• Animal Bioscience
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• v.37 no.8
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• pp.1333-1344
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• 2024

Objective: Litter size and piglet loss at birth significantly impact piglet production and are closely associated with sow parity. Understanding how these traits vary across different parities is crucial for effective herd management. This study investigates the patterns of the number of born alive piglets (NBA), number of piglet losses (NPL), and the proportion of piglet losses (PPL) at birth in Landrace sows under tropical conditions. Additionally, it aims to identify the most suitable model for describing these patterns. Methods: A dataset comprising 2,322 consecutive reproductive records from 258 Landrace sows, spanning parities from 1 to 9, was analyzed. Modeling approaches including 2nd and 3rd degree polynomial models, the Wood gamma function, and a longitudinal model were applied at the individual level to predict NBA, NPL, and PPL. The choice of the best-fitting model was determined based on the lowest mean and standard deviation of the difference between predicted and actual values, Akaike information criterion (AIC), and Bayesian information criterion (BIC). Results: Sow parity significantly influenced NBA, NPL, and PPL (p<0.0001). NBA increased until the 4th parity and then declined. In contrast, NPL and PPL decreased until the 2nd parity and then steadily increased until the 8th parity. The 2nd and 3rd degree polynomials, and longitudinal models showed no significant differences in predicting NBA, NPL, and PPL (p>0.05). The 3rd degree polynomial model had the lowest prediction standard deviation and yielded the smallest AIC and BIC. Conclusion: The 3rd degree polynomial model offers the most suitable description of NBA, NPL, and PPL patterns. It holds promise for applications in genetic evaluations to enhance litter size and reduce piglet loss at birth in sows. These findings highlight the importance of accounting for sow parity effects in swine breeding programs, particularly in tropical conditions, to optimize piglet production and sow performance.

• Journal of Animal Reproduction and Biotechnology
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• v.35 no.1
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• pp.42-49
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• 2020

As a preclinical study, many researchers have been attempted to convert the porcine PSCs into several differentiated cells with transplantation of the differentiated cells into the pigs. Here, we attempted to derive neuronal progenitor cells from pig embryonic germ cells (EGCs). As a result, neuronal progenitor cells could be derived directly from pig embryonic germ cells through the serum-free floating culture of EB-like aggregates (SFEB) method. Treating retinoic acid was more efficient for inducing neuronal lineages from EGCs rather than inhibiting SMAD signaling. The differentiated cells expressed neuronal markers such as PAX6, NESTIN, and SOX1 as determined by qRT-PCR and immunostaining. These data indicated that pig EGCs could provide valid models for human therapy. Finally, it is suggested that developing transgenic pig for disease models as well as differentiation methods will provide basic preclinical data for human regenerative medicine and lead to the success of stem cell therapy.

• Reproductive and Developmental Biology
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• v.37 no.1
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• pp.41-49
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• 2013

Ovarian cancer is the most lethal world-wide gynecological disease among women due to the lack of molecular biomarkers to diagnose the disease at an early stage. In addition, there are few well established relevant animal models for research on human ovarian cancer. For instance, rodent models have been established through highly specialized genetic manipulations, but they are not an excellent model for human ovarian cancer because histological features are not comparable to those of women, mice have a low incidence of tumorigenesis, and they experience a protracted period of tumor development. However, the laying hen is a unique and highly relevant animal model for research on human ovarian cancer because they spontaneously develop epithelial cell-derived ovarian cancer (EOC) as occurs in women. Our research group has identified common histological and physiological aspects of ovarian tumors from women and laying hens, and we have provided evidence for several potential biomarkers to detect, monitor and target for treatment of human ovarian cancers based on the use of both genetic and epigenetic factors. Therefore, this review focuses on ovarian cancer of laying hens and relevant regulatory mechanisms, based on genetic and epigenetic aspects of the disease in order to provide new information and to highlight the advantages of the laying hen model for research in ovarian carcinogenesis.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.10
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• pp.1335-1340
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• 2011

Different genetic parameters for weaning weight and wool traits were estimated using restricted maximum likelihood (REML) in Angora rabbits. Total wool yield of first (I), second (II) and third (III) clips were taken as a separate trait under study. The records from more than 2,700 animals were analysed through fitting six animal models with various combinations of direct and maternal effects. A log likelihood ratio test was used to select the most appropriate model for each trait. Direct heritability estimates for the wool traits were found to be moderate to high across different models. Heritability estimates obtained from the best model were 0.24, 0.22, 0.20 and 0.21 for weaning weight, clip I, II and III; respectively. Maternal effects especially due to permanent environment had higher importance at clip I and found to be declining in subsequent clips. The estimates of repeatability of doe effect on wool traits were 0.44, 0.26 and 0.18 for clip I, II and III; respectively. Weaning weight had moderately high genetic correlations with clip I (0.57) and II (0.45), but very low (0.11) with clip III. Results indicated that genetic improvement for wool yield in Angora rabbit is possible through direct selection. Further, weaning weight could be considered as desirable trait for earliest indirect selection for wool yield in view of its high genetic correlation with wool traits.

