• Asian-Australasian Journal of Animal Sciences
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• v.26 no.8
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• pp.1119-1126
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• 2013

The objective of this study was to compare the goodness of fit of four lactation curve models: Wood's Gamma model (WD), Wilmink (WL), and Pollott's multiplicative two (POL2) and three parameters (POL3) and to determine the environmental factors affecting the complete lactation curve of F1 dairy sheep under organic management. A total of 5,382 weekly milk yields records from 150 ewes, under organic management were used. Residual mean square (RMS), determination coefficients ($R^2$), and correlation (r) analysis were used as an indicator of goodness of fit for each model. WL model best fitted the lactation curves as indicated by the lower RMS values (0.019), followed by WD (0.023), POL2 (0.025) and POL3 (0.029). The four models provided total milk yield (TMY) estimations that were highly correlated (0.93 to 0.97) with observed TMY (89.9 kg). The four models under estimated peak yield (PY), whereas POL2 and POL3 gave nearer peak time lactation estimations. Ewes lambing in autumn had higher TMY and showed a typical curve shape. Higher TMY were recorded in second and third lambing. Season of lambing, number of lambing and type of lambing had a great influenced over TMY shaping the complete lactation curve of F1 dairy sheep. In general terms WL model showed the best fit to the F1 dairy sheep lactation curve under organic management.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.1
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• pp.53-59
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• 2000

Data from a village household dairy survey was compared with technical parameters of three model farms (0.2, 0.4 and 0.8 ha in extent) established by the Mid-country Livestock Development Centre (MLDC). In terms of land size, about 67% of the 250 dairy farmers interviewed corresponded with the MLDC models, but only 33% of the farmers were keeping dairy cattle under conditions comparable to the MLDC models (no regular off-farm income). In the 0.2 ha category, village farmers kept more cows, and in the other two categories the village farmers kept less cows than their MLDC model counterparts. In all three categories, the milk production per cow was higher in the model farms (1540 to 2137 vs. 1464 to 1508 litres/cow/year), and this could be attributed to higher feeding levels of concentrates in the model farms as compared to the village farmers (430 to 761 vs. 233 to 383 kg/cow/year). The amount of milk produced from fodder was higher in the village situation in comparison to the models. In the mid country, dairy production seems to depend on access to fodder resources rather than on the extent of land owned. Except in the 0.8 ha village category, the highest contribution to the total income was made by the dairy component (44 to 60%). With 0.8 ha village farmers, the income contribution from dairy and crops was similar (41%). Income from other livestock was important for the 0.2 ha MLDC model, but for all other categories their contribution to total income ranged from 0 to 10%. Access to fodder resources outside own-farm land is vital for economic dairy production. As such, an in-depth analysis of feed resources available and their accessibility needs to be further investigated.

• Food Science of Animal Resources
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• v.35 no.1
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• pp.108-113
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• 2015

The purpose of this study was to develop predictive models for the growth of Listeria monocytogenes in pork Bulgogi at various storage temperatures. A two-strain mixture of L. monocytogenes (ATCC 15313 and isolated from pork Bulgogi) was inoculated on pork Bulgogi at 3 Log CFU/g. L. monocytogenes strains were enumerated using general plating method on Listeria selective medium. The inoculated samples were stored at 5, 15, and $25^{\circ}C$ for primary models. Primary models were developed using the Baranyi model equations, and the maximum specific growth rate was shown to be dependent on storage temperature. A secondary model of growth rate as a function of storage temperature was also developed. As the storage temperature increased, the lag time (LT) values decreased dramatically and the specific growth rate of L. monocytogenes increased. The mathematically predicted growth parameters were evaluated based on the modified bias factor ($B_f$), accuracy factor ($A_f$), root mean square error (RMSE), coefficient of determination ($R^2$), and relative errors (RE). These values indicated that the developed models were reliably able to predict the growth of L. monocytogenes in pork Bulgogi. Hence, the predictive models may be used to assess microbiological hygiene in the meat supply chain as a function of storage temperature.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.9 no.1
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• pp.3-8
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• 2023

