• Journal of Animal Science and Technology
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• v.54 no.6
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• pp.395-400
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• 2012

This study was conducted to estimate the growth curve parameters for the body weight (BW) and body length (BL) of miniature pigs in Korea. Growth curve parameters were estimated through a nonlinear regression model using Gompertz, Logistic, and von Bertalanffy methods. A total of 25 piglets were measured monthly from birth up to 15 months of age to estimate both body weight and length. Results showed that the estimated average values for the body weight (body length) were 31.83 kg (58.77 cm) for the mature weight (A), 3.06 (1.74) for the growth ratio (${\beta}$), and 0.28 (0.52) for the maturing rate (${\kappa}$). Average inflection points showing maximum growth rate estimated each month for body weight were 3.97 kg and 11.70 cm, while for the body length were 1.06 kg and 21.61 cm. Moreover, the estimated maturation rates of the body weight and length for the group of Sire 1 were 0.22 and 0.40 respectively, whereas for the group of Sire 2 these values were 0.34 and 0.39. On the other hand, for the groups of Dam 1, Dam 2, and Dam 3, maturation rates for their body weights were 0.26, 0.28 and 0.33 respectively, while for their body lengths these values were 0.43, 0.37, and 0.38, respectively. The study also indicated a negative relationship between the values of mature weight and maturity rate for the body weight will result to a higher inflection point which is in contrast for the body length where results show that a positive relationship between the values of mature length and the maturity rate will result to a higher inflection point. Furthermore, the growth performance of miniature pig varies across stages but using these estimated growth curve parameters could improve the genetic traits of miniature pig.

• The Korean Journal of Vision Science
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• v.20 no.4
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• pp.431-442
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• 2018

Purpose : The purpose of this study was to investigate subjective symptoms according to the wearing, purchase and fitting status of soft contact lens wearers, and consumer perception of base curve. Methods : A survey was conducted for those who visited optical shops and lens shops in Seoul from June to August 2018. A total of 98 answer sheets they submitted were used for the analysis. The chi-square test and Fisher's exact test were used to compare subjective symptoms (dryness, glare, uncomfortable fitting, and decreased vision) according to whether fitting condition is screened (case history and push-up test, ect relevant to wearing sensation), and the odds ratio (OR) was obtained by the logistic regression analysis. Results : When the contact lenses were purchased, the rate of which the visual acuity test was performed was 86.6% at optical shop and 64.7% at lens shop. When purchasing contact lens and the contact lens was not tested for fitting, they more experienced dryness (OR 4.41, 95% CI 1.25-15.62) and uncomfortable fitting (OR 2.68, 95% CI 1.08-6.64) than testing for fitting. In addition, it was investigated that 87.8% of contact lens wearers did not know about the term base curve, 92.9% did not listen to an explanation related to the base curve when purchasing contact lenses, and 96.9% did not experience with base curve test. Conclusion : It would be thought that satisfaction of the contact lens fitting of existing consumers should be improved by changing a proper base curve by confirming the fitting condition when prescribing soft contact lens.

• Journal of Animal Science and Technology
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• v.48 no.1
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• pp.29-38
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• 2006

