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Background: The morphology of the zygomatic complex significantly influences facial appearance, leading to a focus on zygomatic osteotomy. The current technique, the "L-shaped" zygomatic osteotomy, requires a small incision and preoperative osteotomy design for an osteotomy guide. However, the use of multiple software programs in the design process makes it time-consuming and clinically challenging., Method: Artificial intelligence technology offers a solution by integrating digital medical technology into medicine. AI algorithms were developed based on point cloud models, using 2000 cases of three-dimensional CT data for training. Eighty CT data sets were randomly chosen for both AI and manual skull segmentation designs. The effectiveness, symmetry, safety, and aesthetic outcomes were compared., Result: The AI zygomatic osteotomy showed superior performance in symmetry and aesthetics compared to manual zygomatic osteotomy. The complex structure of the zygomatic arch highlights the advantages of AI-driven osteotomy design, especially in intricate cases. Additionally, the AI osteotomy scheme demonstrated no compromise in safety indicators compared to the manual approach., Conclusion: AI zygomatic osteotomy proves to be a safe and effective alternative to manual zygomatic osteotomy, showcasing enhanced symmetry and aesthetic outcomes. The efficiency and precision of AI-driven design in complex zygomatic osteotomies make it a promising advancement in this field., Competing Interests: Conflict of interest statement The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025. Published by Elsevier Ltd.)

Introduction: Fat grafting procedures for body contouring and cosmetic reconstruction have received widespread attention., Method: In recent years, there has been an increase in post-fat grafting infections caused by Mycobacterium abscessus (MA), and there is a lack of representative and standardized murine models of infection; therefore, there has been limited research on the treatment of post-fat grafting MA infections. To overcome this challenge, we constructed an MA infection model after fat grafting., Result: By evaluating skin charge, dermatopathology, and inflammatory markers, we found that the fat graft + 1 × 109 CFU/mL bacterial suspension infection group had significant inflammatory symptoms and elevated inflammatory factors on postoperative day 10., Conclusion: The model construction process was simple and reproducible, which paves the way for further studies on the impact of MA pathogenesis and the efficacy of new treatments., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)