Disease outbreaks pose serious threats to humans, as highlighted by the recent pandemic, underscoring the need for an institutionalized multi-sectoral approach like One Health, encompassing human, animal, and environmental health. One Health has demonstrated efficacy in addressing emerging issues such as antimicrobial resistance and zoonotic disease spillover. While integrating the human-animal sector has yielded positive outcomes, the majority of zoonotic spillovers originate from wildlife, emphasizing the crucial role of environmental surveillance within global One Health systems. Additionally, climate change intensifies the frequency and emergence of infectious diseases and spillover events. Tackling the complexity and interconnectedness of health challenges necessitates integrated solutions that incorporate broader structural factors, aiding in the prevention, detection, and mitigation of disease outbreaks. Embracing One Health through multi-sectoral preparedness can effectively confront the escalating threats of pandemics and other emerging diseases.

Disease outbreaks pose serious threats to humans, as highlighted by the recent pandemic, underscoring the need for an institutionalized multi-sectoral approach like One Health, encompassing human, animal, and environmental health. One Health has demonstrated efficacy in addressing emerging issues such as antimicrobial resistance and zoonotic disease spillover. While integrating the human-animal sector has yielded positive outcomes, the majority of zoonotic spillovers originate from wildlife, emphasizing the crucial role of environmental surveillance within global One Health systems. Additionally, climate change intensifies the frequency and emergence of infectious diseases and spillover events. Tackling the complexity and interconnectedness of health challenges necessitates integrated solutions that incorporate broader structural factors, aiding in the prevention, detection, and mitigation of disease outbreaks. Embracing One Health through multi-sectoral preparedness can effectively confront the escalating threats of pandemics and other emerging diseases.

Disease outbreaks pose serious threats to humans, as highlighted by the recent pandemic, underscoring the need for an institutionalized multi-sectoral approach like One Health, encompassing human, animal, and environmental health. One Health has demonstrated efficacy in addressing emerging issues such as antimicrobial resistance and zoonotic disease spillover. While integrating the human-animal sector has yielded positive outcomes, the majority of zoonotic spillovers originate from wildlife, emphasizing the crucial role of environmental surveillance within global One Health systems. Additionally, climate change intensifies the frequency and emergence of infectious diseases and spillover events. Tackling the complexity and interconnectedness of health challenges necessitates integrated solutions that incorporate broader structural factors, aiding in the prevention, detection, and mitigation of disease outbreaks. Embracing One Health through multi-sectoral preparedness can effectively confront the escalating threats of pandemics and other emerging diseases.

Disease outbreaks pose serious threats to humans, as highlighted by the recent pandemic, underscoring the need for an institutionalized multi-sectoral approach like One Health, encompassing human, animal, and environmental health. One Health has demonstrated efficacy in addressing emerging issues such as antimicrobial resistance and zoonotic disease spillover. While integrating the human-animal sector has yielded positive outcomes, the majority of zoonotic spillovers originate from wildlife, emphasizing the crucial role of environmental surveillance within global One Health systems. Additionally, climate change intensifies the frequency and emergence of infectious diseases and spillover events. Tackling the complexity and interconnectedness of health challenges necessitates integrated solutions that incorporate broader structural factors, aiding in the prevention, detection, and mitigation of disease outbreaks. Embracing One Health through multi-sectoral preparedness can effectively confront the escalating threats of pandemics and other emerging diseases.

Disease outbreaks pose serious threats to humans, as highlighted by the recent pandemic, underscoring the need for an institutionalized multi-sectoral approach like One Health, encompassing human, animal, and environmental health. One Health has demonstrated efficacy in addressing emerging issues such as antimicrobial resistance and zoonotic disease spillover. While integrating the human-animal sector has yielded positive outcomes, the majority of zoonotic spillovers originate from wildlife, emphasizing the crucial role of environmental surveillance within global One Health systems. Additionally, climate change intensifies the frequency and emergence of infectious diseases and spillover events. Tackling the complexity and interconnectedness of health challenges necessitates integrated solutions that incorporate broader structural factors, aiding in the prevention, detection, and mitigation of disease outbreaks. Embracing One Health through multi-sectoral preparedness can effectively confront the escalating threats of pandemics and other emerging diseases.

