• BMB Reports
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• 제43권4호
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• pp.233-244
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• 2010

Parkinson's disease (PD) is the second most common neurodegenerative disease, and 5-10% of the PD cases are genetically inherited as familial PD (FPD). LRRK2 (leucine-rich repeat kinase 2) was first reported in 2004 as a gene corresponding to PARK8, an autosomal gene whose dominant mutations cause familial PD. LRRK2 contains both active kinase and GTPase domains as well as protein-protein interaction motifs such as LRR (leucine-rich repeat) and WD40. Most pathogenic LRRK2 mutations are located in either the GTPase or kinase domain, implying important roles for the enzymatic activities in PD pathogenic mechanisms. In comparison to other PD causative genes such as parkin and PINK1, LRRK2 exhibits two important features. One is that LRRK2's mutations (especially the G2019S mutation) were observed in sporadic as well as familial PD patients. Another is that, among the various PD-causing genes, pathological characteristics observed in patients carrying LRRK2 mutations are the most similar to patients with sporadic PD. Because of these two observations, LRRK2 has been intensively investigated for its pathogenic mechanism (s) and as a target gene for PD therapeutics. In this review, the general biochemical and molecular features of LRRK2, the recent results of LRRK2 studies and LRRK2's therapeutic potential as a PD target gene will be discussed.

• 산업경영시스템학회지
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• 제44권3호
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• pp.33-38
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• 2021

Recently, transfer learning techniques with a base convolutional neural network (CNN) model have widely gained acceptance in early detection and classification of crop diseases to increase agricultural productivity with reducing disease spread. The transfer learning techniques based classifiers generally achieve over 90% of classification accuracy for crop diseases using dataset of crop leaf images (e.g., PlantVillage dataset), but they have ability to classify only the pre-trained diseases. This paper provides with an evaluation scheme on selecting an effective base CNN model for crop disease transfer learning with regard to the accuracy of trained target crops as well as of untrained target crops. First, we present transfer learning models called CDC (crop disease classification) architecture including widely used base (pre-trained) CNN models. We evaluate each performance of seven base CNN models for four untrained crops. The results of performance evaluation show that the DenseNet201 is one of the best base CNN models.

• Journal of Microbiology and Biotechnology
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• 제33권9호
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• pp.1111-1118
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• 2023

As a long-term condition that affects the airways and lungs, chronic obstructive pulmonary disease (COPD) is characterized by inflammation, emphysema, breathlessness, chronic cough, and sputum production. Currently, the bronchodilators and anti-inflammatory drugs prescribed for COPD are mostly off-target, warranting new disease management strategies. Accumulating research has revealed the gut-lung axis to be a bidirectional communication system. Cigarette smoke, a major exacerbating factor in COPD and lung inflammation, affects gut microbiota composition and diversity, causing gut microbiota dysbiosis, a condition that has recently been described in COPD patients and animal models. For this review, we focused on the gut-lung axis, which is influenced by gut microbial metabolites, bacterial translocation, and immune cell modulation. Further, we have summarized the findings of preclinical and clinical studies on the association between gut microbiota and COPD to provide a basis for using gut microbiota in therapeutic strategies against COPD. Our review also proposes that further research on probiotics, prebiotics, short-chain fatty acids, and fecal microbiota transplantation could assist therapeutic approaches targeting the gut microbiota to alleviate COPD.

• 치위생과학회지
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• 제21권1호
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• pp.45-51
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• 2021

Background: Periodontal disease, also known as gum disease, is a major dental inflammatory disease with a very high prevalence; it is the main cause of tooth loss. Therefore, diagnostic biomarkers that can monitor gum inflammation are important for oral healthcare. Since the gingival crevicular fluid (GCF) adequately reflects changes in the periodontal environment, they have become a target for the development of effective diagnostic biomarkers for periodontitis. In the present study, the level of the target molecules suggested as diagnostic biomarkers for periodontitis were analyzed in GCF samples collected from healthy individuals and periodontitis patients. In addition, useful targets for the diagnosis of periodontitis were evaluated. Methods: GCF samples were collected from healthy individuals and periodontitis patients using absorbent paper points. SDS-PAGE and Coomassie staining were performed for protein analysis. The protein concentrations of GCF specimens were determined using the Bradford method. The levels of the target molecules appropriate for diagnosing periodontal disease were measured by ELISA, according to the manufacturer's protocol. Results: The protein concentration of GCF collected from periodontitis patients was 3.72 fold higher than that in an equal volume of GCF collected from healthy individuals. ELISA analysis showed that the level of interukin-6 (IL-6), IL-8, metalloproteinases 2 (MMP-2), MMP-9, tumor necrosis factor-alpha (TNF-α), azurocidin, and odontogenic ameloblast-associated protein (ODAM) were higher in the GCF samples from the periodontitis patients than in those from the healthy individuals. However, the level of IL-6 and TNF-α were relatively low (> 5 pg/ml). The prostaglandin E2 (PGE2) levels were not significantly different between the two GCF samples. Conclusion: These results indicate that IL-8, MMP-2, MMP-9, azurocidin, and ODAM are potentially useful diagnostic biomarkers for periodontitis; combining multiple biomarkers will improve the diagnostic accuracy of periodontitis.