• Journal of Korean Medicine Rehabilitation
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• v.26 no.4
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• pp.9-21
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• 2016

Objectives This study is to review the effect of herbal medicine on treatment of sciatic nerve injury induced animal models reported in domestic & foreign journals. Methods 5 electronic databases (Pubmed, CAJ, RISS, Oasis, Koreantk) were searched with term as sciatic nerve injury, and animal study reports on sciatic nerve impairment with herbal medicine treatment were extracted. Results 31 articles were reviewd. All studies used SD rat. 26 studies used crush injury at the sciatic nerve using haemostatic forcep and 5 studies used sciatic nerve transection. 15 studies used single herb extract and 16 studies used complex herb medicine. Angelica gigantis radix was the most frequently used herb. Each study showed significant changes of improvement indicators from sciatic nerve impairment. Conclusions Various herb medicine are expected to have positive effects on sciatic nerve impairment.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.29 no.1
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• pp.131-144
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• 2016

Objective : This study is to review the effect of herbal medicines on treatment of Allergic Rhinitis in animal models reported in Korean domestic journals.Methods : The Databases(NDSL, Koreantk, OASIS, KISS) are searched with terms as Allergic Rhinitis. among them, only animal study reports were reviewed. Animal model, intervention, and observation methods of measuring indicators were extracted.Results : 27 articles were reviewed. All studies used OVA to induce Allergic Rhinitis. 7 studies used simple herbal medicines, 20 studies used complex herbal medicines, To evaluate the effect of the Herbal medicines, 23 studies used immunological examination, 18 studies used histological examination, 16 studies used hematologic examination, 3 studies used macroscopy The evidences of 5 studies is insufficient to show that Herbal medicines are effective for treatment of Allergic Rhinitis.

• Clinics in Shoulder and Elbow
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• v.17 no.2
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• pp.84-90
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• 2014

In conducting animal studies using rotator cuff, researchers should select the appropriate types of animals and experimental models. This should also be followed by complete understanding of the selected experimental animals as well as the methods for evaluating the results. Thus, researchers could minimize errors and failure in conducting animal experimental studies. Further, this will provide a basis of establishing new idea and theory about rotator cuff diseases.

• Journal of Biomedical Engineering Research
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• v.30 no.1
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• pp.1-9
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• 2009

Many types of small animal imaging modalities, like micro-CT, micro-PET, and micro-SPECT, have been recently developed worldwide. Small animal imaging systems are now recognized as indispensable tools to validate efficacy and safety of new drugs or new therapeutic methods using the animal disease models. With increasing demands for small animal imaging in biomedical research, multimodal small animal imaging systems, like micro-PET/CT or micro PET/MRI, are now also being developed. Small animal imaging with spatial resolution and sensitivity comparable to human imaging is quite challenging since laboratory small animals are much smaller than human beings. Research activities in Korea on small animal imaging systems are reviewed in this paper. In the field of micro-CT and micro-PET, many world-class technologies have been developed successfully in Korea. It is expected that the developed animal imaging system technologies can be used in the development of clinical imaging systems in Korea in the near future.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.6
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• pp.759-767
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• 2016

The aim of this study was to compare two random regression models (RRM) fitted by fourth ($RRM_4$) and fifth-order Legendre polynomials ($RRM_5$) with a lactation model (LM) for evaluating Holstein cattle in Brazil. Two datasets with the same animals were prepared for this study. To apply test-day RRM and LMs, 262,426 test day records and 30,228 lactation records covering 305 days were prepared, respectively. The lowest values of Akaike's information criterion, Bayesian information criterion, and estimates of the maximum of the likelihood function (-2LogL) were for $RRM_4$. Heritability for 305-day milk yield (305MY) was 0.23 ($RRM_4$), 0.24 ($RRM_5$), and 0.21 (LM). Heritability, additive genetic and permanent environmental variances of test days on days in milk was from 0.16 to 0.27, from 3.76 to 6.88 and from 11.12 to 20.21, respectively. Additive genetic correlations between test days ranged from 0.20 to 0.99. Permanent environmental correlations between test days were between 0.07 and 0.99. Standard deviations of average estimated breeding values (EBVs) for 305MY from $RRM_4$ and $RRM_5$ were from 11% to 30% higher for bulls and around 28% higher for cows than that in LM. Rank correlations between RRM EBVs and LM EBVs were between 0.86 to 0.96 for bulls and 0.80 to 0.87 for cows. Average percentage of gain in reliability of EBVs for 305-day yield increased from 4% to 17% for bulls and from 23% to 24% for cows when reliability of EBVs from RRM models was compared to those from LM model. Random regression model fitted by fourth order Legendre polynomials is recommended for genetic evaluations of Brazilian Holstein cattle because of the higher reliability in the estimation of breeding values.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.1
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• pp.116-123
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• 2003

Forages are the most important feed resource for ruminants worldwide, whether fed as pastures, forage crops or conserved hay, silage or haylage. There is large variability in the quality of forages so measurement and prediction of feeding value and nutritive value are essential for high levels of production. Within a commercial animal production system, methods of prediction must be inexpensive and rapid. At least 50% of the variation in feeding value of forages is due to variation in voluntary feed intake. Identification of the factors that constrain voluntary feed intake allows these differences to be managed and exploited in forage selection. Constraints to intake have been predicted using combinations of metabolic and physical factors within the animal while simple measurements such as the energy required to shear the plant material are related to constraints to intake with some plant material. Animals respond to both pre- and post-ingestive feedback signals from forages. Pre-ingestive signals may play a role in intake with signals including taste, odour and texture together with learned aversions to nutrients or toxins (post-ingestive feedback signals). The challenge to forage evaluation is identification of the factors which are most important contributors to these feedback signals. Empirical models incorporating chemical composition are also widely used. The models tend to be useful within the ranges of the datasets used in their development but none can claim to have universal application. Mechanistic models are becoming increasingly complex and sophisticated and incorporate both feed characteristics and use of biochemical pathways within the animal. Improvement in utilisation through the deliberate selection of pasture plants for high feeding value appears to have potential and has been poorly exploited. Use of Near Infrared Reflectance Spectroscopy is a simple method that offers significant potential for the preliminary screening of plants with genetic differences in feeding value. Near Infrared Reflectance Spectroscopy will only be as reliable as the calibration sets from which the equations are generated.