Advancements and Challenges in Robot-Assisted Bone Processing in Neurosurgical Procedures.

OBJECTIVE: Practical applications of nerve decompression using neurosurgical robots remain unexplored. Our ongoing research and development initiatives, utilizing industrial robots, aim to establish a secure and efficient neurosurgical robotic system. The principal objective of this study was to automate bone grinding, which is a pivotal component of neurosurgical procedures. METHODS: To achieve this goal, we integrated an endoscope system into a manipulator and conducted precision bone machining using a neurosurgical drill, recording the grinding resistance values across 3 axes. Our study encompassed 2 core tasks: linear grinding, such as laminectomy, and cylindrical grinding, such as foraminotomy, with each task yielding unique measurement data. RESULTS: In linear grinding, we observed a proportional increase in grinding resistance values in the machining direction with acceleration. This observation suggests that 3-axis resistance measurements are a valuable tool for gauging and predicting deep cortical penetration. However, problems occurred in cylindrical grinding, and a significant error of 10% was detected. The analysis revealed that multiple factors, including the tool tip efficiency, machining speed, teaching methods, and deflection in the robot arm and jig joints, contributed to this error. CONCLUSION: We successfully measured the resistance exerted on the tool tip during bone machining with a robotic arm across 3 axes. The resistance ranged from 3 to 8 Nm, with the measurement conducted at a processing speed approximately twice that of manual surgery performed by a surgeon. During the simulation of foraminotomy under endoscopic grinding conditions, we encountered a -10% error margin.

bFGF-releasing biodegradable nanoparticles for effectively engrafting transplanted hepatocyte sheet.

Hepatic tissue engineering has been applied for the treatment of intractable liver diseases, and hepatocyte sheets are promising for this purpose. However, hepatocyte sheets have poor survival after transplantation because of their high metabolic activity. In this study, we aimed to develop basic fibroblast growth factor (bFGF)-releasing nanoparticles to prolong the survival of hepatocyte sheets after transplantation. The nanoparticles were prepared by electrospraying a bFGF-dispersed poly(D,l-lactide-co-glycolide) emulsion. bFGF-loaded PLGA nanoparticles can be developed by optimizing the applied electrospray voltage and the oil:water ratio of the emulsion. The prepared nanoparticles exhibited prompt release at the initial duration and continuous gradual release at the subsequent duration. Hepatocyte sheet engraftment was evaluated by transplanting hepatocyte sheets containing the prepared nanoparticles into rats. The hepatocyte sheets with the prepared nanoparticles exhibited longer survival than those without the bFGF nanoparticles or solution owing to the local and continuous release of bFGF from the nanoparticles and the subsequent enhanced angiogenesis at the transplantation site. These results indicated that the prepared bFGF-releasing nanoparticles can enhance the efficiency of hepatocyte sheet transplantation. The developed bFGF-releasing nanoparticles would be useful for the transplantation of cellular tissue with post-transplantation survival challenges.

Extracting the Secrets of OpenSSL with RAMBleed.

Concomitant with the increasing density of semiconductors, various attacks that threaten the integrity and security of dynamic random access memory (DRAM) have been devised. Among these, a side-channel attack called RAMBleed is a prolific one that utilizes a general user-level account without special rights to read secret information. Studies have reported that it can be used to obtain OpenSSH secret keys. However, a technique for deriving the Rivest-Shamir-Adleman (RSA) secret keys used in OpenSSL under realistic parameters and environments has not been reported. We propose a method that uses RAMBleed to obtain OpenSSL secret keys and demonstrate its efficacy using the example of an Apache server. The proposed method exploits the fact that, in the operation of an Apache server that uses OpenSSL, the RSA private keys are deployed on DRAM at a set time. Although the result of reading this secret information contains a few errors, error-free secret information is obtainable when it is used with RSA cryptanalysis techniques. We performed a series of attacks incorporating RAMBleed and eventually retrieved the OpenSSL RSA private key, indicating that secret information is obtainable with high probability. The proposed method can easily and externally be executed without administrator privileges on a server using DRAM that is vulnerable to RAMBleed, showing that RAMBleed is also a major threat to OpenSSL.