Current Issue : October-December Volume : 2025 Issue Number : 4 Articles : 5 Articles
The electric field enhancement effect induced by localized surface plasmon resonance (LSPR) plays a critical role in imaging and sensing applications. In particular, nanocube structures with narrow gaps provide large hotspot areas, making them highly promising for high-sensitivity applications. This study predicts the electric field enhancement effect of structures combining silver nanocubes and a 10 nm thick silver thin film using the finite-difference time-domain (FDTD) method. We demonstrate that the interaction between the silver nanocubes and silver thin film allows control over sharp LSPR peaks in the visible wavelength range. Specifically, the structure with a spacer layer between the silver nanocubes and the silver thin film is suitable for multimodal imaging, while the direct contact structure of the silver nanocubes and the silver thin film shows potential as a highly sensitive refractive index sensor. The 10 nm thick silver thin film enables backside illumination due to its transparency in the visible wavelength region, making it compatible with inverted microscopes and allowing for versatile applications, such as living cell imaging and observations in liquid media. These structures are particularly expected to contribute to advancements in bioimaging and biosensing....
Background: Effective rehabilitation of the upper extremity function is vital for individuals recovering from stroke or cervical spinal cord injury, as it can enable them to regain independence in daily tasks. While robotic therapy provides precise and consistent motor training, it often lacks the integration of real-world objects that stimulate sensorimotor experiences. The Toronto Rehabilitation Institute—Hand Function Test (TRI-HFT) utilizes 19 everyday items to assess hand function. This study aims to modify the 3D-printed TRI-HFT objects to ensure their compatibility with robotic manipulation, thereby enhancing the functional relevance of robotassisted rehabilitation, and to evaluate the usability of the new robotic system to ensure its safety and technical performance. Results: We successfully redesigned the 3D-TRI-HFT objects to enable manipulation by a robotic arm equipped with a gripper. The modified 3D-printed objects closely matched the original specifications, with most weight and size deviations within acceptable limits. Performance tests demonstrated reliable robotic manipulation, achieving a 100% success rate in 50 pick-and-place trials for each object without any breakage or slippage. Usability assessments further supported the system’s performance, indicating that participants found the system engaging, useful, and comfortable. Conclusions: The modified 3D-printed TRI-HFT objects allow seamless integration into robotic therapy, facilitating the use of real-world objects in rehabilitation exercises. These modifications enhance functional engagement without compromising user interaction with the objects, demonstrating the feasibility of combining traditional rehabilitation tools with robotic systems, potentially leading to improved outcomes in upper extremity rehabilitation. Future research may focus on adapting these designs for compatibility with a broader range of robotic equipment, reducing the cost of the objects as 3D printing technology advances, and evaluating the system’s performance among individuals with stroke and SCI....
DNA information storage holds tremendous potential due to its scalability, long lifespan, and environmental sustainability. The synthesis and reading of complex DNA data structures are of central importance. In this work, we propose new encoding schemes through novel synthesis methods of DNA and peptide nanostructures. Silicon nitride (SiNx) solid-state nanopores (ssNPs) are employed as the detection platform to enable scalable and inexpensive reading. This approach is no longer constrained by the limitations of single-base sequencing technologies. Peptide nanostructures are introduced as a data medium via click-chemistry, expanding encoding sources. By integrating a photosensitive PC-linker, this approach endows the data chain with functionalities for encryption and data formatting, enhancing the security and organization of biological information storage. Our study presents a comprehensive framework for data management from data synthesis to post-processing, which includes encryption, decryption, and erasure functionalities....
Background: This observational, prospective, analytical, and cross-sectional study was designed to systematically analyze ocular biometric parameters in patients with nuclear cataract exhibiting nuclear hardness grade ≥ 3 according to the Emery- Little classification under slit-lamp examination who scheduled for phacoemulsification. Ocular biometric measurements were acquired using the IOL Master 700, a sweptsource optical coherence tomography (SS-OCT) device. Results: Age was negatively correlated with axial length (AL), anterior chamber depth (ACD), white-to-white (WTW), and pupil diameter (PD) (rAL = − 0.13, rACD = − 0.26, rWTW = − 0.18, all P < 0.001; rPD = − 0.09, P < 0.01) but positively correlated with total steep keratometry (TKs) (rTKs = 0.13, P < 0.001). AL was negatively correlated with total flat keratometry (TKf ), TKs, and WTW (rTKf = − 0.3, rTKs = − 0.27, rWTW = − 0.18, all P < 0.001) but positively correlated with ACD and PD (rACD = 0.43, rPD = 0.10, all P < 0.001). Men had smaller TK and PD but larger WTW than women. Conclusions: These findings highlight significant sex-related differences in biometric parameters among patients with nuclear cataract, which are closely related to AL and age. Considering variation with these parameters helps personalize surgical plans and prevent complications....
This article explores the transformative role of artificial intelligence in accelerating biomedical research, with a particular focus on Alzheimer's disease. The article examines how AI platforms have revolutionized traditional research methodologies through enhanced data processing capabilities, improved diagnostic accuracy, and accelerated drug discovery processes. The article highlights significant advancements in four key areas: AI-enabled research platforms and infrastructure, early detection and diagnostic applications, genomic analysis and target discovery, and autonomous research systems. These innovations have led to unprecedented improvements in processing complex datasets, identifying early disease markers, analyzing genetic variations, and automating research processes. The article demonstrates how AI integration has dramatically reduced research timelines while maintaining high accuracy rates across various applications, potentially transforming the future of biomedical research and therapeutic interventions....
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