Recently, virtual reality (VR) and augmented reality (AR) have received increasing attention, with the development of VR/AR devices such as head-mounted displays, haptic devices, and AR glasses. Medicine is considered to be one of the most effective applications of VR/AR. In this article, we describe a systematic literature review conducted to investigate the state-of-the-art VR/AR technology relevant to plastic surgery. The 35 studies that were ultimately selected were categorized into 3 representative topics: VR/AR-based preoperative planning, navigation, and training. In addition, future trends of VR/AR technology associated with plastic surgery and related fields are discussed.
Eyeglasses ; Glass ; Plastics* ; Surgery, Plastic*

The anomalous retro-psoas iliac artery is an extremely rare congenital iliolumbar vascular anomaly. A 51-year-old woman presented to our emergency department with worsening right lower extremity pain and weakness for 3 months. CT angiography of the right lower extremity showed no evidence of stenosis in the lower extremity arteries and the incidental finding of an anomalous right retro-psoas iliac artery. Herein, we report a rare case of anomalous retro-psoas iliac artery. Surgeons and clinicians need to be aware of this rare congenital anomaly to avoid severe complications during pelvic or orthopedic surgery.

No abstract available.
Extracellular Matrix Proteins* ; Extracellular Matrix* ; Peptides* ; Titanium*

There is a potential role of collagenase-3 in alveolar bone loss and periodontal disease progression, we need to develope or find chemotherapeutic drugs or herbal agents which may regulate the expression of MMP-13. Ginseng saponin, one of the major components of Korea ginseng(panax ginseng) root, has many various biologic effects, such as cytotoxic effect, tumoricidal effects, cytokine regulations, and protein biosynthesis effect. The purpose of this study was to determine the effects of Korea red ginseng saponin on MMP-13 gene expression in osteoblasts. The experimental groups were cultured with ginseng saponin in concentration of 1.0, 10, 25, 50, 100, 250 and 500microgram/ml for MTT assay. Primary rat calvarial cells were pre-treated for 1 hour with ginseng saponin(100 microgram/ml) and then stimulated with IL-1beta(1.0ng/ml) and PTH (10 nM). MMP-13 gene expression was evaluated by RT-PCR. The results were as follows: Ginseng saponin was cytotoxic to osteoblast at concentration exceeding 250microgram/ml for longer than 24 hours in tissue culture(p<0.01). In RT-PCR analysis, steady state MMP-13 mRNA levels were increased approximately 350% by IL-1beta, and 400% by PTH when normalized to untreated control. IL-1beta-indued MMP-13 mRNA expression was reduced 50% by pre- treatment with ginseng saponin. But ginseng saponin didn't inhibit MMP-13 expression from PTH stimulated cells. This results suggest that ginseng saponin inhibit IL-1beta-indued MMP-13 mRNA expres- sion.
Alveolar Bone Loss ; Animals ; Gene Expression ; Korea ; Matrix Metalloproteinase 13 ; Osteoblasts ; Panax* ; Periodontal Diseases ; Protein Biosynthesis ; Rats* ; RNA, Messenger* ; Saponins* ; Social Control, Formal

Phospholipids are key components of cellular membrane and signaling. Among cellular phospholipids, phosphoinositides, phosphorylated derivatives of phosphatidylinositol are important as a participant in essential metabolic processes in animals. However, due to its low abundance in cells and tissues, it is difficult to identify the composition of phosphoinositides. Recent advances in mass spectrometric techniques, combined with established separation methods, have allowed the rapid and sensitive detection and quantification of a variety of lipid species including phosphoinositides. In this mini review, we briefly introduce progress in profiling of cellular phosphoinositides using mass spectrometry. We also summarize current progress of matrices development for the analysis of cellular phospholipids using matrix-assisted laser desorption/ionization mass spectrometry. The phosphoinositides profiling and phospholipids imaging will help us to understand how they function in a biological system and will provide a powerful tool for elucidating the mechanism of diseases such as diabetes, cancer and neurodegenerative diseases. The investigation of cellular phospholipids including phosphoinositides using electrospray ionization mass spectrometry and matrix-assisted laser desorption/ionization mass spectrometry will suggest new insights on human diseases, and on clinical application through drug development of lipid related diseases.
Animals ; Humans ; Mass Spectrometry/*methods ; Phosphatidylinositols/*metabolism ; Phospholipids/*metabolism ; Spectrometry, Mass, Electrospray Ionization ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization

No abstract available.
Animals ; Enzyme-Linked Immunosorbent Assay ; Fibroblasts* ; Mice* ; p38 Mitogen-Activated Protein Kinases* ; Periodontal Ligament* ; Polymerase Chain Reaction

No abstract available.
Actinobacillus* ; Aggregatibacter actinomycetemcomitans* ; Animals ; Osteoclasts ; Rats*

Purpose: This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared. Materials and Methods: A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which weredetermined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method. Results: In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (P<0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The timerequired to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually,compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz). Conclusion Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculatethese measurements, the efficiency of diagnosis and treatment may be improved.

Purpose: This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared. Materials and Methods: A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which weredetermined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method. Results: In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (P<0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The timerequired to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually,compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz). Conclusion Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculatethese measurements, the efficiency of diagnosis and treatment may be improved.

Purpose: This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared. Materials and Methods: A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which weredetermined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method. Results: In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (P<0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The timerequired to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually,compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz). Conclusion Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculatethese measurements, the efficiency of diagnosis and treatment may be improved.