Single Small Extracellular Vesicle (sEV) Quantification by Upconversion Nanoparticles

Proximity labeling-assisted click conjugation for electrochemical analysis of specific subpopulations in circulating extracellular vesicles

Sensitive and accurate analysis of specific subpopulations in circulating extracellular vesicles (EVs) can provide a wealth of information for cancer diagnosis and management. Thus, we propose herein a new electrochemical biosensing method based on a proximity labeling-assisted click conjugation strategy. The method's core design is use of antibody-guided proximity labeling to equip target EVs with a large amount of alkyne groups, so that azide-tagged silver nanoparticles can be accurately loaded onto target EV surfaces, via click conjugation, to generate significant electrochemical responses. Adopting CD44-positive EVs as the model, the electrochemical method was demonstrated by analyzing target EVs across a wide linear range (103-109 particles/mL) with acceptable sensitivity and specificity. Satisfactory utility in clinical blood samples, and versatility with human epidermal growth factor receptor-2-positive EVs as alternative targets, were also shown. This method may thus provide a novel approach to specific subgroup analyses of circulating EVs, and is expected to offer reliable guidance for cancer diagnoses and management strategies.

Advances of machine learning-assisted small extracellular vesicles detection strategy

Detection of extracellular vesicles (EVs), particularly small EVs (sEVs), is of great significance in exploring their physiological characteristics and clinical applications. The heterogeneity of sEVs plays a crucial role in distinguishing different types of cells and diseases. Machine learning, with its exceptional data processing capabilities, offers a solution to overcome the limitations of conventional detection methods for accurately classifying sEV subtypes and sources. Principal component analysis, linear discriminant analysis, partial least squares discriminant analysis, XGBoost, support vector machine, k-nearest neighbor, and deep learning, along with some combined methods such as principal component-linear discriminant analysis, have been successfully applied in the detection and identification of sEVs. This review focuses on machine learning-assisted detection strategies for cell identification and disease prediction via sEVs, and summarizes the integration of these strategies with surface-enhanced Raman scattering, electrochemistry, inductively coupled plasma mass spectrometry and fluorescence. The performance of different machine learning-based detection strategies is compared, and the advantages and limitations of various machine learning models are also evaluated. Finally, we discuss the merits and limitations of the current approaches and briefly outline the perspective of potential research directions in the field of sEV analysis based on machine learning.

Articular cartilage repair biomaterials: strategies and applications

Articular cartilage injury is a frequent worldwide disease, while effective treatment is urgently needed. Due to lack of blood vessels and nerves, the ability of cartilage to self-repair is limited. Despite the availability of various clinical treatments, unfavorable prognoses and complications remain prevalent. However, the advent of tissue engineering and regenerative medicine has generated considerable interests in using biomaterials for articular cartilage repair. Nevertheless, there remains a notable scarcity of comprehensive reviews that provide an in-depth exploration of the various strategies and applications. Herein, we present an overview of the primary biomaterials and bioactive substances from the tissue engineering perspective to repair articular cartilage. The strategies include regeneration, substitution, and immunization. We comprehensively delineate the influence of mechanically supportive scaffolds on cellular behavior, shedding light on emerging scaffold technologies, including stimuli-responsive smart scaffolds, 3D-printed scaffolds, and cartilage bionic scaffolds. Biologically active substances, including bioactive factors, stem cells, extracellular vesicles (EVs), and cartilage organoids, are elucidated for their roles in regulating the activity of chondrocytes. Furthermore, the composite bioactive scaffolds produced industrially to put into clinical use, are also explicitly presented. This review offers innovative solutions for treating articular cartilage ailments and emphasizes the potential of biomaterials for articular cartilage repair in clinical translation.

