DNA-based nanomachines have received increasing attention due to their great potential to mimic natural biological motors and create novel modes of motion. Here, we report a DNAzyme-based walking machine, which can operate in living cells after triggered by intracellular miRNA-21. The walking machine is constructed by assembling DNAzyme walking strands and FAM-labeled substrate strands on a single gold nanoparticle (AuNP). The DNAzyme walking strand is first silenced by a blocker strand. After cellular uptake, DNAzyme-based walker can be triggered by intracellular miRNA-21 and autonomously walk along the AuNP-based 3D track fueled by DNAzyme-catalyzed substrate cleavage. Each walking step results in the cleavage of a substrate strand and the release of a FAM-labeled DNA strand, allowing real-time monitoring of the operation of the machine. The DNAzyme-based walking machine has been successfully applied to image and monitor miRNA-21 expression levels in living cells with excellent specificity and reliability. This walking machine would hold great potential in the miRNA associated biological research and disease diagnostics.
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http://dx.doi.org/10.1016/j.bios.2019.04.031 | DOI Listing |
J Insect Sci
January 2025
School of Biological Sciences, University of Aberdeen, King's College, Aberdeen, UK.
Radio frequency identification (RFID) technology and marker recognition algorithms can offer an efficient and non-intrusive means of tracking animal positions. As such, they have become important tools for invertebrate behavioral research. Both approaches require fixing a tag or marker to the study organism, and so it is useful to quantify the effects such procedures have on behavior before proceeding with further research.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Science and Engineering, Saga University, Saga 840-8502, Japan.
Infrared array sensor-based fall detection and activity recognition systems have gained momentum as promising solutions for enhancing healthcare monitoring and safety in various environments. Unlike camera-based systems, which can be privacy-intrusive, IR array sensors offer a non-invasive, reliable approach for fall detection and activity recognition while preserving privacy. This work proposes a novel method to distinguish between normal motion and fall incidents by analyzing thermal patterns captured by infrared array sensors.
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January 2025
Centre for Automation and Robotics (CAR UPM-CSIC), Escuela Técnica Superior de Ingeniería y Diseño Industrial (ETSIDI), Universidad Politécnica de Madrid, Ronda de Valencia 3, 28012 Madrid, Spain.
Analysis of the human gait represents a fundamental area of investigation within the broader domains of biomechanics, clinical research, and numerous other interdisciplinary fields. The progression of visual sensor technology and machine learning algorithms has enabled substantial developments in the creation of human gait analysis systems. This paper presents a comprehensive review of the advancements and recent findings in the field of vision-based human gait analysis systems over the past five years, with a special emphasis on the role of vision sensors, machine learning algorithms, and technological innovations.
View Article and Find Full Text PDFBiomedicines
January 2025
Department of Management Information Systems, Keimyung University, Daegu 42601, Republic of Korea.
: Diabetes is a dangerous disease that is accompanied by various complications, including cardiovascular disease. As the global diabetes population continues to increase, it is crucial to identify its causes. Therefore, we predicted diabetes using an AI model and quantitatively examined causal relationships using a causal discovery and inference model.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
School of Mechanical Engineering, Jiangsu University of Technology, Changzhou 213001, China.
To reduce hip joint muscles' activation during walking with an active hip exoskeleton. Few studies examine the optimal active assistance timing of the hip exoskeleton based on muscle activation characteristics. Sixteen gender-balanced healthy adults (mean age 28.
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