Abstract: Abstract Seminal plasma (SP) is rich in extracellular vesicles (EVs), which are still poorly studied, especially in livestock species. To better understand their functional role in both spermatozoa and endometrial epithelial cells, proper characterization of EVs is an essential step. The objective was to phenotypically characterize porcine seminal EVs (sEVs) using cryogenic electron microscopy (cryo-EM), which allows visualization of EVs in their native state. Porcine ejaculates are released in fractions, each containing SP from different source. This allows characterization sEVs released from various male reproductive tissues. Two experiments were performed, the first with SP from the entire ejaculate (n:6) and the second with SP from three ejaculate fractions (n:15): the first 10 mL of the sperm-rich ejaculate fraction (SRF-P1) with SP mainly from the epididymis, the remainder of the SRF (SRF-P2) with SP mainly from the prostate, and the post-SRF with SP mainly from the seminal vesicles. The sEVs were isolated by size exclusion chromatography and 1840 cryo-EM sEV images were acquired using a Jeol-JEM-2200FS/CR-EM. The size, electron density, complexity, and peripheral corona layer were measured in each sEV using the ImageJ software. The first experiment showed that sEVs were structurally and morphologically heterogeneous, although most (83.1%) were small (less than 200 nm), rounded, and poorly electrodense, and some have a peripheral coronal layer. There were also larger sEVs (16.9%) that were irregularly shaped, more electrodense, and few with a peripheral coronal layer. The second experiment showed that small sEVs were more common in SRF-P1 and SRF-P2, indicating that they originated mainly from the epididymis and prostate. Large sEVs were more abundant in post-SRF, indicating that they originated mainly from seminal vesicles. Porcine sEVs are structurally and morphologically heterogeneous. This would be explained by the diversity of reproductive organs of origin.

Abstract: Exosomes which are tiny extracellular vesicles (30-150 nm), transport vital proteins and gene materials such as miRNA, mRNA, or DNA, whose role in cell communication and epithelia regulation is critical. Many techniques have been developed as a result of studying exosomes' biochemical and physicochemical properties, although there is still no standard method to isolate exosomes simply with high yield. Commercial kits have gained popularity for exosome extraction despite concerns about their effectiveness in scientific research. On the other hand, ultracentrifugation remains the gold standard isolation method. This study compares these two common exosome isolation methods to determine their impact on the quality and quantity of exosomes isolated from bone marrow (BM) and Wharton's jelly (WJ)-derived mesenchymal stem cells. Isolated exosomes from the two sources of the cell's conditioned medium by two methods (polymer kit and ultracentrifuge) were characterized using western blotting, scanning electron microscopy (SEM), dynamic light scattering (DLS), and the Bradford assay. Western blot analysis confirmed separation efficiency based on CD81 and CD63 markers, with the absence of calnexin serving as a negative control. The Morphology of exosomes studied by SEM image analysis revealed a similar round shape appearance and their sizes (30-150 nm) were the same in both isolation techniques. The DLS analysis of the sample results was consistent with the SEM ones, showing a similar size range and very low disparity. The exosome protein content concentration analysis revealed that exosomes isolated by the polymer-based kits contained higher protein concentration density and purity (p <0.001). In general, though the protein yield was higher when the polymer-based kits were used, there were no significant differences in morphology, or size between WJ-derived and BM-derived exosomes, regardless of the isolation method employed.

Abstract: The physiological origins and functions of extracellular vesicles (EVs) and lipoproteins (LPs) propel advancements in precision medicine by offering non-invasive diagnostic and therapeutic prospects for cancers, cardiovascular, and neurodegenerative diseases. However, EV/LP diagnostics (ExoLP-Dx) face considerable challenges. Their intrinsic heterogeneity, spanning biogenesis pathways, surface protein composition, and concentration metrics complicate traditional diagnostic approaches. Commonly used methods such as nanoparticle tracking analysis, enzyme-linked immunosorbent assay, and nuclear magnetic resonance do not provide any information about their proteomic subfractions, including active proteins/enzymes involved in essential pathways/functions. Size constraints limit the efficacy of flow cytometry for small EVs and LPs, while ultracentrifugation isolation is hampered by co-elution with non-target entities. In this perspective, we propose a charge-based electrokinetic membrane sensor, with silica nanoparticle reporters providing salient features, that can overcome the interference, long incubation time, sensitivity, and normalization issues of ExoLP-Dx from raw plasma without needing sample pretreatment/isolation. A universal EV/LP standard curve is obtained despite their heterogeneities.

