• Proceedings of the Korean Society of Applied Pharmacology
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• 1995.04a
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• pp.35-36
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• 1995

To gain insight into the etiological mechanism of dementia and to develop clinically effective congnitive enhancers, it is required to prepare animal models with symptoms and mechanism resemble to that in human. Dementia is mainly classified into two types : senile type of Alzheimer's disease (STAD) and cerebral ischemia-induced one. As animal models of cerebral ischemia, a couple of types in rats have been introduced : one is the occlusion of bilateral carotid arteries-induced forebrain/global ischemia and the other is the occlusion of middle cerebral arteries-induced focal/regional ischemia.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2672-2679
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• 2012

The study was done to provide basic data of medical quality evaluation after developing the comorbidity disease mortality measurement modeled on the severity-adjustment method of AMI. This study analyzed 699,701 cases of Hospital Discharge Injury Data of 2005 and 2008, provided by the Korea Centers for Disease Control and Prevention. We used logistic regression to compare the risk-adjustment model of the Charlson Comorbidity Index with the predictability and compatibility of our severity score model that is newly developed for calibration. The models severity method included age, sex, hospitalization path, PCI presence, CABG, and 12 variables of the comorbidity disease. Predictability of the newly developed severity models, which has statistical C level of 0.796(95%CI=0.771-0.821) is higher than Charlson Comorbidity Index. This proves that there are differences of mortality, prevalence rate by method of mortality model calibration. In the future, this study outcome should be utilized more to achieve an improvement of medical quality evaluation, and also models will be developed that are considered for clinical significance and statistical compatibility.

• YAKHAK HOEJI
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• v.55 no.6
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• pp.510-515
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• 2011

Isoquinoline compounds including berberine enhance L-DOPA-induced cytotoxicity in PC12 cells. In this study, the effects of berberine on L-DOPA therapy in unilateral 6-hydroxydopamine (6-OHDA)-induced rat models of parkinsonism were investigated. Rats were prepared for the models of Parkinson's disease by 6-OHDA-lesioning for 14 days and then treated with L-DOPA (10 mg/kg) with or without berberine (5 and 30 mg/kg, i.p.) for 21 days. Treatment with berberine (5 and 30 mg/kg, i.p.) showed a dopaminergic cell loss in substantia nigra of 6-OHDA-lesioned rats treated with L-DOPA: 30 mg/kg berberine was more intensive neurotoxic. The levels of dopamine were also decreased by berberine (5 and 30 mg/ kg) in striatum-substantia nigra of 6-OHDA-lesioned rats treated with L-DOPA. These results suggest that berberine aggravates cell death of dopaminergic neurons in L-DOPA-treated 6-OHDA-lesioned rat models of Parkinson's disease. Therefore, the long-term L-DOPA therapeutic patients with isoquinoline compounds including berberine may need to be checked for the adverse symptoms.

• Journal of the Korean Applied Science and Technology
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• v.39 no.3
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• pp.442-453
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• 2022

Various animal models have been used to study the efficacy and action mechanisms of human diseases and medicines. Zebrafish (Danio rerio) is increasingly and successfully used as a model in translational research on human diseases. We obtained necessary information from original peer reviewed articles published in scientific 54 journals, such as Pubmed, Google Scholar, Scopus scince their inception until Dec, 2020 using the following terms: zebrafish animal models, herbal medicine, in vivo screening. In this review, we discuss the recent contributions of the various zebrafish disease models to study of herbal medicines. We focused on cancer, eye diseases, vascular diseases, diabetes and its complications, and cosmetic dermatology. We also highlight the molecular action mechanisms of medicines against these disease, demonstrated using zebrafish embryo. Zebrafish can be pivotal in bridging the gap from lab to clinical bedside. It is used as a model to understand human diseases pathogenies with further scope for drug development. Furthermore, zebrafish can reduce rat and mouse animals in biomedical research.

• Journal of Ginseng Research
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• v.47 no.3
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• pp.448-457
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• 2023

