ICP-MS and Photothermal Dual-Readout Assay for Ultrasensitive and Point-of-Care Detection of Pancreatic Cancer Exosomes

Pressure and multicolor dual-mode detection of mucin 1 based on the pH-regulated dual-enzyme mimic activities of manganese dioxide nanosheets

Mucin 1 is an essential tumor biomarker, and developing cost-effective and portable methods for mucin 1 detection is crucial in resource-limited settings. Herein, the pH-regulated dual-enzyme mimic activities of manganese dioxide nanosheets were demonstrated, which were integrated into an aptasensor for dual-mode detection of mucin 1. Under acidic conditions, manganese dioxide nanosheets with oxidase mimic activities catalyzed the oxidation of 3,3',5,5'-tetramethylbenzidine sulfate, producing visible multicolor signals; while under basic conditions, manganese dioxide nanosheets with catalase mimic activities were used as catalyst for the decomposition of hydrogen peroxide, generating gas pressure signals. The proposed method allows the naked eye detection of mucin 1 through multicolor signal readout and the quantitative detection of mucin 1 with a handheld pressure meter or a UV-vis spectrophotometer. The study demonstrates that manganese dioxide nanosheets with pH-regulated dual-enzyme mimic activities can facilitate multidimensional transducing signals. The use of manganese dioxide nanosheets for the transduction of different signals avoids extra labels and simplifies the operation procedures. Besides, the signal readout mode can be selected according to the available detection instruments. Therefore, the use of manganese dioxide nanosheets with pH-regulated dual-enzyme mimic activities for dual-signal readout provides a new way for mucin 1 detection.

Dual-Aptamer Recognition of DNA Logic Gate Sensor-Based Specific Exosomal Proteins for Ovarian Cancer Diagnosis

Clinical diagnosis of ovarian cancer lacks high accuracy due to the weak selection of specific biomarkers along with the circumstance biomarkers localization. Clustering analysis of proteins transported on exosomes enables a more precise screening of effective biomarkers. Herein, through bioinformatics analysis of ovarian cancer and exosome proteomes, two coexpressed proteins, EpCAM and CD24, specifically enriched, were identified, together with the development of an as-derived dual-aptamer targeted exosome-based strategy for ovarian cancer screening. In brief, a DNA ternary polymer with aptamers targeting EpCAM and CD24 was designed to present a logic gate reaction upon recognizing ovarian cancer exosomes, triggering a rolling circle amplification chemiluminescent signal. A dynamic detection range of 6 orders of magnitude was achieved by quantifying exosomes. Moreover, for clinical samples, this strategy could accurately differentiate exosomes from healthy persons, other cancer patients, and ovarian cancer patients, enabling promising in situ detection. By accurately selecting biomarkers and constructing a dual-targeted exosomal protein detection strategy, the limitation of insufficient specificity of traditional protein markers was circumvented. This work contributed to the development of exosome-based prognosis monitoring in ovarian cancer through the identification of disease-specific exosome protein markers.

Exploring capabilities of elemental mass spectrometry for determination of metal and biomolecules in extracellular vesicles

Extracellular vesicles (EVs) are increasingly recognized as crucial components influencing various pathophysiological processes, such as cellular homeostasis, cancer progression, and neurological disease. However, the lack of standardized methods for EV isolation and classification, coupled with ambiguity in biochemical markers associated with EV subtypes, remains a major challenge. This Trends article highlights the most common approaches for EV isolation and characterization, along with recent applications of elemental mass spectrometry (MS) to analyse metals and biomolecules in EVs obtained from biofluids or in vitro cellular models. Considering the promising capabilities of elemental MS, the article also looks ahead to the potential analysis of EVs at the single-vesicle and single-cell levels using ICP-MS. These approaches may offer valuable insights into individual characteristics of EVs and their functions, contributing to a deeper understanding of their role in various biological processes.

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.

