Search Results (43)

Exosomes are nanoscale extracellular vesicles (EVs) that carry biomolecular signatures reflective of their parent cells, making them powerful tools for non-invasive diagnostics and therapeutic monitoring. Despite their potential, clinical application is hindered by challenges such as low abundance, heterogeneity, and the complexity of biological samples. To address these limitations, plasmonic biosensing technologies—particularly propagating surface plasmon resonance (PSPR), localized surface plasmon resonance (LSPR), and surface-enhanced Raman scattering (SERS)—have been developed to enable label-free, highly sensitive, and multiplexed detection at the single-vesicle level. This review outlines recent advancements in nanoplasmonic platforms for exosome detection and profiling, emphasizing innovations in nanostructure engineering, microfluidic integration, and signal enhancement. Representative applications in oncology, neurology, and immunology are discussed, along with the increasingly critical role of artificial intelligence (AI) in spectral interpretation and diagnostic classification. Key technical and translational challenges—such as assay standardization, substrate reproducibility, and clinical validation—are also addressed. Overall, this review highlights the synergy between exosome biology and plasmonic nanotechnology, offering a path toward real-time, precision diagnostics via sub-femtomolar detection of exosomal miRNAs through next-generation biosensing strategies. Full article

Artificial insemination (AI) is a key breeding technique in the swine industry; however, the lack of reliable biomarkers for semen quality limits its effectiveness. Seminal plasma (SP) contains extracellular vesicles (EVs) that present a promising, non-invasive biomarker for semen quality. This study explores the biochemical profiles of boar SP to assess semen quality through near-infrared spectroscopy (NIRS) and proteomics of SP-EVs. Fresh semen from mature Duroc boars was evaluated based on sperm motility, classifying samples as Passed (≥70%) or Failed (<70%). NIRS analysis identified distinct variations in water structures at specific wavelengths (C1, C5, C12 nm), achieving high accuracy (92.2%), sensitivity (94.2%), and specificity (90.3%) through PCA-LDA. Proteomic analysis of SP-EVs revealed 218 proteins in Passed and 238 in Failed samples. Nexin-1 and seminal plasma protein pB1 were upregulated in Passed samples, while LGALS3BP was downregulated. The functional analysis highlighted pathways associated with single fertilization, filament organization, and glutathione metabolism in Passed samples. Integrating NIRS with SP-EV proteomics provides a robust approach to non-invasive assessment of semen quality. These findings suggest that SP-EVs could serve as effective biosensors for rapid semen quality assessment, enabling better boar semen selection and enhancing AI practices in swine breeding. Full article

Polycystic ovary syndrome (PCOS) affects 6–19% of reproductive-age women worldwide, yet diagnosis remains challenging due to heterogeneous presentations and symptoms overlapping with other endocrine disorders. Recent studies have shown that gut dysbiosis plays a significant role in PCOS pathophysiology, with bacterial extracellular vesicles (BEVs) functioning as critical mediators of the gut–ovary axis. BEVs carry distinct cargos in PCOS patients—including specific miRNAs and inflammatory proteins—and show promise for both diagnostic and therapeutic applications. Artificial intelligence (AI) is emerging as a promising significant tool in PCOS research due to improved diagnostic accuracy and the capability to analyze complex datasets combining microbiome, BEV, and clinical parameters. These integrated approaches have the potential to better address PCOS multifactorial nature, enabling improved phenotypic classification and personalized treatment strategies. This review examines recent advances in the last 25 years in microbiome, BEV, and AI applications in PCOS research using PubMed, Web of Science, and Scopus databases. We explore the diagnostic potential of the AI-driven analysis of microbiome and BEV profiles, and address ethical considerations including data privacy and algorithmic bias. As these technologies continue to evolve, they hold increasing potential for the improvement of PCOS diagnosis and management, including the development of safer, more precise, and effective interventions. Full article

