Nano- and micro-carriers of therapeutic molecules offer numerous advantages for drug delivery, and the shape of these particles plays a vital role in their biodistribution and their interaction with cells. However, analysing how microparticles are taken up by cells presents methodological challenges. Qualitative methods like microscopy provide detailed imaging but are time-consuming, whereas quantitative methods such as flow cytometry enable high-throughput analysis but struggle to differentiate between internalised and surface-bound particles. Instead, imaging flow cytometry combines the best of both worlds, offering high-resolution imaging with the efficiency of flow cytometry, allowing for quantitative analysis at the single-cell level. This study focuses on fluorescently labelled silicon oxide microchips of various morphologies but related surface areas and volumes: rectangular cuboids and apex-truncated square pyramid microchips fabricated using photolithography techniques, offering a reliable basis for comparison with the more commonly studied spherical particles. Imaging flow cytometry was utilised to evaluate the effect of particle shape on cellular uptake using RAW 264.7 cells and revealed phagocytosis of particles with all shapes. Increasing the particle dose enhanced the uptake, while macrophage stimulation had minimal effect. Using a ratio particle:cell of 10:1 cuboids and spheres showed an uptake rate of approximately 50%, in terms of the percentage of cells with internalised particles, and the average number of particles taken up per cell ranging from about 1-1.5 particle/cell for all the different shapes. This study indicates how differently shaped micro-carriers offer insights into particle uptake variations, demonstrating the potential of non-spherical micro-carriers for precise drug delivery applications.

In the event of a large-scale incident involving radiological or nuclear exposures, there is a potential for large numbers of individuals to have received doses of radiation sufficient to cause adverse health effects. It is imperative to quickly identify these individuals in order to provide information to the medical community to assist in making decisions about their treatment. The cytokinesis-block micronucleus assay is a well-established method for performing biodosimetry. This assay has previously been adapted to imaging flow cytometry and has been validated as a high-throughput option for providing dose estimates in the range of 0-10 Gy. The goal of this study was to test the ability to further optimize the assay by reducing the time of culture to 48 h from 68 h as well as reducing the volume of blood required for the analysis to 200 μL from 2 mL. These modifications would provide efficiencies in time and ease of processing impacting the ability to manage large numbers of samples and provide dose estimates in a timely manner. Results demonstrated that either the blood volume or the culture time could be reduced while maintaining dose estimates with sufficient accuracy for triage analysis. Reducing both the blood volume and culture time, however, resulted in poor dose estimates. In conclusion, depending on the needs of the scenario, either culture time or the blood volume could be reduced to improve the efficiency of analysis for mass casualty scenarios.

Blood-derived extracellular vesicles (EVs) hold great therapeutic potential. As blood contains mixed EV populations, it is challenging to study EVs originating from different cells separately. Blood cell concentrates manufactured in blood banks offer an excellent non-invasive source of blood cell-specific EV populations. To study blood cell-specific EVs, we isolated EVs from platelet (TREVs) and red blood cell (EryEVs) concentrates and characterized them using nanoparticle tracking analysis, imaging flow cytometry, electron microscopy and western blot analysis and co-cultured them with peripheral blood mononuclear cells (PBMCs). Our aim was to use imaging flow cytometry to investigate EV interaction with PBMCs as well as study their effects on T-lymphocyte populations to better understand their possible biological functions. As a conclusion, TREVs interacted with PBMCs more than EryEVs. Distinctively, TREVs were uptaken into CD11c+ monocytes rapidly and into CD19+ B-lymphocytes in 24 h. EryEVs were not uptaken into CD11c+ monocytes before the 24-h time point, and they were only seen on the surface of lymphocytes. Neither TREVs nor EryEV were uptaken into CD3+ T-lymphocytes and no effect on T-cell populations was detected. We have previously seen similar differences in targeting PC-3 cancer cells. Further studies are needed to address the functional properties of blood cell concentrate-derived EVs. This study demonstrates that imaging flow cytometry can be used to study the distinctive differences in the interaction and uptake of EVs. Considering our current and previous results, EVs present a new valuable component for the future development of blood-derived therapeutics.

