As a typical biomarker, the expression of microRNA is closely related to the occurrence of cancer. However, in recent years, the detection methods have had some limitations in the research and application of microRNAs. In this paper, an autocatalytic platform was constructed through the combination of a nonlinear hybridization chain reaction and DNAzyme to achieve efficient detection of microRNA-21. Fluorescently labeled fuel probes can form branched nanostructures and new DNAzyme under the action of the target, and the newly formed DNAzyme can trigger a new round of reactions, resulting in enhanced fluorescence signals. This platform is a simple, efficient, fast, low-cost, and selective method for the detection of microRNA-21, which can detect microRNA-21 at concentrations as low as 0.004 nM and can distinguish sequence differences by single-base differences. In tissue samples from patients with liver cancer, the platform shows the same detection accuracy as real-time PCR but with better reproducibility. In addition, through the flexible design of the trigger chain, our method could be adapted to detect other nucleic acid biomarkers.
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http://dx.doi.org/10.1016/j.jbc.2023.104751 | DOI Listing |
Sci Rep
December 2024
Imperial College London, London, UK.
Accurate estimation of the soil resilient modulus (M) is essential for designing and monitoring pavements. However, experimental methods tend to be time-consuming and costly; regression equations and constitutive models usually have limited applications, while the predictive accuracy of some machine learning studies still has room for improvement. To forecast M efficiently and accurately, a new model named black-winged kite algorithm-extreme gradient boosting (BKA-XGBOOST) is proposed.
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December 2024
Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, China.
MicroRNAs (miRNAs) are small, non-coding RNAs that play pivotal roles in gene regulation; they are increasingly recognized as vital biomarkers for various diseases, notably cancer. Conventional methods for miRNA detection, such as quantitative PCR and microarray analysis, often entail intricate sample preparation and lack the requisite sensitivity to detect low-abundance miRNAs like miRNA-21. This protocol presents an innovative approach that combines branched hybridization chain reaction (bHCR) with DNAzyme technology for the precise detection of miRNA-21.
View Article and Find Full Text PDFHealth Care Sci
December 2024
School of Computer Science and Engineering, Vellore Institute of Technology Vellore India.
Background: The global impact of the highly contagious COVID-19 virus has created unprecedented challenges, significantly impacting public health and economies worldwide. This research article conducts a time series analysis of COVID-19 data across various countries, including India, Brazil, Russia, and the United States, with a particular emphasis on total confirmed cases.
Methods: The proposed approach combines auto-regressive integrated moving average (ARIMA)'s ability to capture linear trends and seasonality with long short-term memory (LSTM) networks, which are designed to learn complex nonlinear dependencies in the data.
Sci Rep
December 2024
Department of Electrical Engineering, College of Engineering, King Saud University, Riyadh, 11421, Saudi Arabia.
The world is moving towards the utilization of hydrogen vehicle technology because its advantages are uniformity in power production, more efficiency, and high durability when compared to fossil fuels. So, in this work, the Proton Exchange Membrane Fuel Stack (PEMFS) device is selected for producing the energy for the hydrogen vehicle. The merits of this fuel technology are the possibility of operating less source temperature, and more suitability for stationery and transportation applications.
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December 2024
Innovative Global Program, Shibaura Institute of Technology, Tokyo, 135-8548, Japan.
This paper presents a novel and comprehensive control framework for the Rotary Inverted Pendulum (RIP), focusing on a hybrid control strategy that addresses the limitations of conventional methods in nonlinear and complex systems. The proposed controller synergistically combines an Optimized Fuzzy Logic Controller (OFLC) with Sliding Mode Control (SMC), leveraging the strengths of both techniques to achieve superior performance. The integration of Particle Swarm Optimization (PSO) into the OFLC significantly enhances its adaptability and precision, while the SMC law provides robust disturbance rejection and system stability.
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