Cytometry Part A最新文献

High dimensional flow cytometry relies on multiple laser sources to excite the wide variety of fluorochromes now available for immunophenotyping. Ultraviolet lasers (usually solid state 355 nm) are a critical part of this as they excite the BD Horizon™ Brilliant Ultraviolet (BUV) series of polymer fluorochromes. The BUV dyes have increased the number of simultaneous fluorochromes available for practical high-dimensional analysis to greater than 40 for spectral cytometry. Immunologists are now seeking to increase this number, requiring both novel fluorochromes and additional laser wavelengths. A laser in the deep ultraviolet (DUV) range (from ca. 260 to 320 nm) has been proposed as an additional excitation source, driven by the on-going development of additional polymer dyes with DUV excitation. DUV lasers emitting at 280 and 320 nm have been previously validated for flow cytometry but have encountered practical difficulties both in probe excitation behavior and in availability. In this article, we validate an even shorter DUV 266 nm laser source for flow cytometry. This DUV laser provided minimal excitation of the BUV dyes (a desirable characteristic for high-dimensional analysis) while demonstrating excellent excitation of quantum nanoparticles (Qdots) serving as surrogate fluorochromes for as yet undeveloped DUV excited dyes. DUV 266 nm excitation may therefore be a viable candidate for expanding high-dimensional flow cytometry into the DUV range and providing an additional incidental excitation wavelength for spectral cytometry. Excitation in a spectral region with strong absorption by nucleic acids and proteins (260–280 nm) did result in strong autofluorescence requiring care in fluorochrome selection. DUV excitation of endogenous molecules may nevertheless have additional utility for label-free analysis applications.

The differential of leukocytes functions as the first indicator in clinical examinations. However, microscopic examinations suffered from key limitations of low throughputs in classifying leukocytes while commercially available hematology analyzers failed to provide quantitative accuracies in leukocyte differentials. A home-developed imaging and impedance flow cytometry of microfluidics was used to capture fluorescent images and impedance variations of single cells traveling through constrictional microchannels. Convolutional and recurrent neural networks were adopted for data processing and feature extractions, which were then fused by a support vector machine to realize the four-part differential of leukocytes. The classification accuracies of the four-part leukocyte differential were quantified as 95.4% based on fluorescent images plus the convolutional neural network, 90.3% based on impedance variations plus the recurrent neural network, and 99.3% on the basis of fluorescent images, impedance variations, and deep neural networks. Based on single-cell fluorescent imaging and impedance variations coupled with deep neural networks, the four-part leukocyte differential can be realized with almost 100% accuracy.

In biomedicine, the automatic processing of medical microscope images plays a key role in the subsequent analysis and diagnosis. Cell or nucleus segmentation is one of the most challenging tasks for microscope image processing. Due to the frequently occurred overlapping, few segmentation methods can achieve satisfactory segmentation accuracy yet. In this paper, we propose an approach to separate the overlapped cells or nuclei based on the outer Canny edges and morphological erosion. The threshold selection is first used to segment the foreground and background of cell or nucleus images. For each binary connected domain in the segmentation image, an intersection based edge selection method is proposed to choose the outer Canny edges of the overlapped cells or nuclei. The outer Canny edges are used to generate a binary cell or nucleus image that is then used to compute the cell or nucleus seeds by the proposed morphological erosion method. The nuclei of the Human U2OS cells, the mouse NIH3T3 cells and the synthetic cells are used for evaluating our proposed approach. The quantitative quantification accuracy is computed by the Dice score and 95.53% is achieved by the proposed approach. Both the quantitative and the qualitative comparisons show that the accuracy of the proposed approach is better than those of the area constrained morphological erosion (ACME) method, the iterative erosion (IE) method, the morphology and watershed (MW) method, the Generalized Laplacian of Gaussian filters (GLGF) method and ellipse fitting (EF) method in separating the cells or nuclei in three publicly available datasets.

Early diagnosis and prompt initiation of appropriate treatment are critical for improving the prognosis of acute leukemia. Acute leukemia is diagnosed by microscopic morphological examination of bone marrow smears and flow cytometric immunophenotyping of bone marrow cells stained with fluorophore-conjugated antibodies. However, these diagnostic processes require trained professionals and are time and resource-intensive. Here, we present a novel diagnostic approach using ghost cytometry, a recently developed high-content flow cytometric approach, which enables machine vision-based, stain-free, high-speed analysis of cells, leveraging their detailed morphological information. We demonstrate that ghost cytometry can detect leukemic cells from the bone marrow cells of patients diagnosed with acute lymphoblastic leukemia and acute myeloid leukemia without relying on biological staining. The approach presented here holds promise as a precise, simple, swift, and cost-effective diagnostic method for acute leukemia in clinical practice.

Flow cytometry is routinely used in the assessment of skeletal muscle progenitor cell (myoblast) populations. However, a full gating strategy, inclusive of difficult to interpret forward and side scatter data, which documents cytometric analysis of differentiated myoblasts (myotubes) has not been reported. Beyond changes in size and shape, there are substantial metabolic and protein changes in myotubes allowing for their potential identification within heterogenous cell suspensions. To establish the utility of flow cytometry for determination of myoblasts and myotubes, C2C12 murine cell populations were assessed for cell morphology and metabolic reprogramming. Laser scatter, both forward (FSC; size) and side (SSC; granularity), measured cell morphology, while mitochondrial mass, reactive oxygen species (ROS) generation and DNA content were quantified using the fluorescent probes, MitoTracker green, CM-H₂DCFDA and Vybrant DyeCycle, respectively. Immunophenotyping for myosin heavy chain (MyHC) was utilized to confirm myotube differentiation. Cellular viability was determined using Annexin V/propidium iodide dual labelling. Fluorescent microscopy was employed to visualize fluorescence and morphology. Myotube and myoblast populations were resolvable through non-intuitive interpretation of laser scatter-based morphology assessment and mitochondrial mass and activity assessment. Myotubes appeared to have similar sizes to the myoblasts based on laser scatter but exhibited greater mitochondrial mass (159%, p < 0.0001), ROS production (303%, p < 0.0001), DNA content (18%, p < 0.001) and expression of MyHC (147%, p < 0.001) compared to myoblasts. Myotube sub-populations contained a larger viable cluster of cells which were unable to be fractionated from myoblast populations and a smaller population cluster which likely contains apoptotic bodies. Imaging of differentiated myoblasts that had transited through the flow cytometer revealed the presence of intact, ‘rolled-up’ myotubes, which would alter laser scatter properties and potential transit through the laser beam. Our results indicate that myotubes can be analyzed successfully using flow cytometry. Increased mitochondrial mass, ROS and DNA content are key features that correlate with MyHC expression but due to myotubes ‘rolling up’ during flow cytometric analysis, laser scatter determination of size is not positively correlated; a phenomenon observed with some size determination particles and related to surface properties of said particles. We also note a greater heterogeneity of myotubes compared to myoblasts as evidenced by the 2 distinct sub-populations. We suggest that acoustic focussing may prove effective in identifying myotube sub populations compared to traditional hydrodynamic focussing.