The objective of this study was to estimate genetic variances of growth curve parameters in Hanwoo cows. The data used in this study were records from 1,083 Hanwoo cows raised at Hanwoo Experiment Station, National Livestock Research Institute(NLRI). First evaluation model(Model I) fit year-season of birth and age of dam as fixed effects and second model(Model II) added age at the final weight as a linear covariate to Model I. Heritability estimates of A, b and k from Gompertz model were 0.22, 0.11 and 0.07 using modelⅠ and 0.28, 0.11 and 0.12 using modelⅡ. Those from Von Bertalanffy model were 0.22, 0.11 and 0.07 using modelⅠ, 0.28, 0.11 and 0.12 using modelⅡ. Heritability estimates of A, b and k from Logistic model were 0.14, 0.07 and 0.05 using modelⅠ, 0.18, 0.07 and 0.12 using modelⅡ. Heritability estimates of A from Gompertz model were higher than those from Von Bertalanffy model or Logistic model in both model Ⅰand model Ⅱ. Heritability estimates of b from Logistic model were higher than those from Gompertz model or Von Bertalanffy model in both modelⅠand model Ⅱ. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight, 12 month weight, 18 month weight, 24 month weight, 36 month weight were after linear age adjustment 0.27, 0.11, 0.19, 0.14, 0.16, 0.23, 0.52 and 0.32, respectively. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight and 24 month weight fit by Gompertz model were larger than those estimated from linearly adjusted data. Heritability estimates of 12 month weight, 18 month weight and 36 month weight fit by Von Bertalanffy model were larger than those estimated from linearly adjusted data. In the multitrait analyses for parameters from Gompertz model, genetic and phenotypic correlations between A and k parameters were －0.47 and －0.67 using modelⅠand －0.56 and －0.63 using model Ⅱ. Those between the A and b parameters were 0.69 and 0.34 using modelⅠand 0.72 and 0.37 using model Ⅱ. Those between the b and k parameters were －0.26 and 0.01 using modelⅠand －0.30 and 0.01 using model Ⅱ. In the multitrait analyses for parameters from Von Bertalanffy model, genetic and phenotypic correlations between A and k parameters were －0.49 and －0.67 suing model Ⅰ and －0.57 and －0.70 using modelⅡ. Those between the A and b parameters were 0.61 and 0.33 using modelⅠ and 0.60 and 0.30 using model Ⅱ. Those between the b and k parameters were －0.20 and 0.02 using modelⅠ and 0.16 and 0.00 using modelⅡ. In the multitrait analyses for parameters from Logistic model, genetic and phenotypic correlations between A and k parameters were －0.43 and －0.67 using model Ⅰ and －0.50 and －0.63 using modelⅡ. Those between the A and b parameters were 0.47 and 0.22 using modelⅠ and 0.38 and 0.24 using modelⅡ. Those between the b and k parameters were －0.09 and 0.02 using model Ⅰ and －0.02 and 0.13 using model Ⅱ.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.457-462
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• 2020

Osteoporosis is a disease that occurs mainly in the elderly and increases the risk of fractures due to structural deterioration of bone mass and tissues. The purpose of this study are to assess the relationship between nutritional components and osteoporosis and to evaluate models for predicting osteoporosis based on nutrient components. In experimental method, association was performed using binary logistic regression, and predictive models were generated using the naive Bayes algorithm and variable subset selection methods. The analysis results for single variables indicated that food intake and vitamin B2 showed the highest value of the area under the receiver operating characteristic curve (AUC) for predicting osteoporosis in men. In women, monounsaturated fatty acids showed the highest AUC value. In prediction model of female osteoporosis, the models generated by the correlation based feature subset and wrapper based variable subset methods showed an AUC value of 0.662. In men, the model by the full variable obtained an AUC of 0.626, and in other male models, the predictive performance was very low in sensitivity and 1-specificity. The results of these studies are expected to be used as the basic information for the treatment and prevention of osteoporosis.

• Journal of the Korean Society of Radiology
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• v.11 no.3
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• pp.131-137
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• 2017

This study investigated the risk factor of Gallbladder stone in Busan and Kyungnam area. The subjects of the experiment was performed with patients by abdominal ultrasonography among the patients who came to the P hospital from June 2016 to December 2016. Among them, risk factors were analyzed on 353 people at the same time when abdominal ultrasonography and hematological test. The statistical analysis of risk factors related to the Gallbladder stone was performed by independent t-test and chi-square test. In consider of difference verification result for calculations odds ratio about independent variables, multiple logistic regression analysis to conduct verify adequacy by calculating forecasting model from variable. As a result, Gallbladder stone risk factors have relevance to age ${\gamma}GTP$ with probability model and values to calculated. Age was showed sensitivity 49.7%, specificity 82.2%, receiver operating characteristic area under curve 0.724. Forecasting probability sensitivity 69.3%, specificity 62.4%, receiver operating characteristic area under curve 0.699 showed, ${\gamma}GTP$ confirmed validity of forecasting model.