Liquid biopsy has gained attention in oncology as a non-invasive diagnostic tool, offering valuable insights into tumor biology through the analysis of circulating nucleic acid (cfDNA and cfRNA), circulating tumor cells (CTCs), extracellular vesicles (EVs), and tumor-educated platelets (TEPs). In this review, we summarize the clinical use of liquid biopsies in cancer now and look forward to its future, with a particular emphasis on some the methods used to isolate the liquid biopsy analytes. This technique provides real-time information on tumor dynamics, treatment response, and disease progression, with the potential for early diagnosis and personalized treatment. Despite its advantages, liquid biopsy faces several challenges, particularly in detecting analytes in early-stage cancers and evaluating the tumor molecular fraction. Tumor burden, molecular fraction, and the presence of subclones can impact the sensitivity and specificity of the analysis. Recent advancements in artificial intelligence (AI) have enhanced the diagnostic accuracy of liquid biopsy by integrating data, and multimodal approaches that combine multiple biomarkers such as ctDNA, CTCs, EVs, and TEPs show promise in providing a more comprehensive view of tumor characteristics. Liquid biopsy has the potential to revolutionize cancer care by providing rapid, non-invasive, and cost-effective diagnostics, enabling timely interventions and personalized treatment strategies. Full article

Background/Objectives: Extracellular vesicles (EVs) are nanoscale, membrane-enclosed structures that play key roles in intercellular communication and biological regulation. Among them, Lactobacillus paracasei-derived EVs (Lp-EVs) have attracted attention for their anti-inflammatory and anti-aging properties, making them promising candidates for therapeutic and cosmetic use. However, methods for specific detection and quantitative evaluation of Lp-EVs are still limited. This study aims to develop a surface plasmon resonance (SPR)-based sensor system for the precise and selective detection of Lp-EVs. Methods: Anti-p40 antibodies were immobilized on gold thin films to construct an SPR sensing platform. The overexpression of the p40 protein on Lp-EVs was confirmed using flow cytometry and Western blotting. For functional evaluation, Lp-EVs were applied to an artificial skin membrane mounted on a Franz diffusion cell, followed by SPR-based quantification and fluorescence imaging to assess their skin penetration behavior. Results: The developed SPR sensor demonstrated high specificity and a detection limit of 0.12 µg/mL, with a linear response range from 0.1 to 0.375 µg/mL. It successfully discriminated Lp-EVs from other bacterial EVs. In the skin diffusion assay, Lp-EVs accumulated predominantly in the epidermal layer without penetrating into the dermis, likely due to their negative surface charge and interaction with the hydrophobic epidermal lipid matrix. Fluorescence imaging confirmed this epidermal confinement, which increased over 24 h. Conclusions: This study presents a sensitive and selective SPR-based platform for detecting Lp-EVs and demonstrates their potential for targeted epidermal delivery. These findings support the use of Lp-EVs in skin-focused therapeutic and cosmetic applications. Future studies will explore strategies such as microneedle-assisted delivery to enhance transdermal penetration and efficacy. Full article

Advances in neuro-oncology have transformed the diagnosis and management of brain tumors, which are among the most challenging malignancies due to their high mortality rates and complex neurological effects. Despite advancements in surgery and chemoradiotherapy, the prognosis for glioblastoma multiforme (GBM) and brain metastases remains poor, underscoring the need for innovative diagnostic strategies. This review highlights recent advancements in imaging techniques, liquid biopsies, and artificial intelligence (AI) applications addressing current diagnostic challenges. Advanced imaging techniques, including diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS), improve the differentiation of tumor progression from treatment-related changes. Additionally, novel positron emission tomography (PET) radiotracers, such as ¹⁸F-fluoropivalate, ¹⁸F-fluoroethyltyrosine, and ¹⁸F-fluluciclovine, facilitate metabolic profiling of high-grade gliomas. Liquid biopsy, a minimally invasive technique, enables real-time monitoring of biomarkers such as circulating tumor DNA (ctDNA), extracellular vesicles (EVs), circulating tumor cells (CTCs), and tumor-educated platelets (TEPs), enhancing diagnostic precision. AI-driven algorithms, such as convolutional neural networks, integrate diagnostic tools to improve accuracy, reduce interobserver variability, and accelerate clinical decision-making. These innovations advance personalized neuro-oncological care, offering new opportunities to improve outcomes for patients with central nervous system tumors. We advocate for future research integrating these tools into clinical workflows, addressing accessibility challenges, and standardizing methodologies to ensure broad applicability in neuro-oncology. Full article

