Purpose: This study aimed to explore the practices, perceptions, and barriers related to specialty palliative care (SPC) referrals among oncologists in Korea, highlighting the clinical implications of early integration. Materials and Methods: A cross-sectional online survey targeting board-certified hemato-oncology specialists was conducted between August 1-25, 2024. The survey assessed referral practices, attitudes toward early SPC integration, referral criteria, barriers, and institutional characteristics. Results: A total of 227 oncologists participated (response rate, 36.7%). Among them, 68.7% reported frequent SPC referrals, with higher referral rates observed among younger physicians, those in tertiary hospitals, and institutions with in-house SPC teams (p < 0.001). Although 74.9% supported early SPC integration, referrals were often inconsistently timed, frequently occurring after disease progression or at the discontinuation of chemotherapy. For time-based referrals, the most commonly endorsed triggers were disease progression despite palliative second-line treatment and a prognosis of expected mortality within 6-12 months. Need-based referral triggers such as patient or family requests (96.5%), psychological distress (89.9%), or uncontrolled symptoms (83.3%), were also widely endorsed. The major barriers to early SPC integration included patient and family resistance (70.0%) and limited availability of SPC teams (34.4%). Conclusion This study emphasizes the importance of systematic efforts to promote timely SPC integration in Korea, including education to raise patient awareness, improved referral systems, and enhanced infrastructure. The positive attitudes toward early SPC among oncologists reflect a growing recognition of its value, highlighting the need for strategies that align with international standards.

Purpose: This study aimed to develop and implement an antimicrobial stewardship education program for physician assistant nurses and to evaluate its effects on their knowledge and clinical performance. Methods: A quasi-experimental, single-group pre-post design was conducted with 50 physician assistant nurses at a university hospital in Seoul, Republic of Korea. The antimicrobial stewardship education program, developed using the ADDIE model, consisted of 12 sessions including lectures and case-based learning (CBL)-based discussions.Knowledge was measured before and immediately after the intervention, while performance was assessed pre-intervention and four weeks post-program. Data were analyzed using paired t-tests, Wilcoxon signed-rank tests, and analysis of covariance (ANCOVA). Results: Knowledge scores significantly improved from 44.65±7.45 to 58.50±10.11 (p<.001), and all subdomains showed significant increases (p<.001). Performance scores increased from 3.68±0.77 to 4.28±0.68 (p<.001). Knowledge gain did not differ significantly between the medical and surgical departments (p=.710). Likewise, after adjusting for pre-test scores, no significant difference in performance improvement was observed between the two departments (ANCOVA, p=.170). These results indicate that the program was effective across both departments regardless of their characteristics. Conclusion The antimicrobial stewardship education program improved both knowledge and performance among physician assistant nurses. This program may contribute to the standardization of antimicrobial stewardship education and to appropriate antimicrobial use and the reduction of antimicrobial resistance.

Background: Sleep disorders and insomnia are prevalent worldwide, with negative health outcomes. The Pittsburgh Sleep Quality Index (PSQI) is a widely used self-report assessment tool for evaluating sleep quality, comprising seven subdomains. The Korean version of the PSQI (PSQI-K) has been tested for reliability and validity in small sample sizes but lacks large-scale validation using objective measures. Methods: This study was conducted with 268 Korean adults attending health check programs. Participants completed the PSQI-K questionnaire and wore Fitbit devices (Fitbit Inc., USA) to ascertain sleep parameters. Reliability was analyzed using the Cronbach’s α coefficient, and construct validity was determined through factor analysis. Criteria validity was assessed by correlating their index scores with Fitbit sleep parameters. We identified the optimal cutoff for detecting sleep disorders. Results: The Cronbach’s α coefficient was 0.61, indicating adequate internal consistency. Factor analysis revealed three factors, explaining 48.2% of sleep quality variance. The index scores were negatively correlated with Fitbit sleep efficiency, total sleep time, and number of awakenings (P<0.05). The optimal cutoff point for identifying sleep disorder groups was ≥6. Conclusion The PSQI-K demonstrated good reliability and validity when correlated with Fitbit sleep parameters, offering a practical screening tool for identifying sleep disorders among Korean adults. Cutoff scores can help identify patients for sleep interventions. However, further large-scale studies are required to validate these findings.

