Unexplained Recurrent Pregnancy Loss: Clinical Application of Immunophenotyping

PROBLEM

Recurrent pregnancy loss (RPL) is defined as the failure of two or more pregnancies and affects approximately 5% of couples, often without a clear cause. The etiologies of RPL include factors such as maternal age, endocrine dysfunction, uterine abnormalities, chromosomal abnormalities, thrombophilias, infections, and autoimmune disorders. However, these conditions account for only 50%-60% of RPL cases. Research has explored whether an altered immune system, compared to the physiological state, may be linked to RPL. This review aims to determine whether specific immunophenotypes are associated with unexplained Recurrent Pregnancy Loss (uRPL) and whether targeted therapies addressing specific immunophenotypic alterations can improve pregnancy outcomes.

METHODS

A literature review was conducted using Pubmed/Medline, Scopus, and Embase databases, analyzing data from 95 articles published between 2001 and 2023. The roles of various cells of the immune system (B lymphocytes, T lymphocytes, natural killer cells, macrophages) in different tissues (peripheral blood, menstrual blood) were specifically investigated in women with uRPL.

DISCUSSION AND CONCLUSION

Specific immunophenotypes have been demonstrated to be associated with this condition. However, there is a need to standardize immunophenotyping assays and conduct more trials to stratify RPL risk and improve potential therapeutic strategies.

Flow cell sorting followed by PCR-based clonality testing may assist in questionable diagnosis and monitoring of acute lymphoblastic leukemia

INTRODUCTION

Multicolor flow cytometry (MFC) has highly reliable and flexible algorithms for diagnosis and monitoring of acute lymphoblastic leukemia (ALL). However, MFC analysis can be affected by poor sample quality or novel therapeutic options (e.g., targeted therapies and immunotherapy). Therefore, an additional confirmation of MFC data may be needed. We propose a simple approach for validation of MFC findings in ALL by sorting questionable cells and analyzing immunoglobulin/T-cell receptor (IG/TR) gene rearrangements via EuroClonality-based multiplex PCR.

PATIENTS AND METHODS

We obtained questionable MFC results for 38 biological samples from 37 patients. In total, 42 cell populations were isolated by flow cell sorting for downstream multiplex PCR. Most of the patients (n = 29) had B-cell precursor ALL and were investigated for measurable residual disease (MRD); 79% of them received CD19-directed therapy (blinatumomab or CAR-T).

RESULTS

We established the clonal nature of 40 cell populations (95.2%). By using this technique, we confirmed very low MRD levels (<0.01% MFC-MRD). We also applied it to several ambiguous findings for diagnostic samples, including those with mixed-phenotype acute leukemia, and the results obtained impacted the final diagnosis.

CONCLUSION

We have demonstrated possibilities of a combined approach (cell sorting and PCR-based clonality assessment) to validate MFC findings in ALL. The technique is easy to implement in diagnostic and monitoring workflows, as it does not require isolation of a large number of cells and knowledge of individual clonal rearrangements. We believe it provides important information for further treatment.

Label-free microfluidic cell sorting and detection for rapid blood analysis

Blood tests are considered as standard clinical procedures to screen for markers of diseases and health conditions. However, the complex cellular background (>99.9% RBCs) and biomolecular composition often pose significant technical challenges for accurate blood analysis. An emerging approach for point-of-care blood diagnostics is utilizing "label-free" microfluidic technologies that rely on intrinsic cell properties for blood fractionation and disease detection without any antibody binding. A growing body of clinical evidence has also reported that cellular dysfunction and their biophysical phenotypes are complementary to standard hematoanalyzer analysis (complete blood count) and can provide a more comprehensive health profiling. In this review, we will summarize recent advances in microfluidic label-free separation of different blood cell components including circulating tumor cells, leukocytes, platelets and nanoscale extracellular vesicles. Label-free single cell analysis of intrinsic cell morphology, spectrochemical properties, dielectric parameters and biophysical characteristics as novel blood-based biomarkers will also be presented. Next, we will highlight research efforts that combine label-free microfluidics with machine learning approaches to enhance detection sensitivity and specificity in clinical studies, as well as innovative microfluidic solutions which are capable of fully integrated and label-free blood cell sorting and analysis. Lastly, we will envisage the current challenges and future outlook of label-free microfluidics platforms for high throughput multi-dimensional blood cell analysis to identify non-traditional circulating biomarkers for clinical diagnostics.

