Background and Objectives: Inconsistencies in nasal nitric oxide (nNO) values, due to anatomical variations and comorbidities, challenge the accurate assessment of upper airway inflammation severity. We hypothesized that changes in nNO levels following treatment for chronic rhinitis would be consistent and provide relative value. This study aimed to evaluate the correlation between changes in nNO levels and symptomatic improvements following treatment for chronic rhinitis. Methods: This prospective observational study included 46 participants diagnosed with chronic rhinitis between December 2021 and November 2023. nNO measurements, evaluations of four nasal and two ocular symptoms, and quality of life questionnaires were conducted at baseline and after one month of treatment. Baseline laboratory tests included serum total immunoglobulin E levels, blood eosinophil percentages, and skin prick tests. Results: The Total Nasal Symptom Score (TNSS), TNSS with ocular symptoms (TNSS eye), and Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) scores significantly decreased following treatment (all p<0.001). nNO levels also decreased significantly after treatment (p=0.036). Moreover, changes in nNO were significantly correlated with changes in TNSS, TNSS eye, and RQLQ scores (p=0.047, r=0.294; p=0.021, r=0.340; and p=0.004, r=0.419, respectively). Conclusion In patients with chronic rhinitis, changes in TNSS, TNSS eye, and RQLQ scores were correlated with changes in nNO levels after treatment. nNO may serve as a potential objective evaluation tool for chronic rhinitis, particularly in patients who have difficulty reporting symptoms.

Background and Objectives: Inconsistencies in nasal nitric oxide (nNO) values, due to anatomical variations and comorbidities, challenge the accurate assessment of upper airway inflammation severity. We hypothesized that changes in nNO levels following treatment for chronic rhinitis would be consistent and provide relative value. This study aimed to evaluate the correlation between changes in nNO levels and symptomatic improvements following treatment for chronic rhinitis. Methods: This prospective observational study included 46 participants diagnosed with chronic rhinitis between December 2021 and November 2023. nNO measurements, evaluations of four nasal and two ocular symptoms, and quality of life questionnaires were conducted at baseline and after one month of treatment. Baseline laboratory tests included serum total immunoglobulin E levels, blood eosinophil percentages, and skin prick tests. Results: The Total Nasal Symptom Score (TNSS), TNSS with ocular symptoms (TNSS eye), and Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) scores significantly decreased following treatment (all p<0.001). nNO levels also decreased significantly after treatment (p=0.036). Moreover, changes in nNO were significantly correlated with changes in TNSS, TNSS eye, and RQLQ scores (p=0.047, r=0.294; p=0.021, r=0.340; and p=0.004, r=0.419, respectively). Conclusion In patients with chronic rhinitis, changes in TNSS, TNSS eye, and RQLQ scores were correlated with changes in nNO levels after treatment. nNO may serve as a potential objective evaluation tool for chronic rhinitis, particularly in patients who have difficulty reporting symptoms.

Purpose: Prostate cancer ranks as the second most common cancer in men globally, representing a significant cause of cancer-related mortality. Metastasis, the spread of cancer cells from the primary site to distant organs, remains a major challenge in managing prostate cancer. Pyruvate dehydrogenase kinase 4 (PDK4) is implicated in the regulation of aerobic glycolysis, emerging as a potential player in various cancers. However, its role in prostate cancer remains unclear. This study aims to analyze PDK4 expression in prostate cancer cells and human samples, and to explore the gene's clinical significance. Materials and Methods: PDK4 expression was detected in cell lines and human tissue samples. Migration ability was analyzed using Matrigel-coated invasion chambers. Human samples were obtained from the Kyungpook National University Chilgok Hospital. Results: PDK4 expression was elevated in prostate cancer cell lines compared to normal prostate cells, with particularly high levels in DU145 and LnCap cell lines. PDK4 knockdown in these cell lines suppressed their invasion ability, indicating a potential role of PDK4 in prostate cancer metastasis. Furthermore, our results revealed alterations in epithelial-mesenchymal transition markers and downstream signaling molecules following PDK4 suppression, suggesting its involvement in the modulation of invasion-related pathways. Furthermore, PDK4 expression was increased in prostate cancer tissues, especially in castration-resistant prostate cancer, compared to normal prostate tissues, with PSA and PDK4 expression showing a significantly positive correlation. Conclusions PDK4 expression in prostate cancer is associated with tumor invasion and castration status. Further validation is needed to demonstrate its effectiveness as a therapeutic target.