Parkinson's disease is a neurodegenerative disease caused by damage to brain neurons related to dopamine. Non-clinical animal models mainly used in Parkinson's disease research include drug-induced models of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine and 6-hydroxydopamine, and genetically modified transgenic animal models. Parkinson's diagnosis can be made using brain imaging of the substantia nigra-striatal dopamine system and using a radiotracer that specifically binds to the dopamine transporter. In this study, ¹⁸F-N-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane was used to confirm the image evaluation cutoff between normal and parkinson's disease models, and to confirm model persistence over time. In addition, the efficacy of single or combined administration of clinically used therapeutic drugs in parkinson's animal models was evaluated. Image analysis was performed using the PMOD software. Converted to standardized uptake value, and analyzed by standardized uptake value ratio by dividing the average value of left striatum by the average value of right striatum obtained by applying positron emission tomography images to the atlas magnetic resonance template. The image cutoff of the normal and the parkinson's disease model was calculated as SUVR=0.829, and it was confirmed that it was maintained during the test period. In the three-drug combination administration group, the right and left striatum showed a high symmetry of more than 0.942 on average and recovered significantly. Images using ¹⁸F-N-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane are thought to be able to diagnose and evaluate treatment efficacy of non-clinical Parkinson's disease.

• Laboraroty Animal Research
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• v.34 no.4
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• pp.160-165
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• 2018

Breast cancer remains the second leading cause of cancer death among woman, worldwide, despite advances in identifying novel targeted therapies and the development of treating strategies. Classification of clinical subtypes (ER+, PR+, HER2+, and TNBC (Triple-negative)) increases the complexity of breast cancers, which thus necessitates further investigation. Mouse models used in breast cancer research provide an essential approach to examine the mechanisms and genetic pathway in cancer progression and metastasis and to develop and evaluate clinical therapeutics. In this review, we summarize tumor transplantation models and genetically engineered mouse models (GEMMs) of breast cancer and their applications in the field of human breast cancer research and anti-cancer drug development. These models may help to improve the knowledge of underlying mechanisms and genetic pathways, as well as creating approaches for modeling clinical tumor subtypes, and developing innovative cancer therapy.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.6
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• pp.858-861
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• 2001

Near Infrared spectroscopy was applied to the samples of processed pork to see the effect of grinding on chemical components analyses. Data from conventional chemical analyses of moisture, fat, protein, NaCl were put into calibration model by NIR of reflectance mode. The other properties observed were pH and color parameters ($L^*,\;a^*,\;b^*$). Spectral ranges of 400~2500 nm and 400~1100 nm were compared for color parameters. Spectral ranges of 400~2500 nm and 1100~2500 nm were compared for chemical components and pH. Different spectral ranges caused little changes in the coefficients of determination or standard errors. $R^{2,}s$ of calibration models for color parameters were in the range of 0.97 to 1.00. $R^{2,}s$ of calibration models of intact sausages for moisture, protein, fat, NaCl and pH were 0.98, 0.89, 0.95, 0.73 and 0.77, respectively using spectra at 1100~2500 nm. $R^{2,}s$ of calibration models of ground sausages for moisture, protein, fat, NaCl and pH were 0.97, 0.91, 0.97, 0.42 and 0.56, respectively using spectra at 1100~2500 nm.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.5
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• pp.575-579
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• 2000

First lactation records of 683 Murrah buffaloes maintained at NDRI, Karnal which were progeny of 84 sires used for comparing the heritability estimates of age at first calving, first lactation milk yield and first service period under single and multiple trait models using restricted maximum likelihood (REML) method of estimation under an individual animal model. The results indicated that the heritability estimates may vary under single and multiple trait models depending upon the magnitude of genetic and environmental correlation among the traits being considered. Therefore, a single or multiple trait model is recommended for estimation of variance components depending upon the goal of breeding programme. However, there may not be any advantage of considering a trait with zero or near zero heritability and having no or very low genetic correlation with other traits in the model. Lower heritability estimates of part lactation yield (120-day milk yield) implied that there may not be any advantage of considering this trait in place of actual 305-day milk yield, whereas, comparable heritability estimates of predicted 305-day milk yield suggested that it could be used for sire evaluation to reduce the cost of milk recording under field conditions.

