Biology subjects

Dev, A.

Publications and source records attributed to Dev, A..

16 recordsLinked to original sources

bioRxiv2026

BeatRatePy - Automated Hight-Throughput Python-Based Beat Rate Quantification and Generation of Speed and Contraction Traces

Analysing cardiac motion from label free imaging can be difficult, especially when recordings vary in quality or show complex movement. We developed a Python-based pipeline that automatically measures beat rate, contraction, speed from transmitted light timelapse data. The workflow runs in a Jupyter notebook and uses straightforward steps that can be followed easily, making the analysis accessible including to users with limited coding experience. Using human iPSC-derived cardiomyocytes imaged on a Zeiss Cell Discoverer 7, the pipeline produced beat rates, contraction and contraction speed measurements that matched expected behaviour. To test wider use, we applied the same workflow to killifish larvae heart recordings and public datasets, changing only basic input parameters. The pipeline performed consistently across these different systems and did not require changes to the underlying code. By supporting clear parameter control and use across laboratories, microscopy platforms and repositories, this approach strengthens reproducible analysis of cardiac motion from label free imaging.

cell biology↗

bioRxiv2026

Integrated Transcriptomic Profiling Reveals MAPK14-Related Inflammatory Signalling Associated with Postoperative Atrial Fibrillation

Postoperative atrial fibrillation (POAF) affects up to half of patients after cardiac surgery and raises long-term risk of stroke and death. Why only some patients develop it, despite similar surgical exposure, remains poorly understood. We studied a pilot cohort of 20 patients undergoing cardiac surgery in Northwest England, comparing those who developed POAF within four days (n=10) with those who did not (n=10). Circulating plasma RNA was profiled using the NanoString nCounter Cardiovascular Disease panel, and differentially expressed genes were mapped onto protein-protein interaction networks using STRING and Cytoscape. Candidate genes were then validated by RT-qPCR in the same cohort, alongside serial ELISA measurement of plasma MAPK14 protein. Peripheral blood monocyte, neutrophil and total white blood cell counts were also compared between the two groups on postoperative Days 1, 2 and 4. Screening identified MAPK14, COX6C and COX7B as elevated in POAF, with PTPN12 reduced. These genes clustered within a connected inflammatory and stress-response network, and pathway enrichment pointed to immune activation. RT-qPCR confirmed higher MAPK14, COX6C and COX7B expression in POAF patients. Plasma MAPK14 rose after surgery in both groups, with the largest increase in POAF patients on day two, though this did not reach significance. Peripheral blood monocyte counts were significantly higher in POAF patients than in those without POAF at all three postoperative timepoints, whereas neutrophil and total white blood cell counts did not differ significantly between groups. These early findings identify a circulating plasma RNA signature linked to MAPK14-related inflammatory signalling as a candidate marker of POAF susceptibility, warranting confirmation in a larger, adequately powered cohort.

physiology↗

bioRxiv2026

AI-Discovered Cognitive Models Reveal Novel Insights into Human and Animal Learning

Scientific models are widely used across the natural sciences as an interface between scientific theories and empirical data [1]. Such models play a key role, for example, in the study of human and animal learning, where they express algorithmic hypotheses and relate them to psychology and neuroscience data [2, 3]. These models are traditionally handcrafted by expert researchers based on existing theory or new insights. Such handcrafted models, however, are now known to fall short of capturing the full richness of behavior, even in their narrow domains [4-7]. An alternative data-driven approach has emerged, seeking to discover new insights by fitting and interpreting flexible models [8-11]. However, these tools require substantial human effort to derive insight from data, and it has been unclear how to discover new ideas from data efficiently. Here, we present DataDIVER, a general approach for automatically discovering computational models from data, and demonstrate that these models surface novel mechanistic insights into human and animal learning. Our approach delivers models that take the form of short computer programs, which are optimized both to fit data well and to be simple. These programs explicitly connect with existing theoretical frameworks and are readily understandable by human scientists. They can also be used to make novel predictions, some of which we show are borne out in re-analysis of existing data. General-purpose tools for surfacing new ideas from data, especially in combination with the large datasets that are increasingly available in many fields, stand to dramatically accelerate scientific discovery.

animal behavior and cognition↗

bioRxiv2026

Modeling Post-traumatic memory deficits: Repeated head injury effects on Novelty detection in Drosophila