• Investigative Magnetic Resonance Imaging
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• v.25 no.3
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• pp.164-171
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• 2021

Purpose: Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD). Brain atrophy in this disease spectrum begins in the medial temporal lobe structure, which can be recognized by magnetic resonance imaging. To overcome the unsatisfactory inter-observer reliability of visual evaluation, quantitative brain volumetry has been developed and widely investigated for the diagnosis of MCI and AD. The aim of this study was to assess the prediction accuracy of quantitative brain volumetry using a fully automated segmentation software package, NeuroQuant^®, for the diagnosis of MCI. Materials and Methods: A total of 418 subjects from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease cohort were included in our study. Each participant was allocated to either a cognitively normal old group (n = 285) or an MCI group (n = 133). Brain volumetric data were obtained from T1-weighted images using the NeuroQuant software package. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to investigate relevant brain regions and their prediction accuracies. Results: Multivariate logistic regression analysis revealed that normative percentiles of the hippocampus (P < 0.001), amygdala (P = 0.003), frontal lobe (P = 0.049), medial parietal lobe (P = 0.023), and third ventricle (P = 0.012) were independent predictive factors for MCI. In ROC analysis, normative percentiles of the hippocampus and amygdala showed fair accuracies in the diagnosis of MCI (area under the curve: 0.739 and 0.727, respectively). Conclusion: Normative percentiles of the hippocampus and amygdala provided by the fully automated segmentation software could be used for screening MCI with a reasonable post-processing time. This information might help us interpret structural MRI in patients with cognitive impairment.

• Journal of Trauma and Injury
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• v.34 no.1
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• pp.3-12
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• 2021

Purpose: To evaluate the severity of trauma, many scoring systems and predictive models have been presented. The quick Sequential Organ Failure Assessment (qSOFA) is a simple scoring system based on vital signs, and we expect it to be easier to apply to trauma patients than other trauma assessment tools. Methods: This study was a cross-sectional study of trauma patients who visited the emergency department of Jeju National University Hospital. We excluded patients under the age of 18 years and unknown outcomes. We calculated the qSOFA, the Modified Early Warning Score (mEWS), Revised Trauma Score (RTS), and Injury Severity Score (ISS) based on patients' initial vital signs and assessments performed in the emergency department (ED). The primary outcome was mortality within 14 days of trauma. We analyzed qSOFA scores using multivariate logistic regression analysis and compared the predictive accuracy of these scoring systems using the area under the receiver operating characteristic curve (AUROC). Results: In total, 27,764 patients were analyzed. In the multivariate logistic regression analysis of the qSOFA, the adjusted odds ratios with 95% confidence interval (CI) for mortality relative to a qSOFA score of 0 were 27.82 (13.63-56.79) for a qSOFA score of 1, 373.31 (183.47-759.57) for a qSOFA score of 2, and 494.07 (143.75-1698.15) for a qSOFA score of 3. In the receiver operating characteristic (ROC) curve analysis for the qSOFA, mEWS, ISS, and RTS in predicting the outcomes, for mortality, the AUROC for the qSOFA (AUROC [95% CI]; 0.912 [0.871-0.952]) was significantly greater than those for the ISS (0.700 [0.608-0.793]) and RTS (0.160 [0.108-0.211]). Conclusions: The qSOFA was useful for predicting the prognosis of trauma patients evaluated in the ED.

• Korean Journal of Applied Biomechanics
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• v.31 no.1
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• pp.1-15
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• 2021

Objective: The aim of this study was to investigate 1) the difference in static lower extremity alignment (SLEA) according to a history of lateral ankle sprain (LAS), 2) to identify SLEA factors affecting LAS, and 3) to present the cut-off value and 4) the usefulness and limitations of the SLEA measurement. Method: This case-control study recruited 88 men (age: 27.78±4.69 yrs) and 39 women (age: 24.62±4.20 yrs) subjects with and without LAS. SLEA measurement protocol included Q angle, tibiofemoral angle, genu recurvatum, rear foot (RF) angle, tibal varum and torsion, navicular drop, ankle dorsiflexion range of motion (DF ROM). Independent t-test, logistic regression and receiver operating characteristic (ROC) curve were used for statistical analysis. Results: Men with a history of LAS had significantly smaller Q angles both in standing and in supine position, while women with a history of LAS had significantly greater DF ROM in non-weight bearing (NWB; p < 0.05). Logistic regression model suggests tibial varum (OR = 0.779, p = 0.021) and WB DF ROM (OR = 1.067, p = 0.045) were associated with LAS in men. In case of women, there were no significant SLEA factors for LAS, however, ROC curve analysis revealed standing RF angle (AUC = 0.647, p = 0.028) and NWB DF ROM (AUC = 0.648, p = 0.026) could be affecting factors for LAS. Conclusion: There are differences in SLEA according to the history of LAS, furthermore, the identified items were different by sex. In case of men, tibial varum and WB DF ROM affect LAS occurrence. Standing RF angle and NWB DF ROM of women could be a predictor for LAS. However, since the sensitivity and specificity in most of the SLEA measurements are low, kinematic in dynamic tasks should be considered together for a more accurate evaluation of LAS risk.