Background: The rapid economic development of South Korea provides a unique model to study changes in the clinical characteristics, treatment approaches, and clinical outcomes of patients with rheumatic mitral stenosis (MS) relative to socioeconomic growth. Methods: From the Multicenter mitrAl STEnosis with Rheumatic etiology (MASTER) registry, 2,337 patients diagnosed with moderate or severe rheumatic MS between January 2001 and December 2020 were analyzed. Patients were grouped into consecutive 5-year intervals based on their year of diagnosis. Clinical characteristics, echocardiographic data, and clinical outcomes were assessed. Results: Over 20 years, the severity of mitral stenosis increased from 79.1% to 90.2%; similarly, the average age at diagnosis increased from 54.3 to 63.0 years (all P < 0.001). Comorbidities such as hypertension and atrial fibrillation increased (6.3% to 29.5% and 41.4% to 46.9%, respectively; all P for trend < 0.05). The rate of mitral intervention within five years after diagnosis increased from 31.2% to 47.4% (P for trend < 0.001). However, clinical outcomes of rheumatic mitral stenosis deteriorated over time in the composite outcomes (log-rank test, P < 0.001). Conversely, the incidence of stroke remained stable (60.6–73.7%; P < 0.001), which might be attributed to the increased use of anticoagulation therapy. Conclusion This study observed an increase in patient age, comorbidities, and valve disease severity as the country transitioned from a developing to developed status. Despite a rise in mitral valve interventions, clinical outcomes deteriorated over 20 years, highlighting the need for modified treatment approaches to improve patient outcomes.

Purpose: The use of two adjacent radiation beams to treat a lesion that is larger than the maximum field of a machine may lead to higher or lower dose distribution at the junction than expected. Therefore, evaluation of the junction dose is crucial for radiotherapy. Volumetric modulated arc therapy (VMAT) can effectively protect surrounding normal tissues by implementing a complex dose distribution; therefore, two adjacent VMAT fields can effectively treat large lesions. However, VMAT can lead to significant errors in the junction dose between fields if setup errors occur due to its highly complex dose distributions. Methods: In this study, setup errors of ±1, ±3, and ±5 mm were assumed during radiotherapy for treating large lesions in the lower abdomen, and their effects on the treatment dose distribution and target coverage were analyzed using gamma pass rate (GP) and homogeneity index (HI). All studies were performed using a computational simulation method based on our radiation treatment planning software. Results: Consequently, when the setup error was more than ±3 mm, most GP values using a 3%/3-mm criterion decreased by <90%. GP was independent of the direction of the field gap (FG), whereas HI values were relatively more affected by negative values for FG. Conclusions Therefore, the size and direction of setup errors should be carefully managed when performing dual-isocentric VMATs for large targets.

Purpose: The use of two adjacent radiation beams to treat a lesion that is larger than the maximum field of a machine may lead to higher or lower dose distribution at the junction than expected. Therefore, evaluation of the junction dose is crucial for radiotherapy. Volumetric modulated arc therapy (VMAT) can effectively protect surrounding normal tissues by implementing a complex dose distribution; therefore, two adjacent VMAT fields can effectively treat large lesions. However, VMAT can lead to significant errors in the junction dose between fields if setup errors occur due to its highly complex dose distributions. Methods: In this study, setup errors of ±1, ±3, and ±5 mm were assumed during radiotherapy for treating large lesions in the lower abdomen, and their effects on the treatment dose distribution and target coverage were analyzed using gamma pass rate (GP) and homogeneity index (HI). All studies were performed using a computational simulation method based on our radiation treatment planning software. Results: Consequently, when the setup error was more than ±3 mm, most GP values using a 3%/3-mm criterion decreased by <90%. GP was independent of the direction of the field gap (FG), whereas HI values were relatively more affected by negative values for FG. Conclusions Therefore, the size and direction of setup errors should be carefully managed when performing dual-isocentric VMATs for large targets.

Purpose: The use of two adjacent radiation beams to treat a lesion that is larger than the maximum field of a machine may lead to higher or lower dose distribution at the junction than expected. Therefore, evaluation of the junction dose is crucial for radiotherapy. Volumetric modulated arc therapy (VMAT) can effectively protect surrounding normal tissues by implementing a complex dose distribution; therefore, two adjacent VMAT fields can effectively treat large lesions. However, VMAT can lead to significant errors in the junction dose between fields if setup errors occur due to its highly complex dose distributions. Methods: In this study, setup errors of ±1, ±3, and ±5 mm were assumed during radiotherapy for treating large lesions in the lower abdomen, and their effects on the treatment dose distribution and target coverage were analyzed using gamma pass rate (GP) and homogeneity index (HI). All studies were performed using a computational simulation method based on our radiation treatment planning software. Results: Consequently, when the setup error was more than ±3 mm, most GP values using a 3%/3-mm criterion decreased by <90%. GP was independent of the direction of the field gap (FG), whereas HI values were relatively more affected by negative values for FG. Conclusions Therefore, the size and direction of setup errors should be carefully managed when performing dual-isocentric VMATs for large targets.