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Magnetic particle imaging (MPI), using superparamagnetic nanoparticles as an imaging tracer, is touted as a quantitative biomedical imaging technology, but MPI signal properties have never been characterized for magnetic nanoparticles undergoing biodegradation. We show that MPI signal properties can increase or decrease as iron oxide nanoparticles degrade, depending on the nanoparticle formulation and nanocrystal size, and degradation rate and mechanism. Further, we show that long-term in vitro MPI experiments only roughly approximate long-term in vivo MPI signal properties. Further, we demonstrate for the first time, an environmentally sensitive MPI contrast mechanism opening the door to smart contrast paradigms in MPI.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7643918 | PMC |
http://dx.doi.org/10.1021/acsanm.0c00779 | DOI Listing |
The evolutionary patterns exhibited by the ring and stem regions of the RNA secondary structure are distinct. Incorporating RNA secondary structure information into evolutionary models can improve the reliability of phylogenetic trees constructed using RNA sequences. However, empirically derived RNA evolutionary models remain scarce.
View Article and Find Full Text PDFNanoscale
August 2025
School of Chemistry, University of New South Wales, Sydney, NSW 2052, Australia.
Achieving high spatial resolution in magnetic particle imaging (MPI) remains a major challenge in advancing MPI capabilities. In this study, Mn-Fe oxide nanoparticle tracers with octopod morphology were synthesized, showing a 2.3-fold improvement in spatial resolution while maintaining strong signal intensity at higher tracer concentrations.
View Article and Find Full Text PDFSci Data
August 2025
Korea Advanced Institute of Science and Technology (KAIST), School of Computing, Daejeon, 34141, Republic of Korea.
Wearable technology is a promising tool for everyday health monitoring, with heart rate variability (HRV) providing key insights into current and potential health conditions. However, previous HRV datasets were collected under controlled clinical conditions, rather than in complex real-world environments. Here, we collected continuous physiological and motion signals using smartwatches from 49 healthy individuals (mean age: 28.
View Article and Find Full Text PDFNat Commun
August 2025
Department of Life Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Parkinson's disease (PD), a progressive neurodegenerative disorder, presents complex motor symptoms and lacks effective disease-modifying treatments. Here we show that integrating artificial intelligence (AI) with optogenetic intervention, termed optoRET, modulating c-RET (REarranged during Transfection) signalling, enables task-independent behavioural assessments and therapeutic benefits in freely moving male AAV-hA53T mice. Utilising a 3D pose estimation technique, we developed tree-based AI models that detect PD severity cohorts earlier and with higher accuracy than conventional methods.
View Article and Find Full Text PDFTalanta
August 2025
Department of Chemistry, Gauhati University, Guwahati, 781014, India. Electronic address:
The H quantitative Nuclear Magnetic Resonance (qNMR) has emerged as a powerful analytical tool due to its high sensitivity, ability to provide absolute quantification, and most importantly, its univocal structural assignment. So far, H qNMR has been used to quantify only the major constituents of the essential oils (EOs). Since the minor constituents of the EOs play a role in its various properties, quantification of minor constituents is essential.
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