Hybrid closing-wedge DTO using PSI was selected for a patient wit severe deformity post-fracture malunion, which enable good alignment correction and patient satisfaction.

Background: High tibial osteotomy (HTO) is an effective treatment option for deformity correction after fracture. However, performing precise corrective osteotomy for cases with a severe varus deformity and a significant posterior slope poses a significant challenge. Three-dimensional (3D) bone model construction and patient-specific instrumentation (PSI) created from preoperative Computed tomography (CT) may be useful tools in achieving successful outcome for such cases.

Transformer-based classification of visceral pain-related local field potential patterns in the brain.

Neuronal ensemble activity entrained by local field potential (LFP) patterns underlies a variety of brain functions, including emotion, cognition, and pain perception. Recent advances in machine learning approaches may enable more effective methods for analyzing LFP patterns across multiple brain areas than conventional time-frequency analysis. In this study, we tested the performance of two machine learning algorithms, AlexNet and the Transformer models, to classify LFP patterns in eight pain-related brain regions before and during acetic acid-induced visceral pain behaviors.

Trial Analysis of Brain Activity Information for the Presymptomatic Disease Detection of Rheumatoid Arthritis.

This study presents a trial analysis that uses brain activity information obtained from mice to detect rheumatoid arthritis (RA) in its presymptomatic stages. Specifically, we confirmed that F759 mice, serving as a mouse model of RA that is dependent on the inflammatory cytokine IL-6, and healthy wild-type mice can be classified on the basis of brain activity information. We clarified which brain regions are useful for the presymptomatic detection of RA.