Idiopathic pulmonary fibrosis (IPF) is characterized by maladaptive epithelial–mesenchymal crosstalk and progressive extracellular matrix accumulation, whereas currently available antifibrotic agents merely decelerate functional decline.This study investigated whether exosomes derived from human mesenchymal stem cells derived from embryonic stem cells (ESC-MSCs) restore epithelial stress responses and attenuate fibrotic remodeling. Human IPF lung transcriptomes were integrated with a bleomycin-induced murine model analyzed by RNA sequencing and protein signaling, together with cigarette smoke extract-induced injury in A549 epithelial cells. ESC-MSCs-derived exosomes exhibited typical morphology and size distribution, enrichment of tetraspanins, and absence of endoplasmic reticulum contamination, consistent with high-purity preparations. Across human IPF and bleomycin-injured lungs, transcriptomic profiling revealed prominent enrichment of extracellular matrix and cytoskeletal gene programs, whereas mitogen-activated protein kinase (MAPK) and Smad families displayed only modest alterations at the mRNA level. In vivo administration of exosomes during the fibrotic remodeling phase, via either intravenous or intratracheal delivery, resulted in improved body weight, reduced lung weight-to-body weight ratios, and decreased collagen deposition and Ashcroft scores. These structural and functional improvements were accompanied by suppression of profibrotic and mesenchymal markers and selective attenuation of activator protein-1 (AP-1) activity. In epithelial injury models, ESC-MSCs-derived exosomes enhanced cell viability, restored redox homeostasis, and constrained stress-induced mesenchymal gene expression and MAPK phosphorylation in both co-treatment and post-treatment settings. Collectively, these data support an epithelial-centered mechanism in which ESC-MSCs-derived exosomes re-establish oxidative balance and selectively restrict AP-1-driven stress signaling, thereby secondarily limiting extracellular matrix accumulation and fibrotic remodeling.

This study compares biomarker levels among environmentally vulnerable residents in Korea, the general Korean population, and Asians in the United States. We selected 953 exposed residents and 204 controls from the Forensic Research via Omics Markers in Environmental Health Vulnerable Areas (FROM) study (2021-2023), 4,239 participants from the fourth Korean National Environmental Health Survey (2018-2020), and 996 Asians from the U.S. National Health and Nutrition Examination Survey (2017-March 2020). The analyzed biomarkers included blood and urinary metals, urinary metabolites of polycyclic aromatic hydrocarbons, nicotine, volatile organic compounds, and serum perfluorocarbon metabolites. The highest median biomarker levels varied by pollution source among older adults. In refineries, blood lead and cadmium (Cd), as well as urinary Cd and 2-hydroxyfluorene, were highest. Abandoned metal mines exhibited the highest blood and urinary mercury, urinary Cd, total arsenic (As), 2-naphthol, and cotinine levels. Coal-fired power plants showed the highest urinary 1- hydroxyphenanthrene levels, while cement factories had the highest urinary As3+ levels. Sprawls demonstrated the highest urinary monomethylarsonic acid, 1-hydroxypyrene, and phenylglyoxylic acid levels, and industrial areas recorded the highest levels of trans, trans-muconic acid, benzylmercapturic acid, and 2-methylhippuric acid. In general, biomarker levels were higher among exposed residents in the FROM study than in the general population; however, urinary 2-hydroxyfluorene and As5+ levels did not differ significantly. Exposure to pollution sources in environmentally vulnerable areas may elevate biomarker levels in residents.

This study compares biomarker levels among environmentally vulnerable residents in Korea, the general Korean population, and Asians in the United States. We selected 953 exposed residents and 204 controls from the Forensic Research via Omics Markers in Environmental Health Vulnerable Areas (FROM) study (2021-2023), 4,239 participants from the fourth Korean National Environmental Health Survey (2018-2020), and 996 Asians from the U.S. National Health and Nutrition Examination Survey (2017-March 2020). The analyzed biomarkers included blood and urinary metals, urinary metabolites of polycyclic aromatic hydrocarbons, nicotine, volatile organic compounds, and serum perfluorocarbon metabolites. The highest median biomarker levels varied by pollution source among older adults. In refineries, blood lead and cadmium (Cd), as well as urinary Cd and 2-hydroxyfluorene, were highest. Abandoned metal mines exhibited the highest blood and urinary mercury, urinary Cd, total arsenic (As), 2-naphthol, and cotinine levels. Coal-fired power plants showed the highest urinary 1- hydroxyphenanthrene levels, while cement factories had the highest urinary As3+ levels. Sprawls demonstrated the highest urinary monomethylarsonic acid, 1-hydroxypyrene, and phenylglyoxylic acid levels, and industrial areas recorded the highest levels of trans, trans-muconic acid, benzylmercapturic acid, and 2-methylhippuric acid. In general, biomarker levels were higher among exposed residents in the FROM study than in the general population; however, urinary 2-hydroxyfluorene and As5+ levels did not differ significantly. Exposure to pollution sources in environmentally vulnerable areas may elevate biomarker levels in residents.

