Fine particulate matter (FPM) is a major component of air pollution and has emerged as a significant global health concern owing to its adverse health effects. Previous studies have investigated the correlation between bone health and FPM through cohort or review studies. However, the effects of FPM exposure on bone health are poorly understood. This study aimed to investigate the effects of FPM on bone health and elucidate these effects in vitro and in vivo using mice. Micro-CT analysis in vivo revealed FPM exposure decreased bone mineral density, trabecular bone volume/total volume ratio, and trabecular number in the femurs of mice, while increasing trabecular separation. Histological analysis showed that the FPM-treated group had a reduced trabecular area and an increased number of osteoclasts in the bone tissue. Moreover, in vitro studies revealed that low concentrations of FPM significantly enhanced osteoclast differentiation. These findings further support the notion that short-term FPM exposure negatively impacts bone health, providing a foundation for further research on this topic.

Purpose: Identifying and managing risk factors for lower urinary tract symptoms (LUTS) is crucial because it impacts the quality of life of elderly individuals. Lifestyle factors, including physical activity (PA), and their relationship with LUTS have not been well studied. This objective of this study was to investigate the association between PA and LUTS. Materials and Methods: A total of 7,296 men were included in this cross-sectional study. PA was quantified in metabolic equivalent (MET)-hours per week, and LUTS severity was assessed using the international prostate symptom score. Logistic regression was used to analyze the association between PA and LUTS, including voiding and storage symptoms. Results: The average age of the participants was 57.8 years, and the prevalence of LUTS was 41.3%. After adjusting for potential confounders, PA was inversely associated with the prevalence and severity of moderate-to-severe LUTS, showing a dose-response pattern (all p for trend <0.01). Compared to the minimal activity group, which engaged in <5 MET-hours per week of PA, the odds ratios for moderate to severe LUTS were 0.83 (95% confidence interval [CI]: 0.72–0.97) for men engaging in 15–30 MET-hours per week, 0.82 (95% CI: 0.71–0.95) for 30–60 MET-hours per week, and 0.72 (95% CI: 0.62–0.84) for ≥60 MET-hours per week. The possible protective effect of PA was still observed in the additional analysis for voiding and storage symptoms showing the same dose-response pattern (all p for trend <0.01). Conclusions A higher PA level was associated with a lower prevalence and severity of total, voiding, and storage LUTS in a dose-dependent manner in Korean men.

Background: Traditionally, dental implants require a healing period of 4 to 9 months for osseointegration, with longer recovery times considered when bone grafting is needed. This retrospective study evaluates the clinical efficacy of demineralized dentin matrix (DDM) combined with recombinant human bone morphogenetic protein-2 (rhBMP-2) during dental implant placement to expedite the osseointegration period for early loading. Methods: Thirty patients (17 male, 13 female; mean age 55.0 ± 8.8 years) requiring bone grafts due to implant fixture exposure (more than four threads; ≥ 3.2 mm) were included, with a total of 96 implants placed. Implants were inserted using a two-stage protocol with DDM/rhBMP-2 grafts. Early loading was initiated at two months postoperatively in the mandible and three months in the maxilla. Clinical outcomes evaluated included primary and secondary stability (implant stability quotient values), healing period, bone width, and marginal bone level assessed via cone-beam computed tomography. Results: All implants successfully supported final prosthetics with a torque of 50Ncm, without any osseointegration failures. The average healing period was 69.6 days in the mandible and 90.5 days in the maxilla, with significantly higher secondary stability in the mandible (80.7 ± 6.7) compared to the maxilla (73.0 ± 9.2, p < 0.001). Histological analysis confirmed new bone formation and vascularization. Conclusion DDM/rhBMP-2 grafting appears to significantly reduce the healing period, enabling early loading with stable and favorable clinical outcomes.

Purpose: Although some medications trigger the worsening of myasthenia gravis (MG), their clinical influence on patients with MG has not been significantly evaluated. We aimed to investigate whether the risk of clinical worsening of MG increases after administering cautionary drugs in patients with MG. Materials and Methods: This retrospective case-control study was based on the medical records of patients diagnosed with MG between 2007 and 2020. We analyzed the risk of MG worsening in patients exposed to cautionary drugs during the risk period, defined as 6 months from the first exposure to cautionary drugs. The risk of MG worsening in the exposed patients was compared to that in the non-exposed patients, who were individually matched in a 1:1 ratio with exposed cases for sex, age, thymoma, and autoantibodies. Results: Of the 2002 patients diagnosed with MG, 552 (27.6%) were exposed to cautionary drugs. Neuromuscular blocking agents (320 patients) and beta blockers (66123 person-days) were the most frequently prescribed medications. After exact matching, 220 exposed and 220 non-exposed patients were enrolled. The incidence rate of clinical worsening during the risk period was significantly higher in the exposed patients than in the non-exposed patients (odds ratio=4.09; 95% confidence interval, 1.88–8.90;p<0.001). Clinical worsening was observed in 31 (14.1%) of the exposed patients and in 8 (3.6%) of the non-exposed patients. Conclusion The administration of cautionary drugs increased the risk of clinical worsening in patients with MG. Clinicians should be aware of this risk when cautionary drugs need to be administered.

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.