Abstract: Sahiwal cattle, known for their high milk yield, are propagated through artificial insemination (AI) using male germplasm, largely contingent on semen quality. Spermatozoa, produced in the testes, carry genetic information and molecular signals essential for successful fertilization. Seminal plasma, in addition to sperm, contains nano-sized lipid-bound extracellular vesicles (SP-EVs) that carry key biomolecules, including fertility-related miRNAs, which are essential for bull fertility. The current study focused on miRNA profiling of SP-EVs from high-fertile (HF) and low-fertile (LF) Sahiwal bulls. SP-EVs were isolated using size exclusion chromatography (SEC) and characterized by dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA). Western blotting detected the EV-specific protein markers TSG101 and CD63. The DLS analysis showed SP-EV sizes of 170–180 nm in HF and 130–140 nm in LF samples. The NTA revealed particle concentrations of 5.76 × 10 10 to 5.86 × 10 11 particles/mL in HF and 5.31 × 10 10 to 2.70 × 10 11 particles/mL in LF groups, with no significant differences in size and concentration between HF and LF. High-throughput miRNA sequencing identified 310 miRNAs in SP-EVs from both groups, with 61 upregulated and 119 downregulated in HF bull. Further analysis identified 41 miRNAs with significant fold changes and p-values, including bta-miR-1246, bta-miR-195, bta-miR-339b, and bta-miR-199b, which were analyzed for target gene prediction. Gene Ontology (GO) and KEGG pathway analyses indicated that these miRNAs target genes involved in transcription regulation, ubiquitin-dependent endoplasmic reticulum-associated degradation (ERAD) pathways, and signalling pathways. Functional exploration revealed that these genes play roles in spermatogenesis, motility, acrosome reactions, and inflammatory responses. qPCR analysis showed that bta-miR-195 had 80% higher expression in HF spermatozoa compared to LF, suggesting its association with fertility status ( p &lt; 0.05). In conclusion, this study elucidates the miRNA cargoes in SP-EVs as indicators of Sahiwal bull fertility, highlighting bta-miR-195 as a potential fertility factor among the various miRNAs identified.

Abstract: Abstract Background The lack of standardized protocols for isolating extracellular vesicles (EVs), especially from biobank-stored blood plasma, translates to limitations for the study of new biomarkers. This study examines whether a combination of current isolation methods could enhance the specificity and purity of isolated EVs for diagnosis and personalized medicine purposes. Results EVs were isolated from healthy human plasma stored for one year by ultracentrifugation (UC), size exclusion chromatography (SEC), or SEC and UC combined (SEC + UC). The EV isolates were then characterized by transmission electron microscopy imaging, nanoparticle tracking analysis (NTA) and western blotting. Proteomic procedures were used to analyze protein contents. The presence of EV markers in all isolates was confirmed by western blotting yet this analysis revealed higher albumin expression in EVs-UC, suggesting plasma protein contamination. Proteomic analysis identified 542 proteins, SEC + UC yielding the most complex proteome at 364 proteins. Through gene ontology enrichment, we observed differences in the cellular components of EVs and plasma in that SEC + UC isolates featured higher proportions of EV proteins than those derived from the other two methods. Analysis of proteins unique to each isolation method served to identify 181 unique proteins for the combined approach, including those normally appearing in low concentrations in plasma. This indicates that with this combined method, it is possible to detect less abundant plasma proteins by proteomics in the resultant isolates. Conclusions Our findings reveal that the SEC + UC approach yields highly pure and diverse EVs suitable for comprehensive proteomic analysis with applications for the detection of new biomarkers in biobank-stored plasma samples.

Abstract: Morphologies of nanoparticles and aggregates play an important role in their properties for a range of applications. In particular, significant synthesis efforts have been directed toward controlling nanoparticle morphology and aggregation behavior in biomedical applications, as their size and shape have a significant impact on cellular uptake. Among several techniques for morphological characterization, transmission electron microscopy (TEM) can provide direct and accurate characterization of nanoparticle/aggregate morphology details. Nevertheless, manually analyzing a large number of TEM images is still a laborious process. Hence, there has been a surge of interest in employing machine learning methods to analyze nanoparticle size and shape. In order to achieve accurate nanoparticle analysis using machine learning methods, reliable and automated nanoparticle segmentation from TEM images is critical, especially when the nanoparticle image contrast is weak and the background is complex. These challenges are particularly pertinent in biomedical applications. In this work, we demonstrate an efficient, robust, and automated nanoparticle image segmentation method suitable for subsequent machine learning analysis. Our method is robust for noisy, low-electron-dose cryo-TEM images and for TEM cell images with complex, strong-contrast background features. Moreover, our method does not require any a priori training datasets, making it efficient and general. The ability to automatically, reliably, and efficiently segment nanoparticle/aggregate images is critical for advancing precise particle/aggregate control in biomedical applications.

Abstract: Background: Extracellular vesicles (EVs), including exosomes, are promising pharmaceutical modalities. They are purified from cell culture supernatant; however, the preparation may contain EVs with the desired therapeutic effects and different types of EVs, lipoproteins, and soluble proteins. Evaluating the composition of particulate impurities and the levels of protein impurities in final preparations is critical for quality control. However, few analytical methods can detect these impurities. Methods: We established and evaluated an analytical method using size-exclusion chromatography–multi-angle light scattering (SEC-MALS) for particle and protein impurity analyses of EV samples. Results: In the particle size distribution analysis of EV samples, SEC-MALS showed higher resolution compared with nanoparticle tracking analysis (NTA) and dynamic light scattering (DLS). MALS showed comparable accuracy and precision to that of other methods for particle size evaluation using polystyrene standard beads with 60, 100, or 200 nm diameter. Coupling SEC-MALS with UV detection quantitatively evaluated soluble protein impurities. Proteomic analysis on the SEC-MALS-fractionated samples identified different EV and lipoprotein marker proteins in different fractions. Conclusions: SEC-MALS can characterize EV preparations obtained from human adipose-derived mesenchymal stem cells, suggesting that it can evaluate the particle component composition in various EV samples and therapeutic exosome preparations.

