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Pancreatic β cells secrete insulin in response to elevated levels of glucose. Stem cell derived β (SCβ) cells aim to replicate this glucose-stimulated insulin secretion (GSIS) function, but current preparations cannot provide the same level of insulin as natural β cells. Here, we develop an assay to measure GSIS at the single cell level to investigate the functional heterogeneity of SCβ cells and donor-derived islet cells. Our assay involves randomly depositing single cells and insulin capture microbeads in opentop nanowells (40 × 40 × 55 μm³ ) fabricated on glass-bottom imaging microwell plates. Insulin secreted from single cells is captured on microbeads and then stained using a detection antibody. The nanowell microstructure limits diffusion of secreted insulin. The glass substrate provides an optically flat surface for quantitative microscopy to measure the concentration of secreted insulin. We used this approach to measure GSIS from SCβ cells and donor-derived islet cells after 15 minutes exposure to 3.3 mM and 16.7 mM glucose. Both cell types exhibited significant GSIS heterogeneity, where elite cells (<20%) produced the majority of the secreted insulin (55–78%). This assay provides an immediate readout of single cell glucose-stimulated insulin secretion in a flexible well plate-based format. [ABSTRACT FROM AUTHOR]

Background: The biophysical properties of red blood cells (RBCs) provide potential biomarkers for the quality of donated blood. Blood unit segments provide a simple and nondestructive way to sample RBCs in clinical studies of transfusion efficacy, but it is not known whether RBCs sampled from segments accurately represent the biophysical properties of RBCs in blood bags. Study Design and Methods: RBCs were sampled from blood bags and segments every two weeks during 8 weeks of storage at 4°C. RBC deformability was measured by deformability‐based sorting using the microfluidic ratchet device in order to derive a rigidity score. Standard hematological parameters, including mean corpuscular volume (MCV), red cell distribution width (RDW), mean cell hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and hemolysis were measured at the same time points. Results: Deformability of RBCs stored in blood bags was retained over 4 weeks storage, but a progressive loss of deformability was observed at weeks 6 and 8. This trend was mirrored in blood unit segments with a strong correlation to the blood bag data. Strong correlations were also observed between blood bag and segment for MCV, MCHC, and MCH but not for hemolysis. Conclusion: RBCs sampled from blood unit segments accurately represent the biophysical properties of RBCs in blood bags but not hemolysis. Blood unit segments provide a simple and nondestructive sample for measuring RBC biophysical properties in clinical studies. [ABSTRACT FROM AUTHOR]

A fundamental challenge to multiplexing microfluidic chemotaxis assays at scale is the requirement for time-lapse imaging to continuously track migrating cells. Drug testing and drug screening applications require the ability to perform hundreds of experiments in parallel, which is not feasible for assays that require continuous imaging. To address this limitation, end-point chemotaxis assays have been developed using fluid flow to align cells in traps or sieves prior to cell migration. However, these methods require precisely controlled fluid flow to transport cells to the correct location without undesirable mechanical stress, which introduce significant set up time and design complexity. Here, we describe a microfluidic device that eliminates the need for precise flow control by using centrifugation to align cells at a common starting point. A chemoattractant gradient is then formed using passive diffusion prior to chemotaxis in an incubated environment. This approach provides a simple and scalable approach to multiplexed chemotaxis assays. Centrifugal alignment is also insensitive to cell geometry, enabling this approach to be compatible with primary cell samples that are often heterogeneous. We demonstrate the capability of this approach by assessing chemotaxis of primary neutrophils in response to an fMLP (N-formyl-met-leu-phe) gradient. Our results show that cell alignment by centrifugation offers a potential avenue to develop scalable end-point multiplexed microfluidic chemotaxis assays. [ABSTRACT FROM AUTHOR]

Immunocytochemistry (ICC), or immunofluorescence microscopy, is an essential biological technique for phenotyping cells in both research and diagnostic applications. Standard ICC methods often do not work well when the cell sample contains a small number of cells (<10 000) because of the significant cell loss that occurs during washing, staining, and centrifugation steps. Cell loss is particularly relevant when working with rare cells, such as circulating tumor cells, where such losses could significantly bias experimental outcomes. In order to eliminate cell loss in ICC protocols, we present a method to encapsulate the cell sample in a photo-polymerized hydrogel thin-film. The hydrogel thin-film is permeable to antibodies and other ICC reagents, thereby allowing the use of standard ICC protocols without modification. The cell sample is physically constrained by the hydrogel at the bottom surface of a standard (unmodified) imaging microtiter plate, thereby enabling the acquisition of high-quality micrographs regardless of the properties of the cell sample or staining reagents. Furthermore, while standard ICC requires several centrifugation steps during staining and washing, our hydrogel encapsulation method requires only a single centrifugation step. This property greatly reduces the time required to perform ICC protocols and is more compatible with robotic platforms. In this study, we show that standard ICC and Cytospin protocols are extremely lossy (>70% loss) when the sample contains less than 10 000 cells, while encapsulating the cells using a permeable hydrogel thin-film results in a lossless ICC process. [ABSTRACT FROM AUTHOR]

