Associations between plasma metabolites and heavy metal exposure in residents of environmentally polluted areas.

Heavy metals are commonly released into the environment through industrial processes such as mining and refining. The rapid industrialization that occurred in South Korea during the 1960s and 1970s contributed significantly to the economy of the country; however, the associated mining and refining led to considerable environmental pollution, and although mining is now in decline in South Korea, the detrimental effects on residents inhabiting the surrounding areas remain. The bioaccumulation of toxic heavy metals leads to metabolic alterations in human homeostasis, with disruptions in this balance leading to various health issues. This study used metabolomics to explore metabolomic alterations in the plasma samples of residents living in mining and refining areas. The results showed significant increases in metabolites involved in glycolysis and the surrounding metabolic pathways, such as glucose-6-phosphate, phosphoenolpyruvate, lactate, and inosine monophosphate, in those inhabiting polluted areas. An investigation of the associations between metabolites and blood clinical parameters through meet-in-the-middle analysis indicated that female residents were more affected by heavy metal exposure, resulting in more metabolomic alterations. For women, inhabiting the abandoned mine area, metabolites in the glycolysis and pentose phosphate pathways, such as ribose-5-phosphate and 3-phosphoglycerate, have shown a negative correlation with albumin and calcium. Finally, Mendelian randomization(MR) was used to determine the causal effects of these heavy metal exposure-related metabolites on heavy metal exposure-related clinical parameters. Metabolite biomarkers could provide insights into altered metabolic pathways related to exposure to toxic heavy metals and improve our understanding of the molecular mechanisms underlying the health effects of toxic heavy metal exposure.

Status of MyHealthWay and Suggestions for Widespread Implementation, Emphasizing the Utilization and Practical Use of Personal Medical Data.

OBJECTIVES: In the Fourth Industrial Revolution, there is a focus on managing diverse medical data to improve healthcare and prevent disease. The challenges include tracking detailed medical records across multiple institutions and the necessity of linking domestic public medical entities for efficient data sharing. This study explores MyHealthWay, a Korean healthcare platform designed to facilitate the integration and transfer of medical data from various sources, examining its development, importance, and legal implications. METHODS: To evaluate the management status and utilization of MyHealthWay, we analyzed data types, security, legal issues, domestic versus international issues, and infrastructure. Additionally, we discussed challenges such as resource and infrastructure constraints, regulatory hurdles, and future considerations for data management. RESULTS: The secure sharing of medical information via MyHealthWay can reduce the distance between patients and healthcare facilities, fostering personalized care and self-management of health. However, this approach faces legal challenges, particularly relating to data standardization and access to personal health information. Legal challenges in data standardization and access, particularly for secondary uses such as research, necessitate improved regulations. There is a crucial need for detailed governmental guidelines and clear data ownership standards at institutional levels. CONCLUSIONS: This report highlights the role of Korea's MyHealthWay, which was launched in 2023, in transforming healthcare through systematic data integration. Challenges include data privacy and legal complexities, and there is a need for data standardization and individual empowerment in health data management within a systematic medical big data framework.

Surgical Correction of a Sinus Venosus Atrial Septal Defect with Partial Anomalous Pulmonary Venous Connections Using Cardiac Computed Tomography Imaging and a 3D-Printed Model.

Sinus venosus atrial septal defects (SVASDs), concurrent with partial anomalous pulmonary venous connections (PAPVCs), are a rare congenital heart disease in dogs. Surgical correction is essential when clinical signs or significant hemodynamic changes are present. We aimed to report on the successful surgical correction of an SVASD with PAPVCs, using a computed tomography (CT)-based customized 3D cardiac model. A 10-month-old male poodle was referred for corrective surgery for an ASD. Echocardiography confirmed a hemodynamically significant left-to-right shunting flow through an interatrial septal defect and severe right-sided heart volume overload. For a comprehensive diagnosis, a CT scan was performed, which confirmed an SVASD with PAPVCs. A customized 3D cardiac model was used for preoperative decision-making and surgical rehearsal. The defect was repaired using an autologous pericardial patch under a cardiopulmonary bypass (CPB). Temporary pacing was applied for sinus bradycardia and third-degree atrioventricular block. The patient recovered from the anesthesia without further complications. The pacemaker was removed during hospitalization and the patient was discharged without complications 2 weeks post-surgery. At the three-month follow-up, there was no shunting flow in the interatrial septum and the right-sided volume overload had been resolved. The cardiac medications were discontinued, and there were no complications. This report indicates the validity of surgical correction under CPB for an SVASD with PAPVCs, and the advantages of utilizing a CT-based 3D cardiac model for preoperative planning to increase the surgical success rate.