Abstract: Background: Detailed characterization of extracellular vesicles (EVs) is crucial for their application in medical diagnostics. However, the complexity of their chemical composition and the heterogeneity of EV populations make their characterization challenging. Here we describe two analytical procedures that can help overcome this challenge. Methods: Small EVs were isolated from conditioned cell culture media using ultracentrifugation and characterized using nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM). Raman spectroscopy was used to assess the overall composition of the isolated samples and lipids extracted from them. Sulfophosphovanillin (SPV) colorimetric assay was used to quantify the contents of lipid. Results: Six samples of EVs were characterized. The lipid contents measured using SPV assay was in reasonable agreement with the quantitative estimates based on the particle size and concentration measured using NTA. The most peaks observed in the Raman spectra could be attributed to either proteins or lipids, and their origins was confirmed by lipid extraction. The protein-to-lipid ratio was estimated based on the Raman spectra. Conclusions: The experiential procedures described in this study will help to overcome the challenge of quick and highly informative characterization of the EVs.

Abstract: Extracellular vesicles (EVs) in cerebrospinal fluid (CSF) represent a valuable source of biomarkers for central nervous system (CNS) diseases, offering new pathways for diagnosis and monitoring. However, existing methods for isolating EVs from CSF often prove to be labor-intensive and reliant on specialized equipment, hindering their clinical application. In this study, we present a novel, clinically compatible method for isolating EVs from CSF. We optimized the use of ExoGAG, a commercially available reagent that has been tested in plasma, urine and semen, and compared it directly with differential ultracentrifugation using Western blotting, protein quantification, nanoparticle tracking analysis, and cryogenic electron microscopy. Additionally, we analyzed the presence of specific microRNAs (miRNAs) known to be present in CSF-derived EVs. Our data demonstrate that ExoGAG is an effective method for isolating EVs from CSF, yielding a higher amount of EVs compared to traditional ultracentrifugation methods, and with comparable levels of specific miRNAs. In conclusion, the use of ExoGAG in a clinical setting may facilitate the testing of biomarkers essential for tracking brain pathology in CNS diseases.

Abstract: Peritoneal dialysis inevitability results in activation of inflammatory processes and its efficiency is highly variable between patients. An improved method to isolate biomarkers and study pathophysiological mechanisms in peritoneal dialysis effluent (PDE) is expected to be of much benefit for the development of this treatment approach and help with patient management. Extracellular vesicles (EVs) are released as part of normal cellular processes. Their proteome is expected to reflect both type and health of their cell of origin. Although there is a significant interest in using EVs for "liquid biopsies", little is reported of their presence or composition in plentiful dialysis waste fluids, including peritoneal dialysis effluent (PDE). Here we determined the presence of EVs in PDE and subsequently characterized their proteome. EVs were first isolated from PDE using differential centrifugation, then a further enrichment using size exclusion chromatography (SEC) was performed. The presence of EVs was demonstrated using transmission electron microscopy, and their particle counts were investigated using nanoparticle tracking analysis and dynamic light scattering. Using tandem mass spectrometry, marker proteins from three types of EVs i.e. apoptotic bodies, ectosomes, and exosomes were identified. The proteomic results demonstrated that the isolation of EVs by differential centrifugation helped enrich for over 2,000 proteins normally masked by abundant proteins in PDE such as albumin and SEC markedly further improved the isolation of low abundant proteins. Gene ontology analysis of all identified proteins showed the marked enrichment of exosome and membrane-associated proteins. Over 3,700 proteins were identified in total, including many proteins with known roles in peritoneal pathophysiology. This study demonstrated the prominence of EVs in PDE and their potential value as a source of biomarkers for peritoneal dialysis patients.

Abstract: <p>Supplementary Figure S1 shows characterization of EVs. (A) Western blots of whole cell lysates (WCL) and EVs from MDA-MB-231 showing EV markers and a Golgi marker (GM130, as a negative control for EV-specific proteins). (B) Nanoparticle tracking analysis (NTA) of MDA-MB-231 EVs showing size distribution (n=3 biological replicates). Data are presented as mean ± standard error of the mean (SEM).</p>

Abstract: Abstract Objective Extracellular vesicles (EVs) have been shown to play a critical role in promoting tumorigenesis. As EV research grows, it is of importance to have standardization of isolation, quality control, characterization and validation methods across studies along with reliable references to explore troubleshooting solutions. Therefore, our objective with this Research Note was to isolate EVs from multiple breast cancer cell lines and to describe and perform protocols for validation as outlined by the list of minimal information for studies of EVs (MISEV) from the International Society for Extracellular Vesicles. Results To isolate EVs, two techniques were employed: ultracentrifugation and size exclusion chromatography. Ultracentrifugation yielded better recovery of EVs in our hands and was therefore used for further validation. In order to satisfy the MISEV requirements, protein quantification, immunoblotting of positive (CD9, CD63, TSG101) and negative (TGFβ1, β-tubulin) markers, nanoflow cytometry and electron microscopy was performed. With these experiments, we demonstrate that yield of validated EVs varied between different breast cancer cell lines. Protocols were optimized to accommodate for low levels of EVs, and various technical and troubleshooting suggestions are included for potential application to other cell types that may provide benefit to investigators interested in future EV studies.

