Phosphoinositide 3-kinase (PI3K)-δ-dependent Akt activation is known to play critical roles in various immune responses of white blood cells in which PI3K-δ isoform is mostly expressed in contrast to the classes IA PI3Ks p110α and p110β. However, the immunological role of PI3K-δ isoform is still controversial in airway epithelium under house dust mite (HDM)-induced allergic response. This study aimed to evaluate the role of PI3K-δ isoform in HDM-induced allergic responses, focusing on NLRP3 inflammasome activation in airway epithelium. We used wild-type mice and PI3K-δ knock-out (KO) mice for HDM-induced asthma animal model and also performed in vitro experiments using primary cultured murine tracheal epithelial cells and human airway epithelial cells. PI3K-δ activated HDM-induced NLRP3 inflammasome and epithelial cell-derived cytokines in the lung including airway epithelial cells. PI3K-δ KO mice or knock-down of PI3K-δ using siRNA exhibited the significant reduction in allergic asthmatic features and the suppression of NLRP3 inflammasome assembly as well as epithelial cell-derived cytokines. Interestingly, significantly increased expression of PI3K-δ isoform was observed in stimulated airway epithelial cells and the increases in epithelial cell-derived cytokines were markedly suppressed by blocking PI3K-δ, while these cytokine levels were independent of NLRP3 inflammasome activation. The results of this study suggest that PI3K-δ-isoform can promote HDM-induced allergic airway inflammation via NLRP3 inflammasome-dependent response as well as via NLRP3 inflammasome-independent epithelial cell activation.

This study aimed to develop a large language model (LLM) chatbot for radiation therapy education and compare the performance of portable document format (PDF)- and webpage-based question-and-answer (Q&A) chatbots. An LLM chatbot was created using the EmbedChain framework, OpenAI GPT-3.5-Turbo API, and Gradio UI. The performance of both chatbots was evaluated based on 10 questions and their corresponding answers, using the parameters of accuracy, semantic similarity, consistency, and response time. The accuracy scores were 0.672 and 0.675 for the PDF- and webpage-based Q&A chatbots, respectively. The semantic similarity between the two chatbots was 0.928 (92.8%). The consistency score was one for both chatbots. The average response time was 3.3 s and 2.38 s for the PDF- and webpage-based chatbots, respectively. The LLM chatbot developed in this study demonstrates the potential to provide reliable responses for radiation therapy education. However, its reliability and efficiency must be further optimized to be effectively utilized as an educational tool.

Background: MRI safety management is essential for patient safety and for standardizing institutional practices. However, nationwide data on MRI safety readiness in Korean tertiary hospitals remain limited. Purpose: To evaluate MRI safety management across all 47 Korean tertiary hospitals and identify major gaps in safety infrastructure, staffing, and education. Study Type: Cross‐sectional census survey. Population: MRI safety managers from all 47 Korean tertiary hospitals in 2025. Assessment: A structured 50‐item questionnaire was developed based on the American College of Radiology (ACR) MRI safety guidelines. A composite safety maturity index (0–100) was calculated as the unweighted arithmetic mean of four domain scores derived from 32 binary safety‐practice items, with mandatory items weighted 2 and recommended items weighted 1 in accordance with the 2024 ACR Manual on MR Safety. Statistical Tests: Descriptive statistics were used to summarize institutional characteristics and safety compliance. Comparisons of staffing patterns by time period were evaluated using inferential tests, with statistical significance set at p < 0.05. Results: The response rate was 100% (47/47). The mean number of MRI units per hospital was 5.32 ± 3.50, and 3.0 T systems were predominant. Compliance was universal for closed‐circuit television (CCTV) monitoring and MR Conditional monitoring devices but was low for ferromagnetic detection systems (17.0%), Magnetic Resonance Safety Officer (MRSO) appointment (17.0%), and Level 1 safety education (23.4%). MRI‐related safety incidents were reported by 44.7% of hospitals. Two‐person staffing decreased significantly from 97.9% on weekday daytime hours to 55.3% on Saturdays, 44.7% at night, and 38.3% on holidays. The overall composite safety maturity score was 63.08 ± 15.04. Data Conclusion: Considerable variability remains in MRI safety management across Korean tertiary hospitals. These findings highlight the need for national MRI safety standards in the Republic of Korea. Evidence Level: 4. Technical Efficacy: Stage 4.