External quality assessment of flow cytometric bronchoalveolar lavage cellular analysis: 20 years' experience in The Netherlands

BACKGROUND

Bronchoalveolar (BAL) cellular analysis can be supportive in the diagnosis of interstitial lung disease. The flow cytometric analysis of BAL fluid cells is complicated by cell fragility and adherence and autofluorescence of macrophages, making conventional analysis of BAL fluid cells as done in external quality schemes (EQA) for blood lymphocyte subsets, not representative. Following a procedure for stabilized BAL cells, a separate EQA was set up. The results of 20 years' experience are presented.

METHODS

From each round between 2000 and 2020 the following flow cytometric parameters were recorded from each participant: total lymphocyte population (TLY), CD3+ lymphocytes, CD3+ CD4+ lymphocytes, CD3+ CD8+ lymphocytes, CD3- CD16+/56+ lymphocytes, CD19+ lymphocytes and CD103 + CD3+ lymphocytes. In addition, the eosinophils and neutrophils were recorded. The mean and standard deviation of each parameter per round were calculated. The 40 rounds were divided in four respective groups of 10 in order to compare the results as function of time. In addition the interpretation of the results of participants was scored.

RESULTS

The median SD in the four groups was below 10% for all parameters except for TLY and the CD103+ CD3+ lymphocytes. No improvement in time was observed for any (sub)population except for the CD3+ CD4+ subset. Interpretation of the results varied based on disease, with greatest consensus for sarcoidosis cases and lowest for nonspecific interstitial lung disease cases.

CONCLUSIONS

A dedicated EQA for BAL fluid cellular analysis appears to be justified as the test material is substantially different from that of peripheral blood. We show that adequate analytical and post-analytical quality control can be achieved.

Developments of Conventional and Microfluidic Flow Cytometry Enabling High-Throughput Characterization of Single Cells

This article first reviews scientific meanings of single-cell analysis by highlighting two key scientific problems: landscape reconstruction of cellular identities during dynamic immune processes and mechanisms of tumor origin and evolution. Secondly, the article reviews clinical demands of single-cell analysis, which are complete blood counting enabled by optoelectronic flow cytometry and diagnosis of hematologic malignancies enabled by multicolor fluorescent flow cytometry. Then, this article focuses on the developments of optoelectronic flow cytometry for the complete blood counting by comparing conventional counterparts of hematology analyzers (e.g., DxH 900 of Beckman Coulter, XN-1000 of Sysmex, ADVIA 2120i of Siemens, and CELL-DYN Ruby of Abbott) and microfluidic counterparts (e.g., microfluidic impedance and imaging flow cytometry). Future directions of optoelectronic flow cytometry are indicated where intrinsic rather than dependent biophysical parameters of blood cells must be measured, and they can replace blood smears as the gold standard of blood analysis in the near future.

Prototype Smartphone-Based Device for Flow Cytometry with Immunolabeling via Supra-nanoparticle Assemblies of Quantum Dots

Methods for the detection, enumeration, and typing of cells are important in many areas of research and healthcare. In this context, flow cytometers are a widely used research and clinical tool but are also an example of a large and expensive instrument that is limited to specialized laboratories. Smartphones have been shown to have excellent potential to serve as portable and lower-cost platforms for analyses that would normally be done in a laboratory. Here, we developed a prototype smartphone-based flow cytometer (FC). This compact 3D-printed device incorporated a laser diode and a microfluidic flow cell and used the built-in camera of a smartphone to track immunofluorescently labeled cells in suspension and measure their color. This capability was enabled by high-brightness supra-nanoparticle assemblies of colloidal semiconductor quantum dots (SiO₂@QDs) as well as a support vector machine (SVM) classification algorithm. The smartphone-based FC device detected and enumerated target cells against a background of other cells, simultaneously and selectively counted two different cell types in a mixture, and used multiple colors of SiO₂@QD-antibody conjugates to screen for and identify a particular cell type. The potential limits of multicolor detection are discussed alongside ideas for further development. Our results suggest that innovations in materials and engineering should enable eventual smartphone-based FC assays for clinical applications.

