• Journal of Preventive Veterinary Medicine
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• v.41 no.3
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• pp.129-132
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• 2017

The current study identified risk factors associated with porcine circovirus type 2 (PCV2) infection on pig farms in the Republic of Korea using a multinomial logistic regression model to evaluate the PCV2 infection status of pigs at different growth stages. Compulsory disinfection of visitors (odds ratio [OR]: 0.019, 95% confidence interval [CI]: <0.001-0.378, p=0.0095), compulsory registration of visitors (OR: 0.002, 95% CI: <0.001-0.184, p=0.0070), regular blood testing (OR: 0.012, 95% CI: <0.001-0.157, p=0.0007), and running on-farm biosecurity learning programs for workers (OR: 0.156, 95% CI: 0.040-0.604, p=0.0072 and OR: 0.201, 95% CI: 0.055-0.737, p=0.0155, respectively) were identified as factors which could reduce the risk of PCV2 infection. However, visitation by a regular veterinarian (OR: 32.733, 95% CI: 3.768-284.327, p=0.0016) was associated with PCV2 infection.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2889-2892
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• 2014

Death receptor 4 (TRAIL-R1 or DR4) polymorphisms have been associated with cancer risk, but findings have been inconsistent. To estimate the relationship in detail, a meta-analysis was here performed. A search of PubMed was conducted to investigate the association between DR4 C626G, A683C and A1322G polymorphisms and cancer risk, using odds ratios (ORs) with 95% confidence intervals. The results suggested that DR4 C626G and A683C polymorphisms were indeed associated with cancer risk (for C626G, dominant model, OR 0.991, 95%CI 0.866-1.133, p=0.015; for A683C, additive model, OR=1.140, 95%CI: 0.948-1.370, p=0.028; dominant model, OR=1.156, 95%CI: 0.950-1.406, p=0.080) in the Caucasian subgroup. However, the association was not significant between DR4 polymorphism A1322G with cancer risk in Caucasians (For A1322G, additive model: OR 1.085, 95%CI 0.931-1.289, p=0.217; dominant model: OR 1.379, 95%CI 0.934-2.035, p=0.311; recessive model: OR 1.026, 95%CI 0.831-1.268 p=0.429.). In summary, our finding suggests that DR4 polymorphism C626G and A683 rather than A1322G are associated with cancer risk in Caucasians.

• Archives of Plastic Surgery
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• v.51 no.2
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• pp.163-168
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• 2024

Background The study determined to compare the clinical outcomes of traditional gold weight implantation for the correction of paralytic lagophthalmos with those of a newly designed model. Methods In this retrospective cohort study, we enrolled 30 patients (76% females; average age 60.8 ± 12 years) with facial palsy who underwent implantation of either the traditional pretarsal gold weight (PT group; n = 15) or a new supratarsal model (ST group; n = 15) from May 2014 to April 2019. The main outcome measures were the 12-month postoperative weight prominence, weight migration, improvement of lagophthalmos, upper eyelid contour, and upper eyelid ptosis. The secondary outcome was long-term (24 months) reoperative rate. Results The new model group had significantly better eyelid contour (risk ratio [RR] 3.16, 95% confidence interval [CI] 1.62-6.15, p = 0.001), less weight prominence (RR 1.74, 95% CI 1.13-2.70, p = 0.013), less weight migration (RR 1.31, 95% CI 1.12-1.54, p = 0.001), and less eyelid ptosis (RR 2.36, 95% CI 1.21-4.59, p = 0.011) than the traditional model group. Improvement of lagophthalmos was not statistically significant between the two groups (RR 1.44, 95% CI 0.72-2.91, p = 0.303). The 24-month reoperative rate was 53.3% in the PT group versus 13.3% in the ST group (RR 2.00, 95% CI 1.15-3.49, p = 0.015). Conclusion The newly designed supratarsal gold weight showed superior postoperative outcomes than the standard traditional model.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3717-3721
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• 2012

Purpose: Any association between the CYP1A1 Ile462Val polymorphism and endometrial cancer risk remains inconclusive. For a more precise estimate, we performed the present meta-analysis. Methods: PUBMED, OVID and EMBASE were searched for the studies which met inclusion criteria. Data in all eligible studies were evaluated and extracted by two authors independently. The meta-analysis estimated pooled odds ratio (OR) with 95% confidence interval (CI) for endometrial cancer risk attributable to the CYP1A1 Ile462Val polymorphism. Results: A total of 7 studies were included in this meta-analysis. The results indicated no association between endometrial cancer risk and the CYP1A1 Ile462Val polymorphism (for Val vs Ile allele model [OR 1.09, 95% CI 0.73-1.62]; for Val.Val vs Ile.Ile genotype model [OR 1.54, 95% CI 0.56-4.23]; for (Ile.Val + Val.Val) vs Ile.Ile genotpye model [OR 1.08, 95% CI 0.71-1.63]; for Val.Val vs (Ile.Ile + Ile.Val) genotype model [OR 1.46, 95% CI 0.53-4.04]). Conclusions: This meta-analysis suggests that there is no association between endometrial cancer risk and the CYP1A1 Ile462Val polymorphism.