Traumatic brain injury (TBI) is a leading cause of neurological dysfunction, yet the mechanisms linking repeated concussions to cognitive impairment remain poorly defined. Here, we used a controlled Drosophila model of repetitive head trauma using a piezoelectric actuator to deliver reproducible mild, moderate, or severe concussions. Repeated trauma significantly reduced lifespan and induced transient locomotor deficits, persistent motivational impairments, and surprisingly sleep behavior was only altered with injury protocols expanding across more than one day. At the cellular level, concussions triggered a delayed but robust proliferation of astrocyte-like glia, consistent with neuroinflammatory responses observed in mammalian models. To investigate circuit-level consequences, we examined novelty detection within the mushroom body, focusing on MBON-3, a neuron that shows plasticity consistent with odor habituation similar to previously reported for MBON-3. Functional calcium imaging revealed that concussed flies exhibited disrupted odor-induced plasticity and diminished baseline responsiveness in MBON-3 at one- and five- days post-injury, despite intact Kenyon cell input. Notably, these deficits were force-dependent and largely reversible by ten days, highlighting both vulnerability and resilience within this defined circuit. Together, our findings demonstrate that repeated concussions in Drosophila produce dose-dependent behavioral, cellular, and circuit dysfunctions that parallel mammalian TBI. This work establishes a genetically tractable platform for dissecting the mechanisms of concussion-induced cognitive decline and for identifying potential targets for intervention.

neuroscience↗

bioRxiv2026

Naringenin Attenuates Cisplatin-Induced Hepatotoxicity and Nephrotoxicity by Restoring Glutathione Homeostasis and Suppressing Lipid Peroxidation in a Murine Model

Cisplatin is a cornerstone chemotherapeutic agent for a broad spectrum of solid malignancies, yet its clinical utility is substantially curtailed by dose-limiting organ toxicity, principally nephrotoxicity and hepatotoxicity, mediated through reactive oxygen species (ROS)-driven oxidative stress, glutathione depletion, and lipid peroxidation. Naringenin (NAR), a bioactive citrus flavanone, possesses potent free-radical scavenging, anti-inflammatory, and cytoprotective properties that make it a compelling candidate for chemoprotection. The present study investigated whether oral naringenin supplementation (50 mg/kg body weight/day for 30 days) could mitigate cisplatin-induced oxidative injury to the liver and kidney in male Swiss albino mice. Cisplatin was administered intraperitoneally at 2.3 mg/kg body weight in three cycles of five consecutive days followed by a five-day interval. Biochemical indices of oxidative stress, such as malondialdehyde (MDA), reduced glutathione (GSH), and glutathione S-transferase (GST) activity, were assayed in liver and kidney homogenates on day 45. Cisplatin administration significantly elevated hepatic and renal MDA levels, indicating pronounced lipid peroxidation, and markedly depleted the concentrations of GSH and the activity of GST in both organs. Compared with cisplatin alone, naringenin coadministration significantly attenuated the increase in the level of MDA, restored the level of GSH, and rescued the activity of GST in both tissues, with more pronounced effects in the kidney. Notably, compared with the control, naringenin alone did not alter any biochemical parameters, confirming its physiological safety at the administered dose. These findings demonstrate that naringenin has meaningful hepatoprotective and nephroprotective effects against cisplatin-induced oxidative toxicity, possibly through antioxidant augmentation, glutathione repletion, and membrane stabilization mechanisms. This study provides a rational preclinical basis for evaluating naringenin as a coadministered chemoprotectant in cisplatin-based chemotherapy regimens.

pharmacology and toxicology↗

bioRxiv2026

Lysosomal abundance in young and aged mouse hearts assessed by In Vivo Imaging Systems (IVIS) Lysotracker imaging and autophagy-related gene expression

