Digital microfluidics-based digital counting of single-cell copy number variation (dd-scCNV Seq).

Single-cell copy number variations (CNVs), major dynamic changes in humans, result in differential levels of gene expression and account for adaptive traits or underlying disease. Single-cell sequencing is needed to reveal these CNVs but has been hindered by single-cell whole-genome amplification (scWGA) bias, leading to inaccurate gene copy number counting. In addition, most of the current scWGA methods are labor intensive, time-consuming, and expensive with limited wide application. Here, we report a unique single-cell whole-genome library preparation approach based on digital microfluidics for digital counting of single-cell Copy Number Variation (dd-scCNV Seq). dd-scCNV Seq directly fragments the original single-cell DNA and uses these fragments as templates for amplification. These reduplicative fragments can be filtered computationally to generate the original partitioned unique identified fragments, thereby enabling digital counting of copy number variation. dd-scCNV Seq showed an increase in uniformity in the single-molecule data, leading to more accurate CNV patterns compared to other methods with low-depth sequencing. Benefiting from digital microfluidics, dd-scCNV Seq allows automated liquid handling, precise single-cell isolation, and high-efficiency and low-cost genome library preparation. dd-scCNV Seq will accelerate biological discovery by enabling accurate profiling of copy number variations at single-cell resolution.

mitoSplitter: A mitochondrial variants-based method for efficient demultiplexing of pooled single-cell RNA-seq.

Single-cell RNA-seq (scRNA-seq) analysis of multiple samples separately can be costly and lead to batch effects. Exogenous barcodes or genome-wide RNA mutations can be used to demultiplex pooled scRNA-seq data, but they are experimentally or computationally challenging and limited in scope. Mitochondrial genomes are small but diverse, providing concise genotype information. We developed "mitoSplitter," an algorithm that demultiplexes samples using mitochondrial RNA (mtRNA) variants, and demonstrated that mtRNA variants can be used to demultiplex large-scale scRNA-seq data. Using affordable computational resources, mitoSplitter can accurately analyze 10 samples and 60,000 cells in 6 h. To avoid the batch effects from separated experiments, we applied mitoSplitter to analyze the responses of five non-small cell lung cancer cell lines to BET (Bromodomain and extraterminal) chemical degradation in a multiplexed fashion. We found the synthetic lethality of TOP2A inhibition and BET chemical degradation in BET inhibitor-resistant cells. The result indicates that mitoSplitter can accelerate the application of scRNA-seq assays in biomedical research.

Synergetic collision and space separation in microfluidic chip for efficient affinity-discriminated molecular selection.

Efficient molecular selection is a prerequisite for generating molecular tools used in diagnosis, pathology, vaccinology, and therapeutics. Selection efficiency is thermodynamically highly dependent on the dissociation equilibrium that can be reached in a single round. Extreme shifting of equilibrium towards dissociation favors the retention of high-affinity ligands over those with lower affinity, thus improving the selection efficiency. We propose to synergize dual effects by deterministic lateral-displacement microfluidics, including the collision-based force effect and the two-dimensional (2D) separation-based concentration effect, to greatly shift the equilibrium. Compared with previous approaches, this system can remove more low- or moderate-affinity ligands and maintain most high-affinity ligands, thereby improving affinity discrimination in selection. This strategy is demonstrated on phage display in both experiment and simulation, and two peptides against tumor markers ephrin type-A receptor 2 (EphA2) and CD71 were obtained with high affinity and specificity within a single round of selection, which offers a promising direction for discovery of robust binding ligands for a wide range of biomedical applications.

LINEAGE: Label-free identification of endogenous informative single-cell mitochondrial RNA mutation for lineage analysis.

