• Asian-Australasian Journal of Animal Sciences
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• v.21 no.9
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• pp.1227-1232
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• 2008

Carcass characteristics data of Hanwoo (N = 1,084) were collected from two stations of the National Livestock Institute of Animal Science (NIAS), Korea and records from thirteen individual cow-calf operators were analyzed to estimate variance and covariance components and the effect of different slaughter endpoints. Carcass traits analyzed were cold carcass weight (CWT, kg), REA (rib eye area, cm2), back fat thickness (mm) and marbling score (1-7). Four different models were examined. All models included sex and contemporary group as fixed effects and the animal's direct genetic potential and environment as random effects. The first model fitted a linear covariate of age at slaughter. The second model fitted both linear and quadratic covariates of age at slaughter. The third model fitted a linear covariate of body weight at slaughter. The fourth model fitted both linear covariates of age at slaughter and body weight at slaughter. Variance components were estimated using the REML procedure with Gibb's sampler. Heritability estimate of CWT was in the range of 0.08-0.11 depending on the model applied. Heritability estimates of BF, REA and MS were in the ranges of 0.23-0.28, 0.19-0.26, and 0.44-0.45, respectively. Genetic correlations between CWT and BF, between CWT and REA, and between CWT and MS were in the ranges of -0.33 - -0.14, 0.73-0.84, and -0.01- 0.11, respectively. Genetic correlations between REA and BF, between MS and BF and between REA and MS were in the ranges of -0.82 ~ -0.72, 0.04~0.28 and -0.08 ~ -0.02, respectively. Variance and covariance components estimated varied by model with different slaughter endpoints. Body weight endpoint was more effective for direct selection in favor of yield traits and body weight endpoints affected more of the correlated response to selection for the traits of yield and quality of edible portion of beef.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.2
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• pp.203-211
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• 2020

Objective: Staphylococcus aureus (S. aureus) is one of the major microorganisms responsible for subclinical mastitis in dairy cattle. The present study was designed with the aim to explore the DNA methylation patterns using the Fluorescence-labeled methylation-sensitive amplified polymorphism (F-MSAP) techniques in a S. aureus-infected mouse model. Methods: A total of 12 out-bred Institute of Cancer Research female mice ranging from 12 to 13 weeks-old were selected to construct a mastitis model. F-MSAP analysis was carried out to detect fluctuations of DNA methylation between control group and S. aureus mastitis group. Results: Visible changes were observed in white cell counts in milk, percentage of granulocytes, percentage of lymphocytes, CD⁴⁺/CD⁸⁺ ratio (CD⁴⁺/CD⁸⁺), and histopathology of mice pre- and post-challenge with S. aureus. These findings showed the suitability of the S. aureus-infected mouse model. A total of 369 fragments was amplified from udder tissue samples from the two groups (S. aureus-infected mastitis group and control group) using eight pairs of selective primers. Results indicated that the methylation level of mastitis mouse group was higher than that in the control group. In addition, NCK-associated protein 5 (Nckap5) and transposon MTD were identified to be differentially methylated through secondary polymerase chain reaction and sequencing in the mastitis group. These observations might play an important role in the development of S. aureus mastitis. Conclusion: Collectively, our study suggests that the methylation modification in Nckap5 and transposon MTD might be considered as epigenetic markers in resistance to S. aureus-infected mastitis and provided a new insight into S. aureus mastitis research in dairy industry and public health.

• Korean Journal of Biological Psychiatry
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• v.6 no.2
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• pp.161-169
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• 1999

There are a number of approaches in developing experimental models for depression, but there is no such thing as a best model for depressive syndrome. Animal models are subject to the obvious limitations inherent in the assumption that human psychopathology can be represented accurately in lower animals. Recently, the concern increasingly is to develop a variety of experimental paradigms in animals to study selected aspects of human psychopathology, and animal models should be understood as basically experimental preparations that are developed to carry out these objects. Therefore, a battery of a variety of animal models should be applied to permit detailed pathophysiological studies and to develop new antidepressant treatments. Animal models of depression basically consider behavioral isomorphism with the human depression a plus, but not a req-uirement, and the model behavior should be defined operationally in order to be reproduced reliably by other researchers and be responsive to those agents possessing demonstrated clinical efficacy in human depression. In conclusion, animal models of depression have played a significant role in elucidating pathophysiology of depression and developing current treatments for depression, but there is no single comprehensive model for depression until now. Each of the proposed animal model has its advantages and limitations. In other words, certain paradigms are suitable for studying certain phenomena, whereas others are more suitable for studying other aspects. The best model for depression depends upon what the question is.