Terahertz Spectroscopic Analysis in Protein Dynamics: Current Status

Proteins play a key role in living organisms. The study of proteins and their dynamics provides information about their functionality, catalysis and potential alterations towards pathological diseases. Several techniques are used for studying protein dynamics, e.g., magnetic resonance, fluorescence imaging techniques, mid-infrared spectroscopy and biochemical assays. Spectroscopic analysis, based on the use of terahertz (THz) radiation with frequencies between 0.1 and 15 THz (3–500 cm−1), was underestimated by the biochemical community. In recent years, however, the potential of THz spectroscopy in the analysis of both simple structures, such as polypeptide molecules, and complex structures, such as protein complexes, has been demonstrated. The THz absorption spectrum provides some information on proteins: for small molecules the THz spectrum is dominated by individual modes related to the presence of hydrogen bonds. For peptides, the spectral information concerns their secondary structure, while for complex proteins such as globular proteins and viral glycoproteins, spectra also provide information on collective modes. In this short review, we discuss the results obtained by THz spectroscopy in the protein dynamics investigations. In particular, we will illustrate advantages and applications of THz spectroscopy, pointing out the complementary information it may provide.

Introduction to Multiparametric Flow Cytometry and Analysis of High-Dimensional Data

Multiparametric flow cytometry is a technique utilized in translational experiments that utilizes fluorescently tagged antibodies and functional fluorescent dyes to measure proteins on the surface or in the cytoplasm of cells and to measure processes occurring within cells themselves. These fluorescent molecules, or fluorophores, can be tagged to antibodies to measure specific biological molecules such as proteins inside or on the surface of cells. Small organic compounds such as the nucleic acid binding dye propidium iodide (PI) can permeate compromised cell membranes when cells are no longer viable or used to measure DNA content of cycling cells. Successful completion of flow cytometry experiments requires expertise in both the preparation of the samples, acquisition of the samples on instruments, and analyses of the results. This chapter describes the principles needed to conduct a successful multiparameter flow cytometry experiment needed for drug development with references to well established internet resources that are useful to those less experienced in the field. In addition, we provide a brief introduction to data analysis including complex analysis of 10+ parameters simultaneously. These high-dimensional datasets require novel methods for analysis due to the volume of data collected, which are also introduced in this chapter.

SCHNEL: scalable clustering of high dimensional single-cell data

MOTIVATION

Single cell data measures multiple cellular markers at the single-cell level for thousands to millions of cells. Identification of distinct cell populations is a key step for further biological understanding, usually performed by clustering this data. Dimensionality reduction based clustering tools are either not scalable to large datasets containing millions of cells, or not fully automated requiring an initial manual estimation of the number of clusters. Graph clustering tools provide automated and reliable clustering for single cell data, but suffer heavily from scalability to large datasets.

RESULTS

We developed SCHNEL, a scalable, reliable and automated clustering tool for high-dimensional single-cell data. SCHNEL transforms large high-dimensional data to a hierarchy of datasets containing subsets of data points following the original data manifold. The novel approach of SCHNEL combines this hierarchical representation of the data with graph clustering, making graph clustering scalable to millions of cells. Using seven different cytometry datasets, SCHNEL outperformed three popular clustering tools for cytometry data, and was able to produce meaningful clustering results for datasets of 3.5 and 17.2 million cells within workable time frames. In addition, we show that SCHNEL is a general clustering tool by applying it to single-cell RNA sequencing data, as well as a popular machine learning benchmark dataset MNIST.

AVAILABILITY AND IMPLEMENTATION

Implementation is available on GitHub (https://github.com/biovault/SCHNELpy). All datasets used in this study are publicly available.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Preserving Single Cells in Space and Time for Analytical Assays

Analytical assays performed within clinical laboratories influence roughly 70% of all medical decisions by facilitating disease detection, diagnosis, and management. Both in clinical and academic research laboratories, single-cell assays permit measurement of cell diversity and identification of rare cells, both of which are important in the understanding of disease pathogenesis. For clinically utility, the single-cell assays must be compatible with the clinical workflow steps of sample collection, sample transportation, pre-analysis processing, and single-cell assay; therefore, it is paramount to preserve cells in a state that resembles that in vivo rather than measuring signaling behaviors initiated in response to stressors such as sample collection and processing. To address these challenges, novel cell fixation (and more broadly, cell preservation) techniques incorporate programmable fixation times, reversible bond formation and cleavage, chemoselective reactions, and improved analyte recovery. These technologies will further the development of individualized, precision therapies for patients to yield improved clinical outcomes.