Critical limb ischemia (CLI) poses a substantial and intricate challenge in vascular medicine, necessitating the development of innovative therapeutic strategies to address its multifaceted pathophysiology. Conventional revascularization approaches often fail to adequately address the complexity of CLI, necessitating the identification of alternative methodologies. This review explores uncharted territory beyond traditional therapies, focusing on the potential of two distinct yet interrelated entities: cell-derived extracellular vesicles (EVs) and artificial nanovesicles. Cell-derived EVs are small membranous structures naturally released by cells, and artificial nanovesicles are artificially engineered nanosized vesicles. Both these vesicles represent promising avenues for therapeutic intervention. They act as carriers of bioactive cargo, including proteins, nucleic acids, and lipids, that can modulate intricate cellular responses associated with ischemic tissue repair and angiogenesis. This review also assesses the evolving landscape of CLI revascularization through the unique perspective of cell-derived EVs and artificial nanovesicles. The review spans the spectrum from early preclinical investigations to the latest translational advancements, providing a comprehensive overview of the current state of research in this emerging field. These groundbreaking vesicle therapies hold immense potential for revolutionizing CLI treatment paradigms. Full article

Artificial insemination (AI), as an efficient assisted reproduction technology, can help the livestock industry to improve livestock and poultry breeds, optimize production performance and improve reproductive efficiency. AI technology has been widely used in pig production in China, but boar fertility affects the effectiveness of AI, and more and more studies have shown that there are significant differences in the fertility of boars with similar semen quality indicators. Therefore, this study aimed to identify biomarker molecules that indicate the level of boar fertility, which is important for improving the efficiency of AI. In this study, we collected 40 mL of ejaculates per boar used for extracellular vesicle (EV) characterization in 20 boars and identified 53 differentially expressed miRNAs by small RNA sequencing, of which 44 miRNAs were up-regulated in the high-fertility seminal EVs compared with low-fertility seminal EVs, and nine miRNAs were down-regulated. miR-26a was most significantly down-regulated in the high-fertility group compared to the low-fertility group, and it was hypothesized that this miRNA could be used as a biomolecular marker of semen reproductive performance. To further determine the effect of miR-26a on sperm function, we successfully established a miR-26a overexpression model and found that miR-26a reduced sperm viability, motility, acrosome integrity, plasma membrane integrity and ATP levels. Bioinformatics analysis and dual luciferase reporter analysis revealed that miR-26a directly targets High mobility group A1 (HMGA1). In conclusion, miR-26a can be used as a biomarker to identify high and low fertility in boar semen. Full article

Pancreatic cancer (PC) is an increasing cause of cancer-related death, with a dismal prognosis caused by its aggressive biology, the lack of clinical symptoms in the early phases of the disease, and the inefficacy of treatments. PC is characterized by a complex tumor microenvironment. The interaction of its cellular components plays a crucial role in tumor development and progression, contributing to the alteration of metabolism and cellular hyperproliferation, as well as to metastatic evolution and abnormal tumor-associated immunity. Furthermore, in response to intrinsic oncogenic alterations and the influence of the tumor microenvironment, cancer cells undergo a complex oncogene-directed metabolic reprogramming that includes changes in glucose utilization, lipid and amino acid metabolism, redox balance, and activation of recycling and scavenging pathways. The advent of omics sciences is revolutionizing the comprehension of the pathogenetic conundrum of pancreatic carcinogenesis. In particular, metabolomics and genomics has led to a more precise classification of PC into subtypes that show different biological behaviors and responses to treatments. The identification of molecular targets through the pharmacogenomic approach may help to personalize treatments. Novel specific biomarkers have been discovered using proteomics and metabolomics analyses. Radiomics allows for an earlier diagnosis through the computational analysis of imaging. However, the complexity, high expertise required, and costs of the omics approach are the main limitations for its use in clinical practice at present. In addition, the studies of extracellular vesicles (EVs), the use of organoids, the understanding of host–microbiota interactions, and more recently the advent of artificial intelligence are helping to make further steps towards precision and personalized medicine. This present review summarizes the main evidence for the application of omics sciences to the study of PC and the identification of future perspectives. Full article

