Echinochrome A (Ech A) isolated from marine organisms is a therapeutic effector for various cardiovascular diseases, but its precise mechanisms are unclear.This study identified the role and mechanisms mediating the effects of Ech A on the migration of vascular smooth muscle cells (VSMCs) induced by high-mobility group box 1 (HMGB1). Compared to the control cells, the migration of VSMCs stimulated with HMGB1 (100 ng/ml) was markedly increased, which was significantly attenuated in cells pretreated with MPIIIB10 (100 ng/ml), a neutralizing monoclonal antibody for osteopontin (OPN). In VSMCs stimulated with HMGB1, the increased expression of OPN mRNA and protein was accompanied by an increased OPN promoter activity. In reporter gene assays using OPN promoter-luciferase constructs, the promoter region 538-234 bp of the transcription start site containing the binding sites for activator protein 1 (AP-1) was shown to be responsible for the increased transcriptional activity by HMGB1. In addition, the binding activity of AP-1 was increased in HMGB1-stimulated cells, highlighting the pivotal role of AP-1 on OPN expression in HMGB1-stimulated VSMCs. An examination of the vascular effects of Ech A showed that the increased AP-1 binding/promoter activities and OPN expression induced by HMGB1 were attenuated in cells pretreated with Ech A (3 or 10 μM). Similarly, Ech A inhibited HMGB1-induced VSMC migration in a concentration-dependent manner. These findings suggest that Ech A inhibits VSMC migration by suppressing OPN expression.Hence, Ech A is suggested as a potential therapeutic strategy for vascular remodeling in the injured vasculatures.

Purpose: This study aimed to explore the effects of both the presence and size of posterior subependymal germinal matrix hemorrhage (PS-GMH), considered a mild form of hemorrhage, on the neurodevelopmental outcomes of extremely preterm infants. Methods: A retrospective analysis was conducted on 221 extremely preterm infants, assessing their initial and term-equivalent age (TEA) cranial ultrasound (cUS) examinations from 2016 to 2021. Infants were classified based on the presence and size (small/large) of PS-GMH. Neurodevelopmental outcomes at corrected ages of 18-24 months were analyzed in 135 infants. Results: PS-GMH was identified in 86.9% (192/221) of the infants, with 13.5% (26/192) exhibiting large PS-GMH. Among the 135 infants who were followed up, those with PS-GMH were found to have younger gestational ages (P<0.001) and a higher incidence of maternal chorioamnionitis (P=0.016) than those without PS-GMH. Significant differences were observed in the incidence of grade II intraventricular hemorrhage (IVH) on initial cUS (P=0.003) and ventriculomegaly at TEA cUS (P=0.026) across the groups with no PS-GMH, small PS-GMH, and large PS-GMH. The large PS-GMH group exhibited a higher occurrence of grade II IVH than the small PS-GMH group (P=0.006). However, ventriculomegaly incidence did not significantly vary with PS-GMH status. Neurodevelopmental outcomes were also not significantly different across PS-GMH statuses. The adjusted odds ratios for any neurodevelopmental impairment, compared to the no PS-GMH group, were 1.70 (95% confidence interval [CI], 0.40 to 7.26; P=0.471) for all PS-GMH, 1.61 (95% CI, 0.37 to 6.93; P=0.526) for small PS-GMH, and 3.84 (95% CI, 0.62 to 24.00; P=0.150) for large PS-GMH. Conclusion PS-GMH was frequently observed in extremely preterm infants; however, it did not independently predict adverse neurodevelopmental outcomes.

