Explore the vast range of titles available.

In fluorescence-activated cell sorting, characteristic target features are labeled with a specific fluorophore, and cells displaying different fluorophores are sorted. Ota et al. describe a technique called ghost cytometry that allows cell sorting based on the morphology of the cytoplasm, labeled with a single-color fluorophore. The motion of cells relative to a patterned optical structure provides spatial information that is compressed into temporal signals, which are sequentially measured by a single-pixel detector. Images can be reconstructed from this spatial and temporal information, but this is computationally costly. Instead, using machine learning, cells are classified directly from the compressed signals, without reconstructing an image. The method was able to separate morphologically similar cell types in an ultrahigh-speed fluorescence imaging–activated cell sorter. Science , this issue p. 1246 Morphology-based cell classification and sorting is achieved at high accuracy and throughput without obtaining images. Ghost imaging is a technique used to produce an object’s image without using a spatially resolving detector. Here we develop a technique we term “ghost cytometry,” an image-free ultrafast fluorescence “imaging” cytometry based on a single-pixel detector. Spatial information obtained from the motion of cells relative to a static randomly patterned optical structure is compressively converted into signals that arrive sequentially at a single-pixel detector. Combinatorial use of the temporal waveform with the intensity distribution of the random pattern allows us to computationally reconstruct cell morphology. More importantly, we show that applying machine-learning methods directly on the compressed waveforms without image reconstruction enables efficient image-free morphology-based cytometry. Despite a compact and inexpensive instrumentation, image-free ghost cytometry achieves accurate and high-throughput cell classification and selective sorting on the basis of cell morphology without a specific biomarker, both of which have been challenging to accomplish using conventional flow cytometers.

The biophysical properties of cells reflect their identities, underpin their homeostatic state in health, and define the pathogenesis of disease. Recent leapfrogging advances in biophysical cytometry now give access to this information, which is obscured in molecular assays, with a discriminative power that was once inconceivable. However, biophysical cytometry should go 'deeper' in terms of exploiting the information-rich cellular biophysical content, generating a molecular knowledge base of cellular biophysical properties, and standardizing the protocols for wider dissemination. Overcoming these barriers, which requires concurrent innovations in microfluidics, optical imaging, and computer vision, could unleash the enormous potential of biophysical cytometry not only for gaining a new mechanistic understanding of biological systems but also for identifying new cost-effective biomarkers of disease. Recent advances in biophysical cytometry now make it possible to recapitulate cellular heterogeneity at the levels of throughput, precision, specificity, and sensitivity that were once inconceivable.Technological developments in state-of-the-art biophysical cytometry include single-cell mass assays, cell traction force assays, deformability and impedance cytometry, and label-free imaging cytometry.Next-generation biophysical cytometry could be more comprehensive and information-rich by exploring multimodal integration, such as simultaneous read-out of cell mass, stiffness, and morphology.How molecular signatures translate into cellular biophysical properties is not fully understood. Advanced techniques involving microfluidics, imaging, and deep learning could investigate this link.Standardizing the protocols and datasets of biophysical cytometry will be crucial to ensure wide dissemination.

This article reports on a conference workshop conducted at CYTO 2018. During the workshop a new Open Science forum \"CYTO Lab Hacks\" has been launched within the International Society for the Advancement of Cytometry (ISAC). Its goal is to serve as an open, transparent, sustainable and accessible forum for innovation-exchange in cytometry. Here we report the captured status quo, the perceived requirements of the members in relation to open innovation sharing and dissemination and publicize the format of \"CYTO Lab Hacks\".

This article reports on a conference workshop conducted at CYTO 2018. During the workshop a new Open Science forum \"CYTO Lab Hacks\" has been launched within the International Society for the Advancement of Cytometry (ISAC). Its goal is to serve as an open, transparent, sustainable and accessible forum for innovation-exchange in cytometry. Here we report the captured status quo, the perceived requirements of the members in relation to open innovation sharing and dissemination and publicize the format of \"CYTO Lab Hacks\".

This article reports on a conference workshop conducted at CYTO 2018. During the workshop a new Open Science forum \"CYTO Lab Hacks\" has been launched within the International Society for the Advancement of Cytometry (ISAC). Its goal is to serve as an open, transparent, sustainable and accessible forum for innovation-exchange in cytometry. Here we report the captured status quo, the perceived requirements of the members in relation to open innovation sharing and dissemination and publicize the format of \"CYTO Lab Hacks\".

Key Points Standardized immunophenotyping assays are a requisite for accomplishing the proposed Human Immunology Project, which involves the comprehensive elucidation of the metrics of healthy versus diseased or perturbed human immune systems. The variables inherent in flow cytometry immunophenotyping are largely known, and include reagent choice, sample handling, instrument setup and data analysis; strategies to mitigate each of these variables are available. Several groups, including the Human Immunophenotyping Consortium, are standardizing reagent panels for flow cytometry. Together with the adoption of such standard panels, an infrastructure for aggregating and mining results will be needed. Availability of such panels and the data-mining infrastructure should result in more rapid biomarker discovery for immunologically relevant diseases. The authors use flow cytometry of peripheral blood mononuclear cells as an example to outline the approaches to assay standardization that will be required to realize the full potential of immunophenotyping as a research tool and in the clinic. The heterogeneity in the healthy human immune system, and the immunological changes that portend various diseases, have been only partially described. Their comprehensive elucidation has been termed the 'Human Immunology Project'. The accurate measurement of variations in the human immune system requires precise and standardized assays to distinguish true biological changes from technical artefacts. Thus, to be successful, the Human Immunology Project will require standardized assays for immunophenotyping humans in health and disease. A major tool in this effort is flow cytometry, which remains highly variable with regard to sample handling, reagents, instrument setup and data analysis. In this Review, we outline the current state of standardization of flow cytometry assays and summarize the steps that are required to enable the Human Immunology Project.