Background and Objectives: Inconsistencies in nasal nitric oxide (nNO) values, due to anatomical variations and comorbidities, challenge the accurate assessment of upper airway inflammation severity. We hypothesized that changes in nNO levels following treatment for chronic rhinitis would be consistent and provide relative value. This study aimed to evaluate the correlation between changes in nNO levels and symptomatic improvements following treatment for chronic rhinitis. Methods: This prospective observational study included 46 participants diagnosed with chronic rhinitis between December 2021 and November 2023. nNO measurements, evaluations of four nasal and two ocular symptoms, and quality of life questionnaires were conducted at baseline and after one month of treatment. Baseline laboratory tests included serum total immunoglobulin E levels, blood eosinophil percentages, and skin prick tests. Results: The Total Nasal Symptom Score (TNSS), TNSS with ocular symptoms (TNSS eye), and Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) scores significantly decreased following treatment (all p<0.001). nNO levels also decreased significantly after treatment (p=0.036). Moreover, changes in nNO were significantly correlated with changes in TNSS, TNSS eye, and RQLQ scores (p=0.047, r=0.294; p=0.021, r=0.340; and p=0.004, r=0.419, respectively). Conclusion In patients with chronic rhinitis, changes in TNSS, TNSS eye, and RQLQ scores were correlated with changes in nNO levels after treatment. nNO may serve as a potential objective evaluation tool for chronic rhinitis, particularly in patients who have difficulty reporting symptoms.

Objectives: . Microorganisms are likely present in continuous positive airway pressure (CPAP) devices in daily use. Given the potential risk of infection among CPAP users, we aimed to compare the microbiomes of CPAP devices with those of nasal mucosa samples obtained from patients using these devices. Methods: . We conducted a prospective cohort study at multiple tertiary medical institutions. Samples were collected from the tubes and filters of CPAP devices and the nasal mucosa of device users. Microbiomes and mycobiomes were analyzed using 16S ribosomal RNA and internal transcribed spacer region sequencing. The results were compared according to sampling site and usage duration for each patient. Results: . Overall, 27 paired samples of human nasal mucosa and CPAP components were analyzed. Bacteria were detected in 7 of the 27 tubes (25.9%) and in 22 of the 27 filters (81.5%). Fungi were found in 2 tubes (7.4%) and 16 filters (59.3%). The most prevalent bacterial phyla across all samples were Actinobacteria and Firmicutes. Fungi were not detected in any nasal mucosa samples. However, fungi were identified in the CPAP filters and tubes, with the Basidiomycota and Ascomycota phyla predominating. No significant associations were identified according to sampling site or duration of CPAP use. Conclusion . Some bacteria or fungi are detectable in CPAP samples, even after a short period of CPAP usage. However, the association between respiratory infections and these microbiomes or mycobiomes was not investigated. Further research is required to clarify the risk posed by CPAP devices as a microbial contamination source.

Objective: To investigate whether reader training improves the performance and agreement of radiologists in interpreting unenhanced breast magnetic resonance imaging (MRI) scans using diffusion-weighted imaging (DWI). Materials and Methods: A study of 96 breasts (35 cancers, 24 benign, and 37 negative) in 48 asymptomatic women was performed between June 2019 and October 2020. High-resolution DWI with b-values of 0, 800, and 1200 sec/mm 2 was performed using a 3.0-T system. Sixteen breast radiologists independently reviewed the DWI, apparent diffusion coefficient maps, and T1-weighted MRI scans and recorded the Breast Imaging Reporting and Data System (BI-RADS) category for each breast. After a 2-h training session and a 5-month washout period, they re-evaluated the BI-RADS categories. A BI-RADS category of 4 (lesions with at least two suspicious criteria) or 5 (more than two suspicious criteria) was considered positive.The per-breast diagnostic performance of each reader was compared between the first and second reviews. Inter-reader agreement was evaluated using a multi-rater κ analysis and intraclass correlation coefficient (ICC). Results: Before training, the mean sensitivity, specificity, and accuracy of the 16 readers were 70.7% (95% confidence interval [CI]: 59.4–79.9), 90.8% (95% CI: 85.6–94.2), and 83.5% (95% CI: 78.6–87.4), respectively. After training, significant improvements in specificity (95.2%; 95% CI: 90.8–97.5; P = 0.001) and accuracy (85.9%; 95% CI: 80.9–89.8; P = 0.01) were observed, but no difference in sensitivity (69.8%; 95% CI: 58.1–79.4; P = 0.58) was observed. Regarding inter-reader agreement, the κ values were 0.57 (95% CI: 0.52–0.63) before training and 0.68 (95% CI: 0.62–0.74) after training, with a difference of 0.11 (95% CI: 0.02–0.18; P = 0.01). The ICC was 0.73 (95% CI: 0.69–0.74) before training and 0.79 (95% CI: 0.76–0.80) after training (P = 0.002). Conclusion Brief reader training improved the performance and agreement of interpretations by breast radiologists using unenhanced MRI with DWI.

Objective: The purpose of this study was to identify the associations of chronic physical disease between patients with severe mental illness (SMI) and the general population of South Korea. Methods: This study was conducted with National Health Insurance Corporation data from 2014 to 2019. A total of 848,058 people were diagnosed with SMI in this period, and the same number of controls were established by matching by sex and age. A descriptive analysis was conducted on the sociodemographic characteristics of patients with SMI. Conditional logistic regression analysis was performed to identify the associations between comorbid physical disease in patients with SMI and those of the general population. SAS Enterprise Guide 7.1 (SAS Inc, Cary, NC, USA) were used to perform all statistical tests. Results: The analysis revealed significant differences in medical insurance, income level, and Charlson Comorbidity Index weighted by chronic physical disease, between patients with SMI and the general population. Conditional logistic regression analysis between the two groups also revealed significant differences in eight chronic physical diseases except hypertensive disease. Conclusion This study confirmed the vulnerability of patients with SMI to chronic physical diseases and we were able to identify chronic physical disease that were highly related to patients with SMI.