Background: s/Aims: In hepatocellular carcinoma (HCC), which exhibits high mortality and recurrence rates globally, the traits of cancer stem cells (CSCs) that significantly influence recurrence and metastasis are not well understood. CSCs are self-renewing cell types identified in most liquid and solid cancers, contributing to tumor initiation, growth, resistance, recurrence, and metastasis following chemo-radiotherapy or trans-arterial chemoembolization therapy. Methods: CSCs are classified based on the expression of cell surface markers such as CD133, which varies depending on the tumor type. Proteomic analysis of liver cancer cell lines with cancer stem cell potential and HCC cancer cell lines lacking stem cell propensity was conducted to compare and analyze specific expression patterns. Results: Proteomic profiling and enrichment analysis revealed higher expression of the calcium-binding protein S100 family in CD133+ Huh7 cells than in CD133- or wild-type cells. Furthermore, elevated expression of S100 family members was confirmed in an actual CD133+ liver cancer cell line via protein-protein network analysis and quantitative polymerase chain reaction (qPCR). Conclusion The S100 family members are not only new markers of cancer stem cells but will also assist in identifying new treatment strategies for CSC metastasis and tumor advancement.

Objective: We aimed to investigate the associations of the triglyceride-glucose index, which measures insulin resistance, and the incidence of Parkinson’s disease. Methods: Our study used the Health Screening Cohort database of the National Health Insurance Service of South Korea (2002–2019). We included 310,021 participants who had no previous history of Parkinson’s disease and for whom more than 3 triglyceride-glucose index measurements were available. A diagnosis of Parkinson’s disease was determined via the International Classification of Diseases Tenth edition (G20) with a specific reimbursement code for rare intractable diseases and a history of prescriptions for anti-Parkinsonism drugs. Results: During a median of 9.64 years (interquartile range 8.72–10.53), 4,587 individuals (1.5%) had Parkinson’s disease. Based on a multivariable time-dependent Cox proportional hazards model, a per-unit increase in triglyceride-glucose index score was associated with a significantly increased risk of Parkinson’s disease (hazard ratio [HR]: 1.062; 95% confidence interval [CI] 1.007–1.119). In a sensitivity analysis, the triglyceride-glucose index was associated with the incidence of Parkinson’s disease in a non–diabetes mellitus cohort (HR: 1.093; 95% CI 1.025–1.165), but not in the diabetes mellitus cohort (HR: 0.990; 95% CI 0.902–1.087). In a restricted cubic spline analysis, the association between the triglyceride-glucose index and the incidence risk of Parkinson’s disease showed a nonlinear increasing (J-shaped) trend. Conclusion Our study demonstrated that higher triglyceride-glucose index scores were associated with the incidence of Parkinson’s disease in the general population, particularly in a nondiabetic mellitus cohort.

Objective: The Huntington’s Disease Quality of Life Battery for Carers (HDQoL-C) is used to evaluate caregiver quality of life. This study aimed to develop and validate the Korean version of the HDQoL-C (K-HDQoL-C) to assess the burden on Korean caregivers of Huntington’s disease (HD) patients. Methods: A total of 19 HD caregivers (7 females, mean age 55.4±14.6 years) participated in this study. The K-HDQoL-C, a translation of the English version, consisted of demographic information, caring aspects, life satisfaction, and feelings about life. It was administered twice, 2 weeks apart. Internal consistency was evaluated using Cronbach’s α, and test-retest reliability was assessed with intraclass correlation coefficients. The relationship with the Zarit Burden Interview-12 (ZBI-12) was analyzed. Results: The internal consistencies of the K-HDQoL-C were 0.771 (part 2), 0.938 (part 3), and 0.891 (part 4). The test-retest reliability ranged from 0.908 to 0.936. Part 3 was negatively correlated with the ZBI-12, and part 4 was positively correlated with the ZBI-12 (r=-0.780, 0.923; p<0.001). Conclusion The K-HDQoL-C effectively evaluates the challenges faced by HD caregivers, particularly in terms of care aspects and life satisfaction.

Objectives: Lonely death is defined as “a person living in a state of social isolation, disconnected from family, relatives, and others, who dies from suicide, illness, or other causes”. This study investigated the characteristics of individuals who die alone in Korea. Methods: We constructed a database of lonely death cases by linking data from the Korea Crime Scene Investigation Unit of the Korea National Police Agency with National Health Insurance Service (NHIS) records. A descriptive analysis was performed to evaluate the demographics, underlying diseases, and healthcare utilization patterns among lonely death cases. Results: Among the 3122 individuals identified as lonely death cases, 2621 (84.0%) were male and 501 (16.0%) were female. The most common age group was 50-59 years (n=930, 29.8%). The NHIS covered 2161 individuals (69.2%), whereas 961 individuals (30.8%) were enrolled in Medical Aid (MA). The highest number of lonely deaths occurred in Seoul areas, with 1468 cases (47.0%). Mood disorders were diagnosed in 1020 individuals (32.7%), and various alcohol-related diseases, including alcoholic liver disease, were also observed. Outpatient visits increased leading up to death but declined in the final 3 months, while hospitalizations decreased and emergency room visits slightly increased. Conclusions Most lonely death cases involved male in their 50s, with a disproportionately high number of MA beneficiaries compared to the general population. Many of these individuals also experienced mental health issues or alcohol-related disorders. Preventing social isolation and strengthening social safety nets are critical to reducing the occurrence of lonely deaths.