mitochondria for drug discovery were successfully demonstrated.

Platelet Phenotyping by Full Spectrum Flow Cytometry

Platelets play key roles in hemostasis, immunity, and inflammation, and tests of platelet phenotype and function are useful in studies of disease biology and pathology. Full spectrum flow cytometry offers distinct advantages over standard tests and enables the sensitive and simultaneous detection of many biomarkers. A typical assay provides a wealth of information on platelet biology and allows the assessment of in vivo activation and in vitro reactivity, as well as the discovery of novel phenotypes. Here, we describe the analysis of platelets by full spectrum flow cytometry and discuss a range of controls and methods for interpreting results. © 2023 Wiley Periodicals LLC. Basic Protocol: Platelet phenotyping by full spectrum flow cytometry Support Protocol 1: Spectral unmixing Support Protocol 2: Data preprocessing.

Prism Design for Spectral Flow Cytometry

Flow cytometers are instruments used for the rapid quantitative analysis of cell suspension. Traditional flow cytometry uses multi-channel filters to detect fluorescence, whereas full-spectrum fluorescence based on dispersion detection is a more effective and accurate method. The application of various dispersion schemes in flow cytometry spectroscopy has been studied. From the perspective of modern detectors and demand for the miniaturization of flow cytometry, prism dispersion exhibits higher and more uniform light energy utilization, meaning that it is a more suitable dispersion method for small flow cytometers, such as microfluidic flow cytometers. Prism dispersion designs include the size, number, and placement of prisms. By deducing the formula of the final position of light passing through the prism and combining it with the formula of transmittance, the design criteria of the top angle and the incident angle of the prism in pursuit of the optimum transmittance and dispersion index can be obtained. Considering the case of multiple prisms, under the premise of pursuing a smaller size, the optimal design criteria for dispersion system composed of multiple prisms can be obtained. The design of prism dispersion fluorescence detection was demonstrated with a microfluidic flow cytometer, and the effectiveness of the design results was verified by microsphere experiments and practical biological experiments. This design criterion developed in this study is generally applicable to spectral flow cytometers.

Automating the High-Throughput Screening of Protein-Based Optical Indicators and Actuators

Over the last 25 years, protein engineers have developed an impressive collection of optical tools to interface with biological systems: indicators to eavesdrop on cellular activity and actuators to poke and prod native processes. To reach the performance level required for their downstream applications, protein-based tools are usually sculpted by iterative rounds of mutagenesis. In each round, libraries of variants are made and evaluated, and the most promising hits are then retrieved, sequenced, and further characterized. Early efforts to engineer protein-based optical tools were largely manual, suffering from low throughput, human error, and tedium. Here, we describe approaches to automating the screening of libraries generated as colonies on agar, multiwell plates, and pooled populations of single-cell variants. We also briefly discuss emerging approaches for screening, including cell-free systems and machine learning.

Flow Cytometry - Sophisticated Tool for Basic Research or/and Routine Diagnosis; Impact of the Complementarity in Both Pre- as Well as Clinical Studies

Flow cytometry is a sophisticated technology used widely in both basic research and as a routine tool in clinical diagnosis. The technology has progressed from single parameter detection in the 1970s and 1980s to high end multicolor analysis, with currently 30 parameters detected simultaneously, allowing the identification and purification of rare subpopulations of cells of interest. Flow cytometry continues to evolve and expand to facilitate the investigation of new diagnostic and therapeutic avenues. The present review gives an overview of basic theory and instrumentation, presents and compares the advantages and disadvantages of conventional, spectral and imaging flow cytometry as well as mass cytometry. Current methodologies and applications in both research, pre- and clinical settings are discussed, as well as potential limitations and future evolution. This finding encourages the reader to promote such relationship between basic science, diagnosis and multidisciplinary approach since the standard methods have limitations (e.g., in differentiating the cells after staining). Moreover, such path inspires future cytometry specialists develop new/alternative frontiers between pre- and clinical diagnosis and be more flexible in designing the study for both human as well as veterinary medicine.

Cross-platform immunophenotyping of human peripheral blood mononuclear cells with four high-dimensional flow cytometry panels

Immunophenotyping using high dimensional flow cytometry is a central component of human immune system multi-omic studies. We present four high parameter flow cytometry panels for deep immunophenotyping of human peripheral blood mononuclear cells (PBMC). This set of four 25+ color panels include 64 cell surface markers to resolve broad immune compartment populations, as well as activation and memory of specific T, B, natural killer (NK), and myeloid lineages. Common lineage bridging markers are integrated into each panel to allow for inter-panel quality control through major lineage frequency verification. These panels were developed using a five laser BD Symphony A5 conventional cytometer and successfully transferred to a five laser Cytek Aurora spectral cytometer capable of acquiring the panels. Nine representative PBMC samples were stained with the four phenotyping panels and acquired on both instruments to evaluate population frequency and visual staining patterns for gating between the systems. Both instruments produced comparable high quality flow cytometry data and supported our decision to acquire samples on the spectral cytometer moving forward. This modular set of panels and instrument performance metrics provide guidelines for designing flow cytometry experiments suitable for longitudinal or cross-sectional immune profiling.

Revealing the Dynamics of Mitochondrial Microenvironment during Apoptosis under Two-photon Fluorescence Lifetime Microscopy by a Cyclic Iridium (III) Complex

Mitochondria-mediated apoptosis is a major mode of cell death and is inextricably linked to various pathological processes such as tumorigenesis. However, there is still a paucity of non-toxic tools that...