Selective staining of extracellular vesicles (EVs) is a major challenge for diagnostic and therapeutic applications. Herein, the EV labeling properties of a new class of tetranuclear polypyridylruthenium(II) complexes, Rubb₇-TNL and Rubb₇-TL, as phosphorescent stains are described. These new stains have many advantages over standard stains to detect and characterize EVs, including: high specificity for EV staining versus cell staining; high phosphorescence yields; photostability; and a lack of leaching from EVs until incorporation with target cells. As an example of their utility, large EVs released from control (basal) or lipopolysaccharide (LPS)-stimulated THP-1 monocytic leukemia cells were studied as a model of immune system EVs released during bacterial infection. Key findings from EV staining combined with flow cytometry were as follows: (i) LPS-stimulated THP-1 cells generated significantly larger and more numerous large EVs, as compared with those from unstimulated cells; (ii) EVs retained native EV physical properties after staining; and (iii) the new stains selectively differentiated intact large EVs from artificial liposomes, which are models of cell membrane fragments or other lipid-containing debris, as well as distinguished two distinct subpopulations of monocytic EVs within the same experiment, as a result of biochemical differences between unstimulated and LPS-stimulated monocytes. Comparatively, the staining patterns of A549 epithelial lung carcinoma-derived EVs closely resembled those of THP-1 cell line-derived EVs, which highlighted similarities in their selective staining despite their distinct cellular origins. This is consistent with the hypothesis that these new phosphorescent stains target RNA within the EVs. Full article

Circulating microRNAs (miRNAs) were investigated as biomarkers for the diagnosis of early pregnancy in cattle. The levels of prospective miRNA biomarkers and the features of extracellular vesicles (EVs) in the blood were evaluated. In Study 1, plasma samples from cows 21 days after artificial insemination (AI) were examined using RT-qPCR to determine the levels of seven circulating miRNAs. Only the levels of miR-126-3p were significantly lower in the pregnant group than in the non-pregnant group. In Study 2, among individuals not pregnant at the first AI, the miRNA levels were compared between the individuals pregnant at the second AI and those who remained non-pregnant. The miR-25 levels were significantly higher in the pregnant group at the second AI than in the pregnant group at the first AI; miR-19b, miR-27b, and miR-29a levels were also high. In the non-pregnant group, changes were absent in the miRNA levels in the same individual between the first and second AIs. In Study 3, Western blotting and RT-qPCR showed the presence of miRNAs in EVs and their levels were lower than in plasma. Thus, circulating miR-126-3p may serve as a biomarker for the diagnosis of early pregnancy in cattle. In addition, the expression of some miRNAs tended to be higher during pregnancy than during non-pregnancy in the same individual, suggesting their potential as an index to determine pregnancy and non-pregnancy rates using a comparative method. Full article

Cell therapy is at the forefront of biomedicine in oncology and regenerative medicine. However, there are still significant challenges to their wider clinical application such as limited efficacy, side effects, and logistical difficulties. One of the potential approaches that could overcome these problems is based on extracellular vesicles (EVs) as a cell-free therapy modality. One of the major obstacles in the translation of EVs into practice is their low yield of production, which is insufficient to achieve therapeutic amounts. Here, we evaluated two primary approaches of artificial vesicle induction in primary T cells and the SupT1 cell line—cytochalasin B as a chemical inducer and ultrasonication as a physical inducer. We found that both methods are capable of producing artificial vesicles, but cytochalasin B induction leads to vesicle yield compared to natural secretion, while ultrasonication leads to a three-fold increase in particle yield. Cytochalasin B induces the formation of vesicles full of cytoplasmic compartments without nuclear fraction, while ultrasonication induces the formation of particles rich in membranes and membrane-related components such as CD3 or HLAII proteins. The most effective approach for T-cell induction in terms of the number of vesicles seems to be the combination of anti-CD3/CD28 antibody activation with ultrasonication, which leads to a seven-fold yield increase in particles with a high content of functionally important proteins (CD3, granzyme B, and HLA II). Full article

