The purpose of this study was to obtain instructions for size selection of prefabricated crown and tooth reduction by 3-dimensional analysis of the size and shape of the maxillary primary central and lateral incisors and prefabricated crowns (celluloid strip, resin veneered stainless steel, and zirconia crowns).The maxillary primary central and lateral incisors of 300 Korean children was scanned with three types of prefabricated crown to create standard three-dimensional tooth models and prefabricated crowns. The shapes of the prefabricated crowns and natural teeth were compared according to four parameters (mesio-distal width, height, labio-palatal width, and labial surface curvature coefficient) and calculated the amount of tooth reduction required for each prefabricated crown.The size 2 resin veneered stainless steel crown, size 1 zirconia crown, and size 2 celluloid strip crown were most similar in shape to the primary central incisor. The size 3 rein veneered stainless steel crown, size 2 zirconia crown, and size 3 celluloid strip crown were most similar to the primary lateral incisor.The amount of tooth reduction was similar in both maxillary primary central and lateral incisors. The incisal reduction was greatest for the zirconia crown. At the proximal surface, the zirconia and celluloid strip crowns required a similar amount of tooth reduction, but more than the resin veneered stainless steel crown. The labial surface reduction was greatest for the zirconia crown. The degree of lingual surface reduction was not significant among the three prefabricated crowns.Among the assessment parameters, mesio-distal crown width was the most important for choosing a prefabricated crown closest to the actual size of the natural crown.
Child ; Crowns ; Humans ; Incisor ; Stainless Steel ; Tooth

The original version of this article contained an error in authorship. The correct information of authorship should be as follows. The authors would like to apologize for any inconvenience caused.

Objectives: This study aimed to compare the Delta, Greenland, and Monte Carlo methods for estimating 95% confidence intervals (CIs) of the population-attributable fraction (PAF). The objectives were to identify the optimal method and to determine the influence of primary parameters on PAF calculations. Methods: A dataset was simulated using hypothetical values for primary parameters (population, relative risk [RR], prevalence, and variance of the beta estimator ) involved in PAF calculations. Three methods (Delta, Greenland, and Monte Carlo) were used to estimate the 95% CIs of the PAFs. Perturbation analysis was performed to assess the sensitivity of the PAF to changes in these parameters. An R Shiny application, the “GDM-PAF CI Explorer,” was developed to facilitate the analysis and visualization of these computations. Results: No significant differences were observed among the 3 methods when both the RR and p-value were low. The Delta method performed well under conditions of low prevalence or minimal RR, while Greenland’s method was effective in scenarios with high prevalence. Meanwhile, the Monte Carlo method calculated 95% CIs of PAFs that were stable overall, though it required intensive computational resources. In a novel approach that utilized perturbation for sensitivity analysis, was identified as the most influential parameter in the estimation of CIs. Conclusions This study emphasizes the necessity of a careful approach for comparing 95% CI estimation methods for PAFs and selecting the method that best suits the context. It provides practical guidelines to researchers to increase the reliability and accuracy of epidemiological studies.

Objectives: This study aimed to compare the Delta, Greenland, and Monte Carlo methods for estimating 95% confidence intervals (CIs) of the population-attributable fraction (PAF). The objectives were to identify the optimal method and to determine the influence of primary parameters on PAF calculations. Methods: A dataset was simulated using hypothetical values for primary parameters (population, relative risk [RR], prevalence, and variance of the beta estimator ) involved in PAF calculations. Three methods (Delta, Greenland, and Monte Carlo) were used to estimate the 95% CIs of the PAFs. Perturbation analysis was performed to assess the sensitivity of the PAF to changes in these parameters. An R Shiny application, the “GDM-PAF CI Explorer,” was developed to facilitate the analysis and visualization of these computations. Results: No significant differences were observed among the 3 methods when both the RR and p-value were low. The Delta method performed well under conditions of low prevalence or minimal RR, while Greenland’s method was effective in scenarios with high prevalence. Meanwhile, the Monte Carlo method calculated 95% CIs of PAFs that were stable overall, though it required intensive computational resources. In a novel approach that utilized perturbation for sensitivity analysis, was identified as the most influential parameter in the estimation of CIs. Conclusions This study emphasizes the necessity of a careful approach for comparing 95% CI estimation methods for PAFs and selecting the method that best suits the context. It provides practical guidelines to researchers to increase the reliability and accuracy of epidemiological studies.