Purpose: This study aimed to evaluate the prognosis of the not evaluated (NE) group by comparing it with the lost to follow-up (LTFU) group among patients with multidrug/rifampin-resistant tuberculosis (MDR/RR-TB). Materials and Methods: This was a retrospective longitudinal follow-up study using an integrated database constructed by data linkage of the three national databases. This database included 7226 cases of MDR/RR-TB notified between 2011 and 2017 in South Korea. Results: Among the 7226 MDR/RR-TB cases, 730 (10.1%) were classified as LTFU group, and 353 (4.9%) as NE group. When comparing NE group with LTFU group, there were no significant differences in the all-cause mortality rate (18.1% vs. 13.8%, p=0.065), median time to death [404 days (interquartile range, IQR 46–850) vs. 443 days (IQR 185–1157), p=0.140], and retreatment rate (26.9% vs.22.2%, p=0.090). After adjusting for potential confounders, the adjusted hazard ratio (aHR) for all-cause mortality (aHR 1.11; 95% confidence interval 0.80-1.53; p=0.531) in NE group was not significantly different than that in LTFU group. Among retreated cases, NE group had a higher treatment success rate (57.9% vs 43.8%, p=0.029) and a lower LTFU rate (11.6% vs 38.3%, p<0.001) compared to LTFU group. Conclusion NE group had an unfavorable outcome comparable to LTFU group, suggesting undetected cases of LTFU or deaths during the referral process. Establishing an efficient patient referral system would contribute to reducing the incidence of NE cases.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Purpose: Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS. Materials and Methods: This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches. Results: TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making. Conclusion TE-WGS is a comprehensive approach in personalized oncology, matching TSO500’s key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: This study aims to understand the structure of meaning in life among patients with cancer through the validation of the Meaning in Life Scale among Korean patients (K-MiLS) with cancer. Methods: From August 2021 to November 2022, participants were recruited from multiple sites in South Korea. Participants completed related questionnaires, including the MiLS, on the web or mobile. Test-retest reliability was assessed between 2 and 4 weeks after the initial assessment. Exploratory and confirmatory factor analyses and Pearson’s correlations were used to evaluate the reliability and validity of the MiLS. A multiple regression analysis was conducted to examine the sociodemographic and disease-related variables correlated with the MiLS. Regarding concurrent validity, a hierarchical regression analysis was performed. Results: The results (n=345) indicated that the K-MiLS has a four-factor structure: Harmony and Peace; Life Perspective, Purpose, and Goals; Confusion and Lessened Meaning; and Benefits of Spirituality. Regarding convergent and discriminant validity, K-MiLS was negatively correlated with Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Fear of Cancer Recurrence Inventory while showing a significantly positive correlation with the Posttraumatic Growth Inventory, Self-Compassion Scale, Functional Assessment of Cancer Therapy-General, and Functional Social Support Questionnaire. Hierarchical regression analysis revealed that the demographic variable influencing MiLS was religious affiliation. Conclusion The K-MiLS had a multidimensional four-factor structure similar to that of the original version. It is also a reliable and valid measure for assessing cancer survivors’ meaning in life after a cancer diagnosis.

Echinochrome A (Ech A) isolated from marine organisms is a therapeutic effector for various cardiovascular diseases, but its precise mechanisms are unclear.This study identified the role and mechanisms mediating the effects of Ech A on the migration of vascular smooth muscle cells (VSMCs) induced by high-mobility group box 1 (HMGB1). Compared to the control cells, the migration of VSMCs stimulated with HMGB1 (100 ng/ml) was markedly increased, which was significantly attenuated in cells pretreated with MPIIIB10 (100 ng/ml), a neutralizing monoclonal antibody for osteopontin (OPN). In VSMCs stimulated with HMGB1, the increased expression of OPN mRNA and protein was accompanied by an increased OPN promoter activity. In reporter gene assays using OPN promoter-luciferase constructs, the promoter region 538-234 bp of the transcription start site containing the binding sites for activator protein 1 (AP-1) was shown to be responsible for the increased transcriptional activity by HMGB1. In addition, the binding activity of AP-1 was increased in HMGB1-stimulated cells, highlighting the pivotal role of AP-1 on OPN expression in HMGB1-stimulated VSMCs. An examination of the vascular effects of Ech A showed that the increased AP-1 binding/promoter activities and OPN expression induced by HMGB1 were attenuated in cells pretreated with Ech A (3 or 10 μM). Similarly, Ech A inhibited HMGB1-induced VSMC migration in a concentration-dependent manner. These findings suggest that Ech A inhibits VSMC migration by suppressing OPN expression.Hence, Ech A is suggested as a potential therapeutic strategy for vascular remodeling in the injured vasculatures.