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: Hashimoto thyroiditis (HT) is suspected to correlate with papillary thyroid carcinoma (PTC) development. While some HT cases exhibit histologic features of immunoglobulin G4 (IgG4)-related disease, the relationship of HT with PTC progression remains unestablished. Methods: This cross-sectional study included 426 adult patients with PTC (≥1 cm) undergoing thyroidectomy at an academic thyroid center. HT was identified based on its typical histologic features. IgG4 and IgG immunohistochemistry were performed. Wholeslide images of immunostained slides were digitalized. Positive plasma cells per 2 mm2 were counted using QuPath and a pre-trained deep learning model. The primary outcome was tumor structural recurrence post-surgery. Results: Among the 426 PTC patients, 79 were diagnosed with HT. With a 40% IgG4 positive/IgG plasma cell ratio as the threshold for diagnosing IgG4-related disease, a cutoff value of >150 IgG4 positive plasma cells per 2 mm2 was established. According to this criterion, 53% (43/79) of HT patients were classified as IgG4-related. The IgG4-related HT subgroup presented a more advanced cancer stage than the IgG4-non-related HT group (P=0.038). The median observation period was 109 months (range, 6 to 142). Initial assessment revealed 43 recurrence cases. Recurrence-free survival periods showed significant (P=0.023) differences, with patients with IgG4 non-related HT showing the longest period, followed by patients without HT and those with IgG4-related HT. Conclusion This study effectively stratified recurrence risk in PTC patients based on HT status and IgG4-related subtypes. These findings may contribute to better-informed treatment decisions and patient care strategies.

Background/Aims: H2 receptor antagonists (H2RA) have been used to treat gastritis by inhibiting gastric acid. Proton pump inhibitors (PPIs) are more potent acid suppressants than H2RA.However, the efficacy and safety of low-dose PPI for treating gastritis remain unclear. The aim was to investigate the efficacy and safety of low-dose PPI for treating gastritis. Methods: A double-blind, noninferiority, multicenter, phase 3 clinical trial randomly assigned 476 patients with endoscopic erosive gastritis to a group using esomeprazole 10 mg (DW1903) daily and a group using famotidine 20 mg (DW1903R1) daily for 2 weeks. The full-analysis set included 319 patients (DW1903, n=159; DW1903R1, n=160) and the per-protocol set included 298 patients (DW1903, n=147; DW1903R1, n=151). The primary endpoint (erosion improvement rate) and secondary endpoint (erosion and edema cure rates, improvement rates of hemorrhage, erythema, and symptoms) were assessed after the treatment. Adverse events were compared. Results: According to the full-analysis set, the erosion improvement rates in the DW1903 and DW1903R1 groups were 59.8% and 58.8%, respectively. According to the per-protocol analysis, the erosion improvement rates in the DW1903 and DW1903R1 groups were 61.9% and 59.6%, respectively. Secondary endpoints were not significantly different between two groups except that the hemorrhagic improvement rate was higher in DW1903 with statistical tendency. The number of adverse events were not statistically different. Conclusions DW1903 of a low-dose PPI was not inferior to DW1903R1 of H2RA. Thus, lowdose PPI can be a novel option for treating gastritis (ClinicalTrials.gov Identifier: NCT05163756).

Objective: To translate the 22-item Longer-term Unmet Needs after Stroke (LUNS) questionnaire, validate it in the Korean stroke population, and assess the reliability of face-to-face and telephone surveys. Methods: Sixty-six adult patients with stroke from Seoul National University Bundang Hospital and Kangwon National University Hospital were involved in the validation. Participants were interviewed twice using the LUNS Korean version: first, a face-to-face survey for validation, and second, a telephone survey for test-retest reliability. Participants completed the Frenchay Activities Index (FAI) and Short Form 12 (SF-12) Mental and Physical Component Summary (MCS and PCS) scores at the first interview. For concurrent validity, the differences in health status (FAI, SF-12 MCS and PCS) between the groups that reported unmet needs and those that did not were analyzed for each item. Cohen’s kappa and percentage of agreement between the first and second administrations were calculated for each item to determine the test-retest reliability. Results: The average age of the participants was 61.2±12.8 years and 74.2% were male. Fifty-seven patients were involved in the second interview. Depending on the unmet needs, SF-12 MCS, PCS, and FAI were significantly different in 12 of 22 items. In the test-retest reliability test, 12 items had a kappa of 0.6 or higher, and two had a kappa of <0.4. Conclusion The LUNS instrument into Korean (LUNS-K) is a reliable and valid instrument for assessing unmet health needs in patients with stroke. In addition, telephone surveys can be considered reliable.