Exosomes are spherical extracellular nanovesicles with an endosomal origin and unilamellar lipid-bilayer structure with sizes ranging from 30 to 100 nm. They contain a large range of proteins, lipids, and nucleic acid species, depending on the state and origin of the extracellular vesicle (EV)-secreting cell. EVs’ function is to encapsulate part of the EV-producing cell content, to transport it through biological fluids to a targeted recipient, and to deliver their cargos specifically within the aimed recipient cells. Therefore, exosomes are considered to be potential biological drug-delivery systems that can stably deliver their cargo into targeted cells. Various cell-derived exosomes are produced for medical issues, but their use for therapeutic purposes still faces several problems. Some of these difficulties can be avoided by resorting to hemisynthetic approaches. We highlight here the uses of alternative exosome-mimes involving cell-membrane coatings on artificial nanocarriers or the hybridization between exosomes and liposomes. We also detail the drug-loading strategies deployed to make them drug-carrier systems and summarize the ongoing clinical trials involving exosomes or exosome-like structures. Finally, we summarize the open questions before considering exosome-like disposals for confident therapeutic delivery. Full article

Despite world-class sophisticated technologies, robotics, artificial intelligence, and machine learning approaches, cancer-associated mortalities and morbidities have shown continuous increments posing a healthcare burden. Drug-based interventions were associated with systemic toxicities and several limitations. Natural bioactive compounds derived nanoformulations, especially nanoquercetin (nQ), are alternative options to overcome drug-associated limitations. Moreover, the EVs-based cargo targeted delivery of nQ can have enormous potential in treating hepatocellular carcinoma (HCC). EVs-based nQ delivery synergistically regulates and dysregulates several pathways, including NF-κB, p53, JAK/STAT, MAPK, Wnt/β-catenin, and PI3K/AKT, along with PBX3/ERK1/2/CDK2, and miRNAs intonation. Furthermore, discoveries on possible checkpoints of anticancer signaling pathways were studied, which might lead to the development of modified EVs infused with nQ for the development of innovative treatments for HCC. In this work, we abridged the control of such signaling systems using a synergetic strategy with EVs and nQ. The governing roles of extracellular vesicles controlling the expression of miRNAs were investigated, particularly in relation to HCC. Full article

Breast cancer (BC) caused 685,000 deaths globally in 2020, earning the title of the most common type of tumor among females. With a multifactorial genesis, BC is influenced by several factors such as age, genetic and epigenetic predisposition, and an individual’s exposome, and its classification is based on morphological/histological, invasiveness, and molecular futures. Extracellular vesicles (EVs) are cell-derived lipid-bilayer-delimited nanoparticles, which are distinguishable by size, genesis, and the markers expressed in exosomes (40 to 150 nm), microvesicles (40 to 10,000 nm), and apoptotic bodies (100–5000 nm). Produced in physiological and pathological cellular contexts, EVs are shuttles of biological material and are implicated in cell-to-cell communications, thus attracting significant interest in diagnostic and drug delivery research. We report and discuss the latest evidence regarding the important role of EVs in BC, deepening their implication in tumorigenesis and metastatic mechanisms. On the other hand, the use of BC-derived EVs as prognostic biomarkers and therapeutic approaches is undergoing investigation. Hence, EVs have become new weapons in precision medicine; however, only with the support of advanced algorithms such as artificial intelligence (AI) can we develop a wide range of information. Looking ahead, it is possible to see the application of AI in the prognosis and diagnosis of different pathologies. Full article