This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

Background/Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. Methods: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. Results: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. Conclusions We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.

Background: High-alert medications (HAMs) are medications that bear a heightened risk of causing significant patient harm if used in error. To facilitate safe use of HAMs, identifying specific HAM lists for clinical setting is necessary. We aimed to develop the national level HAM list for acute care setting. Methods: We used three-step process. First, we compiled the pre-existing lists referring HAMs. Second, we analyzed medication related incidents reported from national patient safety incident report data and adverse events indicating medication errors from the Korea Adverse Event Reporting System (KAERS).We also surveyed the assistant staffs to support patient safety tasks and pharmacist in charge of medication safety in acute care hospital. From findings from analysis and survey results we created additional candidate list of HAMs. Third, we derived the final list for HAMs in acute care settings through expert panel surveys. Results: From pre-existing HAM list, preliminary list consisting of 42 medication class/ingredients was derived. Eight assistant staff to support patient safety tasks and 39 pharmacists in charge of medication safety responded to the survey. Additional 44 medication were listed from national patient safety incident report data, KAERS data and common medications involved in prescribing errors and dispensing errors from survey data. A list of mandatory and optional HAMs consisting of 10 and 6 medication classes, respectively, was developed by consensus of the expert group. Conclusion We developed national level HAM list for Korean acute care setting from pre-existing lists, analyzing medication error data, survey and expert panel consensus.

Purpose: We investigated the possible effects of diabetic ketoacidosis (DKA) at the initial diagnosis of type 1 diabetes mellitus (T1DM) on the clinical outcomes of pediatric patients. Methods: Medical records of children and adolescents with newly diagnosed T1DM seen in the Ajou University Hospital from January 2008 to August 2020 were reviewed and analyzed. Results: Among 129 diagnosed T1DM patients, 40.3% presented with DKA. Although demographic and basic characteristics did not differ between DKA and non-DKA patients, DKA patients needed a significantly higher insulin dosage than non-DKA patients for 2 years after diagnosis. However, control of glycated hemoglobin was not different between the DKA and non-DKA groups during the observation period. In the biochemical analysis, C-peptide, insulin-like growth factor-1, and insulin-like growth factor binding protein 3, high-density lipoprotein cholesterol, free T4, and T3 values were lower, but thyroid-stimulating hormone, initial serum glucose, uric acid, total cholesterol, triglyceride, and low-density lipoprotein cholesterol values were higher in DKA patients than non-DKA patients at the diagnosis of T1DM; however, these differences were temporarily present and disappeared with insulin treatment. Other clinical outcomes, such as height, thyroid function, and urine microalbumin level, did not vary significantly between the DKA and non-DKA groups during 5 years of follow-up. Conclusion DKA at initial presentation reflects the severity of disease progression, and the deleterious effects of DKA seem to impact insulin secretion. Although no difference in long-term prognosis was found, early detection of T1DM should help to reduce DKA-related islet damage and the socioeconomic burden of T1DM.

Purpose: To derive the optimized intraocular lens (IOL) constants from automated and manifest refraction after cataract surgery in Korean patients, and to evaluate whether there is a difference in optimized IOL constants according to the refraction method. Methods: This retrospective multicenter cohort study enrolled 4,103 eyes of 4,103 patients who underwent phacoemulsification and in-the-bag IOL implantation at 18 institutes. Optimized IOL constants for the SRK/T, Holladay, Hoffer Q, and Haigis formulas were calculated via autorefraction or manifest refraction of samples using the same biometry and IOL. The IOL constants derived from autorefraction and manifest refraction were compared. Results: Of the 4,103 eyes, the majority (62.9%) were measured with an IOLMaster 500 followed by an IOLMaster 700 (15.2%). A total of 33 types of IOLs were used, and the Tecnis ZCB00 was the most frequently used (53.0%). There was no statistically significant difference in IOL constants derived from autorefraction and manifest refraction when IOL constants were optimized with a large number of study subjects. On the other hand, optimized IOL constants derived from autorefraction were significantly smaller than those from manifest refraction when the number of subjects was small. Conclusions It became possible to use the IOL constants optimized from Koreans to calculate the IOL power. However, if the IOL constant is optimized using autorefraction in a small sample group, the IOL constant tends to be small, which may lead to refractive error after surgery.

Purpose: To describe current cataract surgery practice patterns and trends among Korean ophthalmologists. Methods: A survey was conducted among members of the Korean Society of Cataract and Refractive Surgery in October 2020. Of the 998 questionnaires, 262 (26.3%) were received for analysis. Data were analyzed using descriptive statistics and compared with those of previous surveys. Results: The largest percentage of respondents (39%) had <5 years of practical experience, and 40% had >11 years of practical experience. The average, median, and mode monthly volumes of cataract surgeries performed by the Korean Society of Cataract and Refractive Surgery members were 31, 20, and 10 cases, respectively. Topical anesthesia was administered by 85% of the respondents. For intraocular lens (IOL) calculations, 96% of the respondents used optical biometry. The proportion of surgeons providing femtosecond laser-assisted cataract surgery increased significantly from 5% in 2018 to 29% in 2020. This increase was accompanied by an increase in the multifocal IOLs. Those who implant multifocal IOL for >10% of their cases increased from 16% (2018) to 29% (2020). Topical nonsteroidal anti-inflammatory drugs were prescribed postoperatively by 76% of the respondents. Most respondents (70%) prescribed these anti-inflammatory drugs for 4 weeks. Conclusions This survey provided a comprehensive update on current cataract surgery practice in the Republic of Korea. The results highlighted the increasing use of premium IOLs, femtosecond laser-assisted cataract surgery, optical biometry, and topical anesthesia to better meet the patients’ needs.

Purpose: Antithyroid drugs (ATDs) are primarily used as an initial treatment in pediatric patients with Graves’ disease (GD). We aimed to investigate the long-term outcomes in pediatric GD patients receiving ATDs. Methods: Retrospective data from a single center were collected from April 2003 to July 2020. A total of 98 children and adolescents aged 2–16 years diagnosed with GD and receiving ATDs was enrolled. We investigated the factors correlated with remission by comparing children who achieved remission after 5 years and those with persistent disease. Results: The study included 76 girls (77.6%) and 22 boys (22.4%). During the 5-year follow-up period, 18 children (18.3%) maintained remission, ATDs could not be discontinued in 74 patients (75.5%), and relapse occurred in 6 patients (6.2%). The remission group had significantly lower thyroid-stimulating hormone-binding inhibitory immunoglobulin (TBII) level at diagnosis (P=0.002) and 3 months (P=0.002), 1 year (P=0.002), 2 years (P≤0.001), 3 years (P≤0.001), 4 years (P≤0.001), and 5 years (P≤0.001) after ATD treatment than did the nonremission group. The remission group also had a shorter time for TBII normalization after ATD treatment (P≤0.001). Multiple logistic regression analysis showed that the time to TBII normalization (cutoff time=2.35 years) was related to GD remission (odds ratio, 0.596; 95% confidence interval, 0.374–0.951). Conclusion TBII level and time to TBII normalization after ATD treatment can be used to predict remission in pediatric GD patients.