• Asian-Australasian Journal of Animal Sciences
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• 제19권1호
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• pp.13-18
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• 2006

Two different animal models, which differ in whether or not taking maternal genetic effect into account, for estimating genetic parameters of cashmere weight, live body weight, cashmere thickness, staple length, fiber diameter, and fiber length in Inner Mongolia White Cashmere Goat were compared via likelihood ratio test. The results indicate that maternal genetic effect has significant influence on live body weight and cashmere thickness, but no significant influence on the other traits. Using models suitable for each trait, both genetic parameters and trends were analyzed with the MTDFREML program. Heritability estimates from single trait models for cashmere weight, live body weight, cashmere thickness, staple length, fiber diameter and fiber length were found to be 0.30, 0.07, 0.21, 0.29, 0.28 and 0.21, respectively. Genetic correlation estimates from two-trait models between live body weight and all other traits (-0.06~0.07) was negligible, as were those between fiber diameter and all other traits (-0.01~0.03) except cashmere thickness (0.19). Cashmere weight and staple length had moderate to low genetic correlations with other traits (-0.24~0.39 and -0.24~0.34, respectively) except for live body weight and fiber diameter. Cashmere thickness had a strong genetic correlation with fiber length (0.81), and low genetic correlation with other traits (0.19~0.34) except live body weight. Genetic trend analysis suggests that selection for cashmere weight was very effective, which has led to the slow genetic progress of cashmere thickness and fiber length due to their genetic correlations with cashmere weight. The selection for live body weight was not effective, which was consistent with its low inheritability.

• 한국축산식품학회지
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• 제30권6호
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• pp.905-909
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• 2010

Two sets of data on carcass traits and beef cut parameters were used to investigate the relationships between carcass and beef cut measurements, which can be used to make predictions of retail cut percentages. One set had a total of 1,141 measurements of Hanwoo cattle of three different sex origins, which were slaughtered in an abattoir located at the National Institute of Animal Science, RDA, Korea from 1996 to 2008. To develop prediction models for retail cut percentage with higher accuracies than the current model, another set consisting of a total of 13,389 records of carcass and beef cut traits were collected from 30 abattoirs and butcheries in Korea from 2008 to 2009. Bulls yielded heavier and leaner carcasses than steers. High correlation coefficients were estimated between amount of body fat and percent retail cut (-0.82) as well as between back fat thickness (BF) and percent retail cut (-0.62). The amount of retail cut, however, was highly correlated with body weight before slaughter (BW, 0.95) or with cold carcass weight (CWT, 0.94). Relationships between percent retail cut and measurable beef yield traits, BF, loin eye area (LEA) or CWT varied by sex class, which must be considered for development of a prediction model with high accuracy. Models of data for all breeds and sexes fit the effects of breed, sex, and interaction of abattoir by butchers, whereas models of data for each breed and sex fit the effect of interaction of abattoir by butcher only. Due to possible future changes in back fat control, we performed a log transformation of BF. Our new models fit better than the currently used model.

• Environmental Analysis Health and Toxicology
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• 제19권3호
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• pp.287-294
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• 2004

Diabetic complication is one of major risk factors leading to vascular disease such as atherosclerosis, stroke, coronary heart disease and etc. Several factors affecting the acceleration of diabetic vascular complication have been known such as hypertension, hyperlipidemia, immune complex and genetic factors. To screen and develop new therapeutics agents for diabetic vascular complication, it is strongly needed to develop animal models for diabetic complications. However in rodents models, diabetic complications is not well developed. Furthermore to assess the possibility of new therapeutics for diabetic vascular complications, diabetic animal models which have the risk factors of diabetic complications is needed. We aim to develop and establish an diabetic animal model which have diabetic complications with hyperlipidemia which is one of risk factors for diabetic complications. We induced insulin -dependent diabetes by intra. venous injection of streptozotocin (35 mg/kg/day) in RICO rats which is a spontaneous animal model for hyperlipidemia. Our models (STZ RICO) showed hyperglycemia, persistent high level of plasma cholesterol and triglyceridemia with severe diabetic renal changes until 28 weeks after induction of diabetes. STZ-RICO rats could be used for the evaluations of newly developed diabetic drugs.