Abstract: Additional file 1: Figure S1. Isolation of plasma EVs by ultracentrifugation (A) NTA demonstrating the size distribution of EVs diluted samples of plasma-derived EVs using ultracentrifugation. (B) Representative TEM image of plasma-derived EVs showing a membrane structure composed of a lipid bilayer (Bar = 200 nm). NTA; nanoparticle tracking analysis; EV; extracellular vesicle; TEM; transmission electron microscope. Figure S2. miR-4488 and miR-342-3p from the psoriatic lesional skin show a weak-to-moderate association with PASI and BSA scores. Skin miR-4488 and miR-342-3p levels plotted against PASI and BSA. The significance of the correlation was tested using Spearman's rank correlation test. *P < 0.05. PASI, Psoriasis Area and Severity Index; BSA, body surface area. Figure S3. EV miR-625-3p correlates across different isolation methods (A) Representative TEM image of plasma-derived EVs using mini-size exclusion chromatography (Bar = 200 nm). (B) Relative expression levels of EV miR-625-3p isolated using miRCURY exosome Kit showing a strong positive correlation with relative expression of EV miR-625-3p isolated after mini-size exclusion chromatography. Result shown represent combined data of two experiments. The significance of the correlation was tested using the Pearson's correlation test. ****P < 0.0001. Figure S4. Venn diagram showing number of predicted gene-targets for miR-625-3p using three different algorithms (miRDB/TargetScan/miRTarBase). The top 100 overlapping genes (6 genes overlapping all three, 94 genes overlapping any two) were chosen for target prediction. Table S1. DE microRNA candidates* identified from next-generation sequencing (NGS). Table S2. miRNA and mRNAPrimers Used for RT-qPCR.

Abstract: Additional file 2: Figure S2. Transmission electron microscopy (A) and nanoparticle tracking analysis (B) of extracellular vesicles originating from HF.

Abstract: Additional file 1: Supplementary Fig. S1. Characterization of MTNs assay. (a) Washing buffer testing either with ethanol or distilled water for effectiveness on the Fe3O4@SiO2-NH2 MNPs. (b) Testing of various transferrin concentrations and determined the optimal concentration via the zeta potential analysis. (c) Performance of MTNs depends on incubation time (24 h or 3 h) with either 10 mL HCT-116 cell culture medium (1-2 & 5-6) or 500 µL human normal serum sample (3-4 & 7-8) using Coomassie blue staining. (d) Western blot result from 24 h incubation with either 10 mL HCT-116 cell culture medium (1-2) or 500 µL human normal serum sample (3-4). Supplementary Fig. S2. Characterization of the isolated exosomes. (a−c) Representative SEM images and NTA of the exosomes isolated from colon cancer CCM using (a and b) MTNs, (c and d) UC, and (e and f) TEI. Supplementary Fig. S3. Validation of exosome isolation. (a and b) Representative (a) SEM image and (b) zeta-potential of the exosomes isolated from colon cancer CCM using MTNs. Supplementary Fig. S4. Flowchart of statistical analysis and batch effect correction (a) From the first 746 quantified proteins, 550 proteins that were quantified at least 70% in at least one of the three groups were selected, log2-transformed, and normalized by the width adjustment method. Then, missing values were estimated from a normal distribution with an area of 0.3 minus 1.8 from the protein distribution for each sample, and batch 1 and batch 2 were adjusted for the batch effect with the protein average. Principal component analysis plot (b) before batch correction and (c) after batch correction. Circle (batch 1 samples), filled rectangle (batch 2 samples), green (Parkinson’s disease), blue (multiple sclerosis), orange (dementia). Supplementary Fig. S5. Distribution of normalized protein abundances based on label-free quantification. (a) Mapping proteins to exosomes public database, Vesiclepedia. Exosome top 100 proteins are highlighted in red. Proteins belonging to Vesiclepedia are shown in blue. The remaining proteins are shown in gray. (b) Mapping proteins to brain-elevated protein in the Human Protein Atlas. Brain-elevated proteins are highlighted in red. The remaining proteins are shown in gray. Supplementary Fig. S6. Boxplots of 20 proteins with top 10 and bottom 10 proteins with loadings of principal component 1. (a) Top 10 proteins (b) Bottom 10 proteins. Green (Parkinson’s disease), blue (multiple sclerosis), orange (dementia); * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, n.s., not significant. Supplementary Fig. S7. Boxplots of 21 proteins highly expressed in the brain in the HPA or annotated in SYNGO. Green (Parkinson’s disease), blue (multiple sclerosis), orange (dementia); * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, n.s., not significant. Supplementary Fig. S8. Principal component analysis (PCA) of plasma exosome proteins and assessment of the relative quality of clustering by silhouette method. (a) PCA by the three sample groups (Parkinson’s disease (PD; N = 10), multiple sclerosis (MS; N = 10), dementia (Dem; N = 10)) and silhouette plot of the groups. (b) PCA by sex (female (N = 16) and male (N = 14)) and silhouette plot of sex. (c) PCA by age groups based on age 65 (age>65 (N = 15) and age≤65 (N = 15)) and silhouette plot of the age groups. Supplementary Table S1. Baseline characteristics of the patients.

