• Journal of Ginseng Research
• /
• 제45권3호
• /
• pp.420-432
• /
• 2021

Background: Many ginsenosides have been shown to be efficacious for major depressive disorder (MDD), which is a highly recurrent disorder, through several preclinical studies. We aimed to review the literature assessing the antidepressant effects of ginsenosides on MDD animal models, to establish systematic scientific evidence in a rigorous manner. Methods: We performed a systematic review on the antidepressant effects of ginsenoside evaluated in in vivo studies. We searched for preclinical trials from inception to July 2019 in electronic databases such as Pubmed and Embase. In vivo studies examining the effect of a single ginsenoside on animal models of primary depression were included. Items of each study were evaluated by two independent reviewers. A meta-analysis was conducted to assess behavioral changes induced by ginsenoside Rg1, which was the most studied ginsenoside. Data were pooled using the random-effects models. Results: A total of 517 studies were identified, and 23 studies were included in the final analysis. They reported on many ginsenosides with different antidepressant effects and biological mechanisms of action. Of the 12 included articles assessing ginsenoside Rg1, pooled results of forced swimming test from 9 articles (mean difference (MD): 20.50, 95% CI: 16.13-24.87), and sucrose preference test from 11 articles (MD: 28.29, 95% CI: 22.90-33.69) showed significant differences compared with vehicle treatment. The risk of bias of each study was moderate, but there was significant heterogeneity across studies. Conclusion: These estimates suggest that ginsenosides, including ginsenoside Rg1, reduces symptoms of depression, modulates underlying mechanisms, and can be a promising antidepressant.

• Asian-Australasian Journal of Animal Sciences
• /
• 제28권10호
• /
• pp.1407-1418
• /
• 2015

A total of 32,817 test-day milk yield (TDMY) records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM) using Legendre's polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield ($PS_i$) and the genetic trend of 305-day milk yield (305MY) were evaluated. The fit quality criteria used indicated RRM employing the Legendre's polynomial of orders 3 and 5 for fitting the genetic additive and permanent environment effects, respectively, as the best model. The heritability and genetic correlation for TDMY throughout the lactation, obtained with the best model, varied from 0.18 to 0.23 and from -0.03 to 1.00, respectively. The heritability and genetic correlation for persistency and 305MY varied from 0.10 to 0.33 and from -0.98 to 1.00, respectively. The use of $PS_7$ would be the most suitable option for the evaluation of Girolando cattle. The estimated breeding values for 305MY of sires and cows showed significant and positive genetic trends. Thus, the use of selection indices would be indicated in the genetic evaluation of Girolando cattle for both traits.

• Asian-Australasian Journal of Animal Sciences
• /
• 제24권12호
• /
• pp.1651-1659
• /
• 2011

This study was conducted to detect quantitative trait loci (QTL) for thirteen growth and meat quality traits in pigs by combing QTL experimental populations. Two F2 reference populations that were sired by Korea native pig (KNP) and dammed by Landrace (LN) or Yorkshire (YK) were generated to construct linkage maps using 123 genetic markers (mostly microsatellites) and to perform QTL analysis on porcine chromosomes (SSCs) 1, 2, 3, 6, 7, 8, 9, 11, 13, 14, and 15. A set of line-cross models was applied to detect QTL, and a series of lack-of-fit tests between the models was used to characterize inheritance mode of QTL. A total of 23, 11 and 19 QTL were detected at 5% chromosome-wise level for the data sets of KNP${\times}$LN, KNP${\times}$YK cross and joint sets of the two cross populations, respectively. With the joint data, two Mendelian expressed QTL for live weight and cooking loss were detected on SSC3 and SSC15 at 1% chromosome-wise level, respectively. Another Mendelian expressed QTL was detected for CIE a on SSC7 at 5% genome-wise level. Our results suggest that QTL analysis by combining data from two QTL populations increase power for QTL detection, which could provide more accurate genetic information in subsequent marker-assisted selection.

• Asian-Australasian Journal of Animal Sciences
• /
• 제28권9호
• /
• pp.1226-1234
• /
• 2015

The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations.

• Asian-Australasian Journal of Animal Sciences
• /
• 제16권8호
• /
• pp.1087-1092
• /
• 2003

As an experimental reference population, crosses between Korean native pig and Landraces were established and information on growth traits was recorded. Animals were genotyped for 24 microsatellite markers covering chromosomes 2, 6, and 7 for partial-genome scan to identify chromosomal regions that have effects on growth traits. quantitative trait loci (QTL) effects were estimated using interval mapping by the regression method under the line cross models with a test for imprinting effects. For test of presence of QTL, chromosome-wide and single position significance thresholds were estimated by permutation test and normal significance threshold for the imprinting test were derived. For tests against the Mendelian model, additive and dominance coefficients were permuted within individuals. Thresholds (5% chromosome-wide) against the no-QTL model for the analyzed traits ranged from 4.57 to 4.99 for the Mendelian model and from 4.14 to 4.67 for the imprinting model, respectively. Partial-genome scan revealed significant evidence for 4 QTL affecting growth traits, and 2 out of the 4 QTLs were imprinted. This study demonstrated that testing for imprinting should become a standard procedure to unravel the genetic control of multi-factorial traits. The models and tests developed in this study allowed the detection and evaluation of imprinted QTL.