• Journal of Microbiology and Biotechnology
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• 제28권9호
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• pp.1413-1425
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• 2018

Shiga toxins (Stxs) are the main virulence factors expressed by the pathogenic Stx-producing bacteria, namely, Shigella dysenteriae serotype 1 and certain Escherichia coli strains. These bacteria cause widespread outbreaks of bloody diarrhea (hemorrhagic colitis) that in severe cases can progress to life-threatening systemic complications, including hemolytic uremic syndrome (HUS) characterized by the acute onset of microangiopathic hemolytic anemia and kidney dysfunction. Shiga toxicosis has a distinct pathogenesis and animal models of Stx-associated HUS have allowed us to investigate this. Since these models will also be useful for developing effective countermeasures to Stx-associated HUS, it is important to have clinically relevant animal models of this disease. Multiple studies over the last few decades have shown that mice injected with purified Stxs develop some of the pathophysiological features seen in HUS patients infected with the Stx-producing bacteria. These features are also efficiently recapitulated in a non-human primate model (baboons). In addition, rats, calves, chicks, piglets, and rabbits have been used as models to study symptoms of HUS that are characteristic of each animal. These models have been very useful for testing hypotheses about how Stx induces HUS and its neurological sequelae. In this review, we describe in detail the current knowledge about the most well-studied in vivo models of Stx-induced HUS; namely, those in mice, piglets, non-human primates, and rabbits. The aim of this review is to show how each human clinical outcome-mimicking animal model can serve as an experimental tool to promote our understanding of Stx-induced pathogenesis.

• The Korean Journal of Physiology and Pharmacology
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• 제24권6호
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• pp.441-452
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• 2020

In vivo animal models are limited in their ability to mimic the extremely complex systems of the human body, and there is increasing disquiet about the ethics of animal research. Many authorities in different geographical areas are considering implementing a ban on animal testing, including testing for cosmetics and pharmaceuticals. Therefore, there is a need for research into systems that can replicate the responses of laboratory animals and simulate environments similar to the human body in a laboratory. An in vitro two-dimensional cell culture model is widely used, because such a system is relatively inexpensive, easy to implement, and can gather considerable amounts of reference data. However, these models lack a real physiological extracellular environment. Recent advances in stem cell biology, tissue engineering, and microfabrication techniques have facilitated the development of various 3D cell culture models. These include multicellular spheroids, organoids, and organs-on-chips, each of which has its own advantages and limitations. Organoids are organ-specific cell clusters created by aggregating cells derived from pluripotent, adult, and cancer stem cells. Patient-derived organoids can be used as models of human disease in a culture dish. Biomimetic organ chips are models that replicate the physiological and mechanical functions of human organs. Many organoids and organ-on-a-chips have been developed for drug screening and testing, so competition for patents between countries is also intensifying. We analyzed the scientific and technological trends underlying these cutting-edge models, which are developed for use as non-animal models for testing safety and efficacy at the nonclinical stages of drug development.

• Asian-Australasian Journal of Animal Sciences
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• 제15권7호
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• pp.925-931
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• 2002

