Recent advances in robotics technology and artificial intelligence (AI) have sparked increased interest in humanoid robots that resemble humans and social robots capable of interacting socially. Alongside this trend, a new field of robot research called human-robot interaction (HRI) is gaining prominence. The aim of this review paper is to introduce the fundamental concepts of HRI and social robots, examine their current applications in the medical field, and discuss the current and future prospects of HRI and social robots in spinal care. HRI is an interdisciplinary field where robotics, AI, social sciences, design, and various disciplines collaborate organically to develop robots that successfully interact with humans as the ultimate goal. While social robots are not yet widely deployed in clinical environments, ongoing HRI research encompasses various areas such as nursing and caregiving support, social and emotional assistance, rehabilitation and cognitive enhancement for the elderly, medical information provision and education, as well as patient monitoring and data collection. Although still in its early stages, research related to spinal care includes studies on robotic support for rehabilitation exercises, assistance in gait training, and questionnaire-based assessments for spinal pain. Future applications of social robots in spinal care will require diverse HRI research efforts and active involvement from spinal specialists.

Recent advances in robotics technology and artificial intelligence (AI) have sparked increased interest in humanoid robots that resemble humans and social robots capable of interacting socially. Alongside this trend, a new field of robot research called human-robot interaction (HRI) is gaining prominence. The aim of this review paper is to introduce the fundamental concepts of HRI and social robots, examine their current applications in the medical field, and discuss the current and future prospects of HRI and social robots in spinal care. HRI is an interdisciplinary field where robotics, AI, social sciences, design, and various disciplines collaborate organically to develop robots that successfully interact with humans as the ultimate goal. While social robots are not yet widely deployed in clinical environments, ongoing HRI research encompasses various areas such as nursing and caregiving support, social and emotional assistance, rehabilitation and cognitive enhancement for the elderly, medical information provision and education, as well as patient monitoring and data collection. Although still in its early stages, research related to spinal care includes studies on robotic support for rehabilitation exercises, assistance in gait training, and questionnaire-based assessments for spinal pain. Future applications of social robots in spinal care will require diverse HRI research efforts and active involvement from spinal specialists.

Recent advances in robotics technology and artificial intelligence (AI) have sparked increased interest in humanoid robots that resemble humans and social robots capable of interacting socially. Alongside this trend, a new field of robot research called human-robot interaction (HRI) is gaining prominence. The aim of this review paper is to introduce the fundamental concepts of HRI and social robots, examine their current applications in the medical field, and discuss the current and future prospects of HRI and social robots in spinal care. HRI is an interdisciplinary field where robotics, AI, social sciences, design, and various disciplines collaborate organically to develop robots that successfully interact with humans as the ultimate goal. While social robots are not yet widely deployed in clinical environments, ongoing HRI research encompasses various areas such as nursing and caregiving support, social and emotional assistance, rehabilitation and cognitive enhancement for the elderly, medical information provision and education, as well as patient monitoring and data collection. Although still in its early stages, research related to spinal care includes studies on robotic support for rehabilitation exercises, assistance in gait training, and questionnaire-based assessments for spinal pain. Future applications of social robots in spinal care will require diverse HRI research efforts and active involvement from spinal specialists.

Recent advances in robotics technology and artificial intelligence (AI) have sparked increased interest in humanoid robots that resemble humans and social robots capable of interacting socially. Alongside this trend, a new field of robot research called human-robot interaction (HRI) is gaining prominence. The aim of this review paper is to introduce the fundamental concepts of HRI and social robots, examine their current applications in the medical field, and discuss the current and future prospects of HRI and social robots in spinal care. HRI is an interdisciplinary field where robotics, AI, social sciences, design, and various disciplines collaborate organically to develop robots that successfully interact with humans as the ultimate goal. While social robots are not yet widely deployed in clinical environments, ongoing HRI research encompasses various areas such as nursing and caregiving support, social and emotional assistance, rehabilitation and cognitive enhancement for the elderly, medical information provision and education, as well as patient monitoring and data collection. Although still in its early stages, research related to spinal care includes studies on robotic support for rehabilitation exercises, assistance in gait training, and questionnaire-based assessments for spinal pain. Future applications of social robots in spinal care will require diverse HRI research efforts and active involvement from spinal specialists.

Recent advances in robotics technology and artificial intelligence (AI) have sparked increased interest in humanoid robots that resemble humans and social robots capable of interacting socially. Alongside this trend, a new field of robot research called human-robot interaction (HRI) is gaining prominence. The aim of this review paper is to introduce the fundamental concepts of HRI and social robots, examine their current applications in the medical field, and discuss the current and future prospects of HRI and social robots in spinal care. HRI is an interdisciplinary field where robotics, AI, social sciences, design, and various disciplines collaborate organically to develop robots that successfully interact with humans as the ultimate goal. While social robots are not yet widely deployed in clinical environments, ongoing HRI research encompasses various areas such as nursing and caregiving support, social and emotional assistance, rehabilitation and cognitive enhancement for the elderly, medical information provision and education, as well as patient monitoring and data collection. Although still in its early stages, research related to spinal care includes studies on robotic support for rehabilitation exercises, assistance in gait training, and questionnaire-based assessments for spinal pain. Future applications of social robots in spinal care will require diverse HRI research efforts and active involvement from spinal specialists.