Uncovering the health implications of abandoned mines through protein profiling of local residents.

Residents in areas with abandoned mines risk significant exposure to abundant heavy metals in the environment. However, current clinical indicators cannot fully reflect the health changes associated with abandoned mine exposure. The aim of this study was to identify biological changes in the residents of abandoned mine areas via proteomic analysis of their blood. Blood samples were collected from abandoned mine and control areas, and mass spectrometry was used for protein profiling. A total of 138 unique or common proteins that were differentially expressed in low-exposure abandoned mine area (LoAMA) or high-exposure abandoned mine area (HiAMA) compared to non-exposure control area (NEA) were analyzed, and identified 4 clusters based on functional similarity. Among the 10 proteins that showed specific change in LoAMA, 4 proteins(Apolipoprotein M, Apolipoprotein E, Apolipoprotein L1, and Cholesteryl ester transfer protein) were cluded in cluster 1(plasma lipoprotein remodeling), and linked to proteins that showed specific change in protein expression in HiAMA. Therefore, it is suggested that 4 proteins are changed at low exposure to an abandoned mine (or initial exposure), and then at high exposure, changes in various proteins involved in linked plasma lipoprotein remodeling are induced, which might triggered by the 4 proteins. Interestingly, in addition to plasma lipoprotein remodeling, proteins involved in other functional networks were changed in the high exposure group. These were all directly or indirectly linked to the 4 biomarkers(Apolipoprotein M, Apolipoprotein E, Apolipoprotein L1, and Cholesteryl ester transfer protein) that changed during low exposure. This suggests their potential utility in identifying areas impacted by abandoned mines. Especially, proteins involved in lipid metabolism and renal function-related diseases in individuals exposed to heavy metals in abandoned mine areas were correlated. Chronic kidney disease is predominantly instigated by cardiovascular disease and is commonly accompanied by dyslipidemia.

Ambient particulate matter and surrounding greenness in relation to sleep quality among pregnant women: A nationwide cohort study.

Background: Particulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed. Objective: This cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women. Methods: Pregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM. Results: After adjusting for confounders, each 10 µg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%-56% of the association between residential greenness and poor sleep quality. Conclusions: This study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health.

Cost-utility analysis of transitional care services for older inpatients with chronic obstructive pulmonary disease (COPD) in Korea.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is associated with a high readmission rate and poses a significant disease burden. South Korea initiated pilot projects on transitional care services (TCS) to reduce readmissions. However, evidence from cost-effectiveness analyses remains undiscovered. This study aimed to evaluate the cost-effectiveness of TCS in patients with COPD from the healthcare system' perspective. METHOD: A cost-utility analysis was conducted using a Markov model containing six components of possible medical use after discharge. Transition probabilities and medical costs were extracted from the National Health Insurance Service Senior Cohort (NHIS-SC), and utility data were obtained from published literature. Sensitivity analyses were performed to test the robustness of the results. RESULTS: Conducting TCS produced an incremental quality-adjusted life years gain of 0.231, 0.275, 0.296 for those in their 60s, 70s, and 80s, respectively, and cost savings of $225.16, $1668, and $2251.64 for those in their 60s, 70s, and 80s, respectively, per patient over a 10-year time horizon. The deterministic sensitivity analysis indicated that the TCS cost and the cost of readmission by other diseases immensely impact the results. The probabilistic sensitivity analyses showed that the probability that the incremental cost-effectiveness ratio is below $23,050 was over 85%, 93%, and 97% for those in the 60s, 70s, and 80s, respectively. CONCLUSIONS: TCS was the dominant option compared to usual care. However, it is advantageous to the healthcare budget preferentially consider patients aged over 70 years with severe TCS symptoms. In addition, it is essential to include the management of underlying comorbidities in TCS intervention. TRIAL REGISTRATION: Clinical Research Information Service (CRIS), KCT0007937. Registered on 24 November 2022.

