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 and Objectives: This study investigated whether an artificial intelligence computer-assisted diagnosis (AI-CAD) software recently developed in our institution named the Severance Artificial intelligence program (SERA) could show similar diagnostic performance for thyroid cancers using ultrasonographic (US) images from a mobile phone (SERA_M) compared to using images directly downloaded from the pictures archive and communication system (PACS) (SERA_P). Materials and Methods: From October 2019 to December 2019, 259 thyroid nodules from 259 patients were included. SERA was run on original and mobile images to evaluate SERA_P and SERA_M. Nodules were categorized according to the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS). To compare diagnostic performance, a logistic regression analysis was conducted using the Generalized Estimating Equation. The area under the curve (AUC) was calculated using the receiver operating characteristic (ROC) curve, and compared using the Delong Method. Results: There were 40 cancers (15.4%) and 219 benign lesions (84.6%). The AUC and sensitivity of SERA_M (0.82 and 85%, respectively) were not statistically different from SERA_P (0.8 and 75%, respectively) (p=0.526 and p=0.091, respectively). The AUC of radiologists (0.856) was not significantly different compared to SERA_P and SERA_M (p=0.163 and p=0.414, respectively). The sensitivity of radiologists (77.5%) was not statistically different compared to SERA_P and SERA_M (p=0.739 and p=0.361, respectively). Conclusion AI-CAD software using pictures taken by a mobile phone showed comparable diagnostic performance with the same software using images directly from PACS.

Purpose: The purpose of the study was to analyze the priorities for educational content regarding precautions to be taken to prevent safety accidents for employees in school foodservice using the Borich priority formula and the Locus for Focus model. Methods: A survey was conducted in February 2019 on 194 employees in elementary school and 122 employees in middle- and high school foodservice in the Jeonbuk area. Demographic characteristics, status of safety accidents, safety education, and their importance and performance levels were assessed using a self-administered questionnaire. The priorities for the educational content on precautions to prevent safety accidents were based on a 3-step analysis method, including the paired sample t-test, Borich priority formula, and the Locus for Focus Model. Results: The average perceived importance of the precautions to be taken against safety accidents of employees in elementary-, middle-, and high schools was higher compared to the average performance of the employees (p < 0.001). The top priority for elementary school employees was caution against falls during the cleaning of the gas hood and the trench in the kitchen. In addition, ‘awareness of chemical signs’ was added as one of the top priorities of middle- and high school employees. The second highest priority items were ‘do stretching’, ‘safely adjusting workbench height’, ‘keeping the right attitude’, ‘using assistive devices when moving heavy things’, and ‘checking the material safety data sheet’, which were the same for all elementary, middle- and high school employees. Conclusion Thus, to improve the educational preparedness of employees in the area of safety precautions, eight safety/accident prevention items should be included in the safety education program.

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.

Staphylococcus aureus (S. aureus ) is known to induce apoptosis of host immune cells and impair phagocytic clearance, thereby being pivotal in the pathogenesis of atopic dermatitis (AD). Adipose-derived stem cells (ASCs) exert therapeutic effects against inflammatory and immune diseases. In the present study, we investigated whether systemic administration of ASCs restores the phagocytic activity of peripheral blood mononuclear cells (PBMCs) and decolonizes cutaneous S.aureus under AD conditions. AD was induced by injecting capsaicin into neonatal rat pups. ASCs were extracted from the subcutaneous adipose tissues of naïve rats and administered to AD rats once a week for a month. Systemic administration of ASCs ameliorated AD-like symptoms, such as dermatitis scores, serum IgE, IFN-γ+/IL-4+ cell ratio, and skin colonization by S. aureus in AD rats. Increased FasL mRNA and annexin V+/7-AAD+ cells in the PBMCs obtained from AD rats were drastically reversed when co-cultured with ASCs. In contrast, both PBMCs and CD163+ cells bearing fluorescent zymosan particles significantly increased in AD rats treated with ASCs. Additionally, the administration of ASCs led to an increase in the mRNA levels of antimicrobial peptides, such as cathelicidin and β-defensin, in the skin of AD rats. Our results demonstrate that systemic administration of ASCs led to decolonization of S. aureus by attenuating apoptosis of immune cells in addition to restoring phagocytic activity. This contributes to the improvement of skin conditions in AD rats. Therefore, administration of ASCs may be helpful in the treatment of patients with intractable AD.

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.