Acute myeloid leukemia (AML) is a heterogenous blood cancer with a dismal prognosis. It emanates from leukemic stem cells (LSCs) arising from the genetic transformation of hematopoietic stem cells (HSCs). LSCs hold prognostic value, but their molecular and immunophenotypic heterogeneity poses challenges: there is no single marker for identifying all LSCs across AML samples. We hypothesized that imaging flow cytometry (IFC) paired with artificial intelligence-driven image analysis could visually distinguish LSCs from HSCs based solely on morphology. Initially, a seven-color IFC panel was employed to immunophenotypically identify LSCs and HSCs in bone marrow samples from five AML patients and ten healthy donors, respectively. Next, we developed convolutional neural network (CNN) models for HSC-LSC discrimination using brightfield (BF), side scatter (SSC), and DNA images. Classification using only BF images achieved 86.96% accuracy, indicating significant morphological differences. Accuracy increased to 93.42% when combining BF with DNA images, highlighting differences in nuclear morphology, although DNA images alone were inadequate for accurate HSC-LSC discrimination. Model development using SSC images revealed minor granularity differences. Performance metrics varied substantially between AML patients, indicating considerable morphologic variations among LSCs. Overall, we demonstrate proof-of-concept results for accurate CNN-based HSC-LSC differentiation, instigating the development of a novel technique within AML monitoring.

Currently, various functionalized nanocarrier systems are extensively studied for targeted delivery of drugs, peptides, and nucleic acids. Joining the approaches of genetic and chemical engineering may produce novel carriers for precise targeting different cellular proteins, which is important for both therapy and diagnosis of various pathologies. Here we present the novel nanocontainers based on vectorized genetically encoded Myxococcus xanthus (Mx) encapsulin, confining a fluorescent photoactivatable mCherry (PAmCherry) protein. The shells of such encapsulins were modified using chemical conjugation of human transferrin (Tf) prelabeled with a fluorescein-6 (FAM) maleimide acting as a vector. We demonstrate that the vectorized encapsulin specifically binds to transferrin receptors (TfRs) on the membranes of mesenchymal stromal/stem cells (MSCs) followed by internalization into cells. Two spectrally separated fluorescent signals from Tf-FAM and PAmCherry are clearly distinguishable and co-localized. It is shown that Tf-tagged Mx encapsulins are internalized by MSCs much more efficiently than by fibroblasts. It has been also found that unlabeled Tf effectively competes with the conjugated Mx-Tf-FAM formulations. That indicates the conjugate internalization into cells by Tf-TfR endocytosis pathway. The developed nanoplatform can be used as an alternative to conventional nanocarriers for targeted delivery of, e.g., genetic material to MSCs.

Cryopreservation of sperm is an essential technique in assisted reproduction in cattle. The objective of the study was to systematically review and synthesize the literature on bull semen quality evaluation based on the comparison of morphological and metabolic parameters of cryopreserved bovine spermatozoa such as DNA integrity, mitochondrial status, plasma membrane alterations, total motility, and morphology (% of abnormal cells). The electronic databases PubMed, Web of Sciences, Scopus, and Google Scholar were searched up to December 2023. Studies and references were included if they reported the following parameters: DNA integrity, mitochondrial status, plasma membrane alterations, total motility, and morphological aberrations (% of abnormal cells) for conventional cryopreserved bovine spermatozoa. After an electronic search, out of 1,526 original studies, only 40 were included in the meta-analysis. Standardized mean differences (SMD) with 95% confidence intervals were estimated for the chosen studies, and a meta-analysis was performed using a random effects model. The tau-squared (tau2) and inconsistency index (I2) quantified heterogeneity among different studies. The regression analysis for the evaluated parameters showed a positive correlation between mitochondrial membrane potential (MMP), total motility, and abnormal morphology and a negative correlation between DNA fragmentation index (DFI) and total motility and MMP. Moreover, subgroup analysis demonstrated similar associations for dairy and non-dairy bull breeds, albeit with lower I2 values. The presence of publication bias was confirmed by Egger\'s test, except for the MMP parameter. A multi-parametric analysis of morphological and metabolic parameters can address the existing limitations of cryopreserved bovine spermatozoa quality assessment. Combining imaging flow cytometry (IFC) with standardization of sperm pre-processing and optimization of the experimental protocols may help to differentiate sperm from cellular debris and cytoplasmic droplets of similar size and alleviate limitations demonstrated by conventional sperm analysis.