Background/Aims: Recently, patients with pancreatic cancer (PC) who underwent resection have exhibited improved survival outcomes, but comprehensive analysis is limited. We analyzed the trends of contributing factors. Methods: Data of patients with resected PC were retrospectively collected from the Korean Health Insurance Review and Assessment Service (HIRA) database and separately at our institution. Cox regression analysis was conducted with the data from our institution a survival prediction score was calculated using the β coefficients. Results: Comparison between the periods 2013–2015 (n=3,255) and 2016–2018 (n=3,698) revealed a difference in the median overall survival (25.9 months vs not reached, p<0.001) when analyzed with the HIRA database which was similar to our single-center data (2013–2015 [n=119] vs 2016–2018 [n=148], 20.9 months vs 32.2 months, p=0.003). Multivariable analyses revealed six factors significantly associated with better OS, and the scores were as follows: age >70 years, 1; elevated carbohydrate antigen 19-9 at diagnosis, 1; R1 resection, 1; stage N1 and N2, 1 and 3, respectively; no adjuvant treatment, 2; FOLFIRINOX or gemcitabine plus nab-paclitaxel after recurrence, 4; and other chemotherapy or supportive care only after recurrence, 5. The rate of R0 resection (69.7% vs 80.4%), use of adjuvant treatment (63.0% vs 74.3%), and utilization of FOLFIRINOX or gemcitabine plus nab-paclitaxel (25.2% vs 47.3%) as palliative chemotherapeutic regimen, all increased between the two time periods, resulting in decreased total survival prediction score (mean: 7.32 vs 6.18, p=0.004). Conclusions Strict selection of surgical candidates, more use of adjuvant treatment, and adoption of the latest combination regimens for palliative chemotherapy after recurrence were identified as factors of recent improvement.

Background/Aims: Advanced biliary tract cancer (BTC) is associated with poor survival. A recent phase II study of triplet combination chemotherapy, including gemcitabine, cisplatin, and nanoparticle albumin-bound (nab)-paclitaxel, has shown promising results. This study aimed to compare the efficacy of triplet and standard doublet chemotherapy in a real-world setting. Methods: Patients with advanced BTC treated with triplet and doublet chemotherapy regimens were recruited. The propensity-score nearest neighbor matching method with a ratio of oneto-one was used to create a matched cohort for comparison. Progression-free survival (PFS), overall survival (OS), and safety profiles were examined in both groups. Results: A total of 68 patients (n=34 per group) were included in the matched cohort, and their baseline characteristics were well balanced. Survival outcomes in the triplet chemotherapy group were not better than those in the doublet chemotherapy group, with a median PFS of 7.5 months (95% confidence interval [CI], 4.1 to 10.9) versus 7.2 months (95% CI, 5.6 to 8.9) (hazard ratio [HR], 0.93; 95% CI, 0.53 to 1.62; p=0.793) and a median OS of 13.7 months (95% CI, 8.8 to 18.7) versus 12.2 months (95% CI, 8.4 to 16.0) (HR 0.73; 95% CI, 0.38 to 1.41; p=0.354), respectively. In addition, the treatment-related severe adverse events, such as neutropenia, were more common in the triplet chemotherapy group. Conclusions Gemcitabine, cisplatin, and nab-paclitaxel did not improve the PFS or OS compared to that achieved by standard chemotherapy in patients with advanced BTC. The benefits of triplet chemotherapy in advanced BTC require examination in large randomized controlled trials.

No abstract available.
Aortic Valve

BACKGROUND: Alopecia areata (AA), a chronic, relapsing hair-loss disorder, is considered to be a T-cell-mediated autoimmune disease. Cold-inducible RNA-binding protein (CIRP) belongs to a family of cold-shock proteins that respond to cold stress, and has been identified as a damage-associated molecular pattern (DAMP) molecule that triggers the inflammatory response. Recent studies have shown that high-mobility group box 1, another DAMP molecule, is elevated in serum and scalp tissue of AA patients, suggesting a relationship between DAMP molecules and the pathogenesis of AA. OBJECTIVE: To investigate the clinical significance of serum CIRP levels in AA. METHODS: The serum levels of CIRP were compared between 68 patients with AA and 20 healthy controls. Additionally, the correlation between CIRP level and various clinical parameters was evaluated. RESULTS: The serum CIRP levels were significantly higher in AA patients compared to healthy subjects. Moreover, there was an association between the serum CIRP level and clinical characteristics, such as disease duration and disease activity. However, there was no significant difference in the serum CIRP level among the clinical types of AA (AA multiplex, alopecia totalis, and alopecia universalis). CONCLUSION: These results suggest that CIRP may play a significant role in the pathogenesis of AA and could be a potential biologic marker for monitoring the disease activity of AA.
Alopecia Areata ; Alopecia ; Autoimmune Diseases ; Biomarkers ; Healthy Volunteers ; Humans ; Inflammation ; RNA-Binding Proteins ; Scalp