• Journal of radiological science and technology
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• v.46 no.5
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• pp.367-377
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• 2023

This study investigates the utility of the Triglyceride-glucose(TyG) index and Cardiometabolic Index(CMI) as predictors for diagnosing metabolic syndrome. The study involved 1970 males, 1459 females, totaling 3429 participants who underwent health checkups at P Hospital in Busan between January 2023 and June 2023. Metabolic syndrome diagnosis was based on the presence of 3 or more risk factors out of the 5 criteria outlined by the American Heart Association/National Heart, Lung, and Blood Institute(AHA/NHLBI), and participants with 2 or fewer risk factors were categorized as normal. Statistical analyses included independent sample t-tests, chi-square tests, Pearson's correlation analysis, Receiver Operating Characteristic(ROC) curve analysis, and logistic regression analysis, using the Statistical Package for the Social Sciences(SPSS) program. Significance was established at p<0.05. The comparison revealed that the metabolic syndrome group exhibited attributes such as advanced age, male gender, elevated systolic and diastolic blood pressures, high blood sugar, elevated triglycerides, reduced LDL-C, elevated HDL-C, higher Cardiometabolic Index, Triglyceride-glucose index, and components linked to abdominal obesity. Pearson correlation analysis showed strong positive correlations between waist circumference/height ratio, waist circumference, Cardiometabolic Index, and triglycerides. Weak positive correlations were observed between LDL-C, body mass index, and Cardiometabolic index, while a strong negative correlation was found between Cardiometabolic Index and HDL-C. ROC analysis indicated that the Cardiometabolic Index(CMI), Triglyceride-glucose(TyG) index, and waist circumference demonstrated the highest Area Under the Curve(AUC) values, indicating their efficacy in diagnosing metabolic syndrome. Optimal cut-off values were determined as >1.34, >8.86, and >84.5 for the Cardiometabolic Index, Triglyceride-glucose index, and waist circumference, respectively. Logistic regression analysis revealed significant differences for age(p=0.037), waist circumference(p<0.001), systolic blood pressure(p<0.001), triglycerides(p<0.001), LDL-C(p=0.028), fasting blood sugar(p<0.001), Cardiometabolic Index(p<0.001), and Triglyceride-glucose index (p<0.001). The odds ratios for these variables were 1.015, 1.179, 1.090, 3.03, and 69.16, respectively. In conclusion, the Cardiometabolic Index and Triglyceride-glucose index are robust predictive indicators closely associated with metabolic syndrome diagnosis, and waist circumference is identified as an excellent predictor. Integrating these variables into clinical practice holds the potential for enhancing early diagnosis and prevention of metabolic syndrome.

• Imaging Science in Dentistry
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• v.50 no.2
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• pp.117-124
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• 2020

Purpose: The purpose of this study was to evaluate possible differences in the location of the inferior alveolar canal in male and female Egyptians. Materials and Methods: This cross-sectional retrospective study involved the evaluation of 210 CBCT scans of Egyptian individuals (18-70 years old). The inferior alveolar canal was localized by measuring 8 linear dimensions: 2 for the vertical localization of the mental foramen (superior and inferior to the mental foramen), 4 at the first molar bifurcation for the vertical and horizontal localization of the inferior alveolar canal (superior, inferior, buccal, and lingual to the inferior alveolar canal), and 2 for the horizontal localization of the mandibular foramen (anterior and posterior to the mandibular foramen). The measurements were statistically analyzed via comparative analysis, stepwise logistic regression, and receiver operating characteristic (ROC) curve analysis. Results: Six of the 8 measured distances differed to a statistically significant extent between the sexes. Regression analysis suggested a logistic function with a concordance index of 84%. The diagnostic accuracy capabilities of the linear measurements as sex predictors were calculated using ROC analysis, and the 6 best predictors for sex determination were selected and ranked from highest to lowest predictive power. Moreover, combining these 6 predictors increased the predictive power to 84%. Conclusion: The location of the inferior alveolar canal in the Egyptian population varies significantly by sex; accordingly, this anatomic landmark could be used as a reliable indicator of sexual dimorphism.