Kwangwoon University

The lack of accuracy and penetration significantly hinder the clinical use of microwave (MW) thermotherapy. To address this issue, we propose a microwave thermal supercharging system (MTSS) featuring a miniature meta surface grid waveguide aperture antenna and MW-chaperone GaMOF-Co/Ni nanotopographies (GCN NTs) as MW absorbing materials. The meta surface grid waveguide aperture antenna, designed with filled meta surfaces, offers a reduced size, constrained MW beams, and focused energy for precise tumor MW thermotherapy. The MW-chaperone GCN NTs with multiple heterogeneous interfaces and magnetic structures were developed to enhance the dielectric and magnetic loss characteristics and improve MW absorption at medical frequencies (>90 %). Enhancing MW energy delivery to boost thermal conversion efficiency through meta surface grid waveguide aperture antenna innovation is analogous to increasing the air pressure in an engine's intake manifold. This system significantly improved the effectiveness of MW thermotherapy, achieving a 93 % inhibition and 100 % survival in vivo under clinically simulated deep-tissue conditions. By transforming microwave fields into programmable, tissue-specific therapeutic heat, this MTSS serves as a modular and device-compatible platform that redefines noninvasive oncology as a precision, energy-directed strategy with scalable clinical potential.

The accurate identification of acupoints is an essential task in acupuncture therapy. Recent advancements in artificial intelligence (AI) have led to the exploration of automated landmark detection systems, which may provide more accurate and reliable acupoint detection. This study investigated the efficiency of an AI model in predicting the shenmen, lung, and mouth auricular acupoints and compared its performance to placements made by a practitioner of traditional Korean medicine.

Ear images from 39 individuals were captured from three different angles. The mask region-based convolutional neural network (Mask R-CNN) model was utilized to isolate the ear region, followed by landmark detection using a CNN model trained on resized images to predict three auricular acupoints. Model reliability was enhanced by treating each acupoint as a separate prediction coordinate. Acupoint distribution was also estimated using a kernel density estimation method.

Centroids of auricular acupoints predicted by the CNN model showed deviations of < 3 pixels from traditional placements by the practitioner. Kernel density estimation showed that CNN predictions led to narrower acupoint distributions compared with those placed by the practitioner, suggesting higher consistency in CNN model predictions across different images.

The AI-driven approach showed significant potential in improving both the accuracy and consistency of auricular acupoint identification. These findings support the integration of AI into acupuncture practice as a reliable tool for enhancing clinical accuracy and precision of acupoint location.

Owing to the expansion of the manufacturing industry, bisphenol A (BPA) is being discharged into aquatic environments, posing a global concern. Numerous studies have recognized the adverse effects of BPA exposure on ecosystems and humans. Therefore, advanced remediation technologies are gaining increasing attention. Beyond the achievements of conventional water treatment processes, sonocatalysis provides several benefits, including effectiveness under ambient conditions, promising mineralization efficiency, and compatibility with nanostructured or hybrid catalysts. This review presents progress and developments made over the past ten years in the field of sonocatalysis related to BPA. Focusing mainly on BPA sonodegradation mechanisms, the effects of solution chemistry (e.g., pH, temperature, naturally occurring ions, natural organic matter, and scavengers), ultrasonication parameters (e.g., ultrasonic frequency, power, and operation mode), and the physicochemical properties of BPA (e.g., pK_a, hydrophobicity, and molecular configuration) were evaluated. Overall, sonocatalysis demonstrated competent BPA degradation, whereas hybrid systems (e.g., O₃, sono-Fenton, and ultraviolet/visible light irradiation) enhanced radical utilization. Finally, we discuss the current limitations and potential areas for future research, with the aim of guiding subsequent investigations towards practical applications.