• Korean Journal of Agricultural Science
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• v.43 no.4
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• pp.595-602
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• 2016

In pigs, individuals in the same pen may show aggressive behavior toward each other, such as tail biting. Such social interactions among pen mates may considerably affect their welfare and performance, both in negative and positive ways. The present study was conducted to investigate social genetic effects on days to 90 kg using data from 12,208 Duroc and Yorkshire pigs that were born between 2008 and 2012. Heritability was estimated using the five following animal models: a basic model with direct heritable effects only (Model 1), a social model with direct and social heritable effects (Model 2), a model accounting for covariance between direct and social heritable effects (Model 3), and two models considering a dilution factor with direct and social heritable effects (Models 4 and 5). The optimal model to represent Duroc pigs was Model 1 which only uses direct heritable effects. Direct heritability (0.21) was higher than total heritability (0.09) and covariance was negative. Model 2 was evaluated as the optimum model for Yorkshire pigs. Yorkshire data showed that total heritability (0.5) was twice as high as direct heritability (0.25) and covariance was positive. Our results suggest that the efficiency of social effects differed among breeding lines. Further research on social effects related to breeds by group size would clarify which is the most efficient selection method that accounts for social genetic effects.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.8
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• pp.1088-1097
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• 2005

Main objectives of this study were to investigate accuracy, bias and power of linear and threshold model segregation analysis methods for detection of major genes in categorical traits in farm animals. Maximum Likelihood Linear Model (MLLM), Bayesian Linear Model (BALM) and Bayesian Threshold Model (BATM) were applied to simulated data on normal, categorical and binary scales as well as to disease data in pigs. Simulated data on the underlying normally distributed liability (NDL) were used to create categorical and binary data. MLLM method was applied to data on all scales (Normal, categorical and binary) and BATM method was developed and applied only to binary data. The MLLM analyses underestimated parameters for binary as well as categorical traits compared to normal traits; with the bias being very severe for binary traits. The accuracy of major gene and polygene parameter estimates was also very low for binary data compared with those for categorical data; the later gave results similar to normal data. When disease incidence (on binary scale) is close to 50%, segregation analysis has more accuracy and lesser bias, compared to diseases with rare incidences. NDL data were always better than categorical data. Under the MLLM method, the test statistics for categorical and binary data were consistently unusually very high (while the opposite is expected due to loss of information in categorical data), indicating high false discovery rates of major genes if linear models are applied to categorical traits. With Bayesian segregation analysis, 95% highest probability density regions of major gene variances were checked if they included the value of zero (boundary parameter); by nature of this difference between likelihood and Bayesian approaches, the Bayesian methods are likely to be more reliable for categorical data. The BATM segregation analysis of binary data also showed a significant advantage over MLLM in terms of higher accuracy. Based on the results, threshold models are recommended when the trait distributions are discontinuous. Further, segregation analysis could be used in an initial scan of the data for evidence of major genes before embarking on molecular genome mapping.

• Biomolecules & Therapeutics
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• v.24 no.3
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• pp.207-243
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• 2016

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and communication impairments, as well as repetitive and restrictive behaviors. The phenotypic heterogeneity of ASD has made it overwhelmingly difficult to determine the exact etiology and pathophysiology underlying the core symptoms, which are often accompanied by comorbidities such as hyperactivity, seizures, and sensorimotor abnormalities. To our benefit, the advent of animal models has allowed us to assess and test diverse risk factors of ASD, both genetic and environmental, and measure their contribution to the manifestation of autistic symptoms. At a broader scale, rodent models have helped consolidate molecular pathways and unify the neurophysiological mechanisms underlying each one of the various etiologies. This approach will potentially enable the stratification of ASD into clinical, molecular, and neurophenotypic subgroups, further proving their translational utility. It is henceforth paramount to establish a common ground of mechanistic theories from complementing results in preclinical research. In this review, we cluster the ASD animal models into lesion and genetic models and further classify them based on the corresponding environmental, epigenetic and genetic factors. Finally, we summarize the symptoms and neuropathological highlights for each model and make critical comparisons that elucidate their clinical and neurobiological relevance.