This study compares biomarker levels among environmentally vulnerable residents in Korea, the general Korean population, and Asians in the United States. We selected 953 exposed residents and 204 controls from the Forensic Research via Omics Markers in Environmental Health Vulnerable Areas (FROM) study (2021-2023), 4,239 participants from the fourth Korean National Environmental Health Survey (2018-2020), and 996 Asians from the U.S. National Health and Nutrition Examination Survey (2017-March 2020). The analyzed biomarkers included blood and urinary metals, urinary metabolites of polycyclic aromatic hydrocarbons, nicotine, volatile organic compounds, and serum perfluorocarbon metabolites. The highest median biomarker levels varied by pollution source among older adults. In refineries, blood lead and cadmium (Cd), as well as urinary Cd and 2-hydroxyfluorene, were highest. Abandoned metal mines exhibited the highest blood and urinary mercury, urinary Cd, total arsenic (As), 2-naphthol, and cotinine levels. Coal-fired power plants showed the highest urinary 1- hydroxyphenanthrene levels, while cement factories had the highest urinary As3+ levels. Sprawls demonstrated the highest urinary monomethylarsonic acid, 1-hydroxypyrene, and phenylglyoxylic acid levels, and industrial areas recorded the highest levels of trans, trans-muconic acid, benzylmercapturic acid, and 2-methylhippuric acid. In general, biomarker levels were higher among exposed residents in the FROM study than in the general population; however, urinary 2-hydroxyfluorene and As5+ levels did not differ significantly. Exposure to pollution sources in environmentally vulnerable areas may elevate biomarker levels in residents.

This study compares biomarker levels among environmentally vulnerable residents in Korea, the general Korean population, and Asians in the United States. We selected 953 exposed residents and 204 controls from the Forensic Research via Omics Markers in Environmental Health Vulnerable Areas (FROM) study (2021-2023), 4,239 participants from the fourth Korean National Environmental Health Survey (2018-2020), and 996 Asians from the U.S. National Health and Nutrition Examination Survey (2017-March 2020). The analyzed biomarkers included blood and urinary metals, urinary metabolites of polycyclic aromatic hydrocarbons, nicotine, volatile organic compounds, and serum perfluorocarbon metabolites. The highest median biomarker levels varied by pollution source among older adults. In refineries, blood lead and cadmium (Cd), as well as urinary Cd and 2-hydroxyfluorene, were highest. Abandoned metal mines exhibited the highest blood and urinary mercury, urinary Cd, total arsenic (As), 2-naphthol, and cotinine levels. Coal-fired power plants showed the highest urinary 1- hydroxyphenanthrene levels, while cement factories had the highest urinary As3+ levels. Sprawls demonstrated the highest urinary monomethylarsonic acid, 1-hydroxypyrene, and phenylglyoxylic acid levels, and industrial areas recorded the highest levels of trans, trans-muconic acid, benzylmercapturic acid, and 2-methylhippuric acid. In general, biomarker levels were higher among exposed residents in the FROM study than in the general population; however, urinary 2-hydroxyfluorene and As5+ levels did not differ significantly. Exposure to pollution sources in environmentally vulnerable areas may elevate biomarker levels in residents.

Purpose: Precise registration between intraoral scans (IOSs) and CBCT images is essential for many digital dentistry applications. The purpose of this study was to develop DentalRegiformer, a fully automated, end-to-end deep learning framework that ensures accurate registration between IOS and CBCT images. Materials and Methods: The network was trained on 88 paired CBCT-IOS datasets from 44 patients, with ground-truth alignments obtained through manual registration performed by trained dental students. To enhance clinical accuracy and efficiency, a multi-stage coarse-to-fine strategy is proposed to integrate segmentation, classification, and registration into a unified pipeline. First, tooth segmentation is performed on CBCT volumes using 3D nnU-Net to generate segmented tooth regions for alignment. Simultaneously, IOS datasets are classified as maxillary or mandibular dentition using a hybrid representation that combines geometric descriptors with point cloud features extracted via a DGCNN network. Registration is then conducted in two phases: coarse alignment using a DCP framework for feature encoding and probabilistic correspondence estimation to compute the initial rigid transformation, followed by fine alignment using GeoTransformer’s local-to-global iterative refinement, which alternates between local feature aggregation and global context integration to progressively enhance correspondence accuracy and achieve precise rigid registration. Results The segmentation model achieved robust results, with a Dice coefficient of 0.924, precision of 0.916, and recall of 0.934. The DGCNN classifier perfectly distinguished maxillary and mandibular arches, achieving sensitivity, specificity, ROC, and accuracy of 1.000.For registration, DentalRegiformer accurately predicted transformation between IOS and CBCT images, yielding an overall RMSE of 0.556 mm; MAEs of 0.231mm, 0.329 mm, and 0.283 mm along the x-, y-, and z-axes, respectively; and inference time of 19.623 seconds. In comparison, the manual method based on combined pair-points and ICP had an RMSE of 0.615 mm;MAEs of 0.244 mm, 0.347 mm, and 0.298 mm along the x-, y-, and z-axes, respectively; and processing time of 431.6 seconds.Discussion and Conclusion: Therefore, DentalRegiformer is a fully automated, deep learning–based solution that minimizes manual intervention and improves clinical efficiency. The framework streamlines digital dental workflows, reduces operator-dependent errors, and facilitates automated, personalized dental care.

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.