Angiosarcoma associated with lymphedema is a rare soft tissue malignancy that occurs owing to chronic lymphedema, primarily following breast cancer surgery. We present a case of an 83-year-old female who developed angiosarcoma 14 years after undergoing breast cancer surgery. Diagnosis was confirmed through excisional biopsy, histopathological evaluation, and imaging. Computed tomography and magnetic resonance imaging revealed diffuse dermal thickening with an enhanced subcutaneous nodular lesion on the right arm. This unusual case emphasizes the importance of vigilant monitoring in patients with chronic lymphedema post-breast cancer surgery, as early radiologic and clinical detection can facilitate timely intervention and improve outcomes.

Background: Sleep disorders and insomnia are prevalent worldwide, with negative health outcomes. The Pittsburgh Sleep Quality Index (PSQI) is a widely used self-report assessment tool for evaluating sleep quality, comprising seven subdomains. The Korean version of the PSQI (PSQI-K) has been tested for reliability and validity in small sample sizes but lacks large-scale validation using objective measures. Methods: This study was conducted with 268 Korean adults attending health check programs. Participants completed the PSQI-K questionnaire and wore Fitbit devices (Fitbit Inc., USA) to ascertain sleep parameters. Reliability was analyzed using the Cronbach’s α coefficient, and construct validity was determined through factor analysis. Criteria validity was assessed by correlating their index scores with Fitbit sleep parameters. We identified the optimal cutoff for detecting sleep disorders. Results: The Cronbach’s α coefficient was 0.61, indicating adequate internal consistency. Factor analysis revealed three factors, explaining 48.2% of sleep quality variance. The index scores were negatively correlated with Fitbit sleep efficiency, total sleep time, and number of awakenings (P<0.05). The optimal cutoff point for identifying sleep disorder groups was ≥6. Conclusion The PSQI-K demonstrated good reliability and validity when correlated with Fitbit sleep parameters, offering a practical screening tool for identifying sleep disorders among Korean adults. Cutoff scores can help identify patients for sleep interventions. However, further large-scale studies are required to validate these findings.

Mammography is the standard screening method for breast cancer, proven to reduce mortality. However, its diagnostic performance varies depending on patient characteristics and radiologist expertise. Dense breast tissue, present in approximately 70% of Korean women aged 40 to 59, limits detection by obscuring malignancies. Additionally, optimal interpretation requires extensive training, which is not always achievable. Artificial intelligence-based computer-aided diagnosis (AI-CAD) has emerged as a promising tool for enhancing mammographic accuracy and efficiency.Current Concepts: AI-CAD has shown diagnostic performance comparable to that of experienced radiologists while addressing the limitations of traditional CAD systems, particularly excessive false positives. Studies suggest AI-CAD improves radiologists' accuracy, particularly among those with limited breast imaging experience. In Europe, AI-assisted reading is increasingly recognized as a viable alternative to traditional double reading. In Korea, adoption of AI-CAD is expanding, with systems approved by the Korean Food and Drug Administration currently in clinical use. Recently, one AI-CAD system received conditional non-reimbursement designation, allowing hospitals to use it for up to 5 years while collecting clinical evidence to support future insurance coverage decisions.Discussion and Conclusion: AI-CAD has significant potential to enhance early breast cancer detection while maintaining acceptable false-positive rates, making it a valuable adjunct in screening programs. Beyond improved detection, AI-CAD may optimize workflow efficiency by triaging cases and prioritizing high-risk examinations. However, its integration into clinical practice necessitates standardized guidelines, regulatory oversight, and further validation through large-scale prospective studies. As AI technology continues to advance, ongoing investigation into its role in personalized breast cancer screening is essential.