Abstract: <p>Supplementary Figure S1 shows characterization of EVs. (A) Western blots of whole cell lysates (WCL) and EVs from MDA-MB-231 showing EV markers and a Golgi marker (GM130, as a negative control for EV-specific proteins). (B) Nanoparticle tracking analysis (NTA) of MDA-MB-231 EVs showing size distribution (n=3 biological replicates). Data are presented as mean ± standard error of the mean (SEM).</p>

Abstract: The robust characterization of lipid nanoparticles (LNPs) encapsulating therapeutics or vaccines is an important and multifaceted translational problem. Sedimentation velocity analytical ultracentrifugation (SV-AUC) has proven to be a powerful approach in the characterization of size-distribution, interactions, and composition of various types of nanoparticles across a large size range, including metal nanoparticles (NPs), polymeric NPs, and also nucleic acid loaded viral capsids. Similar potential of SV-AUC can be expected for the characterization of LNPs, but is hindered by the flotation of LNPs being incompatible with common sedimentation analysis models. To address this gap, we developed a high-resolution, diffusion-deconvoluted sedimentation/flotation distribution analysis approach analogous to the most widely used sedimentation analysis model c(s). The approach takes advantage of independent measurements of the average particle size or diffusion coefficient, which can be conveniently determined, for example, by dynamic light scattering (DLS). We demonstrate the application to an experimental model of extruded liposomes as well as a commercial LNP product and discuss experimental potential and limitations of SV-AUC. The method is implemented analogously to the sedimentation models in the free, widely used SEDFIT software.

Abstract: Abstract STUDY QUESTION What is the transcriptomic response of human blastocysts following internalization of extracellular vesicles (EVs) secreted by the human endometrium? SUMMARY ANSWER EVs secreted by the maternal endometrium induce a transcriptomic response in human embryos that modulates molecular mechanisms related to embryo development and implantation. WHAT IS KNOWN ALREADY EVs mediate intercellular communication by transporting various molecules, and endometrial EVs have been postulated to be involved in the molecular regulation of embryo implantation. Our previous studies showed that endometrial EVs carry miRNAs and proteins associated with implantation events that can be taken up by human blastocysts; however, no studies have yet investigated the transcriptomic response of human embryos to this EV uptake, which is crucial to demonstrate the functional significance of this communication system. STUDY DESIGN, SIZE, DURATION A prospective descriptive study was performed. Primary human endometrial epithelial cells (pHEECs), derived from endometrial biopsies collected from fertile oocyte donors (n = 20), were cultured in vitro to isolate secreted EVs. Following EV characterization, Day 5 human blastocysts (n = 24) were cultured in the presence or absence of the EVs for 24 h and evaluated by RNA-sequencing. PARTICIPANTS/MATERIALS, SETTING, METHODS EVs were isolated from the conditioned culture media using ultracentrifugation, and characterization was performed using western blot, nanoparticle tracking analysis, and transmission electron microscopy. Human blastocysts were devitrified, divided into two groups (n = 12/group), and cultured in vitro for 24 h with or without previously isolated EVs. RNA-sequencing analysis was performed, and DESeq2 was used to identify differentially expressed genes (DEGs) (FDR &lt; 0.05). QIAGEN Ingenuity Pathway Analysis was used to perform the functional enrichment analysis and integration with our recently published data from the pHEECs’ EV-miRNA cargo. MAIN RESULTS AND THE ROLE OF CHANCE Characterization confirmed the isolation of EVs from pHEECs’ conditioned culture media. Among the DEGs in blastocysts co-cultured with EVs, we found 519 were significantly upregulated and 395 were significantly downregulated. These DEGs were significantly enriched in upregulated functions related to embryonic development, cellular invasion and migration, cell cycle, cellular organization and assembly, gene expression, and cell viability; and downregulated functions related to cell death and DNA fragmentation. Further, the intracellular signaling pathways regulated by the internalization of endometrial EVs were previously related to early embryo development and implantation potential, for their role in pluripotency, cellular homeostasis, early embryogenesis, and implantation-related processes. Finally, integrating data from miRNA cargo of EVs, we found that the miRNAs carried by endometrial EVs targeted nearly 80% of the DEGs in human blastocysts. LIMITATIONS, REASONS FOR CAUTION This is an in vitro study in which conditions of endometrial cell culture could not mimic the intrauterine environment. WIDER IMPLICATIONS OF THE FINDINGS This study provides novel insights into the functional relevance of EVs secreted by the human endometrium, and particularly the role of EV-miRNA regulation on global transcriptome behavior of human blastocysts during early embryogenesis and embryo implantation. It provides potential biomarkers that could become useful diagnostic targets for predicting implantation success. STUDY FUNDING/COMPETING INTEREST(S) This study was supported by the Spanish Ministry of Education through FPU awarded to M.S.-B. (FPU18/03735), Generalitat Valenciana through VALi+d Programme awarded to M.C.C.-G. (ACIF/2019/139), and Instituto de Salud Carlos III and cofounded by the European Social Fund (ESF) “Investing in your future” through the Miguel Servet Program (CP20/00120 [H.F.]; CP19/00149 [I.C.]). The authors have no conflicts of interest to disclose. TRIAL REGISTRATION NUMBER N/A.