Enhancing Durability and Capacity Retention of Ultrafine-Grained Aluminum Foil Anodes in Lithium-Ion Batteries.

In this study, we present our successful fabrication of commercial-grade pure aluminum anode foil (99.5%, 2NAl) with an ultrafine-grained (UFG) microstructure and high hardness, achieved through cold rolling. Under identical rolling conditions, a coarse-grained microstructure with a low hardness was attained from the high-purity Al foil (99.99%, 4NAl). The UFG 2NAl foil exhibited enhanced lithium-ion diffusivity and reduced nucleation and activation overpotentials for forming the ß-LiAl phase compared to the 4NAl foil. The high-density grain boundaries in the UFG 2NAl foil facilitated the rapid formation of a uniform ß-LiAl phase layer on its surface, thereby mitigating mechanical damage within the ß-LiAl phase layer caused by volume changes during the lithiation and delithiation processes. The high hardness of the UFG 2NAl sample effectively prevented macroscopic plastic deformation during cycling, thus preserving the integrity of the ß-LiAl phase layer and inhibiting the formation of cracks within the unreacted Al matrix. The collective advantages of reduced overpotential, enhanced Li-ion diffusivity, and high resistance to mechanical damage and plastic deformation in UFG 2NAl contribute to its superior durability and capacity retention compared to the high-purity Al in electrochemical cycling.

Investigation of gut microbiota diversity according to infectious agent in pediatric infectious acute gastroenteritis in a Korean university hospital.

BACKGROUND: Acute gastroenteritis (AGE) is a common cause of pediatric morbidity and mortality worldwide. AGE can cause an imbalance in the intestinal microbiota. This study aimed to investigate the diversity of the gut microbiome in Korean children hospitalized for infectious AGE at a university hospital. METHODS: A total of 23 stool samples from patients aged 5 months to 11 years with AGE were analyzed. Thirteen convalescent stool samples were collected 1 month after discharge. Multiplex polymerase chain reaction (PCR) for the five viruses and 16 bacteria-specific AGE pathogens (PowerChek Multiplex Real time PCR Kit, Seoul, Korea), and 16s rRNA sequencing (Illumina MiSeq Sequencing system, Illumina, USA) were performed. RESULTS: According to the results of multiplex PCR for causative pathogens, the microbiome taxonomic profile (MTP) of the gut microbiome in three groups of AGE, norovirus AGE (n = 11), Campylobacter AGE (n = 7) and Salmonella AGE (n = 5) was compared. The phylum Actinobacteria was significantly more abundant in the norovirus AGE (P = 0.011), whereas the phylum Proteobacteria was significantly more abundant in Salmonella AGE (P = 0.012). Alpha diversity, which indicates species richness and diversity, showed no statistical differences. However, beta diversity, representing the similarity in MTP between norovirus, Campylobacter, and Salmonella AGE, was significantly different (P = 0.007). In convalescence, compared with their corresponding AGE samples, the phylum Firmicutes; and the lower taxa Christensenellaceae (P = 0.0152) and Lachnospiraceae (P = 0.0327) were significantly increased. CONCLUSIONS: In pediatric AGE, the type of infectious agent can affect the diversity and dominance of gut microbiota in pediatric patients. Furthermore, healthy gut bacteria increased during the period of 1 month after infection, allowing a return to a healthy state without causing long-term dysbiosis.

Human-airway surface mesh smoothing based on graph convolutional neural networks.