• 한국산업정보학회논문지
• /
• 제29권2호
• /
• pp.15-25
• /
• 2024

효과적인 동물 생태계 분석을 위해서는 동물 서식 현황을 자동으로 파악할 수 있는 동물 관제 기술이 중요하다. 특히 울음소리로 종을 판별하는 동물 소리 분류 기술은 영상을 통한 판별이 어려운 환경에서 큰 주목을 받고 있다. 기존 연구들은 단일 딥러닝 모델을 사용하여 동물 소리를 분류하였으나, 야외 환경에서 수집된 동물 소리는 많은 배경 잡음을 포함하여 단일 모델의 판별력을 악화시키며, 종에 따른 데이터 불균형으로 인해 모델의 편향된 학습을 야기한다. 이에, 본 논문에서는 클래스의 데이터 수를 고려하여 페널티를 부여하는 Focal Loss를 사용한 여러 분류 모델의 예측결과를 앙상블을 통해 결합하여 잡음이 많은 동물 소리를 효과적으로 분류할 수 있는 기법을 제안한다. 공개 데이터 셋을 사용한 실험에서, 제안된 기법은 단일 모델의 평균 성능에 비해 Recall 기준으로 최대 22.6%의 성능 개선을 달성하였다.

• 대한화장품학회지
• /
• 제38권3호
• /
• pp.219-224
• /
• 2012

최근 유럽연합에서는 동물실험을 통하여 검증된 성분을 함유하고 있는 화장품에 대하여 판매를 금지할 것을 선언하였다. 그리하여 동물실험을 대체할 동물실험 대체모델의 개발이 필요해졌다. 인공피부는 화장품, 의약품 및 의료기기의 안전 테스트에 있어서 아주 중요한 시스템이다. 본 연구에서는 기저막과 표피를 가지고 있는 최적의 인공피부를 만들기 위한 시도를 하였다. 이러한 목적으로 중간엽줄기세표(MSCs, mesenchymal stem cells)와 지방전구세포를 진피세포인 섬유모세포와 혼합하여 진피대체물을 만들었다. 기저막과 표피의 형성은 면역조직화학 염색(immunohistochemical stains)을 통하여 확인하였다. 여러 가지 모델 중에서, 중간엽줄기세포를 혼합한 모델에서 표피의 두께가 제일 두꺼웠으며 또한 PCNA와 involucrin의 분포가 실제 사람피부와 비슷하였다. 결론적으로, 본 연구의 결과는 진피대체물에 중간엽줄기세포를 혼합한 인공피부가 동물실험 대체모델로 개발될 수 있다는 점을 제시한다.

• 한국응용약물학회:학술대회논문집
• /
• 한국응용약물학회 2007년도 Proceedings of The Convention of The Korean Society of Applied Pharmacology
• /
• pp.47-62
• /
• 2007

• 응용통계연구
• /
• 제37권3호
• /
• pp.355-380
• /
• 2024

본 연구에서는 OECD test guideline 데이터를 이용하여 graph기반 딥러닝 모델들의 성능을 비교하고자 한다. OECD TG는 화학물질들이 인체와 환경에 미칠 잠재적 영향에 대해 시험하는 방법이며, 많은 실험이 동물실험을 통해 독성을 확인한다. 동물실험은 많은 시간과 비용이 들며, 윤리적 이슈가 있어 대안을 찾거나 최소화하는 방법들이 연구되고 있다. 딥러닝은 화학물질을 활용하는 다양한 분야에서 사용되고 있으며, 독성예측 분야에도 사용되고 있으며, 특히 graph 기반 모델에 대한 연구가 활발하다. 우리의 목표는 OECD TG 데이터에 대한 graph기반 딥러닝 모델들의 성능을 비교하여 가장 성능이 좋은 모델을 찾는 것이다. 우리는 OECD에서 운영하는 웹사이트 eChemportal.org에서 OECD TG를 따른 결과를 수집하였으며, 전처리 과정을 통해 학습이 불가능하거나 부적절한 화학물질은 제거하였다. 수집된 OECD TG데이터와 화학물질 특성 예측 성능의 벤치마크 데이터셋인 MoleculeNet 데이터를 활용하여 5개의 graph기반 모델들의 독성 예측 성능을 비교하였다.

• Laboraroty Animal Research
• /
• 제34권4호
• /
• pp.185-194
• /
• 2018

The different polymorphisms of the transcription factor 7-like 2 (TCF7L2) gene promote variances in diabetes susceptibility in humans. We investigated whether these genotypes also promote differences in diabetic susceptibility in commercial pigs. Growing pigs (Landrace, both sex, 50-60 kg) with the C/C (n=4) and T/T (n=5) TCF7L2 genotypes were identified and intravenously injected with streptozotocin (STZ, 40 mg/kg) twice in weekly intervals, then a high-energy diet was offered. Oral glucose tolerance tests, blood analyses and the homeostasis model assessment-insulin resistance (HOMA-IR) index calculations were performed. The animals were sacrificed at the end of 12 weeks of treatment to reveal the pancreas histomorphometry. The results showed that all of the treated pigs grew normally despite exhibiting hyperglycemia at two weeks after the induction. The glycemic level of the fasting or postprandial pigs gradually returned to normal. The fasting insulin concentration was significantly decreased for the T/T carriers but not for the C/C carriers, and the resulting HOMA-IR index was significantly increased for the C/C genotype, indicating that the models of insulin dependence and resistance were respectively developed by T/T and C/C carriers. The histopathological results illustrated a significant reduction in the pancreas mass and insulin active sites, which suggested increased damage. The results obtained here could not be compared with previous studies because the TCF7L2 background has not been reported. Growing pigs may be an excellent model for diabetic in children if the animals are genetically pre-selected.