Gibbs sampling algorithms were implemented to the multi-trait threshold animal models with any combinations of multiple binary, ordered categorical, and linear traits and investigate the amount of bias on these models with two kinds of parameterization and algorithms for generating underlying liabilities. Statistical models which included additive genetic and residual effects as random and contemporary group effects as fixed were considered on the models using simulated data. The fully conditional posterior means of heritabilities and genetic (residual) correlations were calculated from 1,000 samples retained every 10th samples after 15,000 samples discarded as "burn-in" period. Under the models considered, several combinations of three traits with binary, multiple ordered categories, and continuous were analyzed. Five replicates were carried out. Estimates for heritabilities and genetic (residual) correlations as the posterior means were unbiased when underlying liabilities for a categorical trait were generated given by underlying liabilities of the other traits and threshold estimates were rescaled. Otherwise, when parameterizing threshold of zero and residual variance of one for binary traits, heritability estimates were inflated 7-10% upward. Genetic correlation estimates were biased upward if positively correlated and downward if negatively correlated when underling liabilities were generated without accounting for correlated traits on prior information. Residual correlation estimates were, consequently, much biased downward if positively correlated and upward if negatively correlated in that case. The more categorical trait had categories, the better mixing rate was shown.

• Journal of Animal Science and Technology
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• 제54권2호
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• pp.71-75
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• 2012

본 연구는 한우 암소 초음파 측정자료 특징을 알아보고, 측정형질에 대한 유전모수를 추정하여 육질 또는 육량 개량을 위한 기초자료를 제공하기 위해 수행되었으며, 2001년부터 2009년까지 한국종축개량협회에 의해 측정된 한우 암소 36,893두를 이용하였고, 그 중 반복기록이 있는 개체는 7,913두였다. 유전모수 추정을 위하여 반복개체모형을 이용하였으며, 유전모수 추정에는 REMLF90 (Miztal, 2001)을 이용하였다. 유전모수 추정모형의 설정을 위하여 흉위, 영양도 및 초음파 측정치에 대한 출생년도, 출생계절, 측정년도, 측정계절, 측정지역, 측정연령 등의 환경효과를 추정하였다. 반복개체모형으로 추정된 배최장근단면적, 등지방두께 및 근내지방도에 대한 유전력이 각각 0.31, 0.38, 0.27로 나타났고, 다형질개체모형으로 추정한 유전력은 각각 0.02, 0.09, 0.07로 낮게 추정되었다. 반복개체모형을 이용한 반복력은 배최장근단면적, 등지방두께, 근내지방도가 각각 0.46, 0.57, 0.39로 나타났다. 분석모형 간의 추정치의 차이를 비교 할 때 반복모형에서의 유전력과 반복력이 높게 추정되었다. 따라서 반복형질 값을 가진 형질들의 측정치를 표준화하여 한우암소개량을 위한 기초자료로 활용된다면 유전능력평가와 개량사업 비용절감에 도움이 될 것으로 기대된다.

• Asian-Australasian Journal of Animal Sciences
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• 제33권12호
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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.

• 한국축산식품학회지
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• 제29권3호
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• pp.289-295
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• 2009

The aim of this research was to develop predictive models for the growth of spoilage bacteria (total viable cells, Pseudomonas spp., and lactic acid bacteria) on frankfurters and to estimate the shelf-life of frankfurters under aerobic conditions at various storage temperatures (5, 15, and $25^{\circ}C$). The primary models were determined using the Baranyi model equation. The secondary models for maximum specific growth rate and lag time as functions of temperature were developed by the polynomial model equation. During 21 d of storage under various temperature conditions, lactic acid bacteria showed the longest lag time and the slowest growth rate among spoilage bacteria. The growth patterns of total viable cells and Pseudomonas spp. were similar each other. These data suggest that Pseudomonas spp. might be the dominant spoilage bacteria on frankfurters. As storage temperature increased, the growth rate of spoilage bacteria also increased and the lag time decreased. Furthermore, the shelf-life of frankfurters decreased from 7.0 to 4.3 and 1.9 (d) under increased temperature conditions. These results indicate that the most significant factor for spoilage bacteria growth is storage temperature. The values of $B_f$, $A_f$, RMSE, and $R^2$ indicate that these models were reliable for identifying the point of microbiological hazard for spoilage bacteria in frankfurters.

• Asian-Australasian Journal of Animal Sciences
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• 제13권3호
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• pp.413-422
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• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.