DNA Repair Molecular Beacon assay: a platform for real-time functional analysis of cellular DNA repair capacity

Numerous studies have shown that select DNA repair enzyme activities impact response and/or toxicity of genotoxins, suggesting a requirement for enzyme functional analyses to bolster precision medicine or prevention. To address this need, we developed a DNA Repair Molecular Beacon (DRMB) platform that rapidly measures DNA repair enzyme activity in real-time. The DRMB assay is applicable for discovery of DNA repair enzyme inhibitors, for the quantification of enzyme rates and is sufficiently sensitive to differentiate cellular enzymatic activity that stems from variation in expression or effects of amino acid substitutions. We show activity measures of several different base excision repair (BER) enzymes, including proteins with tumor-identified point mutations, revealing lesion-, lesion-context- and cell-type-specific repair dependence; suggesting application for DNA repair capacity analysis of tumors. DRMB measurements using lysates from isogenic control and APE1-deficient human cells suggests the major mechanism of base lesion removal by most DNA glycosylases may be mono-functional base hydrolysis. In addition, development of a microbead-conjugated DRMB assay amenable to flow cytometric analysis further advances its application. Our studies establish an analytical platform capable of evaluating the enzyme activity of select DNA repair proteins in an effort to design and guide inhibitor development and precision cancer therapy options.

Proof of Concept for an Automated Image Analysis Method to Quantify Rat Bone Marrow Hematopoietic Lineages on H&E Sections

The bone marrow is an important site for assessment of the hematopoietic toxicity of new drug candidates. Here, we extended our previous work, where we developed a computer algorithm to automatically quantitate overall bone marrow cell density by analyzing digitized images of standard hematoxylin and eosin (H&E) slides of rat bone marrow and further evaluated the capability to quantify myeloid: erythroid + lymphoid (M:EL) ratio and megakaryocyte cell density. We tested the algorithm in a toxicity study, where rats were dosed with two molecules known to affect bone marrow composition, monomethyl auristatin E, and a Bcl-xL inhibitor. The image analysis method detected significant changes in M:EL and megakaryocyte number that were either not found or semiquantitatively described by manual microscopic observation of the same slides. The image analysis results were consistent with other more established but time-consuming methods that measure changes in bone marrow cell composition: smear cytology, flow cytometry, and microscopic assessment. Our work demonstrates the feasibility of a rapid and more quantitative assessment of changes in bone marrow cell lineage composition using a computer algorithm compared to microscopic examination of H&E-stained bone marrow sections.

A Method for the Interpretation of Flow Cytometry Data Using Genetic Algorithms

Background:

Flow cytometry analysis is the method of choice for the differential diagnosis of hematologic disorders. It is typically performed by a trained hematopathologist through visual examination of bidimensional plots, making the analysis time-consuming and sometimes too subjective. Here, a pilot study applying genetic algorithms to flow cytometry data from normal and acute myeloid leukemia subjects is described.

Subjects and Methods:

Initially, Flow Cytometry Standard files from 316 normal and 43 acute myeloid leukemia subjects were transformed into multidimensional FITS image metafiles. Training was performed through introduction of FITS metafiles from 4 normal and 4 acute myeloid leukemia in the artificial intelligence system.

Results:

Two mathematical algorithms termed 018330 and 025886 were generated. When tested against a cohort of 312 normal and 39 acute myeloid leukemia subjects, both algorithms combined showed high discriminatory power with a receiver operating characteristic (ROC) curve of 0.912.

Conclusions:

The present results suggest that machine learning systems hold a great promise in the interpretation of hematological flow cytometry data.

Ultrasensitive automated RNA in situ hybridization for kappa and lambda light chain mRNA detects B-cell clonality in tissue biopsies with performance comparable or superior to flow cytometry