BACKGROUND AND OBJECTIVE: A detailed representation of the airway geometry in the respiratory system is critical for predicting precise airflow and pressure behaviors in computed tomography (CT)-image-based computational fluid dynamics (CFD). The CT-image-based geometry often contains artifacts, noise, and discontinuities due to the so-called stair step effect. Hence, an advanced surface smoothing is necessary. The existing smoothing methods based on the Laplacian operator drastically shrink airway geometries, resulting in the loss of information related to smaller branches. This study aims to introduce an unsupervised airway-mesh-smoothing learning (AMSL) method that preserves the original geometry of the three-dimensional (3D) airway for accurate CT-image-based CFD simulations. METHOD: The AMSL method jointly trains two graph convolutional neural networks (GCNNs) defined on airway meshes to filter vertex positions and face normal vectors. In addition, it regularizes a combination of loss functions such as reproducibility, smoothness and consistency of vertex positions, and normal vectors. The AMSL adopts the concept of a deep mesh prior model, and it determines the self-similarity for mesh restoration without using a large dataset for training. Images of the airways of 20 subjects were smoothed by the AMSL method, and among them, the data of two subjects were used for the CFD simulations to assess the effect of airway smoothing on flow properties. RESULTS: In 18 of 20 benchmark problems, the proposed smoothing method delivered better results compared with the conventional or state-of-the-art deep learning methods. Unlike the traditional smoothing, the AMSL successfully constructed 20 smoothed airways with airway diameters that were consistent with the original CT images. Besides, CFD simulations with the airways obtained by the AMSL method showed much smaller pressure drop and wall shear stress than the results obtained by the traditional method. CONCLUSIONS: The airway model constructed by the AMSL method reproduces branch diameters accurately without any shrinkage, especially in the case of smaller airways. The accurate estimation of airway geometry using a smoothing method is critical for estimating flow properties in CFD simulations.

Cadmium-associated protein changes in residents of contaminated areas: Abandoned mine and smelter.

Cadmium (Cd), a serious environmental contaminant, is associated with adverse health effects. However, the specific changes that the human body experiences in response to exposure to varying concentrations of cadmium remain unknown. The high levels of heavy metal contamination, especially Cd, in abandoned mines and smelter sites make them ideal locations to investigate the physiological manifestations of Cd exposure. This study found that individuals inhabiting abandoned mine and smelter areas had higher concentrations of Cd in their urine and blood compared to those living outside these areas (i.e., the controls). Furthermore, proteomic profiling of blood samples from all study groups was performed to identify proteomic biomarkers associated with chronic and severe Cd exposure. This analysis showed statistically significant correlations between urine Cd levels and sixteen proteins. Among these proteins, seven exhibited significantly altered expressions in samples from contaminated areas compared with those from control areas. Therefore, these proteins were selected as potential markers representing Cd-related protein alterations. Multiple reaction monitoring analysis was performed to validate the expression patterns of the proteins and four proteins were found to exhibit consistent trends. The findings show that Cd exposure significantly affects the expression of certain proteins in the human body. Understanding the underlying mechanisms and diseases associated with Cd-induced protein alterations can aid in the development of effective preventive and therapeutic strategies for individuals exposed to Cd-linked pollution.

Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study.

BACKGROUND: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. METHODS: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO2/FIO2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine). The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley's additive explanations (SHAP). RESULTS: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756-0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626-0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. CONCLUSION: Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Biomarkers of the relationship of particulate matter exposure with the progression of chronic respiratory diseases.

A high level of particulate matter (PM) in air is correlated with the onset and development of chronic respiratory diseases. We conducted a systematic literature review, searching the MEDLINE, EMBASE, and Cochrane databases for studies of biomarkers of the effect of PM exposure on chronic respiratory diseases and the progression thereof. Thirty-eight articles on biomarkers of the progression of chronic respiratory diseases after exposure to PM were identified, four of which were eligible for review. Serum, sputum, urine, and exhaled breath condensate biomarkers of the effect of PM exposure on chronic obstructive pulmonary disease (COPD) and asthma had a variety of underlying mechanisms. We summarized the functions of biomarkers linked to COPD and asthma and their biological plausibility. We identified few biomarkers of PM exposure-related progression of chronic respiratory diseases. The included studies were restricted to those on biomarkers of the relationship of PM exposure with the progression of chronic respiratory diseases. The predictive power of biomarkers of the effect of PM exposure on chronic respiratory diseases varies according to the functions of the biomarkers.