Imaging flow cytometry (ImFC) represents a significant technological advancement in the field of cytometry, effectively merging the high-throughput capabilities of flow analysis with the detailed imaging characteristics of microscopy. In our comprehensive review, we adopt a historical perspective to chart the development of ImFC, highlighting its origins and current state of the art and forecasting potential future advancements. The genesis of ImFC stemmed from merging the hydraulic system of a flow cytometer with advanced camera technology. This synergistic coupling facilitates the morphological analysis of cell populations at a high-throughput scale, effectively evolving the landscape of cytometry. Nevertheless, ImFC\'s implementation has encountered hurdles, particularly in developing software capable of managing its sophisticated data acquisition and analysis needs. The scale and complexity of the data generated by ImFC necessitate the creation of novel analytical tools that can effectively manage and interpret these data, thus allowing us to unlock the full potential of ImFC. Notably, artificial intelligence (AI) algorithms have begun to be applied to ImFC, offering promise for enhancing its analytical capabilities. The adaptability and learning capacity of AI may prove to be essential in knowledge mining from the high-dimensional data produced by ImFC, potentially enabling more accurate analyses. Looking forward, we project that ImFC may become an indispensable tool, not only in research laboratories, but also in clinical settings. Given the unique combination of high-throughput cytometry and detailed imaging offered by ImFC, we foresee a critical role for this technology in the next generation of scientific research and diagnostics. As such, we encourage both current and future scientists to consider the integration of ImFC as an addition to their research toolkit and clinical diagnostic routine.

Myelodysplastic syndrome is primarily characterized by dysplasia in the bone marrow (BM), presenting a challenge in consistent morphology interpretation. Accurate diagnosis through traditional slide-based analysis is difficult, necessitating a standardized objective technique. Over the past two decades, imaging flow cytometry (IFC) has proven effective in combining image-based morphometric analyses with high-parameter phenotyping. We have previously demonstrated the effectiveness of combining IFC with a feature-based machine learning algorithm to accurately identify and quantify rare binucleated erythroblasts (BNEs) in dyserythropoietic BM cells. However, a feature-based workflow poses challenges requiring software-specific expertise. Here we employ a Convolutional Neural Network (CNN) algorithm for BNE identification and differentiation from doublets and cells with irregular nuclear morphology in IFC data. We demonstrate that this simplified AI workflow, coupled with a powerful CNN algorithm, achieves comparable BNE quantification accuracy to manual and feature-based analysis with substantial time savings, eliminating workflow complexity. This streamlined approach holds significant clinical value, enhancing IFC accessibility for routine diagnostic purposes.

The bacterial pathogen Neisseria gonorrhoeae is an urgent global health problem due to increasing numbers of infections, coupled with rampant antibiotic resistance. Vaccines against gonorrhea are being prioritized to combat drug-resistant N. gonorrhoeae. Meningococcal serogroup B vaccines such as four-component meningococcal B vaccine (4CMenB) are predicted by epidemiology studies to cross-protect individuals from natural infection with N. gonorrhoeae and elicit antibodies that cross-react with N. gonorrhoeae. Evaluation of vaccine candidates for gonorrhea requires a suite of assays for predicting efficacy in vitro and in animal models of infection, including the role of antibodies elicited by immunization. Here, we present the development and optimization of assays to evaluate antibody functionality after immunization of mice: antibody binding to intact N. gonorrhoeae, serum bactericidal activity, and opsonophagocytic killing activity using primary human neutrophils [polymorphonuclear leukocytes (PMNs)]. These assays were developed with purified antibodies against N. gonorrhoeae and used to evaluate serum from mice that were vaccinated with 4CMenB or given alum as a negative control. Results from these assays will help prioritize gonorrhea vaccine candidates for advanced preclinical to early clinical studies and will contribute to identifying correlates and mechanisms of immune protection against N. gonorrhoeae.

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