Background: Liver fibrosis is an early stage of liver cirrhosis. As a reversible lesion before cirrhosis, liver failure, and liver cancer, it has been a target for drug discovery. Many antifibrotic candidates have shown promising results in experimental animal models; however, due to adverse clinical reactions, most antifibrotic agents are still preclinical. Therefore, rodent models have been used to examine the histopathological differences between the control and treatment groups to evaluate the efficacy of anti-fibrotic agents in non-clinical research. In addition, with improvements in digital image analysis incorporating artificial intelligence (AI), a few researchers have developed an automated quantification of fibrosis. However, the performance of multiple deep learning algorithms for the optimal quantification of hepatic fibrosis has not been evaluated. Here, we investigated three different localization algorithms, mask R-CNN, DeepLabV3+, and SSD, to detect hepatic fibrosis. Results: 5750 images with 7503 annotations were trained using the three algorithms, and the model performance was evaluated in large-scale images and compared to the training images. The results showed that the precision values were comparable among the algorithms. However, there was a gap in the recall, leading to a difference in model accuracy. The mask R-CNN outperformed the recall value (0.93) and showed the closest prediction results to the annotation for detecting hepatic fibrosis among the algorithms. DeepLabV3+ also showed good performance; however, it had limitations in the misprediction of hepatic fibrosis as inflammatory cells and connective tissue. The trained SSD showed the lowest performance and was limited in predicting hepatic fibrosis compared to the other algorithms because of its low recall value (0.75). Conclusions We suggest it would be a more useful tool to apply segmentation algorithms in implementing AI algorithms to predict hepatic fibrosis in non-clinical studies.

Purpose: Various clinical practice guidelines recommend at least 12 regional lymph nodes should be removed for resected colon cancer. According to a recent study, the lymph node yield (LNY) in colon cancer surgery in the last 20 years has tended to increase from 14.91 to 21.30. However, it is unclear whether these guidelines adequately reflect recent findings on the number of harvested lymph nodes in colon cancer surgery. The aim of this study is to assess the impact of an LNY of more than 25 on survival in right-sided colon cancer. Methods: We included 285 patients who underwent a right hemicolectomy during the period from January 2010 through December 2015. Patients were divided into two groups (<25 nodes and ≥25 nodes). Primary endpoints included 5-year and 10-year survival including disease-free and overall. Results: We found that survival outcomes of patients with a harvest of ≥25 nodes were not significantly different compared with a <25 group. Large tumor size (5 cm) is significantly associated with poor 5-year and 10-year overall survival. Conclusion Survival outcomes of patients with a harvest of ≥25 nodes were not significantly different compared with the <25 group in stage II colon cancer with no risk.

Background: Many studies have reported injury characteristics of individual traumatic situations. However, a comparative analysis of specific risks is meaningful to better understand injury characteristics and help establish injury-prevention measures. This study was conducted to investigate and compare injury characteristics in children and adolescents by various outdoor traumatic situations. Methods: Outdoor traumatic situations were determined and classified into physical activity-related injury (n = 3,983) and pedestrian (n = 784) and passenger (n = 1,757) injuries in traffic accidents. Home injury (n = 16,121) was used as the control group. Then, the characteristics of each outdoor trauma were compared with 1:1 matched indoor trauma (among home injuries); each outdoor traumatic situation’s predisposing risk for the injured body part, injury type, and injury severity were analyzed; and changes by age of frequency ranking among physical activity-related injuries were investigated. Results: Outdoor trauma showed higher risks for limb injuries (injured body part), fracture and muscle/tendon injuries (injury type), and severe injuries (severity) than indoor trauma. Various outdoor traumatic situations presented different predisposing effects on injury characteristics. Among physical activity-related injuries, bicycle injury was commonest across all ages, and playing activities were common causes for injury for individuals of age < 9 years, whereas sports activities overwhelmed the common causes thereafter. Conclusions The findings would help to better understand the specific injury risk of various outdoor traumatic situations and may potentially facilitate the establishment of more effective injury-prevention measures.

Background: Many studies have reported injury characteristics of individual traumatic situations. However, a comparative analysis of specific risks is meaningful to better understand injury characteristics and help establish injury-prevention measures. This study was conducted to investigate and compare injury characteristics in children and adolescents by various outdoor traumatic situations. Methods: Outdoor traumatic situations were determined and classified into physical activity-related injury (n = 3,983) and pedestrian (n = 784) and passenger (n = 1,757) injuries in traffic accidents. Home injury (n = 16,121) was used as the control group. Then, the characteristics of each outdoor trauma were compared with 1:1 matched indoor trauma (among home injuries); each outdoor traumatic situation’s predisposing risk for the injured body part, injury type, and injury severity were analyzed; and changes by age of frequency ranking among physical activity-related injuries were investigated. Results: Outdoor trauma showed higher risks for limb injuries (injured body part), fracture and muscle/tendon injuries (injury type), and severe injuries (severity) than indoor trauma. Various outdoor traumatic situations presented different predisposing effects on injury characteristics. Among physical activity-related injuries, bicycle injury was commonest across all ages, and playing activities were common causes for injury for individuals of age < 9 years, whereas sports activities overwhelmed the common causes thereafter. Conclusions The findings would help to better understand the specific injury risk of various outdoor traumatic situations and may potentially facilitate the establishment of more effective injury-prevention measures.