Search

Abstract Osteoarthritis affects millions of people worldwide but current treatments using analgesics or anti-inflammatory drugs only alleviate symptoms of this disease. Here, we present an injectable, biodegradable piezoelectric hydrogel, made of short electrospun poly-L-lactic acid nanofibers embedded inside a collagen matrix, which can be injected into the joints and self-produce localized electrical cues under ultrasound activation to drive cartilage healing. In vitro, data shows that the piezoelectric hydrogel with ultrasound can enhance cell migration and induce stem cells to secrete TGF-β1, which promotes chondrogenesis. In vivo, the rabbits with osteochondral critical-size defects receiving the ultrasound-activated piezoelectric hydrogel show increased subchondral bone formation, improved hyaline-cartilage structure, and good mechanical properties, close to healthy native cartilage. This piezoelectric hydrogel is not only useful for cartilage healing but also potentially applicable to other tissue regeneration, offering a significant impact on the field of regenerative tissue engineering.

Objects accidentally left behind in the brain following neurosurgical procedures may lead to life-threatening health complications and invasive reoperation. One of the most commonly retained surgical items is the cotton ball, which absorbs blood to clear the surgeon’s field of view yet in the process becomes visually indistinguishable from the brain parenchyma. However, using ultrasound imaging, the different acoustic properties of cotton and brain tissue result in two discernible materials. In this study, we created a fully automated foreign body object tracking algorithm that integrates into the clinical workflow to detect and localize retained cotton balls in the brain. This deep learning algorithm uses a custom convolutional neural network and achieves 99% accuracy, sensitivity, and specificity, and surpasses other comparable algorithms. Furthermore, the trained algorithm was implemented into web and smartphone applications with the ability to detect one cotton ball in an uploaded ultrasound image in under half of a second. This study also highlights the first use of a foreign body object detection algorithm using real in-human datasets, showing its ability to prevent accidental foreign body retention in a translational setting.