Mammography is the standard screening method for breast cancer, proven to reduce mortality. However, its diagnostic performance varies depending on patient characteristics and radiologist expertise. Dense breast tissue, present in approximately 70% of Korean women aged 40 to 59, limits detection by obscuring malignancies. Additionally, optimal interpretation requires extensive training, which is not always achievable. Artificial intelligence-based computer-aided diagnosis (AI-CAD) has emerged as a promising tool for enhancing mammographic accuracy and efficiency.Current Concepts: AI-CAD has shown diagnostic performance comparable to that of experienced radiologists while addressing the limitations of traditional CAD systems, particularly excessive false positives. Studies suggest AI-CAD improves radiologists' accuracy, particularly among those with limited breast imaging experience. In Europe, AI-assisted reading is increasingly recognized as a viable alternative to traditional double reading. In Korea, adoption of AI-CAD is expanding, with systems approved by the Korean Food and Drug Administration currently in clinical use. Recently, one AI-CAD system received conditional non-reimbursement designation, allowing hospitals to use it for up to 5 years while collecting clinical evidence to support future insurance coverage decisions.Discussion and Conclusion: AI-CAD has significant potential to enhance early breast cancer detection while maintaining acceptable false-positive rates, making it a valuable adjunct in screening programs. Beyond improved detection, AI-CAD may optimize workflow efficiency by triaging cases and prioritizing high-risk examinations. However, its integration into clinical practice necessitates standardized guidelines, regulatory oversight, and further validation through large-scale prospective studies. As AI technology continues to advance, ongoing investigation into its role in personalized breast cancer screening is essential.

Background: Sleep disorders and insomnia are prevalent worldwide, with negative health outcomes. The Pittsburgh Sleep Quality Index (PSQI) is a widely used self-report assessment tool for evaluating sleep quality, comprising seven subdomains. The Korean version of the PSQI (PSQI-K) has been tested for reliability and validity in small sample sizes but lacks large-scale validation using objective measures. Methods: This study was conducted with 268 Korean adults attending health check programs. Participants completed the PSQI-K questionnaire and wore Fitbit devices (Fitbit Inc., USA) to ascertain sleep parameters. Reliability was analyzed using the Cronbach’s α coefficient, and construct validity was determined through factor analysis. Criteria validity was assessed by correlating their index scores with Fitbit sleep parameters. We identified the optimal cutoff for detecting sleep disorders. Results: The Cronbach’s α coefficient was 0.61, indicating adequate internal consistency. Factor analysis revealed three factors, explaining 48.2% of sleep quality variance. The index scores were negatively correlated with Fitbit sleep efficiency, total sleep time, and number of awakenings (P<0.05). The optimal cutoff point for identifying sleep disorder groups was ≥6. Conclusion The PSQI-K demonstrated good reliability and validity when correlated with Fitbit sleep parameters, offering a practical screening tool for identifying sleep disorders among Korean adults. Cutoff scores can help identify patients for sleep interventions. However, further large-scale studies are required to validate these findings.

Angiosarcoma associated with lymphedema is a rare soft tissue malignancy that occurs owing to chronic lymphedema, primarily following breast cancer surgery. We present a case of an 83-year-old female who developed angiosarcoma 14 years after undergoing breast cancer surgery. Diagnosis was confirmed through excisional biopsy, histopathological evaluation, and imaging. Computed tomography and magnetic resonance imaging revealed diffuse dermal thickening with an enhanced subcutaneous nodular lesion on the right arm. This unusual case emphasizes the importance of vigilant monitoring in patients with chronic lymphedema post-breast cancer surgery, as early radiologic and clinical detection can facilitate timely intervention and improve outcomes.

Positional information plays a crucial role in embryonic pattern formation, yet its role in tooth development remains unexplored. In this study, we investigated the regional specification of lingual and buccal dental mesenchyme during tooth development. Tooth germs at the cap stage were dissected from mouse mandibles, and their lingual and buccal mesenchymal regions were separated for bulk RNA sequencing. Gene ontology analysis revealed that odontogenesis, pattern specification, and proliferation-related genes were enriched in the lingual mesenchyme, whereas stem cell development, mesenchymal differentiation, neural crest differentiation, and regeneration-related genes were predominant in the buccal mesenchyme. Reaggregation experiments using Wnt1^creERT/+; R26R^tdT/+ and WT mouse models demonstrated that lingual mesenchyme contributes to tooth formation, while buccal mesenchyme primarily supports surrounding tissues. Furthermore, only the lingual part of tooth germs exhibited odontogenic potential when cultured in vitro and transplanted under the kidney capsule. Bulk RNA transcriptomic analysis further validated the regional specification of the lingual and buccal mesenchyme. These findings provide novel insights into the molecular basis of positional information in tooth development and pattern formation.
Animals ; Mice ; Odontogenesis/genetics* ; Tooth Germ/cytology* ; Mesoderm/cytology* ; Cell Differentiation ; Mesenchymal Stem Cells ; Tooth/embryology*