Purpose: Transplantation of stem cells to remodel the trabecular meshwork (TM) has become a new option for restoring aqueous humor dynamics and intraocular pressure homeostasis in glaucoma. In this study, we aimed to design a nanoparticle to label induced pluripotent stem cell (iPSC)-derived TM and improve the delivery accuracy and in vivo tracking efficiency.
Methods: PLGA-SPIO-Cypate (PSC) NPs were designed with polylactic acid-glycolic acid (PLGA) polymers as the backbone, superparamagnetic iron oxide (SPIO) nanoparticles, and near-infrared (NIR) dye cypate. In vitro assessment of cytotoxicity, iron content after NPs labeling, and the dual-model monitor was performed on mouse iPSC-derived TM (miPSC-TM) cells, as well as immortalized and primary human TM cells. Cell function after labeling, the delivery accuracy, in vivo tracking efficiency, and its effect on lowering IOP were evaluated following miPSC-TM transplantation in mice.
Results: Initial in vitro experiments showed that a single-time nanoparticles incubation was sufficient to label iPSC-derived TM and was not related to any change in both cell viability and fate. Subsequent in vivo evaluation revealed that the use of this nanoparticle not only improves the delivery accuracy of the transplanted cells in live animals but also benefits the dual-model tracking in the long term. More importantly, the use of the magnet triggers a temporary enhancement in the effectiveness of cell-based therapy in alleviating the pathologies associated with glaucoma.
Conclusion: This study provided a promising approach for enhancing both the delivery and in vivo tracking efficiency of the transplanted cells, which facilitates the clinical translation of stem cell-based therapy for glaucoma.
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http://dx.doi.org/10.2147/IJN.S346141 | DOI Listing |
Surgeon
January 2025
Department of Arthritis, Affiliated Hospital of Shandong Second Medical University, 2428 Yuhe Road, Kuiwen District, Weifang City, Shandong Province, 261031, PR China. Electronic address:
Hallux valgus (HV) is the most common foot deformity. It has various pathogenic factors that make its pathogenesis challenging to understand. As the disease progresses, patients experience amplified pain and decreased activities, significantly affecting their quality of life.
View Article and Find Full Text PDFJ 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 PDFViruses
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Microbiology Laboratory, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
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Sensors (Basel)
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Department of Biomedical and Robotics Engineering, Incheon National University, Incheon 22012, Republic of Korea.
With the rise of modern healthcare monitoring, heart rate (HR) estimation using remote photoplethysmography (rPPG) has gained attention for its non-contact, continuous tracking capabilities. However, most HR estimation methods rely on stable, fixed sampling intervals, while practical image capture often involves irregular frame rates and missing data, leading to inaccuracies in HR measurements. This study addresses these issues by introducing low-complexity timing correction methods, including linear, cubic, and filter interpolation, to improve HR estimation from rPPG signals under conditions of irregular sampling and data loss.
View Article and Find Full Text PDFSensors (Basel)
January 2025
The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology, Harbin 150080, China.
Video instance segmentation, a key technology for intelligent sensing in visual perception, plays a key role in automated surveillance, robotics, and smart cities. These scenarios rely on real-time and efficient target-tracking capabilities for accurate perception and intelligent analysis of dynamic environments. However, traditional video instance segmentation methods face complex models, high computational overheads, and slow segmentation speeds in time-series feature extraction, especially in resource-constrained environments.
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