• Journal of Veterinary Clinics
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• v.34 no.2
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• pp.140-145
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• 2017

The goal of this study was to investigate risk factors associated with porcine reproductive and respiratory syndrome (PRRS) in pig farms in the Republic of Korea using logistic regression and a multilevel model. A cross-sectional study was applied to 305 pig farms with a questionnaire-based interview by veterinarians between March 2014 and February 2015. The questionnaire comprised eight categories: proximity to neighbors, disinfection, visitors, vehicles, insecticides, wild animals, gilts, and feeding. In total, 61 questions in eight categories related to pig farm biosecurity were investigated. Farms were classified as PRRS stable or unstable based on the results of an antibody test and PCR. For univariate analysis, keeping production records with computers (OR = 0.283, 95% CI = 0.056 - 1.425), accredited farm with no use of antibiotics (OR = 0.412, 95% CI = 0.134 - 1.269), reviewing health record of semen prior to purchasing (OR = 0.492, 95% CI = 0.152 - 1.589), complete isolation of runt pigs (OR = 0.264, 95% CI = 0.084 - 0.829), compulsory registering for visitors (OR = 0.424, 95% CI = 0.111 - 1.612), keeping records of insecticide history (OR = 0.406, 95% CI = 0.089 - 1.846), routine on-farm monitoring by veterinarians (OR = 0.314, 95% CI = 0.069 - 1.423), and use of on-farm checklist for biosecurity monitoring (OR = 0.313, 95% CI = 0.063 - 1.553) were found to decrease the probability of PRRS infection. Multivariate and multilevel analysis revealed only two factors, complete isolation of runt pigs (OR = 0.165, 95% CI = 0.045 - 0.602 and OR = 0.208, 95% CI = 0.055 - 0.782) and compulsory registering for visitors (OR = 0.106, 95% CI = 0.017 - 0.655 and OR = 0.119, 95% CI = 0.017 - 0.809) were found to decrease the probability of PRRS infection. The intracluster correlation coefficient of a province for multilevel model was 0.05. The results of this study might facilitate biosecurity measures for individual farms to reduce the probability of PRRS infection.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7905-7909
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• 2015

Several studies reported there was a polymorphism (rs531564 C > G) in miR-124 gene. To investigate the MiR-124 rs531564 polymorphism and cancer risk. We conducted a literature search of the Medline, Embase and Wangfang Medicine databases to identify all relevant studies for this meta-analysis. We determined that the miR-124 rs531564 polymorphism was significantly associated with decreased risks of cancers in the allelic model (G vs C, OR=0.71, 95% CI=0.53-0.94, P=0.02), homozygote model (GG vs CC, OR=0.42, 95% CI=0.26-0.66, P=0.0002), dominant model (GG/GC vs CC, OR=0.71, 95% CI=0.51-0.98, P=0.04) and recessive model (GG vs GC/CC, OR=0.43, 95% CI=0.27-0.69, P=0.0004). In an analysis stratified by cervical cancer group, significant associations were observed in the allelic model (G vs C, OR=0.46, 95% CI=0.32-0.66, P<0.0001), and dominant model (GG/GC vs CC, OR=0.45, 95% CI=0.3-0.66, P<0.0001). Subgroup analysis also revealed a decreased risk for esophageal squamous cell carcinoma in the homozygote model (GG vs CC, OR=0.45, 95% CI=0.27-0.75, P=0.002) and recessive model (GG vs GC/CC, OR=0.46, 95% CI=0.28-0.75, P=0.002). This meta-analysis suggests that the miR-124 rs531564 C > G polymorphism is an important risk factor for cancers among the Chinese population.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5621-5626
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• 2014