Lysosomal function is essential for cardiac proteostasis and cellular health, yet its regulation during ageing remains poorly defined. We hypothesised that ageing alters both the abundance of acidic organelles and the machinery supporting their acidification. Using fluorescence-based In Vivo Imaging Systems (IVIS) with Lysotracker Red in young (2-4 months) and aged (18 months) mouse hearts, we quantified whole-heart acidic-vesicle signals and assessed expression of lysosomal and autophagy-related genes (Lamp2, Atp6v1a, Sqstm1, Cd63, Atg12, Nfe2l2, M6pr) by RT-qPCR. Whole-heart labelled Lysotracker fluorescence did not differ significantly between age groups, indicating preservation of the total acidic-vesicle pool. No changes in Atp6v1a and Lamp2 expression suggest acidification capacity and structural stability are maintained, whereas the minor, upregulation of Sqstm1 might indicate increased autophagic demand and altered vesicle trafficking, which warrants further investigation. No statistical significant changes in M6pr, Atg12, or Nfe2l2 were detected, suggesting transcriptional stability in enzyme trafficking, core autophagy, and oxidative stress pathways. Regionally, atria showed higher Lysotracker signal than ventricles, consistent with known enrichment of acidic vesicular stores in atrial physiology. These findings highlight the utility of IVIS imaging of Lysotracker-labelled hearts, providing rapid whole-organ assessment of acidic vesicle distribution, albeit with limited depth resolution. Complementary techniques such as RT-qPCR analysis is essential to interpret IVIS findings, enabling insight into underlying molecular changes in lysosomal and autophagy pathways during cardiac ageing.

physiology↗

bioRxiv2025

LoAR-Exo and HiAR-Exo: One-step label-free isolation of extracellular vesicles using inertial microfluidic devices

Extracellular vesicles (EVs) are lipid membrane-bound nanoscale (20 nm - 1000 nm) objects shed by all cells. As EVs play an important role in intercellular signaling, these have emerged as promising biomarkers for many diseases including cancer and neurodegenerative disorders. A major bottleneck in research into EVs and their smooth translation to clinic as disease biomarkers is a lack of access to affordable and user-friendly technologies to quickly isolate EVs from complex biological and clinical samples with acceptable purity and yield. Here, we report two different designs of inertial microfluidic devices (e.g. LoAR-Exo and HiAR-Exo) that can isolate EVs from different kinds of biological samples in a single label-free step using a spiral microchannel design with different aspect ratios. LoAR-Exo has a height-to-width aspect ratio [~] 1, while HiAR-Exo has a height-to-width aspect ratio of 2.5, optimized by COMSOL simulations. We tested both designs by separating polystyrene particles of size < 1 m from a heterogeneous mixture. We then benchmarked the performance of the microfluidic chips against ultracentrifugation and a precipitation kit by isolating EVs from the cell culture-conditioned media (CCM) of MDA-MB-231 cells. We also compared the microchip with SEC by using the CCM from H1975/OR cells. The size distribution of EVs isolated by the microfluidic chip was comparable with ultracentrifugation, precipitation and SEC. In summary, both devices isolated EVs from as little as 1 mL of sample volume using a label-free technique in a continuous manner and without any user intervention. Both microfluidic platforms offer a simple, efficient, and scalable alternative to conventional methods for EV isolation.

bioengineering↗

bioRxiv2025

Imaging cellular activity simultaneously across all organs of a vertebrate reveals body-wide circuits

All cells in an animal collectively ensure, moment-to-moment, the survival of the whole organism in the face of environmental stressors1,2. Physiology seeks to elucidate the intricate network of interactions that sustain life, which often span multiple organs, cell types, and timescales, but a major challenge lies in the inability to simultaneously record time-varying cellular activity throughout the entire body. We developed WHOLISTIC (WHole Organism Live Imaging System for recording Tissue and IntraCellular activity), a method to image second-timescale, time-varying intracellular dynamics across cell-types of the vertebrate body. By advancing and integrating volumetric fluorescence microscopy, machine learning, and pancellular transgenic expression of calcium sensors in transparent young Danio rerio (zebrafish) and with proof of concept in adult Danionella, the method enables real-time recording of cellular dynamics across the organism. Calcium is a universal intracellular messenger, with a large array of cellular processes depending on changes in calcium concentration across varying time-scales, making it an ideal proxy of cellular activity3. Using this platform to screen the dynamics of most cells in the body, we discovered unexpected responses of specific cell types to stimuli, such as chondrocyte reactions to cold, meningeal responses to ketamine, and state-dependent activity, such as oscillatory ependymal-cell activity during periods of extended motor quiescence. At the organ scale, the method uncovered pulsating traveling waves along the kidney nephron. At the multi-organ scale, we uncovered muscle synergies and independencies, as well as muscle-organ interactions. Integration with optogenetics allowed us to all-optically determine the causal direction of brain-body interactions. At the whole-organism scale, the method captured the rapid brainstem-controlled redistribution of blood flow across the body. Finally, we advanced Whole-Body Expansion Microscopy4 to provide ground-truth molecular and ultrastructural anatomical context, explaining the spatiotemporal structure of activity captured by WHOLISTIC. Together, these innovations establish a new paradigm for systems biology, bridging cellular and organismal physiology, with broad implications for both fundamental research and drug discovery.

neuroscience↗

bioRxiv2025

Discovering Symbolic Cognitive Models from Human and Animal Behavior

Symbolic models play a key role in cognitive science, expressing computationally precise hypotheses about how the brain implements a cognitive process. Identifying an appropriate model typically requires a great deal of effort and ingenuity on the part of a human scientist. Here, we adapt FunSearch Romera-Paredes et al. (2024), a recently developed tool that uses Large Language Models (LLMs) in an evolutionary algorithm, to automatically discover symbolic cognitive models that accurately capture human and animal behavior. We consider datasets from three species performing a classic reward-learning task that has been the focus of substantial modeling effort, and find that the discovered programs outperform state-of-the-art cognitive models for each. The discovered programs can readily be interpreted as hypotheses about human and animal cognition, instantiating interpretable symbolic learning and decision-making algorithms. Broadly, these results demonstrate the viability of using LLM-powered program synthesis to propose novel scientific hypotheses regarding mechanisms of human and animal cognition.

animal behavior and cognition↗

bioRxiv2024

Surface adhesion and membrane fluctuations influence the elastic modulus of extracellular vesicles

Elastic properties of nanoscale extracellular vesicles (EVs) are believed to influence their cellular interactions, thus having a profound implication in intercellular communication. Yet, an accurate quantification of the elasticity of such small lipid vesicles is difficult even with AFM-based nanoindentation experiments as it crucially depends on the reliability of the theoretical interpretation of such measurements. Here we describe a complete method composed of theoretical framework, experimental procedure, and appropriate statistical approach for an accurate determination of bending modulus and effective elastic modulus of EVs. Further, we experimentally demonstrate that the quantification of EVs by the elastic modulus from AFM-based force spectroscopy measurement is marred by the interplay of their compositionally inhomogeneous fluid membrane with the adhesion forces from the substrate and thermal effects - two exquisite phenomena that could thus far only be theoretically predicted. The effects result in a large spreading of elastic modulus even for a single EV. Our unified model is then applied to genetically engineered classes of EVs to understand how the alterations in tetraspanin expression may influence their elastic modulus.

biophysics↗

bioRxiv2023

Mesenchymal stem cells ameliorate inflammation in an experimental model of Crohn's disease via the mesentery

ObjectiveMesenchymal stem cells (MSCs) are novel therapeutics for treatment of Crohns disease. However, their mechanism of action is unclear, especially in disease-relevant chronic models of inflammation. Thus, we used SAMP-1/YitFc, a chronic and spontaneous murine model of small intestinal inflammation, to study the therapeutic effect and mechanism of human bone marrow-derived MSCs (hMSC). DesignhMSC immunosuppressive potential was evaluated through in vitro mixed lymphocyte reaction, ELISA, macrophage co-culture, and RT-qPCR. Therapeutic efficacy and mechanism in SAMP were studied by stereomicroscopy, histopathology, MRI radiomics, flow cytometry, RT-qPCR, small animal imaging, and single-cell RNA sequencing (Sc-RNAseq). ResultshMSC dose-dependently inhibited naive T lymphocyte proliferation in MLR via PGE2 secretion and reprogrammed macrophages to an anti-inflammatory phenotype. hMSC promoted mucosal healing and immunologic response early after administration in SAMP model of chronic small intestinal inflammation when live hMSCs are present (until day 9) and resulted in complete response characterized by mucosal, histological, immunologic, and radiological healing by day 28 when no live hMSCs are present. hMSC mediate their effect via modulation of T cells and macrophages in the mesentery and mesenteric lymph nodes (mLN). Sc-RNAseq confirmed the anti-inflammatory phenotype of macrophages and identified macrophage efferocytosis of apoptotic hMSCs as a mechanism of action that explains their long-term efficacy. ConclusionhMSCs result in healing and tissue regeneration in a chronic model of small intestinal inflammation. Despite being short-lived, exert long-term effects via macrophage reprogramming to an anti-inflammatory phenotype. Data Transparency StatementSingle-cell RNA transcriptome datasets are deposited in an online open access repository Figshare (DOI: https://doi.org/10.6084/m9.figshare.21453936.v1)

immunology↗

bioRxiv2022

Analyses of single extracellular vesicles from non-small lung cancer cells to reveal effects by Epidermal growth factor inhibitor treatments