High parameter imaging is an important tool in the life sciences for both discovery and healthcare applications. Imaging Mass Cytometry (IMC) and Multiplexed Ion Beam Imaging (MIBI) are two relatively recent technologies which enable clinical samples to be simultaneously analyzed for up to 40 parameters at subcellular resolution. Importantly, these \"Mass Cytometry Imaging\" (MCI) modalities are being rapidly adopted for studies of the immune system in both health and disease. In this review we discuss, first, the various applications of MCI to date. Second, due to the inherent challenge of analyzing high parameter spatial data, we discuss the various approaches that have been employed for the processing and analysis of data from MCI experiments.

IntroductionCerebral clots arise in various environments such as rapid flow in atherosclerosis, venous stasis, and turbulent flow of atrial fibrillation. Clot pathology evaluation by Martius, Scarlet, and Blue (MSB) staining doesn’t correlate with the etiology, and doesn't allow for a detailed analysis of white blood cells present. In this study, we investigated how clots formed in various flow environments (FE) affect the immune cells within them, using single-cell RNA-seq and flow cytometry. We then evaluated how various FEs lead to differential clot contraction, kinetics, and dynamics in 3D-printed in vitro cerebrovascular clot migration assays.MethodsClots were generated in vitro via a modified Chandler-Loop design (1) at 37°C at static condition, 10 rotations per minute (RPM, low FE) or 40 RPM (high FE) for 1 hour. Single-cell RNA-seq using the 10X Genomics platform was conducted and top 3000 highly variable features were used for principal component analysis (PCA). Multiplex flow cytometry was utilized to validate RNAseq cellular composition analyses. Cerebrovascular 3D-printed in vitro models were utilized to evaluate clot contraction, migration/location and flow obstruction qualities.ResultsTo characterize the WBC clot content, we performed scRNA-seq on clots generated at variable flow. UMAPs were applied to visualize the 20 clusters, and expression patterns were annotated for cellular identities (figure 1A). Enrichment of myeloid cells in the high flow clots vs. enrichment of lymphoid cells in the static clots along with cell identities was validated via multiplex flow cytometry (figure 1C). We next employed 3D-printed cerebral vasculature models to assess clot contraction, kinetics, and dynamics (figure 2), demonstrating significantly increased clot shrinkage (% original by weight) in static clots and significantly more flow obstruction in HF clots. Furthermore, the HF clots consistently migrated less and occluded more proximally than the static clots did (figure 2 B-C).Abstract O-052 Figure 1Abstract O-052 Figure 2ConclusionsOur studies demonstrate that FEs drive variable cellular composition of clots and lead to differential clot qualities that dictate clot migration/location, and extent of vascular occlusion. Understanding these differences can identify novel therapeutic strategies for variable stroke risk factors. Our future directions include functional evaluation of clot burden/qualities by targeting cell types and/or differentially expressed signaling pathways most upregulated at various FEs.DisclosuresY. Ghochani: None. M. Ghovvati: None. T. Imahori: None. E. Tsukagoshi: None. R. Kawaguchi: None. J. Hinman: None. N. Kaneko: None.

As the dimensionality, throughput and complexity of cytometry data increases, so does the demand for user-friendly, interactive analysis tools that leverage high-performance machine learning frameworks. Here we introduce FlowAtlas: an interactive web application that enables dimensionality reduction of cytometry data without down-sampling and that is compatible with datasets stained with non-identical panels. FlowAtlas bridges the user-friendly environment of FlowJo and computational tools in Julia developed by the scientific machine learning community, eliminating the need for coding and bioinformatics expertise. New population discovery and detection of rare populations in FlowAtlas is intuitive and rapid. We demonstrate the capabilities of FlowAtlas using a human multi-tissue, multi-donor immune cell dataset, highlighting key immunological findings. FlowAtlas is available at https://github.com/gszep/FlowAtlas.jl.git .

The EU-supported EuroFlow Consortium aimed at innovation and standardization of immunophenotyping for diagnosis and classification of hematological malignancies by introducing 8-color flow cytometry with fully standardized laboratory procedures and antibody panels in order to achieve maximally comparable results among different laboratories. This required the selection of optimal combinations of compatible fluorochromes and the design and evaluation of adequate standard operating procedures (SOPs) for instrument setup, fluorescence compensation and sample preparation. Additionally, we developed software tools for the evaluation of individual antibody reagents and antibody panels. Each section describes what has been evaluated experimentally versus adopted based on existing data and experience. Multicentric evaluation demonstrated high levels of reproducibility based on strict implementation of the EuroFlow SOPs and antibody panels. Overall, the 6 years of extensive collaborative experiments and the analysis of hundreds of cell samples of patients and healthy controls in the EuroFlow centers have provided for the first time laboratory protocols and software tools for fully standardized 8-color flow cytometric immunophenotyping of normal and malignant leukocytes in bone marrow and blood; this has yielded highly comparable data sets, which can be integrated in a single database.