Abstract: The widespread and increasing use of nanomaterials has resulted in a higher likelihood of exposure by inhalation for nanotechnology workers. However, tracking the internal dose of nanoparticles deposited at the airways level, is still challenging. To assess the suitability of particle number concentration determination as biomarker of internal dose, we carried out a cross sectional investigation involving 80 workers handling nanomaterials. External exposure was characterized by portable counters of particles DISCminiTM (Testo, DE), allowing to categorize 51 workers as exposed and 29 as non-exposed (NE) to nanoparticles. Each subject filled in a questionnaire reporting working practices and health status. Exhaled breath condensate was collected and analysed for the number of particles/ml as well as for inflammatory biomarkers. A clear-cut relationship between the number of airborne particles in the nano-size range determined by the particle counters and the particle concentration in exhaled breath condensate (EBC) was apparent. Moreover, inflammatory cytokines (IL-1β, IL-10, and TNF-α) measured in EBC, were significantly higher in the exposed subjects as compared to not exposed. Finally, significant correlations were found between external exposure, the number concentration of particles measured by the nanoparticle tracking analysis (NTA) and inflammatory cytokines. As a whole, the present study, suggests that NTA can be regarded as a reliable tool to assess the inhaled dose of particles and that this dose can effectively elicit inflammatory effects.

Abstract: Extracellular vesicles (EVs) are membrane-enclosed vesicles released by cells. They carry proteins, nucleic acids, and metabolites which can be transferred to a recipient cell, locally or at a distance, to elicit a functional response. Since their discovery over 30 years ago, the functional repertoire of EVs in both physiological (e.g., organ morphogenesis, embryo implantation) and pathological (e.g., cancer, neurodegeneration) conditions has cemented their crucial role in intercellular communication. Moreover, because the cargo encapsulated within circulating EVs remains protected from degradation, their diagnostic as well as therapeutic (such as drug delivery tool) applications have garnered vested interest. Global efforts have been made to purify EV subtypes from biological fluids and in vitro cell culture media using a variety of strategies and techniques, with a major focus on EVs of endocytic origin called exosomes (30-150 nm in size). Given that the secretome comprises of soluble secreted proteins, protein aggregates, RNA granules, and EV subtypes (such as exosomes, shed microvesicles, apoptotic bodies), it is imperative to purify exosomes to homogeneity if we are to perform biochemical and biophysical characterization and, importantly, functional dissection. Besides understanding the composition of EV subtypes, defining molecular bias of how they reprogram target cells also remains of paramount importance in this area of active research. Here, we outline a systematic "how to" protocol (along with useful insights/tips) to obtain highly purified exosomes and perform their biophysical and biochemical characterization. This protocol employs a mass spectrometry-based proteomics approach to characterize the protein composition of exosomes. We also provide insights on different isolation strategies and their usefulness in various downstream applications. We outline protocols for lipophilic labeling of exosomes to study uptake by a recipient cell, investigating cellular reprogramming using proteomics and studying functional response to exosomes in the Transwell-Matrigel™ Invasion assay.

Abstract: Previous studies demonstrated that EV71-infected cells secrete extracellular vesicles (EVs), facilitating the transfer of viral components to recipient cells and thereby promoting virus spread. Considering lipid signaling plays a crucial role in EVs-mediated cell-to-cell communication, we compared the lipid profile of EVs secreted from uninfected and EV71-infected cells (EVs-Mock and EVs-EV71) using the human rhabdomyosarcoma (RD) cell model. These two groups of EVs were purified by using size exclusion chromatography (SEC), respectively, and evaluated by transmission electron microscopy (TEM), nanoparticle tracking technology (NTA), and Western blotting (WB). In-depth lipidomic analysis of EVs identified 1705 lipid molecules belonging to 43 lipid classes. The data showed a significant increase in the lipid content of EVs after EV71 infection. Meanwhile, we deeply analyzed the changes in lipids and screened for lipid molecules with significant differences compared EVs-EV71 with EVs-Mock EVs. Altogether, we report the alterations in the lipid profile of EVs derived from RD-cells after EV71 infection, which may affect the function of the EVs in the recipient cells.