The assessment of B-cell clonality is a critical component of the evaluation of suspected lymphoproliferative disorders, but analysis from formalin-fixed, paraffin-embedded tissues can be challenging if fresh tissue is not available for flow cytometry. Immunohistochemical and conventional bright field in situ hybridization stains for kappa and lambda are effective for evaluation of plasma cells but are often insufficiently sensitive to detect the much lower abundance of light chains present in B-cells. We describe an ultrasensitive RNA in situ hybridization assay that has been adapted for use on an automated immunohistochemistry platform and compare results with flow cytometry in 203 consecutive tissues and 104 consecutive bone marrows. Overall, in 203 tissue biopsies, RNA in situ hybridization identified light chain-restricted B-cells in 85 (42%) vs 58 (29%) by flow cytometry. Within 83 B-cell non-Hodgkin lymphomas, RNA in situ hybridization identified restricted B-cells in 74 (89%) vs 56 (67%) by flow cytometry. B-cell clonality could be evaluated in only 23/104 (22%) bone marrow cases owing to poor RNA preservation, but evaluable cases showed 91% concordance with flow cytometry. RNA in situ hybridization allowed for recognition of biclonal/composite lymphomas not identified by flow cytometry and highlighted unexpected findings, such as coexpression of kappa and lambda RNA in 2 cases and the presence of lambda light chain RNA in a T lymphoblastic lymphoma. Automated RNA in situ hybridization showed excellent interobserver reproducibility for manual evaluation (average K=0.92), and an automated image analysis system showed high concordance (97%) with manual evaluation. Automated RNA in situ hybridization staining, which can be adopted on commonly utilized immunohistochemistry instruments, allows for the interpretation of clonality in the context of the morphological features in formalin-fixed, paraffin-embedded tissues with a clinical sensitivity similar or superior to flow cytometry.

Promise, Progress, and Pitfalls in the Search for Central Nervous System Biomarkers in Neuroimmunological Diseases: A Role for Cerebrospinal Fluid Immunophenotyping

Biomarkers are central to the translational medicine strategic focus, though strict criteria need to be applied to their designation and utility. They are one of the most promising areas of medical research, but the "biomarker life-cycle" must be understood to avoid false-positive and false-negative results. Molecular biomarkers will revolutionize the treatment of neurological diseases, but the rate of progress depends on a bold, visionary stance by neurologists, as well as scientists, biotech and pharmaceutical industries, funding agencies, and regulators. One important tool in studying cell-specific biomarkers is multiparameter flow cytometry. Cerebrospinal fluid immunophenotyping, or immune phenotypic subsets, captures the biology of intrathecal inflammatory processes, and has the potential to guide personalized immunotherapeutic selection and monitor treatment efficacy. Though data exist for some disorders, they are surprisingly lacking in many others, identifying a serious deficit to be overcome. Flow cytometric immunophenotyping provides a valuable, available, and feasible "window" into both adaptive and innate components of neuroinflammation that is currently underutilized.

Diagnostic Flow Cytometry and the AIDS Pandemic

The onset of the AIDS pandemic in the early 1980s coincided with the convergence of technologies now collectively known as flow cytometry (FCM). Major advances in FCM led significantly toward our understanding of the pathogenicity of the disease, which in turn led to wider adoption of the technology, including using it effectively in a variety of diagnostics. CD4+ T lymphocyte population counts, along with human immunodeficiency virus (HIV) viral load, remain the gold standard in diagnosis and continue to play a major role in the monitoring of advanced retroviral therapies. Arguably, the spread of AIDS (acquired immunodeficiency syndrome), the HIV virus, and the toll of the virus on humanity have been considerably altered by the concurrent development of FCM, the details of which are presented herein.

Single-Cell Cytokine Gene Expression in Peripheral Blood Cells Correlates with Latent Tuberculosis Status

RNA flow cytometry (FISH-Flow) achieves high-throughput measurement of single-cell gene expression by combining in-situ nucleic acid hybridization with flow cytometry. We tested whether antigen-specific T-cell responses detected by FISH-Flow correlated with latent tuberculosis infection (LTBI), a condition affecting one-third of the world population. Peripheral-blood mononuclear cells from donors, identified as positive or negative for LTBI by current medical practice, were stimulated ex vivo with mycobacterial antigen. IFNG and IL2 mRNA production was assayed by FISH-Flow. Concurrently, immunophenotypes of the cytokine mRNA-positive cells were characterized by conventional, antibody-based staining of cell-surface markers. An association was found between donor LTBI status and antigen-specific induction of IFNG and IL2 transcripts. Induction of these cytokine genes, which was detected by FISH-Flow in a quarter the time required to see release of the corresponding proteins by ELISA, occurred primarily in activated CD4+ T cells via T-cell receptor engagement. Moreover, NK cells contributed to IFNG gene induction. These results show that antigen-driven induction of T-cell cytokine mRNA is a measurable single-cell parameter of the host responses associated with latent tuberculosis. FISH-Flow read-outs contribute a multi-scale dimension to the immunophenotyping afforded by antibody-based flow cytometry. Multi-scale, single-cell analyses may satisfy the need to determine disease stage and therapy response for tuberculosis and other infectious pathologies.