Printed Divisional Optical Biochip for Multiplex Visualizable Exosome Analysis at Point-of-Care

Rapid detection of various exosomes is of great significance in early diagnosis and postoperative monitoring of cancers. Here, a divisional optical biochip is reported for multiplex exosome analysis via combining the self-assembly of nanochains and precise surface patterning. Arising from resonance-induced near-field enhancement, the nanochains show distinct color changes after capturing target exosomes for direct visual detection. Then, a series of divisional nanochain-based biochips conjugated with several specific antibodies are fabricated through designed hydrophilic and hydrophobic patterns. Because of the significant wettability difference, one sample droplet is precisely self-splitting into several microdroplets enabling simultaneous identification of multiple target exosomes in 30 min with a sensitivity of 6 × 107 particles mL-1 , which is about two orders lower than enzyme-linked immunosorbent assay. Apart from the trace amount detection, excellent semiquantitative capability is demonstrated to distinguish clinical exosomes from glioblastoma patients and healthy people. This method is simple, versatile, and highly efficient that can be extended as a diagnostic tool for many diseases, promoting the development of liquid biopsy.

Boosting Dye-Sensitized Luminescence by Enhanced Short-Range Triplet Energy Transfer

Dye-sensitization can enhance lanthanide-based upconversion luminescence, but is hindered by interfacial energy transfer from organic dye to lanthanide ion Yb3+ . To overcome these limitations, modifying coordination sites on dye conjugated structures and minimizing the distance between fluorescence cores and Yb3+ in upconversion nanoparticles (UCNPs) are proposed. The specially designed near-infrared (NIR) dye, disulfo-indocyanine green (disulfo-ICG), acts as the antenna molecule and exhibits a 2413-fold increase in luminescence under 808 nm excitation compared to UCNPs alone using 980 nm irradiation. The significant improvement is attributed to the high energy transfer efficiency of 72.1% from disulfo-ICG to Yb3+ in UCNPs, with majority of energy originating from triplet state (T1 ) of disulfo-ICG. Shortening the distance between the dye and lanthanide ions increases the probability of energy transfer and strengthens the heavy atom effect, leading to enhanced T1 generation and improved dye-triplet sensitization upconversion. Importantly, this approach also applies to 730 nm excitation Cy7-SO3 sensitization system, overcoming the spectral mismatch between Cy7 and Yb3+ and achieving a 52-fold enhancement in luminescence. Furthermore, the enhancement of upconversion at single particle level through dye-sensitization is demonstrated. This strategy expands the range of NIR dyes for sensitization and opens new avenues for highly efficient dye-sensitized upconversion systems.

Advanced extracellular vesicle bioinformatic nanomaterials: from enrichment, decoding to clinical diagnostics

Extracellular vesicles (EVs) are membrane nanoarchitectures generated by cells that carry a variety of biomolecules, including DNA, RNA, proteins and metabolites. These characteristics make them attractive as circulating bioinformatic nanocabinets for liquid biopsy. Recent advances on EV biology and biogenesis demonstrate that EVs serve as highly important cellular surrogates involved in a wide range of diseases, opening up new frontiers for modern diagnostics. However, inefficient methods for EV enrichment, as well as low sensitivity of EV bioinformatic decoding technologies, hinder the use of EV nanocabinet for clinical diagnosis. To overcome these challenges, new EV nanotechnology is being actively developed to promote the clinical translation of EV diagnostics. This article aims to present the emerging enrichment strategies and bioinformatic decoding platforms for EV analysis, and their applications as bioinformatic nanomaterials in clinical settings.

Precise Identification and Profiling of Surface Proteins of Ultra Rare Tumor Specific Extracellular Vesicle with Dynamic Quantitative Plasmonic Imaging

Specific detection of tumor-derived EVs (tEVs) in plasma is complicated by nontumor EVs and non-EV particles. To accurately identify tEVs and profile their surface protein expression at single tEV resolution directly with clinical plasma is still an unmet need. Here, we present a Dynamic Immunoassay for Single tEV surface protein Profiling (DISEP), a kinetic assay based on surface plasmon resonance microscopy (SPRM) for specific single tEV profiling. DISEP adopts a pair of low-affinity oligonucleotide probes to respectively label EV surface proteins and functionalize an SPRM biosensor interface. tEVs labeled with the oligonucleotide probes possess distinctive binding kinetics from nonspecific particles in plasma, which permits accurate digital plasmonic counting of single EVs. We demonstrate DISEP for recognizing target EVs among 350-fold background plasma particles with high sensitivity (4677 EVs per μL). Clinical plasma samples were analyzed to discriminate between pancreatic cancer patients (n = 40) and healthy donors (n = 45). With a panel of biomarker signatures (EpCAM, HER2, and GPC1), DISEP only requires 10 μL primary sample from each donor to classify tumor patients with an area under the curve of 0.98. DISEP provides a highly specific EV detection and surface protein profiling strategy for early cancer diagnosis.

