3D bioprinted autologous bone particle scaffolds for cranioplasty promote bone regeneration with both implanted and native BMSCs

Abstract

Although autologous bone grafting is considered to be the gold standard for cranioplasty, unresolved problems remain, such as surgical-site infections and bone flap absorption. In this study, an autologous bone (AB) scaffold was constructed via three-dimensional (3D) bedside-bioprinting technology and used for cranioplasty. To simulate the skull structure, a polycaprolactone shell was designed as an external lamina, and 3D-printed AB and a bone marrow-derived mesenchymal stem cell (BMSC) hydrogel was used to mimic cancellous bone for bone regeneration. Our in vitro results showed that the scaffold exhibited excellent cellular affinity and promoted osteogenic differentiation of BMSCs in both 2D and 3D culture systems. The scaffold was implanted in beagle dog cranial defects for up to 9 months, and the scaffold promoted new bone and osteoid formation. Further in vivo studies indicated that transplanted BMSCs differentiated into vascular endothelium, cartilage, and bone tissues, whereas native BMSCs were recruited into the defect. The results of this study provide a method for bedside bioprinting of a cranioplasty scaffold for bone regeneration, which opens up another window for clinical applications of 3D printing in the future.

Adaptive Prototype Learning and Allocation for Few-Shot Segmentation

“…Li et al [29] adopt DINO-ViT features to perform affordance grounding by transferring affordance knowledge from human-object interaction images to egocentric views. Huang et al [25] propose a novel pipeline that uses LLMs [48] for affordance reasoning, which interacts with VLMs to produce 3D affordance maps for robotic manipulation. Recent studies [38,51,56] delve into the integration of affordance and language models for task-oriented grasping, which allows robots to grasp objects in a more appropriate and safe manner.…”

Advances and Prospects in Materials for Craniofacial Bone Reconstruction

“…34−36 Recently, a 3D-printed autologous bone cranioplasty-composite scaffold laden with autologous bone marrow-derived mesenchymal stem cells (BMSCs) was used to quickly perform bedside bioprinting (BBP) during beagle dog cranioplasty. 37 Apart from autologous bone tissue, cartilage (i.e., auricular concha, nasal septum), periosteum, and tensor fascia lata are also employed in craniofacial bone repair. 38−41 Autotransplantation also has a few drawbacks, including donor site morbidity, unpredictable resorption, and prolonged surgery procedure.…”

“…Autologous bone, taken from a secondary site of patients with bone defects, is regarded as the “gold standard” material for repairing large bone defects by surgeons because of its high biocompatibility, low immune reaction, inherent rigidity, and vascularization potential. , Autologous bone possesses a number of elements good for bone regeneration, including favorable surface tomography, similar mechanical strength, osteogenic cells, and growth factors. Studies have validated the safety and efficiency of autologous bone in craniofacial reconstruction. − Recently, a 3D-printed autologous bone cranioplasty-composite scaffold laden with autologous bone marrow-derived mesenchymal stem cells (BMSCs) was used to quickly perform bedside bioprinting (BBP) during beagle dog cranioplasty …”

CineMPC: Controlling Camera Intrinsics and Extrinsics for Autonomous Cinematography

“…Researchers have been exploring ways to integrate natural language understanding and generation capabilities into robotic systems [8]- [10]. Some applications include the utilization of multimodal foundation models to control manipulators [3], direct actions [11], or design a plan of actions to a robot performing a particular task [12]. Certain works integrate foundation models with reinforcement or imitation learning techniques, achieving human-like behavior in robots [13], [14].…”

“…Existing solutions propose different techniques to control actuators using natural language or giving commands to robots to perform different actions (e.g. move to the room on your left) [3]. Nevertheless, to the best of our knowledge, there are no prior works in the literature that use foundation models to control a swarm of robots.…”