Background: Alzheimer's disease (AD) is a common form of dementia, and impaired mitophagy is a hallmark of AD. Mitophagy is mitochondrial-specific autophagy. Ginsenosides from Ginseng involve in autophagy in cancer. Ginsenoside Rg1 (Rg1 hereafter), a single compound of Ginseng, has neuroprotective effects on AD. However, few studies have reported whether Rg1 can ameliorate AD pathology by regulating mitophagy. Methods: Human SH-SY5Y cell and a 5XFAD mouse model were used to investigate the effects of Rg1. Rg1 (1µM) was added to β-amyloid oligomer (AβO)-induced or APPswe-overexpressed cell models for 24 hours. 5XFAD mouse models were intraperitoneally injected with Rg1 (10 mg/kg/d) for 30 days. Expression levels of mitophagy-related markers were analyzed by western blot and immunofluorescent staining. Cognitive function was assessed by Morris water maze. Mitophagic events were observed using transmission electron microscopy, western blot, and immunofluorescent staining from mouse hippocampus. The activation of the PINK1/Parkin pathway was examined using an immunoprecipitation assay. Results: Rg1 could restore mitophagy and ameliorate memory deficits in the AD cellular and/or mouse model through the PINK1-Parkin pathway. Moreover, Rg1 might induce microglial phagocytosis to reduce β-amyloid (Aβ) deposits in the hippocampus of AD mice. Conclusion: Our studies demonstrate the neuroprotective mechanism of ginsenoside Rg1 in AD models. Rg1 induces PINK-Parkin mediated mitophagy and ameliorates memory deficits in 5XFAD mouse models.

• Molecules and Cells
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• v.47 no.1
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• pp.100005.1-100005.15
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• 2024

Amyotrophic lateral sclerosis is a devastating neurodegenerative disease with a complex genetic basis, presenting both in familial and sporadic forms. The hexanucleotide (G₄C₂) repeat expansion in the C9orf72 gene, which triggers distinct pathogenic mechanisms, has been identified as a major contributor to familial and sporadic Amyotrophic lateral sclerosis cases. Animal models have proven pivotal in understanding these mechanisms; however, discrepancies between models due to variable transgene sequence, expression levels, and toxicity profiles complicate the translation of findings. Herein, we provide a systematic comparison of 7 publicly available Drosophila transgenes modeling the G₄C₂ expansion under uniform conditions, evaluating variations in their toxicity profiles. Further, we tested 3 previously characterized disease-modifying drugs in selected lines to uncover discrepancies among the tested strains. Our study not only deepens our understanding of the C9orf72 G₄C₂ mutations but also presents a framework for comparing constructs with minute structural differences. This work may be used to inform experimental designs to better model disease mechanisms and help guide the development of targeted interventions for neurodegenerative diseases, thus bridging the gap between model-based research and therapeutic application.

• Proceedings of the Zoological Society Korea Conference
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• 2001.10a
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• pp.107.2-108
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• 2001

No Abstract, See Full Text

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1250-1257
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• 2020

The early detection of diseases is important in agriculture because diseases are major threats of reducing crop yield for farmers. The shape and color of plant leaf are changed differently according to the disease. So we can detect and estimate the disease by inspecting the visual feature in leaf. This study presents a vision-based leaf classification method for detecting the diseases of tomato crop. ResNet-50 model was used to extract the visual feature in leaf and classify the disease of tomato crop, since the model showed the higher accuracy than the other ResNet models with different depths. We propose a new ensemble approach using several DCNN classifiers that have the same structure but have been trained at different ranges in the DCNN layers. Experimental result achieved accuracy of 97.19% for PlantVillage dataset. It validates that the proposed method effectively classify the disease of tomato crop.

• Genomics & Informatics
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• v.19 no.1
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• pp.11.1-11.8
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• 2021

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020-December 31, 2020 and January 20, 2020-January 31, 2021) and testing data (January 1, 2021-February 28, 2021 and February 1, 2021-February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values' comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.

• The Journal of Internal Korean Medicine
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• v.44 no.3
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• pp.418-438
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• 2023

Objective: This study was conducted to review the effects of herbal medicine on respiratory diseases induced by the treatment of particulate matter in in vivo animal models. Methods: Literature searches were performed in seven databases (Pubmed, Embase, Cochrane Library, KISS, KTKP, OASIS, and ScienceON). After the searched studies were screened based on the inclusion/exclusion criteria, the publication date, origin, used animals, induction of particulate matter models, herbal medicine used for intervention, study design, outcome measure, and results of studies were analyzed. Results: Among a total of 972 studies primarily searched, 34 studies were finally included in our study. Of this number, 29 studies induced animal models by using only particulate matter, and 5 studies induced animal models with respiratory diseases, such as asthma and chronic obstructive pulmonary disease, by using particulate matter and other materials. In the selected studies, the treatments of herbal medicine in particulate matter models suppressed oxidative stress and inflammation in lung tissue, bronchoalveolar lavage fluid, and blood as well as lung injury in histological analysis. Conclusion: The results of this study suggest that herbal medicine is effective in treating respiratory diseases induced by particulate matter. These results are also expected to be useful data for designing further studies. However, more systematically designed in vivo studies related to particulate matter are needed.