Impact of the Drug Loading Method on the Drug Distribution and Biological Efficacy of Exosomes

Exosomes are biological nanovesicles that are intrinsically loaded with thousands of biomacromolecules and are principally responsible for cell-to-cell communication. Inspired by the natural payload, they have been extensively investigated as drug delivery vehicles; however, the drug distribution, whether into or onto exosomes, is still debatable. In the present work, we have tried to investigate it systemically by selecting 5-fluorouracil (5-FU) (hydrophilic) and paclitaxel (PAC) (hydrophobic), drugs with very different physicochemical characteristics, for the loading to the exosomes. Exosomes were obtained from bovine milk, and the drugs were loaded using three different methods: incubation, sonication, and triton x-100. The particle size was found to be approximately 100 nm in all the cases; however, the highest drug loading was found in the sonication method. Fluorescence spectrophotometer, EDX analysis, EDX mapping, XPS, and XRD analysis indicated the possible presence of more drugs over the surface in the case of the incubation method. Drugs loaded by the sonication method had more controlled release than simple incubation and triton x-100. The method of drug loading had an insignificant effect on the cytotoxicity while in line with our previous observation, the combination (PAC and 5-FU) exhibited synergism as evidenced by ROS assay, colony formation assay, and mitochondrial membrane potential assay.

Amperometric Identification of Single Exosomes and Their Dopamine Contents Secreted by Living Cells

Dopamine (DA) is an important neurotransmitter, which not only participates in the regulation of neural processes but also plays critical roles in tumor progression and immunity. However, direct identification of DA-containing exosomes, as well as quantification of DA in single vesicles, is still challenging. Here, we report a nanopipette-assisted method to detect single exosomes and their dopamine contents via amperometric measurement. The resistive-pulse current measured can simultaneously provide accurate information of vesicle translocation and DA contents in single exosomes. Accordingly, DA-containing exosomes secreted from HeLa and PC12 cells under different treatment modes successfully detected the DA encapsulation efficiency and the amount of exosome secretion that distinguish between cell types. Furthermore, a custom machine learning model was constructed to classify the exosome signals from different sources, with an accuracy of more than 99%. Our strategy offers a useful tool for investigating single exosomes and their DA contents, which facilitates the analysis of DA-containing exosomes derived from other untreated or stimulated cells and may open up a new insight to the research of DA biology.

DNA-Driven Photothermal Amplification Transducer for Highly Sensitive Visual Determination of Extracellular Vesicles

Extracellular vesicles (EVs) are crucial focus of current biomedical research and future medical diagnosis. However, the requirement for specialized sophisticated instruments for quantitative readouts has limited the sensitive measurement of EVs to specialized laboratory settings, which in turn has limited bench-to-bedside translation of EV-based liquid biopsies. In this work, a straightforward temperature-output platform based on a DNA-driven photothermal amplification transducer was developed for the highly sensitive visual detection of EVs using a simple household thermometer. The EVs were specifically recognized by the antibody-aptamer sandwich immune-configuration that was constructed on portable microplates. Via a one-pot reaction, cutting-mediated exponential rolling circle amplification was initiated in situ on the EV surface, generating substantial G-quadruplex-DNA-hemin conjugates. Significant amplification in temperature was achieved from the effective photothermal conversion and regulation guided by the G-quadruplex-DNA-hemin conjugates in the 3,3',5,5'-tetramethylbenzidine-H2O2 system. Through obvious temperature outputs, the DNA-driven photothermal transducer enabled highly sensitive EV detection at close to the single-particle level and supported the highly specific identification of tumor-derived EVs directly in serum samples, without the requirement of any sophisticated instrument or labeling process. Benefiting from highly sensitive visual quantification, an easy-to-use readout, and portable detection, this photothermometric strategy is expected to be deliverable across professional on-site screening to home self-testing as EV-based liquid biopsies.