• Korean Journal of Veterinary Service
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• v.36 no.2
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• pp.67-71
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• 2013

Neonatal infection caused by Cronobacter species can result in serious illnesses such as bacteremia, septicemia, meningitis, and death in at-risk infants who are orally fed contaminated reconstituted powdered infant formulas. The objective of this study was to compare the virulence among three Cronobacter species strains by using an animal model for human neonatal Cronobacter species infections. We acquired timed-pregnant ICR mice and all owed them to give birth naturally. On postnatal day 3, each pup was administered orally a total dose of $1{\times}10^7$ CFU Cronobacter species strain 3439, CDC 1123-79, and 3231. Mice were observed twice daily for morbidity and mortality. At postnatal day 10, the remaining pups were euthanized, and brain, liver, and cecum were excised and analyzed for the presence of Cronobacter species. Cronobacter species were isolated from cecum and other tissues in inoculated mice. In the tissues of Cronobacter species infected mice, meningitis and gliosis were detected in the brain. In this study, we identified the virulence among Cronobacter species strains by using a neonatal mice model which was a very effective animal model for human neonatal Cronobacter species infections.

• Food Science of Animal Resources
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• v.39 no.1
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• pp.84-92
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• 2019

Listeria monocytogenes is a major cause of serious foodborne illness in the dairy foods. Although Caenorhabditis elegans model is well established as a virulence model of pathogenic bacteria, its application on L. monocytogenes is critically unclear. The objective of this study was to carry out an evaluation of L. monocytogenes toxicity using C. elegans nematode as a simple host model. We found that C. elegans nematodes have high susceptibility to L. monocytogenes infection, as a consequence of accumulation of bacteria in the worms' intestine. However, L. innocua, which is known to be non-toxic, is not accumulate in the intestine of worms and is not toxic similarly to Escherichia coli OP50 known as the normal feed source of C. elegans. Importantly, immune-associated genes of C. elegans were intensely upregulated more than 3.0-fold when they exposed to L. monocytogenes. In conclusion, we established that C. elegans is an effective model for studying the toxicity of L. monocytogenes and we anticipate that this system will result in the discovery of many potential anti-listeria agents for dairy foods.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.7
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• pp.923-927
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• 2008

The objective of this study was to compare random regression model and multiple trait animal model estimates of the (co) variance of total sperm cells over the active lifetime of AI boars. Data were provided by Smithfield Premium Genetics (Rose Hill, NC). Total number of records and animals for the random regression model were 19,629 and 1,736, respectively. Data for multiple trait animal model analyses were edited to include only records produced at 9, 12, 15, 18, 21, 24, and 27 months of age. For the multiple trait method estimates of genetic and residual variance for total sperm cells were heterogeneous among age classifications. When comparing multiple trait method to random regression, heritability estimates were similar except for total sperm cells at 24 months of age. The multiple trait method also resulted in higher estimates of heritability of total sperm cells at every age when compared to random regression results. Random regression analysis provided more detail with regard to changes of variance components with age. Random regression methods are the most appropriate to analyze semen traits as they are longitudinal data measured over the lifetime of boars.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.10
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• pp.1490-1495
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• 2006

The purpose of this research was to develop an optimum composition model for a new synbiotic fermented dairy product with high probiotic cell counts, and to experimentally verify this model. The optimum composition model indicated the growth promoter ratio that could provide the highest growth rate for probiotics in this fermented product. Different levels of growth promoters were first blended with milk to improve the growth rates of probiotics, and the optimum composition model was determined. The probiotic viabilities and chemical properties were analyzed for the samples made using the optimal formula. The optimal combination of the growth promoters for the synbiotic fermented milk product was 1.12% peptides, 3% fructooligosaccharides (FOS), and 1.87% isomaltooligosaccharides (IMO). A product manufactured according to the formula of the optimum model was analyzed, showing that the model was effective in improving the viability of both Lactobacillus spp. and Bifidobacterium spp.