Background/Aims: To compare the effects of abatacept and conventional synthetic disease modifying anti-rheumatic drugs (csDMARDs) on the progression and development of rheumatoid arthritis-associated interstitial lung disease (RA-ILD). Methods: This multi-center retrospective study included RA patients receiving abatacept or csDMARDs who underwent at least two pulmonary function tests and/or chest high-resolution computed tomography (HRCT). We compared the following outcomes between the groups: progression of RA-ILD, development of new ILD in RA patients without ILD at baseline, 28-joint Disease Activity Score with the erythrocyte sedimentation rate (DAS28-ESR), and safety. Longitudinal changes were compared between the groups by using a generalized estimating equation. Results: The study included 123 patients who were treated with abatacept (n = 59) or csDMARDs (n = 64). Nineteen (32.2%) and 38 (59.4%) patients treated with abatacept and csDMARDs, respectively, presented with RA-ILD at baseline. Newly developed ILD occurred in one patient receiving triple csDMARDs for 32 months. Among patients with RA-ILD at baseline, ILD progressed in 21.1% of cases treated with abatacept and 34.2% of cases treated with csDMARDs during a median 21-month follow-up. Longitudinal changes in forced vital capacity and diffusing capacity for carbon monoxide were comparable between the two groups. However, the abatacept group showed a more significant decrease in DAS28-ESR and glucocorticoid doses than csDMARDs group during the follow-up. The safety of both regimens was comparable. Conclusions Abatacept and csDMARDs showed comparable effects on the development and stabilization of RA-ILD. Nevertheless, compared to csDMARDs, abatacept demonstrated a significant improvement in disease activity and led to reduced glucocorticoid use.

Objectives: . Microorganisms are likely present in continuous positive airway pressure (CPAP) devices in daily use. Given the potential risk of infection among CPAP users, we aimed to compare the microbiomes of CPAP devices with those of nasal mucosa samples obtained from patients using these devices. Methods: . We conducted a prospective cohort study at multiple tertiary medical institutions. Samples were collected from the tubes and filters of CPAP devices and the nasal mucosa of device users. Microbiomes and mycobiomes were analyzed using 16S ribosomal RNA and internal transcribed spacer region sequencing. The results were compared according to sampling site and usage duration for each patient. Results: . Overall, 27 paired samples of human nasal mucosa and CPAP components were analyzed. Bacteria were detected in 7 of the 27 tubes (25.9%) and in 22 of the 27 filters (81.5%). Fungi were found in 2 tubes (7.4%) and 16 filters (59.3%). The most prevalent bacterial phyla across all samples were Actinobacteria and Firmicutes. Fungi were not detected in any nasal mucosa samples. However, fungi were identified in the CPAP filters and tubes, with the Basidiomycota and Ascomycota phyla predominating. No significant associations were identified according to sampling site or duration of CPAP use. Conclusion . Some bacteria or fungi are detectable in CPAP samples, even after a short period of CPAP usage. However, the association between respiratory infections and these microbiomes or mycobiomes was not investigated. Further research is required to clarify the risk posed by CPAP devices as a microbial contamination source.

Objectives: . Microorganisms are likely present in continuous positive airway pressure (CPAP) devices in daily use. Given the potential risk of infection among CPAP users, we aimed to compare the microbiomes of CPAP devices with those of nasal mucosa samples obtained from patients using these devices. Methods: . We conducted a prospective cohort study at multiple tertiary medical institutions. Samples were collected from the tubes and filters of CPAP devices and the nasal mucosa of device users. Microbiomes and mycobiomes were analyzed using 16S ribosomal RNA and internal transcribed spacer region sequencing. The results were compared according to sampling site and usage duration for each patient. Results: . Overall, 27 paired samples of human nasal mucosa and CPAP components were analyzed. Bacteria were detected in 7 of the 27 tubes (25.9%) and in 22 of the 27 filters (81.5%). Fungi were found in 2 tubes (7.4%) and 16 filters (59.3%). The most prevalent bacterial phyla across all samples were Actinobacteria and Firmicutes. Fungi were not detected in any nasal mucosa samples. However, fungi were identified in the CPAP filters and tubes, with the Basidiomycota and Ascomycota phyla predominating. No significant associations were identified according to sampling site or duration of CPAP use. Conclusion . Some bacteria or fungi are detectable in CPAP samples, even after a short period of CPAP usage. However, the association between respiratory infections and these microbiomes or mycobiomes was not investigated. Further research is required to clarify the risk posed by CPAP devices as a microbial contamination source.