Precision cancer medicine have changed the treatment landscape of non-small cell lung cancer (NSCLC) as illustrated by tyrosine kinase inhibitors (TKIs) towards mutated Epidermal growth factor receptor (EGFR). Yet, responses to such TKIs e.g., erlotinib and osimertinib among patients are heterogenous and there is a need for non-invasive blood-based analytics to follow treatment response and reveal resistance to improve patients treatment outcome. Recently, extracellular vesicles (EVs) have been identified as an important source of tumor biomarkers promising to revolutionize liquid biopsy-based diagnosis of cancer. However, high heterogeneity has been a major bottleneck. The pathological signature is often hidden in the differential expression of membrane proteins in a subset of EVs which are difficult to identify with bulk techniques. Using a fluorescence-based approach, we for the first time demonstrate that the single-EV technique can be used to monitor the treatment response of targeted cancer therapies such as TKIs towards EGFR. To test the hypothesis, we analyzed the membrane proteins of native EVs extracted from EGFR-mutant NSCLC cell line, both prior and post treatment with EGFR-TKIs erlotinib or osimertinib. The selected cell line being refractory to erlotinib and responsive to osimertinib makes it a suitable model system. The expression level of five surface proteins; two common tetraspanins (CD9, CD81) and three markers of specific interest in lung cancer (EGFR, PD-L1, HER2) were studied. The data suggest that in contrast to erlotinib, the osimertinib treatment increases the population of PD-L1, EGFR and HER2 positive EVs while the expression level per EV decreases for all the three markers. The PD-L1 and HER2 expressing EV population seems to increase by several fold because of osimertinib treatment. The observations agree with the previous reports performed on cellular level indicating the biomarker potential of EVs for liquid-biopsy based monitoring of targeted cancer treatments. HighlightsO_LIMembrane protein analyses of single EVs may reveal distinct differences when lung cancer cells are refractory vs responsive under different EGFR-TKI treatments. C_LIO_LIComparison of 1st generation erlotinib and 3rd generation osimertinib shows clear signature on the expression of PD-L1, EGFR, HER2 on single EVs C_LIO_LIColocalization showed a change in common marker combinations before after treatment. C_LIO_LIPD-L1 expression per vesicle decreases while the number of PD-L1 positive EVs increases as a result of osimertinib treatment, indicating that such signature may not be detectable under bulk analysis C_LI

bioengineering↗

bioRxiv2022

Microchip-based electrokinetic biosensor: microfabrication and application in membrane protein profiling of extracellular vesicles

Detection of analyte using streaming current has been previously explored using both experimental and theoretical approaches. However, little has been done to develop a viable microchip which can be exploited to deliver a sensitive, robust, and scalable biosensor device. In this study, we demonstrate the fabrication of such a device on silicon wafer using a scalable silicon microfabrication technology followed by their characterization and optimization for highly sensitive detection of small extracellular vesicles (sEVs). We show that the sensitivity of the devices, estimated using a common protein-ligand pair and sEVs significantly outperforms previous reports using the same principle. Two versions of the microchips, denoted as enclosed and open-top microchip, were developed and compared aiming to discern the importance of high-pressure measurement vs easier and better surface preparation capacity. A custom-built chip-manifold allowing easy interfacing with standard microfluidic connections was also developed. By investigating different electrical, fluidic, morphological, and fluorescence measurements, we show that while the enclosed microchip with its robust glass-silicon bonding can withstand higher pressure and thus generate higher streaming current, the open-top configuration offers several practical benefits including easy surface preparation, uniform probe conjugation, and improvement in the limit of detection (LoD). We further compare two common surface functionalization strategies and show that the proposed microchip can achieve both high sensitivity for membrane protein profiling and low LoD for sEV detection. At the optimum condition, we demonstrate that the microchip can detect sEVs reaching a LoD of 104 sEV/mL, which is among the lowest in the reported microchip-based methods.

bioengineering↗

bioRxiv2021

Multiplexed electrokinetic sensor for detection and therapy monitoring of extracellular vesicles from liquid biopsies of non-small-cell lung cancer patients

