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Background/Objective: With intensifying air pollutant levels and the COVID-19 pandemic, physical inactivity of South Korean children and adolescents may be threatened. Therefore, monitoring and surveillance of physical activity (PA) and relevant indicators are important for policy making pertaining to health promotion. Report Card is a third comprehensive evaluation of PA-related behaviors among and the sources of influence for South Korean children and adolescents. Purpose: To provide the outcome of the South Korea's 2022 Report Card on PA for children and adolescents. Methods: Based on a variety of sources including national surveys collected pre- and during-COVID-19 and information collected from government webpages, 11 indicators were graded by a committee of experts informed by the best available evidence. Data from during-COVID-19 were available for Overall PA, Sedentary Behavior, and Sleep and considered together in generating the overall grades. Results: Grades were assigned to behavioral indicators (Overall PA: D-; Active Transportation: B+; Sedentary Behavior: D; Sleep: F) and sources of Influence (Family and Peers: C-; School: A; Community and Environment: B-; Government: A). Organized Sport and PA, Active Play, and Physical Fitness could not be graded due to the lack of data. The results largely indicated that children and adolescents show unfavorable behavioral grades even with favorable grades observed for the sources of influence indicators. Trivial differences were observed pre- and during-pandemic for Overall PA (≥60 min of MVPA for ≥4 d/wk: 20.8% vs 19.9%) and Sleep (met age-specific recommendation: 14.1% vs 15.0%); however, a marked increase in Sedentary Behavior was observed (≤2 h/d screen time: 28.8% vs 20.1%). A stark weekday vs weekend difference was observed in sleep duration. In terms of PA related sources of influence, high accessibility to PA facilities (81.1%) and high satisfaction of neighborhood public transit (74.6%) and safety (80.7%) were well reflected in our Active Transportation grade (B+). Nonetheless, perception of green environments including outdoor air quality (44.0%), noise (39.6%) and green space (56.5%) showed lower scores, suggesting that new barriers to active lifestyles are emerging for South Korean children and adolescents. Gender differences were also observed for overall PA (≥60 min of MVPA for ≥4 d/wk: 29.1% for boys vs 11.3% for girls) and sleep (met age-specific recommendations: 17.3% for boys vs 11.4% for girls), but not for sedentary behavior (≤2 h/d screen time: 26.4% for boys and 24.9% for girls). Conclusions: Government and school policies/programs and the built environment are, in general, conducive to physically active lifestyles for South Korean children and adolescents; however, behavioural indicators received poor grades except for Active Transportation. A thorough evaluation of policies/programs at government, local, and school levels is needed to ensure that the efforts to have PA-enhancing infrastructure and systems are actually being translated into the behavior of children and adolescents in South Korea. Furthermore, improving PA surveillance, monitoring, and advocacy to ultimately establish healthy lifestyle patterns among children and adolescents is a top priority.

High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes. The main hurdle in cancer genomics is to identify the real causative mutations or genes out of many candidates from an HGT-based cancer genomic analysis. One useful approach is to refer to known cancer genes and associated information. The list of known cancer genes can be used to determine candidates of cancer driver mutations, while cancer gene-related information, including gene expression, protein-protein interaction, and pathways, can be useful for scoring novel candidates. Some cancer gene or mutation databases exist for this purpose, but few specialized tools exist for an automated analysis of a long gene list from an HGT-based cancer genomic analysis. This report presents a new web-accessible bioinformatic tool, called CaGe, a cancer genome annotation system for the assessment of candidates of cancer genes from HGT-based cancer genomics. The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions. With this tool, researchers can classify their candidate genes from cancer genome studies into either previously reported or novel categories of cancer genes and gain insight into underlying carcinogenic mechanisms through a pathway analysis. We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.