Abstract: Non-valvular atrial fibrillation (AF) is the most common type of cardiac arrhythmia. AF is caused by electrophysiological abnormalities and alteration of atrial tissues, which leads to the generation of abnormal electrical impulses. Extracellular vesicles (EVs) are membrane-bound vesicles released by all cell types. Large EVs (lEVs) are secreted by the outward budding of the plasma membrane during cell activation or cell stress. lEVs are thought to act as vehicles for miRNAs to modulate cardiovascular function, and to be involved in the pathophysiology of cardiovascular diseases (CVDs), including AF. This study identified lEV-miRNAs that were differentially expressed between AF patients and non-AF controls.lEVs were isolated by differential centrifugation and characterized by Nanoparticle Tracking Analysis (NTA), Transmission Electron Microscopy (TEM), flow cytometry and Western blot analysis. For the discovery phase, 12 AF patients and 12 non-AF controls were enrolled to determine lEV-miRNA profile using quantitative reverse transcription polymerase chain reaction array. The candidate miRNAs were confirmed their expression in a validation cohort using droplet digital PCR (30 AF, 30 controls). Bioinformatics analysis was used to predict their target genes and functional pathways.TEM, NTA and flow cytometry demonstrated that lEVs presented as cup shape vesicles with a size ranging from 100 to 1000 nm. AF patients had significantly higher levels of lEVs at the size of 101-200 nm than non-AF controls. Western blot analysis was used to confirm EV markers and showed the high level of cardiomyocyte expression (Caveolin-3) in lEVs from AF patients. Nineteen miRNAs were significantly higher (> twofold, p < 0.05) in AF patients compared to non-AF controls. Six highly expressed miRNAs (miR-106b-3p, miR-590-5p, miR-339-3p, miR-378-3p, miR-328-3p, and miR-532-3p) were selected to confirm their expression. Logistic regression analysis showed that increases in the levels of these 6 highly expressed miRNAs associated with AF. The possible functional roles of these lEV-miRNAs may involve in arrhythmogenesis, cell apoptosis, cell proliferation, oxygen hemostasis, and structural remodeling in AF.Increased expression of six lEV-miRNAs reflects the pathophysiology of AF that may provide fundamental knowledge to develop the novel biomarkers for diagnosis or monitoring the patients with the high risk of AF.

Abstract: Characterization and quantification of virus-like particles (VLPs) through high performance liquid chromatography (HPLC)-based methods are challenging because of their large size, structural complexity, internal structural heterogeneity, and instability. Analytical techniques are essential to monitor morphology and internal structural heterogeneity at each process stage. Common analytical tools used in VLP characterization are microscopic techniques (such as transmission electron microscopy [TEM], atomic force-field microscopy [AFM], cryo-electron microscope [cryo-EM]), biochemical techniques (SDS-PAGE, western blotting), and light scattering techniques (such as dynamic light scattering [DLS], nanoparticle tracking analysis [NTA], and size-exclusion chromatography coupled with multi-angle light scattering [SEC-MALS]). However, these techniques are semi-quantitative and do not address morphology and internal heterogeneity. Therefore, HPLC-based techniques are sensitive, robust, and offer better resolution. The purity and titer of VLPs at any process stage can be monitored by reversed-phase chromatography and morphology, and stability-related issues can be monitored by the combination of HPLC and light scattering techniques like SEC-MALS. Challenges in HPLC-based methods are choosing columns with the right pore size and surface chemistry and effective sample preparations, as VLPs are very unstable and prone to fragmentation at process stages and the low titre of the VLPs. This article discusses the challenges and effective solutions for HPLC-based analytical characterization of VLPs.

Abstract: To improve the accuracy of nanoparticle sizes estimation in polydisperse samples and flowing samples, we discuss a novel nanoparticle tracking analysis (NTA) algorithm in detail. A local adaptive threshold segmentation algorithm is used to improve the recognition efficiency of weak light intensity particles, and a new particle matching strategy including multiple optimization steps is proposed to improve the accuracy of trajectory tracking. A flow correction algorithm is introduced to remove the flow vector from the particle motion displacement and retain only the Brownian motion, which enables the NTA algorithm to be applied to flowing samples detection. The particle size measurement experiment of mixed nanosphere solution shows that the polydisperse sample particle sizes measured by the NTA algorithm are close to the true values. The particle size measurement experiment of the nanosphere flow sample shows that the measurement result with the flow correction algorithm is closer to the true value. In summary, we have demonstrated that the proposed NTA algorithm can accurately measure particle sizes of polydisperse samples and flowing samples.