Objectives: This study aimed to compare the Delta, Greenland, and Monte Carlo methods for estimating 95% confidence intervals (CIs) of the population-attributable fraction (PAF). The objectives were to identify the optimal method and to determine the influence of primary parameters on PAF calculations. Methods: A dataset was simulated using hypothetical values for primary parameters (population, relative risk [RR], prevalence, and variance of the beta estimator ) involved in PAF calculations. Three methods (Delta, Greenland, and Monte Carlo) were used to estimate the 95% CIs of the PAFs. Perturbation analysis was performed to assess the sensitivity of the PAF to changes in these parameters. An R Shiny application, the “GDM-PAF CI Explorer,” was developed to facilitate the analysis and visualization of these computations. Results: No significant differences were observed among the 3 methods when both the RR and p-value were low. The Delta method performed well under conditions of low prevalence or minimal RR, while Greenland’s method was effective in scenarios with high prevalence. Meanwhile, the Monte Carlo method calculated 95% CIs of PAFs that were stable overall, though it required intensive computational resources. In a novel approach that utilized perturbation for sensitivity analysis, was identified as the most influential parameter in the estimation of CIs. Conclusions This study emphasizes the necessity of a careful approach for comparing 95% CI estimation methods for PAFs and selecting the method that best suits the context. It provides practical guidelines to researchers to increase the reliability and accuracy of epidemiological studies.

Objectives: This study aimed to compare the Delta, Greenland, and Monte Carlo methods for estimating 95% confidence intervals (CIs) of the population-attributable fraction (PAF). The objectives were to identify the optimal method and to determine the influence of primary parameters on PAF calculations. Methods: A dataset was simulated using hypothetical values for primary parameters (population, relative risk [RR], prevalence, and variance of the beta estimator ) involved in PAF calculations. Three methods (Delta, Greenland, and Monte Carlo) were used to estimate the 95% CIs of the PAFs. Perturbation analysis was performed to assess the sensitivity of the PAF to changes in these parameters. An R Shiny application, the “GDM-PAF CI Explorer,” was developed to facilitate the analysis and visualization of these computations. Results: No significant differences were observed among the 3 methods when both the RR and p-value were low. The Delta method performed well under conditions of low prevalence or minimal RR, while Greenland’s method was effective in scenarios with high prevalence. Meanwhile, the Monte Carlo method calculated 95% CIs of PAFs that were stable overall, though it required intensive computational resources. In a novel approach that utilized perturbation for sensitivity analysis, was identified as the most influential parameter in the estimation of CIs. Conclusions This study emphasizes the necessity of a careful approach for comparing 95% CI estimation methods for PAFs and selecting the method that best suits the context. It provides practical guidelines to researchers to increase the reliability and accuracy of epidemiological studies.

PURPOSE: High mobility group box 1 (HMGB1) plays a central role in the pathogenesis of sepsis and multiple organ dysfunction syndromes. We investigated the associations of a single nucleotide polymorphism (SNP; rs1045411) in HMGB1 with various clinical parameters, severity, and prognosis in patients with sepsis, severe sepsis, or septic shock. MATERIALS AND METHODS: We enrolled 212 adult patients followed for 28 days. All patients were genotyped for rs1045411, and the serum levels of HMGB1 and several cytokines were measured. RESULTS: The proportions of patients according to genotype were GG (71.2%), GA (26.4%), and AA (2.4%). Among patients with chronic lung disease comorbidity, patients with a variant A allele had higher positive blood culture rates and higher levels of various cytokines [interleukin (IL)-1beta, IL-6, IL-10, IL-17, and tumor necrosis factor-alpha] than those with the GG genotype. In the analysis of those with diabetes as a comorbidity, patients with a variant A allele had higher blood culture and Gram-negative culture rates than those with GG genotypes; these patients also had a higher levels of IL-17. In the analysis of those with sepsis caused by a respiratory tract infection, patients with a variant A allele had higher levels of IL-10 and IL-17 (all p<0.05). This polymorphism had no significant impact on patient survival. CONCLUSION: The variant A allele of rs1045411 appears to be associated with a more severe inflammatory response than the GG genotype under specific conditions.
Adult ; Aged ; Alleles ; Asian Continental Ancestry Group/genetics ; China/epidemiology ; Cytokines/*blood/*genetics ; Female ; Genotype ; HMGB1 Protein/blood/*genetics ; Humans ; Interleukin-10/genetics ; Interleukin-17/genetics ; Interleukin-6/blood ; Male ; Middle Aged ; Polymorphism, Genetic/*genetics ; Polymorphism, Single Nucleotide/*genetics ; Prognosis ; Republic of Korea ; Sepsis/immunology/*metabolism/mortality ; Shock, Septic/immunology/*metabolism/mortality ; Survival ; Tumor Necrosis Factor-alpha/genetics

