Search

This study proposes a primary node election method based on probabilistic linguistic term set (PLTS) for the practical Byzantine fault tolerance (PBFT) consensus mechanism to effectively enhance the efficiency of reaching consensus. Specifically, a novel concept of the probabilistic linguistic term set with a confidence interval (PLTS-CI) is presented to express the uncertain complex voting information of nodes during primary node election. Then, a novel score function based on the exponential semantic value and confidence approximation value for the PLTS-CI, called Score-ESCA, is used to solve the problems of comparing different nodes with various voting attitudes. This method helps select the node with the highest score by utilizing complex decision attitudes, making it an accurate primary node election solution. Furthermore, the feasibility of our proposed method is proved by both theoretical analysis and experimental evaluations.

Nucleic acid detection technologies have been widely utilized for various diseases. Conventional laboratory tests are less suitable for use in resource-limited settings as they are time-consuming, high-cost, complex, and heavily dependent on benchtop equipment. Rapid nucleic acid detection methods that consist of rapid nucleic acid extraction steps could overcome these challenges. A paper-based platform has been utilized to develop various rapid nucleic acid extraction methods owing to its cost-effectiveness, portability, and easy-modification. However, the existing paper-based nucleic acid extraction technologies mainly focus on improving the adsorption capacity of nucleic acids without reducing the non-specific adsorption capacity of proteins. In this study, paper-based nucleic acid extraction technology with wash-free, elution-free, and low protein adsorption was developed. The fabrication of paper involves the mixing of polyethylene glycol (PEG)-modified cotton fiber, chitosan (COS)-modified cotton fiber, and cotton fiber to form PEG-modified cotton fiber/chitosan-modified cotton fiber/cotton fiber (PEG-CF/COS-CF/CF) paper by the wet molding method. The result showed that PEG-CF/COS-CF/CF paper has a desirable pore size (23.9 ± 4.03 μm), good mechanical strength (dry: 9.37 Mpa and wet: 0.28 Mpa), and hydrophilicity (contact angle: 42.6° ± 0.36°). NH3+groups of COS and OH−groups of PEG were observed on its surface and the adsorption efficiency of nucleic acid in TE buffer was 42.48% ± 0.30%. The limit of detection of pure DNA with this PEG-CF/COS-CF/CF paper by qPCR was as low as 25 ng. Additionally, this platform could successfully extract nucleic acid from 30 μL of a saliva sample, highlighting its potential use for clinical sample testing. The proposed paper-based nucleic acid extraction platform shows tremendous potential for disease diagnosis in resource-limited settings.

Exosomal microRNAs (miRNAs) are reliable biomarkers of disease progression, allowing for non-invasive detection. However, detection of exosomal miRNAs in situremains a challenge due to low abundance, poor permeability of the lipid bilayers, and slow kinetics of previous methods. Herein, an accelerated DNA nanoprobe was implemented for fast, in situmonitoring of miRNA in exosomes by employing a spatial confinement strategy. This nanoprobe not only detects miRNA in exosomes but also distinguishes tumor exosomes from those derived from normal cells with high accuracy, paving the way toward exosomal miRNA bioimaging and disease diagnosis. Furthermore, the fast response allows for this nanoprobe to be successfully utilized to monitor the process of exosomes endocytosis, making it also a tool to explore exosome biological functions.

Accurate and sensitive strategies for Concanavalin A (Con A) sensing are conducive to the better cognition of various important biological and physiological processes. Here, by designing dextran-functionalized fluorescent microspheres (DxFMs) and boric acid-modified carbon dots (BCDs) as recognition unit and built-in signal reference respectively, a ratiometric fluorescent detection platform was proposed for Con A detection with high reliability. In this protocol, the BCDs/DxFMs precipitation was formed due to the covalent interactions between cis-diol of DxFMs and boronic acid groups of BCDs, thus only fluorescence of BCDs could be detected in the supernatant. When Con A was presented, it could bind to DxFMs through its carbohydrate recognition ability and suppress the subsequent assembly between DxFMs and BCDs, leading to the simultaneous capture of DxFMs and BCDs fluorescence in the supernatant. Since the BCDs content was superfluous, their fluorescence intensities were basically constant in all cases. Based on the unchanged BCDs fluorescence signal and target-dependent DxFMs fluorescence signal in supernatant, the ratiometric detection of Con A was realized. Under optimized conditions, this ratiometric fluorescent platform displayed a linear detection range from 0.125 μg/mL to 12.5 μg/mL with a detection limit of 0.089 μg/mL. Moreover, satisfied analytical outcomes for Con A detection in serum samples were obtained, manifesting huge application potential of this ratiometric fluorescent platform in clinical diagnosis.