• Food Science of Animal Resources
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• v.37 no.1
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• pp.139-146
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• 2017

Response surface methodology (RSM) is a useful set of statistical techniques for modeling and optimizing responses in research studies of food science. In the analysis of response surface data, a second-order polynomial regression model is usually used. However, sometimes we encounter situations where the fit of the second-order model is poor. If the model fitted to the data has a poor fit including a lack of fit, the modeling and optimization results might not be accurate. In such a case, using a fullest balanced model, which has no lack of fit, can fix such problem, enhancing the accuracy of the response surface modeling and optimization. This article presents how to develop and use such a model for the better modeling and optimizing of the response through an illustrative re-analysis of a dataset in Park et al. (2014) published in the Korean Journal for Food Science of Animal Resources.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.5
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• pp.633-639
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• 2008

The genetic relationship of gestation length (GL) with birth and weaning weight (BW, WW) was investigated using data collected from the Hanwoo Experiment Station, National Institute of Animal Science, RDA, Republic of Korea. Analytical mixed models including birth year‐season, sex of calf, linear and quadratic covariates of age of dam (days) and linear covariate of age at weaning (days) as fixed effects were used. Corresponding restricted maximum likelihood (REML) and Bayesian estimates of variance components and heritability were obtained with two models; Model 1 included only direct genetic effect and Model 2 included direct genetic, maternal genetic and permanent environmental effect. All the genetic parameter estimates from REML were corresponding to the Bayesian estimates. Direct heritability estimates for GL, BW, and WW were 0.48, 0.33 and 0.25 by Model 1. From Model 2, direct and maternal heritability estimates were 0.38 and 0.03 for GL, 0.14 and 0.05 for BW, and 0.08 and 0.05 for WW. Genetic correlation estimates between direct and maternal effects were 0.05 for GL, 0.59 for BW, and 0.52 for WW. Estimates of direct genetic correlation between GL and BW (WW) were 0.44 (0.21). Positive genetic correlation of GL with BW and WW imply that selection for greater BW or WW would lead to prolonged gestation length.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.12
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• pp.2039-2049
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• 2020

Objective: This study was conducted to provide models to accurately predict nitrogen (N) and phosphorus (P) excretion of dairy cows on smallholder farms in Indonesia based on readily available farm data. Methods: The generic model in this study is based on the principles of the Lucas equation, describing the relation between dry matter intake (DMI) and faecal N excretion to predict the quantity of faecal N (Q_FN). Excretion of urinary N and faecal P were calculated based on National Research Council recommendations for dairy cows. A farm survey was conducted to collect input parameters for the models. The data set was used to calibrate the model to predict Q_FN for the specific case. The model was validated by comparing the predicted quantity of faecal N with the actual quantity of faecal N (Q_FNACT) based on measurements, and the calibrated model was compared to the Lucas equation. The models were used to predict N and P excretion of all 144 dairy cows in the data set. Results: Our estimate of true N digestibility equalled the standard value of 92% in the original Lucas equation, whereas our estimate of metabolic faecal N was -0.60 g/100 g DMI, with the standard value being -0.61 g/100 g DMI. Results of the model validation showed that the R² was 0.63, the MAE was 15 g/animal/d (17% from Q_FNACT), and the RMSE was 20 g/animal/d (22% from Q_FNACT). We predicted that the total N excretion of dairy cows in Indonesia was on average 197 g/animal/d, whereas P excretion was on average 56 g/animal/d. Conclusion: The proposed models can be used with reasonable accuracy to predict N and P excretion of dairy cattle on smallholder farms in Indonesia, which can contribute to improving manure management and reduce environmental issues related to nutrient losses.