Single-cell RNA-sequencing (scRNA-seq) has become a powerful tool for biomedical research by providing a variety of valuable information with the advancement of computational tools. Lineage analysis based on scRNA-seq provides key insights into the fate of individual cells in various systems. However, such analysis is limited by several technical challenges. On top of the considerable computational expertise and resources, these analyses also require specific types of matching data such as exogenous barcode information or bulk assay for transposase-accessible chromatin with high throughput sequencing (ATAC-seq) data. To overcome these technical challenges, we developed a user-friendly computational algorithm called "LINEAGE" (label-free identification of endogenous informative single-cell mitochondrial RNA mutation for lineage analysis). Aiming to screen out endogenous markers of lineage located on mitochondrial reads from label-free scRNA-seq data to conduct lineage inference, LINEAGE integrates a marker selection strategy by feature subspace separation and de novo "low cross-entropy subspaces" identification. In this process, the mutation type and subspace-subspace "cross-entropy" of features were both taken into consideration. LINEAGE outperformed three other methods, which were designed for similar tasks as testified with two standard datasets in terms of biological accuracy and computational efficiency. Applied on a label-free scRNA-seq dataset of BRAF-mutated cancer cells, LINEAGE also revealed genes that contribute to BRAF inhibitor resistance. LINEAGE removes most of the technical hurdles of lineage analysis, which will remarkably accelerate the discovery of the important genes or cell-lineage clusters from scRNA-seq data.

Fluid nanoporous microinterface enables multiscale-enhanced affinity interaction for tumor-derived extracellular vesicle detection.

Tumor-derived extracellular vesicles (T-EVs) represent valuable markers for tumor diagnosis and treatment guidance. However, nanoscale sizes and the low abundance of marker proteins of T-EVs restrict interfacial affinity reaction, leading to low isolation efficiency and detection sensitivity. Here, we engineer a fluid nanoporous microinterface (FluidporeFace) in a microfluidic chip by decorating supported lipid bilayers (SLBs) on nanoporous herringbone microstructures with a multiscale-enhanced affinity reaction for efficient isolation of T-EVs. At the microscale level, the herringbone micropattern promotes the mass transfer of T-EVs to the surface. At the nanoscale level, nanoporousity can overcome boundary effects for close contact between T-EVs and the interface. At the molecular level, fluid SLBs afford clustering of recognition molecules at the binding site, enabling multivalent binding with an ∼83-fold increase of affinity compared with the nonfluid interface. With the synergetic enhanced mass transfer, interface contact, and binding affinity, FluidporeFace affords ultrasensitive detection of T-EVs with a limit of detection of 10 T-EVs µL-1, whose PD-L1 expression levels successfully distinguish cancer patients from healthy donors. We expect this multiscale enhanced interfacial reaction strategy will inspire the biosensor design and expand liquid biopsy applications, especially for low-abundant targets in clinical samples.

DMF-DM-seq: Digital-Microfluidics Enabled Dual-Modality Sequencing of Single-Cell mRNA and microRNA with High Integration, Sensitivity, and Automation.

Multimodal measurement of single cells provides deep insights into the intricate relationships between individual molecular layers and the regulatory mechanisms underlying intercellular variations. Here, we reported DMF-DM-seq, a highly integrated, sensitive, and automated platform for single-cell mRNA and microRNA (miRNA) co-sequencing based on digital microfluidics. This platform first integrates the processes of single-cell isolation, lysis, component separation, and simultaneous sequencing library preparation of mRNA and miRNA within a single DMF device. Compared with the current half-cell measuring strategy, DMF-DM-seq enables complete separation of single-cell mRNA and miRNA via a magnetic field application, resulting in a higher miRNA detection ability. DMF-DM-seq revealed differential expression patterns of single cells of noncancerous breast cells and noninvasive and aggressive breast cancer cells at both mRNA and miRNA levels. The results demonstrated the anticorrelated relationship between miRNA and their mRNA targets. Further, we unravel the tumor growth and metastasis-associated biological processes enriched by miRNA-targeted genes, along with important miRNA-interaction networks involved in significant signaling pathways. We also deconstruct the miRNA regulatory mechanisms underlying different signaling pathways across different breast cell types. In summary, DMF-DM-seq offers a powerful tool for a comprehensive study of the expression heterogeneity of single-cell mRNA and miRNA, which will be widely applied in basic and clinical research.

Well-Paired-Seq2: High-Throughput and High-Sensitivity Strategy for Characterizing Low RNA-Content Cell/Nucleus Transcriptomes.

Single-cell RNA sequencing (scRNA-seq) is a transformative technology that unravels the intricate cellular state heterogeneity. However, the Poisson-dependent cell capture and low sensitivity in scRNA-seq methods pose challenges for throughput and samples with a low RNA-content. Herein, to address these challenges, we present Well-Paired-Seq2 (WPS2), harnessing size-exclusion and quasi-static hydrodynamics for efficient cell capture. WPS2 exploits molecular crowding effect, tailing activity enhancement in reverse transcription, and homogeneous enzymatic reaction in the initial bead-based amplification to achieve 3116 genes and 8447 transcripts with an average of ∼20000 reads per cell. WPS2 detected 1420 more genes and 4864 more transcripts than our previous Well-Paired-Seq. It sensitively characterizes transcriptomes of low RNA-content single cells and nuclei, overcoming the Poisson limit for cell and barcoded bead capture. WPS2 also profiles transcriptomes from frozen clinical samples, revealing heterogeneous tumor copy number variations and intercellular crosstalk in clear cell renal cell carcinomas. Additionally, we provide the first single-cell-level characterization of rare metanephric adenoma (MA) and uncover potential specific markers. With the advantages of high sensitivity and high throughput, WPS2 holds promise for diverse basic and clinical research.

Decoding Biomechanical Cues Based on DNA Sensors.

Biological systems perceive and respond to mechanical forces, generating mechanical cues to regulate life processes. Analyzing biomechanical forces has profound significance for understanding biological functions. Therefore, a series of molecular mechanical techniques have been developed, mainly including single-molecule force spectroscopy, traction force microscopy, and molecular tension sensor systems, which provide indispensable tools for advancing the field of mechanobiology. DNA molecules with a programmable structure and well-defined mechanical characteristics have attached much attention to molecular tension sensors as sensing elements, and are designed for the study of biomechanical forces to present biomechanical information with high sensitivity and resolution. In this work, a comprehensive overview of molecular mechanical technology is presented, with a particular focus on molecular tension sensor systems, specifically those based on DNA. Finally, the future development and challenges of DNA-based molecular tension sensor systems are looked upon.

In Situ Detection of Nucleic Acids in Extracellular Vesicles via Membrane Fusion.

Extracellular vesicles (EVs) carry diverse biomolecules (e. g., nucleic acids, proteins) for intercellular communication, serving as important markers for diseases. Analyzing nucleic acids derived from EVs enables non-invasive disease diagnosis and prognosis evaluation. Membrane fusion, a fundamental cellular process wherein two lipid membranes merge, facilitates cell communication and cargo transport. Building on this natural phenomenon, recent years have witnessed the emergence of membrane fusion-based strategies for the detection of nucleic acids within EVs. These strategies entail the encapsulation of detection probes within either artificial or natural vesicles, followed by the induction of membrane fusion with EVs to deliver probes. This innovative approach not only enables in situ detection of nucleic acids within EVs but also ensures the maintenance of structural integrity of EVs, thus preventing nucleic acid degradation and minimizing the interference from free nucleic acids. This concept categorizes approaches into universal and targeted membrane fusion strategies, and discusses their application potential, and challenges and future prospects.

Identification of new AAV vectors with enhanced blood-brain barrier penetration efficiency via organ-on-a-chip.

To overcome limitations in the generalizability and efficiency of current AAV vectors, in this current study, we constructed an AAV variant library by the insertion of random heptapeptide sequences in the receptor-binding domain of the AAV9 capsid gene. We then applied a recently developed organ-on-a-chip in vitro model of the human blood-brain barrier (BBB) to iteratively enrich for variants that efficiently cross the BBB and transduce astrocyte cells. Through multiple rounds of screening, we obtained two candidate AAV variants, AAV-M6 and AAV-M8, which showed significantly higher BBB penetration efficiency than AAV9 or AAV-PHP.eB. Quantitative PCR (qPCR) assay showed that AAV-M6 could accumulate to a 5 times higher titer, while AAV-M8 reached a 3 times higher titer, than AAV-PHP.eB in the neural chamber of the model. The transduction assay further verified that the AAV-M6 candidate vector was able to infect HA-1800 cells after crossing the BBB, suggesting it could potentially transduce brain parenchymal cells after crossing the hCMEC/D3 layer at higher efficiency than AAV-PHP.eB. Molecular simulations suggested that the human receptor proteins, LY6D and M6PR, could bind the AAV-M6 heptapeptide insertion with high affinity. This study provides two promising candidate AAV vectors and demonstrates the use of this in vitro BBB model for scalable, high-throughput screening of gene therapies. These tools can drive investigations of the mechanisms underlying BBB permeability and the cell-type specificity of virus vectors.

Beyond single cells: microfluidics empowering multiomics analysis.

Single-cell multiomics technologies empower simultaneous measurement of multiple types of molecules within individual cells, providing a more profound comprehension compared with the analysis of discrete molecular layers from different cells. Microfluidic technology, on the other hand, has emerged as a pivotal facilitator for high-throughput single-cell analysis, offering precise control and manipulation of individual cells. The primary focus of this review encompasses an appraisal of cutting-edge microfluidic platforms employed in the realm of single-cell multiomics analysis. Furthermore, it discusses technological advancements in various single-cell omics such as genomics, transcriptomics, epigenomics, and proteomics, with their perspective applications. Finally, it provides future prospects of these integrated single-cell multiomics methodologies, shedding light on the possibilities for future biological research.

Spatial Engineering of Heterotypic Antigens on a DNA Framework for the Preparation of Mosaic Nanoparticle Vaccines with Enhanced Immune Activation against SARS-CoV-2 Variants.

Mosaic nanoparticle vaccines with heterotypic antigens exhibit broad-spectrum antiviral capabilities, but the impact of antigen proportions and distribution patterns on vaccine-induced immunity remains largely unexplored. Here, we present a DNA nanotechnology-based strategy for spatially assembling heterotypic antigens to guide the rational design of mosaic nanoparticle vaccines. By utilizing two aptamers with orthogonal selectivity for the original SARS-CoV-2 spike trimer and Omicron receptor-binding domain (RBD), along with a DNA soccer-ball framework, we precisely manipulate the spacing, stoichiometry, and overall distribution of heterotypic antigens to create mosaic nanoparticles with average, bipolar, and unipolar antigen distributions. Systematic in vitro and in vivo immunological investigations demonstrate that 30 heterotypic antigens in equivalent proportions, with an average distribution, leads to higher production of broad-spectrum neutralizing antibodies compared to the bipolar and unipolar distributions. Furthermore, the precise assembly utilizing our developed methodology reveals that a mere increment of five Omicron RBD antigens on a nanoparticle (from 15 to 20) not only diminishes neutralization against Omicron variant but also triggers excessive inflammation. This work provides a unique perspective on the rational design of mosaic vaccines by highlighting the significance of the spatial placement and proportion of heterotypic antigens in their structure-activity mechanisms.

Insights of Life Molecules' Dynamic Distribution in Live Cells via Sequence-Structure Bispecific Fluorescent RNA.

Life molecules' distributions in live systems construct the complex dynamic reaction networks, whereas it is still challenging to demonstrate the dynamic distributions of biomolecules in live systems. Herein, we proposed a dynamic analysis strategy via sequence-structure bispecific RNA with state-adjustable molecules to monitor the dynamic concentration and spatiotemporal localization of these biomolecules in live cells based on the new insight of fluorescent RNA (FLRNA) interactions and their mechanism of fluorescence enhancement. Typically, computer-based nucleic acid-molecular docking simulation and molecular theoretical calculation have been proposed to provide a simple and straightforward method for guiding the custom-design of FLRNA. Impressively, a novel FLRNA with sequence and structure bispecific RNA named as a structure-switching aptamer (SSA) was introduced to monitor the real-time concentration and spatiotemporal localization of biomolecules, contributing to a deeper insight of the dynamic monitoring and visualization of biomolecules in live systems.

Digital-scRRBS: A Cost-Effective, Highly Sensitive, and Automated Single-Cell Methylome Analysis Platform via Digital Microfluidics.

Single-cell DNA methylation sequencing is highly effective for identifying cell subpopulations and constructing epigenetic regulatory networks. Existing methylome analyses require extensive starting materials and are costly, complex, and susceptible to contamination, thereby impeding the development of single-cell methylome technology. In this work, we report digital microfluidics-based single-cell reduced representation bisulfite sequencing (digital-scRRBS), the first microfluidics-based single-cell methylome library construction platform, which is an automatic, effective, reproducible, and reagent-efficient technique to dissect the single-cell methylome. Using our digital microfluidic chip, we isolated single cells in 15 s and successfully constructed single-cell methylation sequencing libraries with a unique genome mapping rate of up to 53.6%, covering up to 2.26 million CpG sites. Digital-scRRBS demonstrates a high capacity for distinguishing cell identity and tracking DNA methylation during drug administration. Digital-scRRBS expands the applicability of single-cell methylation methods as a versatile tool for epigenetic analysis of rare cells and populations with high levels of heterogeneity.