Oxidative stress in paroxysmal nocturnal hemoglobinuria and other conditions of complement-mediated hemolysis

The complement (C') system and redox status play important roles in the physiological functioning of the body, such as the defense system, but they are also involved in various pathological conditions, including hemolytic anemia. Herein, we review the interaction between the C' and the redox systems in C'-mediated hemolytic anemias, paroxysmal nocturnal hemoglobinuria (PNH) and autoimmune hemolytic anemia, including acute hemolytic transfusion reaction. Blood cells in these diseases have been shown to have increased oxidative status, which was further elevated by interaction with activated C'. The results suggest that oxidative stress, in conjunction with activated C', may cause the underlying symptoms of these diseases, such as intra- and extravascular hemolysis and thrombotic complications. Antioxidants ameliorate oxidative stress by preventing generation of free radicals, by scavenging and preventing their accumulation, and by correcting their cellular damage. Antioxidants have been shown to reduce the oxidative stress and inhibit hemolysis as well as platelet activation mediated by activated C'. This raises the possibility that treatment with antioxidants might be considered as a potential therapeutic modality for C'-mediated hemolytic anemias. Currently, eculizumab, a humanized monoclonal antibody that specifically targets the C' protein C5, is the main treatment modality for PNH. However, because antioxidants are well tolerated and relatively inexpensive, they might be considered as potential adjuvants or an alternative therapeutic modality for PNH and other C'-mediated hemolytic anemias.

Immune cell profiling to guide therapeutic decisions in rheumatic diseases

Biomarkers are needed to guide treatment decisions for patients with rheumatic diseases. Although the phenotypic and functional analysis of immune cells is an appealing strategy for understanding immune-mediated disease processes, immune cell profiling currently has no role in clinical rheumatology. New technologies, including mass cytometry, gene expression profiling by RNA sequencing (RNA-seq) and multiplexed functional assays, enable the analysis of immune cell function with unprecedented detail and promise not only a deeper understanding of pathogenesis, but also the discovery of novel biomarkers. The large and complex data sets generated by these technologies--big data--require specialized approaches for analysis and visualization of results. Standardization of assays and definition of the range of normal values are additional challenges when translating these novel approaches into clinical practice. In this Review, we discuss technological advances in the high-dimensional analysis of immune cells and consider how these developments might support the discovery of predictive biomarkers to benefit the practice of rheumatology and improve patient care.

Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity

Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC) platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers.

Continuous-flow cytomorphological staining and analysis

Cells suspended in bodily fluids are routinely analyzed by cytopathologists as a means of diagnosing malignancies and other diseases. The physical and morphological properties of these suspended cells are evaluated in making diagnostic decisions, which often requires manual concentration, staining, and washing procedures to extract information about intracellular architecture. The need to manually prepare slides for analysis by a cytopathologist is a labor-intensive process, which is ripe for additional automation to reduce costs but also to potentially provide more repeatable and improved accuracy in diagnoses. We have developed a microfluidic system to perform several steps in the preparation of samples for cytopathology that (i) automates colorimetric staining on-chip, and (ii) images cells in flow, as well as provides (iii) additional quantitative analyses of captured images to aid cytopathologists. A flow-through approach provides benefits by allowing staining and imaging to be performed in a continuous, integrated manner, which also overcomes previous challenges with in-suspension colorimetric staining. We envision such a tool may reduce costs and aid cytopathologists in identifying rare or characteristic cells of interest by providing isolated images along with quantitative metrics on single cells from various rotational angles, allowing efficient determination of disease etiology.

Flow cytometry bioinformatics

Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform.

Portable device for magnetic stimulation: assessment survival and proliferation in human lymphocytes

A device's instrumentation for magnetic stimulation on human lymphocytes is presented. This is a new procedure to stimulate growing cells with ferrofluid in vortices of magnetic field. The stimulation of magnetic vortices was provided at five different frequencies, from 100 to 2500 Hz and intensities from 1.13 to 4.13 mT. To improve the stimulation effects, a paramagnetic ferrofluid was added on the cell culture medium. The results suggest that the frequency changes and the magnetic field variation produce an important increase in the number of proliferating cells as well as in the cellular viability. This new magnetic stimulation modality could trigger an intracellular mechanism to induce cell proliferation and cellular survival only on mitogen stimulated cells.