Abstract: Background: High-grade serous carcinoma (HGSC) is the most lethal of gynecological cancers in developed countries. It usually presents late with non-specific symptoms and most cases are diagnosed at an advanced stage, with 5-year overall survival being around 40%. Biomarkers for screening and early diagnosis of this aggressive disease are, thus, a research priority. Extracellular vesicles (EVs) that reflect the cell of origin and that can be isolated from local fluid and plasma by minimally invasive liquid biopsy are such promising biomarkers. Besides EV concentration and molecular profile, which have been the main focus of research for many years, recent studies have also called attention to EV size distribution. The aim of our study was to evaluate the potential of EV concentration and size distribution in local fluid and plasma as diagnostic biomarkers for HGSC. Methods: Paired pretreatment ascites and plasma samples from 37 patients with advanced HGSC and paired pretreatment free peritoneal fluid (FPF) and plasma samples from 40 controls with benign ovarian pathology (BOP) were analyzed using nanoparticle tracking analysis (NTA). Results: We observed a significant difference in EV concentration in local fluid, but not in plasma, between HGSC patients and the control group. We also found a significant difference in EV size distribution in both local fluid and plasma between HGSC patients and the control group. The receiver operating characteristics (ROC) curve analysis of EV characteristics showed excellent diagnostic performance for the mode, D10, and D50 in local fluid and acceptable diagnostic performance for EV concentration and mean EV size in local fluid, as well as for the mode and D10 value in plasma. Conclusions: The results of our study show that EV concentration in local fluid and more importantly EV size distribution in both local fluid and plasma are significantly changed in the presence of HGSC. Future research of size-dependent molecular profiling of EVs could help identify novel diagnostic biomarkers for HGSC.

Abstract: Short title of the paper … Background: Exosomes are nano-sized vesicles containing proteins, lipids, enzymes, and other substances. Recently, plant-derived exosomes have attracted attention as cosmeceutical materials due to their beneficial effects on anti-aging and regeneration properties. Upcycling involves converting waste materials, into new products. Portulaca oleracea extract offers antioxidant and anti-aging benefits. Artificial neural networks, an application of AI, are computing technologies that mimic the human brain's structure. Method: Purslane waste extract was optimized by AI. To obtain the exosomes ultracentrifugation method was used. To conduct the morphological analysis of exosomes, SEM and TEM were performed. Size and zeta potential were measured. To measure the number of exosome particles per ml nanoparticle tracking assay (NTA) was performed. The exosomes were applied to human mesenchymal stem cells to analyze the cell proliferation activity by Cell Titer Glo. Fish embryo toxicity test was performed to assess the effects of the exosomes on zebrafish embryonic development. Results: The average size of exosomes was approximately 122 nm. It was found that the total number of exosome was 2.42x1010+/- 5.80x108 particles/ml. The zeta potential of exosomes was -15,9 mV, indicating good stability. Exosomes significantly promoted hMSC proliferation. Zebrafish embryos exposed to the dilutions of exosomes below the lethal concentration exhibited development similar to the control. Discussion and Conclusion: Purslane-derived exosomes demonstrated regenerative potential for longevity and anti-aging. These findings may lead to further approaching the use of AI modeling to obtain upcycled plant extracts for exosome derivation. This may open up new avenues to serve novel ingredients for cosmetics industry.

Abstract: Abstract Although the isolation and counting of small extracellular vesicles (sEVs) are essential steps in sEV research, an integrated method with scalability and efficiency has not been developed. Here, we present a scalable and ready‐to‐use extracellular vesicle (EV) isolation and counting system (EVics) that simultaneously allows isolation and counting in one system. This novel system consists of (i) EVi, a simultaneous tandem tangential flow filtration (TFF)‐based EV isolation component by applying two different pore‐size TFF filters, and (ii) EVc, an EV counting component using light scattering that captures a large field‐of‐view (FOV). EVi efficiently isolated 50–200 nm‐size sEVs from 15 µL to 2 L samples, outperforming the current state‐of‐the‐art devices in purity and speed. EVc with a large FOV efficiently counted isolated sEVs. EVics enabled early observations of sEV secretion in various cell lines and reduced the cost of evaluating the inhibitory effect of sEV inhibitors by 20‐fold. Using EVics, sEVs concentrations and sEV PD‐L1 were monitored in a 23‐day cancer mouse model, and 160 clinical samples were prepared and successfully applied to diagnosis. These results demonstrate that EVics could become an innovative system for novel findings in basic and applied studies in sEV research.

Abstract: Abstract Nanoparticles including extracellular vesicles derived from mesenchymal stem cells are of increasing interest for research and clinical use in regenerative medicine. Extracellular vesicles (EVs), including also previously named exosomes, provide a promising cell-free tool for therapeutic applications, which is probably a safer approach to achieve sufficient healing. Storage of EVs may be necessary for clinical applications as well as for further experiments, as the preparation is sometimes laborious and larger quantities tend to be gained. For this purpose, nanoparticles were obtained from mesenchymal stem cells from adipose tissue (AdMSC) of horses and dogs. The EVs were then stored for 7 days under different conditions (− 20 °C, 4 °C, 37 °C) and with the addition of various additives (5 mM EDTA, 25–250 µM trehalose). Afterwards, the size and number of EVs was determined using the nano tracking analyzing method. With our investigations, we were able to show that storage of EVs for up to 7 days at 4 °C does not require the addition of supplements. For the other storage conditions, in particular freezing and storage at room temperature, the addition of EDTA was found to be suitable for preventing aggregation of the particles. Contrary to previous publications, trehalose seems not to be a suitable cryoprotectant for AdMSC-derived EVs. The data are useful for processing and storage of isolated EVs for further experiments or clinical approaches in veterinary medicine.