Multifunctional Nanoprobe-Amplified Enzyme-Linked Immunosorbent Assay on Capillary: A Universal Platform for Simple, Rapid, and Ultrasensitive Dual-Mode Pathogen Detection.

Although the traditional enzyme-linked immunosorbent assay (ELISA) has been widely applied in pathogen detection and clinical diagnostics, it always suffers from complex procedures, a long incubation time, unsatisfying sensitivity, and a single signal readout. Here, we developed a simple, rapid, and ultrasensitive platform for dual-mode pathogen detection based on a multifunctional nanoprobe integrated with a capillary ELISA (CLISA) platform. The novel capture antibodies-modified capillaries can act as a swab to combine in situ trace sampling and detection procedures, eliminating the dissociation between sampling and detection in traditional ELISA assays. With excellent photothermal and peroxidase-like activity, the Fe3O4@MoS2 nanoprobe with a unique p-n heterojunction was chosen as an enzyme substitute and amplified signal tag to label the detection antibody for further sandwich immune sensing. As the analyte concentration increased, the Fe3O4@MoS2 probe could generate dual-mode signals, including remarkable color changes from the chromogenic substrate oxidation as well as photothermal enhancement. Moreover, to avoid false negative results, the excellent magnetic capability of the Fe3O4@MoS2 probe can be used to pre-enrich the trace analytes, amplifying the detection signal and enhancing the immunoassay's sensitivity. Under optimal conditions, specific and rapid detection of SARS-CoV-2 has been realized successfully based on this integrated nanoprobe-enhanced CLISA platform. The detection limits were 5.41 pg·mL-1 for the photothermal assay and 150 pg·mL-1 for the visual colorimetric assay. More importantly, the simple, affordable, and portable platform can also be expanded to rapidly detect other targets such as Staphylococcus aureus and Salmonella typhimurium in practical samples, making it a universal and attractive tool for multiple pathogen analysis and clinical testing in the post COVID-19 era.

Reliable Detection of Extracellular PD-L1 by DNA Computation-Mediated Microfluidics.

Extracellular vesicle PD-L1 (programmed death-1 ligand 1) is of greater value in tumor diagnosis, prognosis, and efficacy monitoring of anti-PD-1/PD-L1 immunotherapy. However, soluble PD-L1 interferes with the accurate detection of extracellular vesicle (EV) PD-L1. Here, we developed a microfluidic differentiation method for the detection of extracellular PD-L1, without the interference of soluble, by DNA computation with lipid probes and PD-L1 aptamer as inputs (DECLA). For the developed DECLA method, a cholesterol-DNA probe was designed that efficiently embeds into the EV membrane, and an aptamer-based PD-L1 probe was used for PD-L1 recognition. Due to the stable secondary structure of the designed connector, only cobinding of cholesterol-DNA and PD-L1 affinity probe induced biotin-labeled connector activation, while soluble PD-L1 cannot hybridize. As a result, PD-L1 EVs can be efficiently captured by streptavidin-functioned herringbone chip and quantified by anti-CD63-induced fluorescence signal. The high specificity of dual-input DNA computation allied to the high sensitivity of microfluidic-based detection was suitable for distinguishing lung cancer patients from healthy donors, highlighting its potential translation to clinical diagnosis and therapy monitoring.

Logic-Gates of Gas Pressure for Portable, Intelligent and Multiple Analysis of Metal Ions.

DNA logic gates have shown outstanding magic in intelligent biology applications, but it remains challenging to construct a portable, affordable and convenient DNA logic gate. Herein, logic gates of gas pressure were innovatively developed for multiplex analysis of metal ions. Hg2+ and Ag+ were input to interact specifically with the respective mismatched base pairs, which activated DNA extension reaction by polymerase and led to the enrichment of platinum nanoparticles for catalyzing the decomposition of peroxide hydrogen. Thus, the gas pressure obtained from a sealed well was used as output for detecting or identifying metal ions. Hg2+ and Ag+ were sensitively and selectively detected, and the assay of the real samples was also satisfactory. Based on this, DNA logic gates, including YES, NOT, AND, OR, NAND, NOR, INHIBIT, and XOR were successfully established using a portable and hand-held gas pressure meter as detector. So, the interactions between DNA and metal ions were intelligently transferred into the output of gas pressure, which made metal ions to be detected portably and identified intelligently. Given the remarkable merits of simplicity, logic operation, and portable output, the metal ion-driven DNA logic gate of gas pressure provides a promising way for intelligent and portable biosensing.

Dual-Mode Logic Gate for Intelligent and Portable Detection of MicroRNA Based on Gas Pressure and Lateral Flow Assay.

Molecular logic gate provides an intelligent option for simultaneous detection of biomarkers. Herein, a dual-mode DNA logic gate was proposed to portably and intelligently detect multiple microRNAs (miRNAs) by gas pressure biosensing and lateral flow assay (LFA). A platinum-coated gold nanoparticle (Au@PtNP) with catalase-like activity was used as a signal reporter to achieve a dual-signal readout. MiRNAs as the input initiated the cyclic strand displacement reaction (SDR) to enrich a large amount of Au@PtNPs. Thus, miRNA can be visually detected by a lateral flow strip (LFS) using the grayish-brown color of Au@PtNPs as output 1. Furthermore, Au@PtNP-catalyzed decomposition of H2O2 resulted in gas pressure as output 2, which was measured by a digital and handheld gas pressure meter. As a consequence, microRNA 21 (miR-21) was sensitively and reliably detected with the limit of detection (LOD) of 7.2 pM. The selectivity and real sample analysis were both satisfactory. Significantly, two-input and three-input AND logic gates were successfully developed to realize multiple detection of two miRNAs and three miRNAs, which provide a promising way for intelligent multi-input analysis. Predictably, with the advantages of portability, simplicity, and affordability, the dual-mode logic gate based on gas pressure biosensing and LFA offers a new perspective on the field of intelligent and portable biosensing and bioanalysis.

Chromogenic Visualization of Single RNA Molecules In Situ with Duplex Capability by Rolling Circle Amplification with Alkaline Phosphatase.

Visualizing spatial patterns of gene expression by optical microscopy at single-molecule resolution represents a long-standing challenge for imaging and molecular engineering technologies. In this study, we developed a method for visualizing mRNA with duplex capability by optical microscopy using rolling circle amplification with streptavidin-modified alkaline phosphatase (SA-ALP) to provide highly selective and sensitive RNA detection. ALP-based RNA detection provides comparable sensitivity and specificity to fluorescence-based in situ assays and similar performance to the current RNAscope technique for single-molecule RNA detection, but with improved ease of operation. This versatile and relatively user-friendly method of single-molecule RNA visualization can also overcome common problems of background interference. Our findings show that the red spots generated by the Fast Red staining in situ are readily quantified by image analysis, even in samples with heavy melanin deposition, supporting the clinical translation of this assay to improve diagnostic assays for recalcitrant tissues. This system was adaptable for duplex assays with multiple probes and multiple stains, which is ALP with horseradish peroxidase to produce red and brown signals to simultaneously visualize two different RNA targets. The duplex assay can be successfully applied to quantify mRNA expression from two genes in situ within single cells and multiple cell types. With the advantages of high sensitivity and low hardware requirements, this versatile and user-friendly method of RNA visualization may enable low-resource institutions to conduct previously inaccessible diagnostic or research questions about the in situ expression and distribution of RNAs at single-molecule resolution.

Encoded Fusion-Mediated MicroRNA Signature Profiling of Tumor-Derived Extracellular Vesicles for Pancreatic Cancer Diagnosis.

MicroRNAs (miRNAs) in tumor-derived extracellular vesicles (tEVs) are important cancer biomarkers for cancer screening and early diagnosis. Multiplex detection of miRNAs in tEVs facilitates accurate diagnosis but remains a challenge. Herein, we propose an encoded fusion strategy to profile the miRNA signature in tEVs for pancreatic cancer diagnosis. A panel of encoded-targeted-fusion beads was fabricated for the selective recognition and fusion of tEVs, with the turn-on fluorescence signals of molecule beacons for miRNA quantification and barcode signals for miRNA identification using readily accessible flow cytometers. Using this strategy, six types of pancreatic-cancer-associated miRNAs can be profiled in tEVs from 2 µL plasma samples (n = 36) in an isolation-free and lysis-free manner with only 2 h of processing, offering a high accuracy (98%) to discriminate pancreatic cancer, pancreatitis, and healthy donors. This encoded fusion strategy exhibits great potential for multiplex profiling of miRNA in tEVs, offering new avenues for cancer diagnosis and screening.