Enhanced Chemiluminescence under the Nanoconfinement of Covalent-Organic Frameworks and Its Application in Sensitive Detection of Cancer Biomarkers

Chemiluminescence (CL) with intensive emission has been pursued for decades. It is still challenging to find a new mechanism to enhance CL. In this work, confinement-enhanced CL was developed for the first time by the coembedding of N-(aminobutyl)-N-(ethylisoluminol) (ABEI) and Co²⁺ into gold nanoparticle-modified covalent-organic frameworks (COFs). For the consideration of improving the hydrophilicity of COFs and facilitating subsequent biological modification, gold nanoparticles were first reduced on the COF surface (Au-COF) in situ without other reducing reagents. By virtue of the abundant imine bond and π backbones, ABEI and Co²⁺ were embedded in Au-COF synergistically through π-π stacking and coordination. The confinement of ABEI and Co²⁺ into Au-COF brought an over 20-fold enhancement of CL intensity compared to that of adding them to a liquid phase, which benefitted from the three aspects of the confinement effect, including the molecular enrichment effect, the physical constraint effect, and the molecular preorganization effect. As proof of concept, a lipid-protein dual-recognition sandwich strategy based on this CL-functionalized COF was developed for the detection of breast cancer cell line-derived extracellular vesicles (EVs) with four orders of magnitude improvement in the detection limit compared to ELISA. The successful distinction of human epidermal growth factor receptor 2 (HER2)-positive patients from HER2-negative patients indicated the great application potential of the proposed bioassay in HER2-positive breast cancer diagnosis. This work proposed a novel enhancement mechanism for CL based on crystalline porous materials, which provides a new perspective for the development of CL-functionalized materials for biosensors and bioassays.

Upconversion nanoscopy revealing surface heterogeneity of tumor-secreted extracellular vesicles

Super-resolution microscopic imaging employing upconversion nanoparticles is applied to reveal the surface heterogeneity of tumor cell-derived small extracellular vesicles, i.e., exosome. The number of surface antigens of every extracellular vesicles can be quantified by both the high imaging resolution and stable brightness of upconversion nanoparticles. This method proves its great potential in nanoscale biological studies.

Nanostructures and Nanotechnologies for the Detection of Extracellular Vesicle

Liquid biopsy has been taken as a minimally invasive examination and a promising surrogate to the clinically applied tissue-based test for the diagnosis and molecular analysis of cancer. Extracellular vesicles (EVs) carry complex molecular information from the tumor, allowing for the multicomponent analysis of cancer and would be beneficial to personalized medicine. In this review, the advanced nanomaterials and nanotechniques for the detection and molecular profiling of EVs, highlight the advantages of nanotechnology in the high-purity isolation and the high-sensitive and high-specific identification of EVs, are summarized. An outlook on the clinical application of nanotechnology-based liquid biopsy in the diagnosis, prognostication, and surveillance of cancer is also provided. It provides information for developing liquid biopsy based on EVs by discussing the advantages and challenges of functionalized nanomaterials and various nanotechnologies.

Current Advances in Technologies for Single Extracellular Vesicle Analysis and Its Clinical Applications in Cancer Diagnosis

Extracellular vesicles (EVs) have been regarded as one of the most potential diagnostic biomarkers for different cancers, due to their unique physiological and pathological functions. However, it is still challenging to precisely analyze the contents and sources of EVs, due to their heterogeneity. Herein, we summarize the advances in technologies for a single EV analysis, which may provide new strategies to study the heterogeneity of EVs, as well as their cargo, more specifically. Furthermore, the applications of a single EV analysis on cancer early diagnosis are also discussed.