Ultrasensitive hydrogel grating detector for real-time continuous-flow detection of trace threat Pb2

Ultrasensitive real-time detection of trace Pb²⁺ in continuous flow is vital to effectively and timely eliminate the potential hazards to ecosystem health and sustainability. This work reports on a micro-structured smart hydrogel grating with ultra-sensitivity, high selectivity, good transparency and mechanical property for real-time detection of Pb²⁺ in continuous flow. The hydrogel grating possesses uniform surface relief microstructures with periodic nano-height ridges made of poly(acrylamide-co-benzo-18-crown-6-acrylamide) networks that crosslinked by tetra-arm star poly(ethylene glycol)acrylamide. The hydrogel grating with good optical transparency and mechanical property can change its height via selective host-guest complexation with Pb²⁺ to output a changed diffraction efficiency. Meanwhile, the periodic nano-ridges with large specific area benefit the contact with Pb²⁺ for fast Pb²⁺-induced height change. Thus, with such rationally designed molecular structures and surface relief microstructures, the hydrogel grating integrated in a glass-based mini-chip allows real-time detection of Pb²⁺ in continuous flow with ultra-sensitivity and high selectivity. The hydrogel grating detector can achieve ultralow detection limit (10^-9 M Pb²⁺), fast response (2 min), and selective detection of Pb²⁺ from dozens of interfering ions even with high concentrations. This high-performance hydrogel grating detector is general and can be extended to detect many analytes due to the wide choice of responsive hydrogels, thus opening new areas for creating advanced smart detectors in analytical science.

Molecular Docking and Intracellular Translocation of Extracellular Vesicles for Efficient Drug Delivery

Extracellular vesicles (EVs), including exosomes, mediate intercellular communication by delivering their contents, such as nucleic acids, proteins, and lipids, to distant target cells. EVs play a role in the progression of several diseases. In particular, programmed death-ligand 1 (PD-L1) levels in exosomes are associated with cancer progression. Furthermore, exosomes are being used for new drug-delivery systems by modifying their membrane peptides to promote their intracellular transduction via micropinocytosis. In this review, we aim to show that an efficient drug-delivery system and a useful therapeutic strategy can be established by controlling the molecular docking and intracellular translocation of exosomes. We summarise the mechanisms of molecular docking of exosomes, the biological effects of exosomes transmitted into target cells, and the current state of exosomes as drug delivery systems.

Facets of ICP-MS and their potential in the medical sciences—Part 2: nanomedicine, immunochemistry, mass cytometry, and bioassays

Inductively coupled–plasma mass spectrometry (ICP-MS) has transformed our knowledge on the role of trace and major elements in biology and has emerged as the most versatile technique in elemental mass spectrometry. The scope of ICP-MS has dramatically changed since its inception, and nowadays, it is a mature platform technology that is compatible with chromatographic and laser ablation (LA) systems. Over the last decades, it kept pace with various technological advances and was inspired by interdisciplinary approaches which endorsed new areas of applications. While the first part of this review was dedicated to fundamentals in ICP-MS, its hyphenated techniques and the application in biomonitoring, isotope ratio analysis, elemental speciation analysis, and elemental bioimaging, this second part will introduce relatively current directions in ICP-MS and their potential to provide novel perspectives in the medical sciences. In this context, current directions for the characterisation of novel nanomaterials which are considered for biomedical applications like drug delivery and imaging platforms will be discussed while considering different facets of ICP-MS including single event analysis and dedicated hyphenated techniques. Subsequently, immunochemistry techniques will be reviewed in their capability to expand the scope of ICP-MS enabling analysis of a large range of biomolecules alongside elements. These methods inspired mass cytometry and imaging mass cytometry and have the potential to transform diagnostics and treatment by offering new paradigms for personalised medicine. Finally, the interlacing of immunochemistry methods, single event analysis, and functional nanomaterials has opened new horizons to design novel bioassays which promise potential as assets for clinical applications and larger screening programs and will be discussed in their capabilities to detect low-level proteins and nucleic acids.