Predictive Role of White Blood Cell Differential Count for the Development of Acute Exacerbation in Korean Chronic Obstructive Pulmonary Disease.

Purpose: Chronic obstructive pulmonary disease (COPD) is a respiratory disease characterized by chronic inflammation. Acute exacerbation of COPD (AECOPD) manifests as acute worsening of respiratory symptoms and is associated with high morbidity and mortality. The aim of the present study was to evaluate the predictive value of white blood count (WBC) and its derived inflammatory biomarkers for AECOPD. Methods: From the Korean COPD Subgroup Study cohort, a prospective and multicenter observational study, 826 patients who had baseline complete blood count (CBC) and 3-year AECOPD data were included. Follow-up CBC data at 1 (n = 385), 2 (n = 294), and 3 (n = 231) years were collected for available patients. The primary outcome was the occurrence of AECOPD at 3 years. The risk of AECOPD was evaluated using a binary logistic analysis. Results: The cumulative incidences of 12-, 24-, and 36-month AECOPD were 47.6%, 60.5%, and 67.6%, respectively. Patients with AECOPD at 3 years had higher baseline WBC counts, neutrophil counts, neutrophil/lymphocyte ratio (NLR), and neutrophil/monocyte ratio than those without AECOPD. Higher WBC count, neutrophil count, and NLR were associated with the 3-year occurrence of AECOPD in the univariate analysis, but only the higher neutrophil count was a significant risk factor (odds ratio [OR] = 1.468; 95% confidence interval [CI]: 1.024-2.104) in the covariates-adjusted analysis. In the analysis of changes in inflammatory parameters, a decrease in the platelet count (OR = 0.502; 95% CI: 0.280-0.902) and NLR (OR = 0.535; 95% CI: 0.294-0.974) at 2 years and an increase in the eosinophil count (OR = 2.130; 95% CI: 1.027-4.416) at 3 years were significantly associated with AECOPD in the adjusted analysis. Conclusion: Our data suggest that a high baseline WBC count, particularly neutrophil count, was associated with a higher incidence of long-term AECOPD.

Associations of Night Shift Status During Pregnancy With Small for Gestational Age and Preterm Births.

BACKGROUND: Shift work, including night shift work, during pregnancy has been associated with adverse birth outcomes such as small for gestational age (SGA) infants and preterm births. This study, conducted in South Korea using the Korean CHildren's ENvironmental health Study (Ko-CHENS) cohort, aimed to investigate the association between shift work and night shift status during pregnancy and adverse birth outcomes. METHODS: The Korean Ko-CHENS is a nationwide prospective birth cohort study of children's environmental diseases, conducted by the Ministry of Environment and the National Institute of Environmental Research. This study included pregnant women recruited from 2015 to 2020 for Ko-CHENS Core Cohorts, and 4,944 out of a total of 5,213 pregnant women were selected as final subjects. A logistic regression model was used to identify the risk factors affecting SGA births, preterm births, and low-birth-weight infants, and the odds ratio (OR) was adjusted. This was confirmed by calculating ORs. Maternal age, infant sex, maternal educational status, body mass index, smoking status, alcohol consumption status, parity, gestational diabetes mellitus, preeclampsia, and abortion history were used as adjusted variables. RESULTS: No statistically significant differences were observed in the birth outcomes or maternal working patterns. There were no significant differences in the adjusted odds ratios (aORs) of SGA and preterm births between the non-worker, day worker, and shift worker. However, there was a significant difference in the aORs of SGA between non-workers and night shift workers. (aORs [95% confidence interval], 2.643 [1.193-5.859]). CONCLUSION: Working during pregnancy did not increase the risk of SGA or preterm birth, and night shift work did not increase the risk of preterm birth. However, night-shift work increases the risk of SGA.

Human Pluripotent Stem Cell-Derived Alveolar Organoids: Cellular Heterogeneity and Maturity.