Er:Y2O3 and Nd:Y2O3 Nanoparticles: Synthesis, Pegylation, Characterization and Study of Their Luminescence Properties

Lanthanide-doped yttrium oxide nanoparticles can display selective upconversion properties, rendering them invaluable in the field of nanomedicine for both sensing and diagnostics. Different syntheses of Er:Y2O3 and Nd:Y2O3 nanoparticles (NPs) were studied and optimized to obtain small particles of regular shape and good crystallinity. The morphological and compositional characterizations of the nanoparticles were obtained with different techniques and showed that both Er:Y2O3 and Nd:Y2O3 NPs were well dispersed, with dimensions of the order of a few tens of nanometers. The photoluminescence and cathodoluminescence measurements showed that both Er:Y2O3 and Nd:Y2O3 NPs had good emission as well as upconversion. The nanophosphors were functionalized by a pegylation procedure to suppress unwanted reactions of the NPs with other biological components, making the NP systems biocompatible and the NPs soluble in water and well dispersed. The pegylated core/shell nanoparticles showed the same morphological and optical characteristics as the core, promoting their strategic role as photoactive material for theragnostics and biosensing.

Label-free imaging and biomarker analysis of exosomes with plasmonic scattering microscopy

Exosome analysis is a promising tool for clinical and biological research applications. However, detection and biomarker quantification of exosomes is technically challenging because they are small and highly heterogeneous. Here, we report an optical approach for imaging exosomes and quantifying their protein markers without labels using plasmonic scattering microscopy (PSM). PSM can provide improved spatial resolution and distortion-free image compared to conventional surface plasmon resonance (SPR) microscopy, with the signal-to-noise ratio similar to objective coupled surface plasmon resonance (SPR) microscopy, and millimeter-scale field of view as a prism-coupled SPR system, thus allowing exosome size distribution analysis with high throughput. In addition, PSM retains the high specificity and surface sensitivity of the SPR sensors and thus allows selection of exosomes from extracellular vesicles with antibody-modified sensor surfaces and in situ analyzing binding kinetics between antibody and the surface protein biomarkers on the captured exosomes. Finally, the PSM can be easily constructed on a popular prism-coupled SPR system with commercially available components. Thus, it may provide an economical and powerful tool for clinical exosome analysis and exploration of fundamental issues such as exosome biomarker binding properties.

Visualization of intercellular cargo transfer using upconverting nanoparticles

Cell-cell communication is important for cellular differentiation, organ function, and immune responses. In intercellular communication, the extracellular vesicles (EVs) play a significant role in delivering the cargo molecules such as genes, proteins, and enzymes, to regulate and control the ability of the recipient cells. In this study, the observation of intercellular cargo transfer via dual-colour imaging using upconverting nanoparticles (UCNPs) has been demonstrated. Using this technique, the intercellular transport via contact-dependent and contact-independent signaling in live HeLa cells was clearly visualized with real-time, long-term single-vesicle tracking. Furthermore, it was demonstrated that the endocytosed UCNPs can be transmitted with the encapsulation of EVs labelled with fluorescent proteins.

Recent progress in upconversion nanomaterials for emerging optical biological applications

The recent advances of upconversion nanoparticles (UCNPs) have made them the ideal "partner" for a variety of biological applications. In this review, we describe the emerging biological optical applications of UCNPs, focus on their potential therapeutic advantages. Firstly, we briefly review the development and mechanisms of upconversion luminescence, including organic and inorganic UCNPs. Next, in the section on UCNPs for imaging and detection, we list the development of UCNPs in visualization, temperature sensing, and detection. In the section on therapy, recent results are described concerning optogenetics and neurotherapy. Tumor therapy is another major part of this section, including the synergistic application of phototherapy such as photoimmunotherapy. In a special section, we briefly cover the integration of UCNPs in therapeutics. Finally, we present our understanding of the limitations and prospects of applications of UCNPs in biological fields, hoping to provide a more comprehensive understanding of UCNPs and attract more attention.