Entropy analysis and grey cluster analysis of multiple indexes of 5 kinds of genuine medicinal materials

5 kinds of genuine medicinal materials, including Diding (Latin name: Corydalis bungeana Turcz), Purslane (Latin name: Portulaca oleracea L.), straw sandal board (Latin name: Hoya carnosa (L.f.) R. Br), June snow (Latin name: Serissa japonica (Thunb.) Thunb.), pine vine rattan (Latin name: Lycopodiastrum casuarinoides (Spring) Holub. [Lycopodium casuarinoides Spring]), were selected as the research objects. The combustion heat, thermo gravimetric parameters, and fat content, calcium content, trace element content, ash content of 5 kinds of genuine medicinal materials were measured. The combustion heat, differential thermal gravimetric analysis, fat content, calcium content, trace elements content, and ash content of 5 kinds of genuine medicinal materials were used to build a systematic multi-index evaluation system by gray pattern recognition and grey correlation coefficient cluster analysis, which can make up for the gaps in this area and provide scientific basis and research significance for the study of genuine medicinal materials quality. The results showed that the order of combustion heat of 5 kinds of genuine medicinal materials, including Diding, Purslane, straw sandal board, June snow, pine vine rattan, was Diding > June snow > straw sandal board > Purslane > pine vine rattan, the order of fat content (%) of 5 kinds of genuine medicinal materials was straw sandal board > Diding > pine vine rattan > June snow > Purslane, the order of calcium content (%) was pine vine rattan > June snow > Purslane > straw sandal board > Diding, the order of ash content was June snow > Purslane > straw sandal board > pine vine rattan > Diding. From the analysis of thermogravimetric analysis results and thermogravimetric combustion stability, the order of combustion stability of 5 kinds of genuine medicinal materials was June snow > pine Vine rattan > straw sandal board > Diding > Portulaca oleracea. The order of the content of 12 trace elements in 5 kinds of genuine medicinal materials, in terms of trace element content, June snow contains the highest trace elements in all samples. According to combustion heat, combustibility (combustion stability of genuine medicinal materials), fat, calcium, ash, trace element content, the comprehensive evaluation results of multi-index analysis constructed by gray correlation degree, gray correlation coefficient factor analysis, and gray hierarchical cluster analysis showed that the comprehensive evaluation multi-index order of 5 genuine medicinal materials, including Diding, Purslane, straw sandal board, June snow and pine vine rattan, was June snow > straw sandal board > Diding > Purslane > pine vine rattan. Therefore, the comprehensive evaluation results of the quality of genuine medicinal materials selected in this study were June snow the best, followed by straw sandal board. This research has important theoretical and practical significance for the multi-index measurement and comprehensive evaluation of genuine medicinal materials, and can provide scientific basis and research significance for the research of multi-index quality control of genuine medicinal material.

Surface plasmon resonance biosensor for exosome detection based on reformative tyramine signal amplification activated by molecular aptamer beacon

Human epidermal growth factor receptor 2 (HER2)-positive exosomes play an extremely important role in the diagnosis and treatment options of breast cancers. Herein, based on the reformative tyramine signal amplification (TSA) enabled by molecular aptamer beacon (MAB) conversion, a label-free surface plasmon resonance (SPR) biosensor was proposed for highly sensitive and specific detection of HER2-positive exosomes. The exosomes were captured by the HER2 aptamer region of MAB immobilized on the chip surface, which enabled the exposure of the G-quadruplex DNA (G4 DNA) that could form peroxidase-like G4-hemin. In turn, the formed G4-hemin catalyzed the deposition of plentiful tyramine-coated gold nanoparticles (AuNPs-Ty) on the exosome membrane with the help of H₂O₂, generating a significantly enhanced SPR signal. In the reformative TSA system, the horseradish peroxidase (HRP) as a major component was replaced with nonenzymic G4-hemin, bypassing the defects of natural enzymes. Moreover, the dual-recognition of the surface proteins and lipid membrane of the desired exosomes endowed the sensing strategy with high specificity without the interruption of free proteins. As a result, this developed SPR biosensor exhibited a wide linear range from 1.0 × 10⁴ to 1.0 × 10⁷ particles/mL. Importantly, this strategy was able to accurately distinguish HER2-positive breast cancer patients from healthy individuals, exhibiting great potential clinical application.