Mitsuru Yagi 교수

Osteoclasts are bone-resorbing cells that play a pivotal role in bone remodeling. Osteoclasts form large multinuclear giant cells by fusion of mononuclear osteoclasts. How cell fusion is mediated, however, is unclear. We identify the dendritic cell-specific transmembrane protein (DC-STAMP), a putative seven-transmembrane protein, by a DNA subtraction screen between multinuclear osteoclasts and mononuclear macrophages. DC-STAMP is highly expressed in osteoclasts but not in macrophages. DC-STAMP-d

Despite the occurrence of PJK in 20% of adult scoliosis patients undergoing long fusion, no significant differences were found in SRS outcome scores and ODI in PJK and non-PJK patients. Fusion to the sacrum and posterior fusion with segmental instrumentation were identified as risk factors. PJK can be minimized by post-operative normalization of global sagittal alignment. A simplified classification based in severity type of PJK showed the majority in class 1A (ligamentous lesion and mild deform

In a long-term review of minimum 5 years, 76% of PJK occurred within 3 months after surgery. Pre-existing low bone mineral density, PSF, fusion to the sacrum, inappropriate global spine alignment, and greater sagittal vertical axis change were significant risk factors for PJK. Careful long-term follow-up should be done for a patient with PJK.

In Brief Study Design. Retrospective case series of surgically treated patients with adult spine deformity (ASD). Objective. To report the incidence of proximal junctional failure (PJF), characterize PJF and evaluate the outcome of revision surgery for PJF. A modified classification is also proposed. Summary of Background Data. Although recent reports have shown the catastrophic results of PJF, few reports have shown the incidence, characteristics, and clinical outcomes of PJF in ASD. Methods. T

Long-term clinical outcome was significantly worse in patients with intramedullary signal intensity changes on MR images. The risk factors were instability of the cervical spine and severe ventral spinal compression. The long-term clinical outcome was also significantly worse in patients with postoperative expansion of the high signal intensity area. The fact that cervical instability was a risk factor for the postoperative expansion of the high signal intensity indicates that this high signal i

dc-stamp expression is regulated differently in osteoclasts and macrophage giant cells. c-Fos and NFATc1, both of which are essential for osteoclast differentiation, are needed for dc-stamp expression and cell-cell fusion in osteoclasts, but both factors are dispensable for giant cell formation by macrophages. Because PU.1 and NF-kappaB are recruited to the dc-stamp promoter after stimulation with GM-CSF + IL-4, dc-stamp transcription is regulated in a cell type-specific manner.

This novel procedure provides effective spinal decompression. Although this method requires more operating time than a conventional method, it requires only minimal muscle trauma and spinal stability maintenance, and allows for early mobilization. This shortens the hospital stay, reduces postoperative back pain, and leads to satisfactory neurological and functional outcomes. Moreover, with the midline approach, decompression was accomplished without compromising the facet joints, even with a nar

TXA treatment group lost significantly less blood and received significantly fewer blood transfusions than the control group without significant differences in intra- and postoperative complications. A multicenter randomized prospective analysis would provide additional information of the efficacy and safety of TXA.

Comparable bone density exists among adult scoliosis patients with no correlation between BMD and curve magnitude, fusion and complication rates. The difference in BMD of the hip and of spine cannot be fully explained in the review. These results will guide in surgical planning, patient selection on the treatment options.

Artificial intelligence (AI) and machine learning (ML) are rapidly becoming integral components of modern healthcare, offering new avenues for diagnosis, treatment, and outcome prediction. This review explores their current applications and potential future in the field of spinal care. From enhancing imaging techniques to predicting patient outcomes, AI and ML are revolutionizing the way we approach spinal diseases. AI and ML have significantly improved spinal imaging by augmenting detection and

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