Background: The exposome encompasses all factors people encounter through life, with the skin constantly exposed. While particulate matter (PM) and sleep deprivation are known to contribute to barrier dysfunction, their combined effects remain unclear. Objective: To evaluate the independent and combined effects of PM exposure and short-term sleep deprivation on skin barrier function. Methods: Forty healthy Korean women (aged 24–58 years) were enrolled in this study. Forearms were divided into 4 sites: control, PM exposure, sleep deprivation, and PM plus sleep deprivation. Parameters such as trans-epidermal water loss (TEWL), hydration, elasticity, roughness, and redness were measured at baseline and post-exposure. RNA sequencing and reverse transcription-polymerase chain reaction were conducted on tape-stripped skin samples. Results: PM exposure significantly increased TEWL (+25.59%, p<0.01), roughness (+21.9%, p<0.01), and redness (+13.7%, p<0.0001) while reducing elasticity (−3.98%, p<0.01). Sleep deprivation modestly reduced elasticity (−1.39%, p<0.05) without affecting other parameters.Combined PM and sleep deprivation did not further exacerbate barrier dysfunction compared to PM alone. RNA sequencing revealed reduced FLG and LORICRIN expression and upregulated endoplasmic reticulum (ER) stress markers (HSP90B1, CANX) in both PM and sleep deprivation conditions. Conclusion PM exposure impaired skin barrier function, while short-term sleep deprivation alone did not significantly affect the barrier, either independently or in combination with PM.However, it was observed that the sleep deprivation-only, while not directly causing barrier damage, induced changes in ER stress-related gene expression in tape-stripped skin samples, like the PM exposure-only. This suggests that such signaling pathways could potentially exacerbate skin barrier deterioration.

Background: An international reference measurement laboratory network for creatinine (Cr) is lacking; therefore, Korea developed an independent evaluation and certification system. The in vitro diagnostics (IVD) certification program, launched in 2017, formed part of a broader Cr standardization initiative intended to enhance accuracy at the manufacturing stage. Methods: The program was designed to evaluate analytical systems, including all reagent lots, calibrators, and instrument models, twice annually. Bias, imprecision, total error (TE), and linearity were evaluated based on established acceptance criteria. A post-certification process allows submission for a second challenge and validation of corrective actions. Results: Between 2017 and 2023, 489 analytical systems were evaluated. Average acceptance rates for bias, imprecision, TE, and linearity were 70.8%, 95.9%, 87.7%, and 87.8%, respectively. The lowest acceptance rate for bias evaluation was 8.7% for the kinetic Jaffe method without compensation in 2018. Over the 7-year period, the mean absolute percentage bias (absBias%), coefficient of variation (CV), and TE were 4.62%, 1.37%,and 7.29%, respectively. The highest absBias% (7.94%) was observed in the 0.0 ≤ Cr < 1.0target value range. Since 2019, a consistent reduction in absBias% has been observed. Conclusions This program is a pioneering response to the absence of a global certification program for Cr assays. It offers significant advantages, including comprehensive evaluations, fee-free participation, and a robust post-certification process. Continuous participation and improvement efforts by manufacturers have contributed to enhanced accuracy in Cr assays.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Purpose: This study aimed to develop a valid and reliable tool to measure awareness of well-dying among middle-aged adults. Methods: A mixed-methods approach was adopted, consisting of a qualitative phase to identify the characteristics of well-dying and a quantitative phase to validate the instrument with middle-aged participants. Initially, 76 items were generated through a literature review and in-depth interviews, and these were reduced to 35 items through expert validation. A pilot survey was conducted with 112 individuals aged 40–65, selected via quota sampling from 17 administrative regions in South Korea. Based on the pilot survey results, the instrument was refined to 32 items for the main survey. The main survey included 314 participants recruited through quota sampling in Busan and Ulsan Metropolitan Cities and Gyeongsang Region. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and reliability testing were performed to validate the instrument. Results: The final scale comprised 23 items across six factors. EFA demonstrated an explanatory power of 69.1%, with factor loadings ranging from 0.53 to 0.88. CFA confirmed the instrument’s validity, and reliability was established with a Cronbach’s α of .93. Conclusion This instrument is a validated and reliable tool for measuring middle-aged individuals’ awareness of well-dying. It can serve as an effective resource for evaluating and assessing well-dying awareness in the middle-aged population.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: Recurrent gynecological clear cell carcinoma (rGCCC) has a low objective response rate (ORR) to chemotherapy. Previous preclinical and clinical data suggest a potential synergy between immune checkpoint inhibitors and bevacizumab in rGCCC.Dostarlimab, a humanized monoclonal antibody targeting programmed cell death protein 1 (PD-1), combined with the anti-angiogenic bevacizumab, presents a novel therapeutic approach. This study will investigate the efficacy of dostarlimab +/− bevacizumab in rGCCC. Methods DOVE is a global, multicenter, international, open-label, randomized phase 2 study of dostarlimab +/− bevacizumab with standard chemotherapy in rGCCC. We will enroll 198 patients with rGCCC and assign them to one of three groups in a 1:1:1 ratio: arm A (dostarlimab monotherapy), B (dostarlimab + bevacizumab), and C (investigator’s choice of chemotherapy [weekly paclitaxel, pegylated liposomal doxorubicin, doxorubicin, or gemcitabine]). Patients with disease progression in arm A or C will be allowed to cross over to arm B. Stratification factors include prior bevacizumab use, prior lines of therapy (1 vs. >1), and primary site (ovarian vs. non-ovarian). Key inclusion criteria are histologically proven recurrent or persistent clear cell carcinoma of the ovary, endometrium, cervix, vagina, or vulva; up to five prior lines of therapy; disease progression within 12 months after platinumbased chemotherapy; and measurable disease. Key exclusion criteria are prior treatment with an anti–PD-1, anti–programmed death-ligand 1, or anti–programmed death-ligand 2 agent.The primary endpoint is progression-free survival determined by investigators. Secondary endpoints are ORR, disease control rate, clinical benefit rate, progression-free survival 2, overall survival, and toxicity. Exploratory objectives include immune biomarkers.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.