Chronic respiratory diseases such as idiopathic pulmonary fibrosis, chronic obstructive pulmonary disease, and respiratory infections injure the alveoli; the damage evoked is mostly irreversible and occasionally leads to death. Achieving a detailed understanding of the pathogenesis of these fatal respiratory diseases has been hampered by limited access to human alveolar tissue and the differences between mice and humans. Thus, the development of human alveolar organoid (AO) models that mimic in vivo physiology and pathophysiology has gained tremendous attention over the last decade. In recent years, human pluripotent stem cells (hPSCs) have been successfully employed to generate several types of organoids representing different respiratory compartments, including alveolar regions. However, despite continued advances in three-dimensional culture techniques and single-cell genomics, there is still a profound need to improve the cellular heterogeneity and maturity of AOs to recapitulate the key histological and functional features of in vivo alveolar tissue. In particular, the incorporation of immune cells such as macrophages into hPSC-AO systems is crucial for disease modeling and subsequent drug screening. In this review, we summarize current methods for differentiating alveolar epithelial cells from hPSCs followed by AO generation and their applications in disease modeling, drug testing, and toxicity evaluation. In addition, we review how current hPSC-AOs closely resemble in vivo alveoli in terms of phenotype, cellular heterogeneity, and maturity.

Phase Angle as a Reliable Biomarker of Frailty to Predict Postoperative Outcomes in Patients Undergoing Off-Pump Coronary Artery Grafting: A Prospective Observational Study.

OBJECTIVE: To elucidate the association between phase angle (PA) and a composite adverse outcome in patients requiring off-pump coronary artery bypass grafting (OPCAB). DESIGN: A prospective observational study. SETTING: High-volume single center. PARTICIPANTS: A total of 229 adult patients who underwent OPCAB from May 2019 to October 2020. INTERVENTIONS: Each patient underwent bioelectrical impedance analysis, including PA assessment before surgery (PApre), immediately postoperatively (PApost), and 1 day postoperatively (PAPOD1), using an Inbody S10. Frailty index and nutritional assessments also were obtained before surgery. MEASUREMENTS AND MAIN RESULTS: Patient outcomes were assessed using a composite adverse outcome comprising death, myocardial infarction, revascularization, new-onset atrial fibrillation, acute kidney injury, stroke, postoperative pulmonary complications, wound complications, sepsis, reoperation, and/or delirium occurring during hospitalization and over the following year. Patients for whom composite adverse outcomes were reported had lower PApre than those without complications (5.4 ± 0.9 v 6.0 ± 0.9, p < 0.001). The PA was significantly associated with in-hospital and 1-year composite postoperative outcomes. The odds ratios (OR, [95% confidence interval]) for PApre by time were in-hospital complications (0.435 [0.314, 0.604], p < 0.001; 1-year complications: 0.459 [0.330, 0.638], p < 0.001) and PAPOD1 (OR, in-hospital complications: 0.400 [0.277, 0.576], 1-year complications: 0.429 [0.298, 0.619], p < 0.001). The PApre was significantly associated with days alive and out of hospital until 1 year. The cut-off value of PApre for optimal prediction of in-hospital complications was 6.0 (area under the curve: 0.691 [0.623-0.758], p < 0.001). CONCLUSION: Low PA as an indicator of frailty is associated with adverse postoperative outcomes after OPCAB. Low PA may be employed as a noninvasive and practical tool for the prediction of prognosis in patients with coronary artery disease.

Factors Associated with Smokers Attending More Than One Smoking Cessation Clinic Visit.