Background: Malaria remains a challenging and fatal infectious disease in developing nations and the urgency for the development of new drugs is even greater due to the rapid spread of anti-malarial drug resistance. While numerous parasite genetic, protein and metabolite biomarkers have been proposed for testing emerging anti-malarial compounds, they do not universally correspond with drug efficacy. The biophysical character of parasitized cells is a compelling alternative to these conventional biomarkers because parasitized erythrocytes become specifically rigidified and this effect is potentiated by anti-malarial compounds, such as chloroquine and artesunate. This biophysical biomarker is particularly relevant because of the mechanistic link between cell deformability and enhanced splenic clearance of parasitized erythrocytes. Methods: Recently a microfluidic mechanism, called the multiplexed fluidic plunger that provides sensitive and rapid measurement of single red blood cell deformability was developed. Here it was systematically used to evaluate the deformability changes of late-stage trophozoite-infected red blood cells (iRBCs) after treatment with established clinical and pre-clinical anti-malarial compounds. Results: It was found that rapid and specific iRBC rigidification was a universal outcome of all but one of these drug treatments. The greatest change in iRBC rigidity was observed for (+)-SJ733 and NITD246 spiroindolone compounds, which target the Plasmodium falciparum cation-transporting ATPase ATP4. As a proof-of-principle, compounds of the bisindole alkaloid class were screened, where cladoniamide A was identified based on rigidification of iRBCs and was found to have previously unreported anti-malarial activity with an IC50 lower than chloroquine. Conclusion: These results demonstrate that rigidification of iRBCs may be used as a biomarker for anti-malarial drug efficacy, as well as for new drug screening. The novel anti-malarial properties of cladoniamide A were revealed in a proof-of-principle drug screen. [ABSTRACT FROM AUTHOR]

Pancreatic β cells secrete insulin in response to elevated levels of glucose. Stem cell derived β (SCβ) cells aim to replicate this glucose-stimulated insulin secretion (GSIS) function, but current preparations cannot provide the same level of insulin as natural β cells. Here, we develop an assay to measure GSIS at the single cell level to investigate the functional heterogeneity of SCβ cells and donor-derived islet cells. Our assay involves randomly depositing single cells and insulin capture microbeads in open-top nanowells (40 × 40 × 55 μm 3 ) fabricated on glass-bottom imaging microwell plates. Insulin secreted from single cells is captured on microbeads and then stained using a detection antibody. The nanowell microstructure limits diffusion of secreted insulin. The glass substrate provides an optically flat surface for quantitative microscopy to measure the concentration of secreted insulin. We used this approach to measure GSIS from SCβ cells and donor-derived islet cells after 15 minutes exposure to 3.3 mM and 16.7 mM glucose. Both cell types exhibited significant GSIS heterogeneity, where elite cells (<20%) produced the majority of the secreted insulin (55-78%). This assay provides an immediate readout of single cell glucose-stimulated insulin secretion in a flexible well plate-based format.

Red blood cells (RBCs) must be highly deformable to transit through the microvasculature to deliver oxygen to tissues. The loss of RBC deformability resulting from pathology, natural aging, or storage in blood bags can impede the proper function of these cells. A variety of methods have been developed to measure RBC deformability, but these methods require specialized equipment, long measurement time, and highly skilled personnel. To address this challenge, we investigated whether a machine learning approach could be used to predict donor RBC deformability based on morphological features from single cell microscope images. We used the microfluidic ratchet device to sort RBCs based on deformability. Sorted cells are then imaged and used to train a deep learning model to classify RBC based image features related to cell deformability. This model correctly predicted deformability of individual RBCs with 81 ± 11% accuracy averaged across ten donors. Using this model to score the deformability of RBC samples was accurate to within 10.4 ± 6.8% of the value obtained using the microfluidic ratchet device. While machine learning methods are frequently developed to automate human image analysis, our study is remarkable in showing that deep learning of single cell microscopy images could be used to assess RBC deformability, a property not normally measurable by imaging. Measuring RBC deformability by imaging is also desirable because it can be performed rapidly using a standard microscopy system, potentially enabling RBC deformability studies to be performed as part of routine clinical assessments.

Circulating tumor cells (CTCs) have been implicated as the seeds of cancer metastasis and therefore have the potential to provide significant prognostic and diagnostic values. Here, we describe a procedure for separating CTCs from whole blood based on size and deformability using the microfluidic ratchet device. This device leverages the ratcheting motion of single cells created as they are deformed through funnel-shaped constrictions using oscillatory flow in order to divert cells based on differences in size and deformability. Subsequent methods for CTC identification and enumeration using immunofluorescence after separation are also described.