Umbilical cord blood (UCB)-derived mesenchymal stem cells (MSCs) have been introduced as a possible therapy in acute lung injury and acute respiratory distress syndrome (ARDS). This case history is reported of a 59-yr-old man who was treated with MSCs in the course of ARDS and subsequent pulmonary fibrosis. He received a long period of mechanical ventilation and weaning proved difficult. On hospital day 114, he underwent the intratracheal administration of UCB-derived MSCs at a dose of 1 x 10(6)/kg. After cell infusion, an immediate improvement was shown in his mental status, his lung compliance (from 22.7 mL/cmH2O to 27.9 mL/cmH2O), PaO2/FiO2 ratio (from 191 mmHg to 334 mmHg) and his chest radiography over the course of three days. Even though he finally died of repeated pulmonary infection, our current findings suggest the possibility of using MSCs therapy in an ARDS patient. It is the first clinical case of UCB-derived MSCs therapy ever reported.
Bacterial Infections/diagnosis ; Drug Resistance, Multiple, Bacterial ; Fetal Blood/*cytology ; Humans ; Male ; *Mesenchymal Stem Cell Transplantation ; Mesenchymal Stromal Cells/*cytology ; Middle Aged ; Respiratory Distress Syndrome, Adult/complications/radiography/*surgery ; Seizures/etiology ; Shock, Septic/diagnosis ; Tomography, X-Ray Computed ; Treatment Outcome

BACKGROUND/OBJECTIVES: Arterial stiffness and endothelial dysfunction are 2 of the independent predictors for cardiovascular disease, while Acanthopanax senticosus Harms (ASH) is a traditional medicinal plant that can improve cardiovascular health. This study aimed to investigate the efficacy of the fruit of ASH on vascular function in apparently healthy subjects. SUBJECTS/METHODS: A 12-week, randomized, double-blind, placebo-controlled design, consisting of healthy adults with at least 2 of the following 3 conditions: borderline high blood pressure (BP; 120 mmHg ≤ systolic BP ≤ 160 mmHg or 80 mmHg ≤ diastolic BP ≤ 100 mmHg), smoking (≥10 cigarettes/day), and borderline blood lipid levels (220 ≤ total cholesterol ≤ 240, 130 ≤ low density lipoprotein cholesterol ≤ 165, or 150 ≤ triglyceride ≤ 220 mg/dL). Randomly assigned 76 subjects who received a placebo or 2 doses of ASH fruit (low, 500 mg/day; high, 1,000 mg/day) completed the intervention. Brachial-ankle pulse wave velocity (baPWV), flow-mediated dilation, carotid intima-media thickness, and BP were measured both at baseline and following the 12-week intervention. Endothelial nitric oxide synthase (eNOS) phosphorylation was assessed by western blotting. RESULTS: Compared with the placebo group, the low-dose group showed more significant changes after the 12-week intervention period in terms of systolic BP (0.1 vs. −7.7 mmHg; P = 0.044), baPWV (31.3 vs. −98.7 cm/s; P = 0.007), and the ratio of phospho-eNOS/eNOS (0.8 vs. 1.22; P = 0.037). CONCLUSIONS These results suggest that ASH fruit extract at 500 mg/day has the potential to improve BP and arterial stiffness via endothelial eNOS activation in healthy adults with smoking and the tendency of having elevated BP or blood lipid parameters.

Objectives: This study aimed to identify the current patterns of cancer incidence and estimate the projected cancer incidence and mortality between 2020 and 2035 in Korea. Methods: Data on cancer incidence cases were extracted from the Korean Statistical Information Service from 2000 to 2017, and data on cancer-related deaths were extracted from the National Cancer Center from 2000 to 2018. Cancer cases and deaths were classified according to the International Classification of Diseases, 10th edition. For the current patterns of cancer incidence, age-standardized incidence rates (ASIRs) and age-standardized mortality rates were investigated using the 2000 mid-year estimated population aged over 20 years and older. A joinpoint regression model was used to determine the 2020 to 2035 trends in cancer. Results: Overall, cancer cases were predicted to increase from 265 299 in 2020 to 474 085 in 2035 (growth rate: 1.8%). The greatest increase in the ASIR was projected for prostate cancer among male (7.84 vs. 189.53 per 100 000 people) and breast cancer among female (34.17 vs. 238.45 per 100 000 people) from 2000 to 2035. Overall cancer deaths were projected to increase from 81 717 in 2020 to 95 845 in 2035 (average annual growth rate: 1.2%). Although most cancer mortality rates were projected to decrease, those of breast, pancreatic, and ovarian cancer among female were projected to increase until 2035. Conclusions These up-to-date projections of cancer incidence and mortality in the Korean population may be a significant resource for implementing cancer-related regulations or developing cancer treatments.