Smoking remains a primary cause of cancers, cardiovascular and respiratory diseases and death. Globally, efforts have been made to reduce smoking rates, but the addictive nature of nicotine, a key component of tobacco, makes cessation challenging for smokers. Medical interventions including medical advice and pharmacotherapies are effective methods for smoking cessation. The frequency of medical interventions correlates with success in smoking cessation. This study aims to compare the characteristics of the patients who visited the smoking cessation clinic once with those who visited more than once, in order to identify factors that are associated with repeat clinic visits. A total of 81 patients who have visited the smoking cessation clinic in Kangwon National University Hospital were included. Patients answered the questionnaire at their first visit. If the patient visited only once, the outcome was defined as negative and if the patient visited more than once, the outcome was defined as positive. The proportion of patients who answered "within 5 min" to the Fagerstrom Test for Nicotine Dependence's (FTND) 1st question and answered "yes" to the FTND's 6th question was higher in the negative outcome group. In the logistic regression, patients who had withdrawal symptoms previously were associated with positive outcomes (adjusted OR 3.466, 95% CI 1.088-11.034 and p value = 0.0354). Withdrawal symptoms during previous attempts were positively related to visiting the clinic more than once.

MESIA: multi-epigenome sample integration approach for precise peak calling.

The assay for transposase-accessible chromatin with sequencing (ATAC-seq) is the most widely used method for measuring chromatin accessibility. Researchers have included multi-sample replication in ATAC-seq experimental designs. In epigenomic analysis, researchers should measure subtle changes in the peak by considering the read depth of individual samples. It is important to determine whether the peaks of each replication have an integrative meaning for the region of interest observed during multi-sample integration. We developed multi-epigenome sample integration approach for precise peak calling (MESIA), which integrates replication with high representativeness and reproducibility in multi-sample replication and determines the optimal peak. After identifying the reproducibility between all replications, our method integrated multiple samples determined as representative replicates. MESIA detected 6.06 times more peaks, and the value of the peaks was 1.32 times higher than the previously used method. MESIA is a shell-script-based open-source code that provides researchers involved in the epigenome with comprehensive insights.

Effects of heavy metal exposure during pregnancy on birth outcomes.

Exposure to heavy metals such as lead, cadmium, and mercury poses serious health risks to pregnant women because of their high toxicity. In this study, we investigated the associations of heavy metal exposure with birth outcomes of Korean infants. Data of 5,215 women between 2015 and 2019 were analyzed. This study was part of the Korean Children's Environmental Health (Ko-CHENS) study. Linear regression and logistic regression analyses were used to examine effects of concentrations of lead, cadmium, and mercury on birth weight, small for gestational age, and large for gestational age after adjusting for maternal age groups, parity, infant sex, education, income, smoking, drinking, body mass index, stillbirth, premature birth, diabetes, hypertension, and gestational diabetes. Besides adjusting for these covariates, each metal was mutually adjusted to estimate birth weight and large for gestational age status. Maternal cadmium concentrations during early pregnancy (ß = - 39.96; 95% confidence interval (CI): - 63.76, - 16.17) and late pregnancy (ß = - 37.24; 95% CI - 61.63, - 12.84) were significantly associated with birth weight. Cadmium levels during early pregnancy (adjusted OR = 0.637; 95% CI 0.444, 0.912) were also associated with large for gestational age status. Our findings suggest that prenatal cadmium exposure, even at a low level of exposure, is significantly associated with low birth weight.

Foci-Xpress: Automated and Fast Nuclear Foci Counting Tool.

In the nucleus, distinct, discrete spots or regions called "foci" have been identified, each harboring a specific molecular function. Accurate and efficient quantification of these foci is essential for understanding cellular dynamics and signaling pathways. In this study, we present an innovative automated image analysis method designed to precisely quantify subcellular foci within the cell nucleus. Manual foci counting methods can be tedious and time-consuming. To address these challenges, we developed an open-source software that automatically counts the number of foci from the indicated image files. We compared the foci counting efficiency, velocity, accuracy, and convenience of Foci-Xpress with those of other conventional methods in foci-induced models. We can adjust the brightness of foci to establish a threshold. The Foci-Xpress method was significantly faster than other conventional methods. Its accuracy was similar to that of conventional methods. The most significant strength of Foci-Xpress is automation, which eliminates the need for analyzing equipment while counting. This enhanced throughput facilitates comprehensive statistical analyses and supports robust conclusions from experiments. Furthermore, automation completely rules out biases caused by researchers, such as manual errors or daily variations. Thus, Foci-Xpress is a convincing, convenient, and easily accessible focus-counting tool for cell biologists.