N-acetyltransferase 2 (NAT2) is a polymorphic enzyme that plays an important role in the metabolism of various potential carcinogens. In recent years, a number of studies have been carried out to investigate the relationship between the rs1799930 and rs1799931 polymorphism in NAT2 and cancer risk in multiple populations for different types of cancer. However, the results were not consistent. Therefore, we performed a meta-analysis to further explore the relationship between NAT2 polymorphism and the risk of cancer. A total of 21 studies involving 15, 450 subjects for rs1799930 and 13, 011 subjects for rs1799931 were included in this meta-analysis. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess strength of associations. We also evaluated the publication bias and performed a sensitivity analysis. Overall, our results showed an apparent significant association between the NAT2 rs1799930 polymorphism and cancer susceptibility in Asians (GA vs. GG: OR=1.22, 95% CI=1.03-1.45; dominant model: OR=1.22, 95% CI=1.03-1.43) and population-based controls (GA vs. GG: OR=1.10, 95% CI=1.01-1.19; dominant model: OR=1.09, 95% CI=1.01-1.18). In contrast, a significant association was observed between the NAT2 rs1799931 G>A polymorphism and decreased cancer susceptibility in overall meta-analysis (AA vs. GG: OR=0.55, 95% CI=0.33-0.93; GA vs. GG: OR=1.00, 95% CI=0.88-1.14; dominant model: OR=0.97, 95% CI=0.86-1.10; recessive model: OR=0.56, 95% CI=0.34-0.94) and the Asian group (AA vs. GG: OR=0.50, 95% CI=0.26-0.94; recessive model, OR=0.50, 95% CI=0.27-0.94). We found that the NAT2 rs1799930 may be a risk factor, while the NAT2 rs1799931 polymorphism is associated with a decreased risk of cancer and is likely a protective factor against cancer development.

• Journal of Preventive Medicine and Public Health
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• v.36 no.4
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• pp.377-382
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• 2003

Objectives : The purpose of this study was to investigate the predictor associated transitions with each stage of smoking cessation based on the Transtheoretical Model, and to provide basic data for smoking cessation programs for adolescents. Methods : The participants were 297 current and former smokers, obtained from stratified random sampling of 2nd graders from 127 high schools in B cities. The data were collected between April 6th and 16th 2002, using a structured self-report questionnaire, and analyzed using a multiple logistic regression, with the SPSS program for Windows (Version 10.0). Results : The predictors of transition from precontemplation to contemplation were consciousness raising (OR=1.22, 95% CI:1.07-1.40), coping pros (OR=.84, 95% CI:.70-1.00) and attitude of parents to smoking (OR=2.97,95% Cl: 94-9.24). The predictors of transition from contemplation to preparation were helping relationships (OR=.83, 95% CI:.72-.96), self-liberation (OR=1.15, 95% CI: 99-1.33) and nicotine dependence (OR=.76, 95% CI: 56-1.03). The only predictor of transition from preparation to action was the social pros (OR=.66, 95% CI:.57-.82). The predictors of transition from action to maintenance were self-reevaluation (OR=.81, 95% CI:.71-.92) and negative affective situation (OR=.85, 95% CI:.72-1.00). Conclusion : Adequate examination on the factors for predicting the transitional stages of change for smoking cessation in Koreans are presented in this study. The results of this study will become the pillar of smoking cessation Planning and application programs.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.343-354
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• 2022

Objective: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children. Materials and Methods: This retrospective multi-center study consisted of a development dataset acquired from two hospitals (n = 149 and 264) and an external test set (n = 95) from a third hospital. Datasets included children with head trauma who underwent both skull radiography and cranial computed tomography (CT). The development dataset was split into training, tuning, and internal test sets in a ratio of 7:1:2. The reference standard for skull fracture was cranial CT. Two radiology residents, a pediatric radiologist, and two emergency physicians participated in a two-session observer study on an external test set with and without AI assistance. We obtained the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity along with their 95% confidence intervals (CIs). Results: The AI model showed an AUROC of 0.922 (95% CI, 0.842-0.969) in the internal test set and 0.870 (95% CI, 0.785-0.930) in the external test set. The model had a sensitivity of 81.1% (95% CI, 64.8%-92.0%) and specificity of 91.3% (95% CI, 79.2%-97.6%) for the internal test set and 78.9% (95% CI, 54.4%-93.9%) and 88.2% (95% CI, 78.7%-94.4%), respectively, for the external test set. With the model's assistance, significant AUROC improvement was observed in radiology residents (pooled results) and emergency physicians (pooled results) with the difference from reading without AI assistance of 0.094 (95% CI, 0.020-0.168; p = 0.012) and 0.069 (95% CI, 0.002-0.136; p = 0.043), respectively, but not in the pediatric radiologist with the difference of 0.008 (95% CI, -0.074-0.090; p = 0.850). Conclusion: A deep learning-based AI model improved the performance of inexperienced radiologists and emergency physicians in diagnosing pediatric skull fractures on plain radiographs.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.1154-1162
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• 2019

China is undertaking an energy reform from fossil fuels to clean energy to accomplish $CO_2$ intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%-53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed.