Heterogeneous Analysis of Extracellular Vesicles for Osteosarcoma Diagnosis.

Osteosarcoma (OS) is the most prevalent primary tumor of bones, often diagnosed late with a poor prognosis. Currently, few effective biomarkers or diagnostic methods have been developed for early OS detection with high confidence, especially for metastatic OS. Tumor-derived extracellular vesicles (EVs) are emerging as promising biomarkers for early cancer diagnosis through liquid biopsy.

Codetection of Proteins and RNAs on Extracellular Vesicles for Pancreatic Cancer Early Diagnosis.

Tumor-derived extracellular vesicles (EVs) carry tumor-specific proteins and RNAs, thus becoming prevalent targets for early cancer diagnosis. However, low expression of EV cargos and insufficient diagnostic power of individual biomarkers hindered EVs application in clinical practice. Herein, we propose a multiplex Codetection platform of proteins and RNAs (Co-PAR) for EVs.

Correlation between membrane proteins and sizes of extracellular vesicles and particles: A potential signature for cancer diagnosis.

Extracellular vesicles and particles (EVPs) are recognized as ideal liquid biopsy tools for cancer detection, and membrane proteins are commonly used EVP biomarkers. However, bulk analysis of EVP membrane protein biomarkers typically fails to meet the clinical requirement for diagnostic accuracy. We investigated the correlation between the membrane protein expression level, the binding kinetics to aptamers and the sizes of EVPs with interferometric plasmonic microscopy (iPM), and demonstrated the implementation of the correlative signature to determine cancer types.

Profiling extracellular vesicle surface proteins with 10 µL peripheral plasma within 4 h.

Extracellular vesicle (EV) surface proteins, expressed by primary tumours, are important biomarkers for early cancer diagnosis. However, the detection of these EV proteins is complicated by their low abundance and interference from non-EV components in clinical samples. Herein, we present a MEmbrane-Specific Separation and two-step Cascade AmpLificatioN (MESS2CAN) strategy for direct detection of EV surface proteins within 4 h.

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 ynamic mmunoassay for ingle tV surface protein rofiling (DISEP), a kinetic assay based on surface plasmon resonance microscopy (SPRM) for specific single tEV profiling.

Dynamic single-molecule sensing by actively tuning binding kinetics for ultrasensitive biomarker detection.

SignificanceThe detection of low-abundance molecular biomarkers is key to the liquid-biopsy-based disease diagnosis. Existing methods are limited by the affinity and specificity of recognition probes and the mass transportation of analyte molecules onto the sensor surfaces, resulting in insufficient sensitivity and long assay time. This work establishes a rapid and ultrasensitive approach by actively tuning binding kinetics and accelerating the mass transportation via nanoparticle micromanipulations.

A Single-Shot Autofocus Approach for Surface Plasmon Resonance Microscopy.

Surface plasmon resonance microscopy (SPRM) has been widely used as a sensitive imaging platform for chemical and biological analysis. The SPRM system inevitably suffers from focus inhomogeneity and drifts, especially in long-term recordings, leading to distorted images and inaccurate quantification. Traditional focus correction approaches require additional optical parts to detect and adjust focal conditions.

Multifunctional Detection of Extracellular Vesicles with Surface Plasmon Resonance Microscopy.

Extracellular vesicles (EVs), including exosomes, are promising circulating biomarkers for disease diagnosis. Conventional EVs analysis requires multiple instrumentations to obtain their phenotypic features, which limits its wide applications. Here, we present a plasmonic biosensor technology for multifunctional analysis of EVs.

Quantitative Amplitude and Phase Imaging with Interferometric Plasmonic Microscopy.

Plasmonic microscopy is a powerful tool for nanoscopic bio- and chemical sample analysis due to its high sensitivity. Phase quantification in plasmonic microscopy would provide inherent information, ..

Overshadow Effect of Psl on Bacterial Response to Physiochemically Distinct Surfaces Through Motility-Based Characterization.

Biofilms of are ubiquitously found on surfaces of many medical devices, which are the major cause of hospital-acquired infections. A large amount of work has been focused on bacterial attachment on surfaces. However, how bacterial cells evolve on surfaces after their attachment is the key to get better understanding and further control of biofilm formation.

Effects of PslG on the Surface Movement of Pseudomonas aeruginosa.

PslG attracted a lot of attention recently due to its great potential abilities in inhibiting biofilms of However, how PslG affects biofilm development still remains largely unexplored. Here, we focused on the surface motility of bacterial cells, which is critical for biofilm development. We studied the effects of PslG on bacterial surface movement in early biofilm development at a single-cell resolution by using a high-throughput bacterial tracking technique.

The application of SVR model in the improvement of QbD: a case study of the extraction of podophyllotoxin.

In order to make a further optimization of process design via increasing the stability of design space, we brought in the model of Support Vector Regression (SVR). In this work, the extraction of podophyllotoxin was researched as a case study based on Quality by Design (QbD). We compared the fitting effect of SVR and the most used quadratic polynomial model (QPM) in QbD, and an analysis was made between the two design spaces obtained by SVR and QPM.