Liquid biopsies based on extracellular vesicle (EV) protein profiles represent a promising tool for treatment monitoring of tumors, including non-small-cell lung cancers (NSCLC). In this study, we present the development of an electrokinetic sensor for multiplexed surface protein profiling of EVs and analysis of clinical samples. The method detects the difference in the streaming current obtained as a result of EV binding to the inner surface of a functionalized microcapillary, thereby estimating the expression level of a surface marker. Using multiple microchannels functionalized with different antibodies in a parallel fluidic connection, we first demonstrate the capacity for simultaneous detection of multiple surface markers in small EVs (sEVs) from NSCLC cells. To investigate the prospects of liquid biopsies based on EVs, we then apply the method to profile sEVs isolated from the pleural effusion (PE) fluids of three NSCLC adenocarcinoma patients with different genomic alterations (ALK-fusion, KRAS and EGFR) and applied treatments (chemotherapy, EGFR or ALK tyrosine kinase inhibitors). These vesicles were targeted against CD9 tetraspanin, as well as EGFR and PD-L1, two markers of interest in NSCLC. The electrokinetic signals showed detection of these markers on sEVs yet highlighting distinct interpatient differences, e.g., increased EGFR levels in sEVs from a patient with EGFR mutation as compared to an ALK-mutant one. The sensors also detected differences in PD-L1 expressions, in line with those measured by complementary methods. The analysis of sEVs from a patient prior and post crizotinib treatment also revealed a significant increase in the expression of some markers, e.g. EGFR and PD-L1. The obtained results hold promise for the application of the method for tumor treatment monitoring based on sEVs from liquid biopsies.

bioengineering↗

bioRxiv2021

Multiparametric Profiling of Single Nanoscale Extracellular Vesicles by Combined Atomic Force and Fluorescence Microscopy: Correlation and Heterogeneity in Their Molecular and Biophysical Features

Being a key player in intercellular communications, nanoscale extracellular vesicles (EVs) offer unique opportunities for both diagnostics and therapeutics. However, their cellular origin and functional identity remain elusive due to the high heterogeneity in their molecular and physical features. Here, for the first time, multiple EV parameters involving membrane protein composition, size and mechanical properties on single small EVs (sEVs) are simultaneously studied by combined fluorescence and atomic force microscopy. Furthermore, their correlation and heterogeneity in different cellular sources are investigated. The study, performed on sEVs derived from Human Embryonic Kidney 293, Cord Blood Mesenchymal Stromal and Human Acute Monocytic Leukemia cell lines, identifies both common and cell line-specific sEV subpopulations bearing distinct distributions of the common tetraspanins (CD9, CD63 and CD81) and biophysical properties. Although the tetraspanin abundances of individual sEVs are independent of their sizes, the expression levels of CD9 and CD63 are strongly correlated. A sEV population co-expressing all the three tetraspanins in relatively high abundance, however, having on average diameters <100 nm and relatively low Young moduli, is also found in all cell lines. Such a multiparametric approach is expected to provide new insights regarding EV biology and functions, potentially deciphering unsolved questions in this field.

bioengineering↗

bioRxiv2021

High throughput imaging of nanoscale extracellular vesicles by scanning electron microscopy for accurate size-based profiling and morphological analysis.

Nanoscale extracellular vesicle (EVs) have been found to play a key role in intercellular communication, offering opportunities for both diagnostics and therapeutics. However, lying below the diffraction limit and also being highly heterogeneous in their size, morphology and abundance, these vesicles pose significant challenges for their physical characterization. Here, we present a direct visual approach for their accurate morphological and size-based profiling by using scanning electron microscopy (SEM). To achieve that, we methodically examined various process steps and developed a protocol to improve the throughput, conformity and image quality while preserving the shape of EVs. The investigation was performed with small EVs (sEVs) isolated from a non-small cell lung cancer (NSCLC) cell line H1975 as well as from a human serum, and the results were compared with those obtained from nanoparticle tracking analysis (NTA). While the comparison of the sEV size distributions showed good agreement between the two methods for large sEVs (diameter >70 nm), the microscopy based approach showed a better capacity for analyses on smaller vesicles, with higher sEV counts compared to NTA. In addition, we demonstrated the possibility of identifying non-EV particles based on size and morphological features. The study also showed process steps that can generate artifacts bearing resemblance with sEVs. The results therefore present a simple way to use a widely available microscopy tool for accurate and high throughput physical characterization of EVs.

bioengineering↗