Purpose: The benefit of adjuvant chemotherapy following curative-intent surgery in pancreatic ductal adenocarcinoma (PDAC) patients who had received neoadjuvant FOLFIRINOX is unclear. This study aimed to assess the survival benefit of adjuvant chemotherapy in this patient population. Materials and Methods: This retrospective study included 218 patients with localized non-metastatic PDAC who received neoadjuvant FOLFIRINOX and underwent curative-intent surgery (R0 or R1) between January 2017 and December 2020. The association of adjuvant chemotherapy with disease-free survival (DFS) and overall survival (OS) was evaluated in overall patients and in the propensity score matched (PSM) cohort. Subgroup analysis was conducted according to the pathology-proven lymph node status. Results: Adjuvant chemotherapy was administered to 149 patients (68.3%). In the overall cohort, the adjuvant chemotherapy group had significantly improved DFS and OS compared to the observation group (DFS: median, 13.8 months [95% confidence interval (CI), 11.0 to 19.1] vs. 8.2 months [95% CI, 6.5 to 12.0]; p < 0.001; and OS: median, 38.0 months [95% CI, 32.2 to not assessable] vs. 25.7 months [95% CI, 18.3 to not assessable]; p=0.005). In the PSM cohort of 57 matched pairs of patients, DFS and OS were better in the adjuvant chemotherapy group than in the observation group (p < 0.001 and p=0.038, respectively). In the multivariate analysis, adjuvant chemotherapy was a significant favorable prognostic factor (vs. observation; DFS: hazard ratio [HR], 0.51 [95% CI, 0.36 to 0.71; p < 0.001]; OS: HR, 0.45 [95% CI, 0.29 to 0.71; p < 0.001]). Conclusion Among PDAC patients who underwent surgery following neoadjuvant FOLFIRINOX, adjuvant chemotherapy may be associated with improved survival. Randomized studies should be conducted to validate this finding.

Quantification of tyrosine hydroxylase (TH)-positive neurons is essential for the preclinical study of Parkinson’s disease (PD). However, manual analysis of immunohistochemical (IHC) images is labor-intensive and has less reproducibility due to the lack of objectivity. Therefore, several automated methods of IHC image analysis have been proposed, although they have limitations of low accuracy and difficulties in practical use. Here, we developed a convolutional neural network-based machine learning algorithm for TH+ cell counting. The developed analytical tool showed higher accuracy than the conventional methods and could be used under diverse experimental conditions of image staining intensity, brightness, and contrast. Our automated cell detection algorithm is available for free and has an intelligible graphical user interface for cell counting to assist practical applications. Overall, we expect that the proposed TH+ cell counting tool will promote preclinical PD research by saving time and enabling objective analysis of IHC images.

Background and Objectives: Paroxysmal atrial fibrillation (AF) is a major potential cause of embolic stroke of undetermined source (ESUS). However, identifying AF remains challenging because it occurs sporadically. Deep learning could be used to identify hidden AF based on the sinus rhythm (SR) electrocardiogram (ECG). We combined known AF risk factors and developed a deep learning algorithm (DLA) for predicting AF to optimize diagnostic performance in ESUS patients. Methods: A DLA was developed to identify AF using SR 12-lead ECG with the database consisting of AF patients and non-AF patients. The accuracy of the DLA was validated in 221 ESUS patients who underwent insertable cardiac monitor (ICM) insertion to identify AF. Results: A total of 44,085 ECGs from 12,666 patient were used for developing the DLA. The internal validation of the DLA revealed 0.862 (95% confidence interval, 0.850–0.873) area under the curve (AUC) in the receiver operating curve analysis. In external validation data from 221 ESUS patients, the diagnostic accuracy of DLA and AUC were 0.811 and 0.827, respectively, and DLA outperformed conventional predictive models, including CHARGE-AF,C2HEST, and HATCH. The combined model, comprising atrial ectopic burden, left atrial diameter and the DLA, showed excellent performance in AF prediction with AUC of 0.906. Conclusions The DLA accurately identified paroxysmal AF using 12-lead SR ECG in patients with ESUS and outperformed the conventional models. The DLA model along with the traditional AF risk factors could be a useful tool to identify paroxysmal AF in ESUS patients.