• BMB Reports
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• 제48권5호
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• pp.256-265
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• 2015

Cardiovascular and neurodegenerative diseases are major health threats in many developed countries. Recently, target tissues derived from human embryonic stem (hES) cells and induced pluripotent stem cells (iPSCs), such as cardiomyocytes (CMs) or neurons, have been actively mobilized for drug screening. Knowledge of drug toxicity and efficacy obtained using stem cell-derived tissues could parallel that obtained from human trials. Furthermore, iPSC disease models could be advantageous in the development of personalized medicine in various parts of disease sectors. To obtain the maximum benefit from iPSCs in disease modeling, researchers are now focusing on aging, maturation, and metabolism to recapitulate the pathological features seen in patients. Compared to pediatric disease modeling, adult-onset disease modeling with iPSCs requires proper maturation for full manifestation of pathological features. Herein, the success of iPSC technology, focusing on patient-specific drug treatment, maturation-based disease modeling, and alternative approaches to compensate for the current limitations of patient iPSC modeling, will be further discussed. [BMB Reports 2015; 48(5): 256-265]

• Journal of Preventive Medicine and Public Health
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• 제40권4호
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• pp.273-277
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• 2007

The purpose of establishing the circulatory disease surveillance system in Korea is to ensure that the problems of circulatory disease importance are being monitored efficiently and effectively. The goals of circulatory disease surveillance system are to monitor the epidemiological trends of circulatory disease and to evaluate the outcome of health activity for controlling circulatory diseases. Surveillance system are being updated to achieve the needs for the integration of the surveillance and information system, the establishment of data standards, the electronic exchange of data, and changes in the goals of circulatory disease surveillance system to facilitate the response of this system to manage the national health problem effectively. This article provides the target diseases and determinant indicators to be monitored, structure of circulatory disease surveillance system, and many tasks and related activities that should be applied to this system.

• Journal of Korean Neurosurgical Society
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• 제38권5호
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• pp.359-365
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• 2005

Objective : The study investigates the extent of brain shift and its effect on the accuracy of the stereotaxic procedure. Methods : Thirty-five patients underwent 40stereotactic procedures between June 2002 and March 2004. There were 26 males, mean age 59years old. There were 34procedures for Parkinson's disease, 2 for essential tremor, 3 for cerebral palsy, 1 for dystonia. Patients were divided in four groups based on postoperative pneumocephalus : under 5cc [9 procedures], between $5{\sim}10cc$ [13procedures], between $10{\sim}15cc$ [11 procedures] and more than 15cc [7procedures]. The coordinates of the anterior commissure[AC], posterior commissure[PC], and target were defined in pre-and intraoperative magnetic resonance image scans and the amount of air volume was measured with @Target (BrainLab, Heimstetten, Germany]. Results : The mean AC-PC was 26.5mm for patients with less than 5cc, 26.9mm for $5{\sim}10cc$, 25.8mm for $10{\sim}15cc$ and 26.2mm for more than 15cc. The length of AC-PC line and coordinates of AC, PC was also not statistically different, Euclidean distance as well as ${\Delta}x$, ${\Delta}y$, ${\Delta}z$ of AC, PC, and target were also not statistically different among the groups [p>,1]. There was a variance in target of $0.7{\sim}7.6mm$, Euclidean distance of 2.5mm, related to electrophysiology but not to brain-shift. Conclusion : The amount of air accumulated in the intracranial space and compressing the cortical surface has no effect on the localization of subcortical stereotactic target and landmarks.

• IMMUNE NETWORK
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• 제22권6호
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• pp.51.1-51.20
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• 2022

Trypanosoma cruzi, the etiological agent of Chagas disease, is an intracellular protozoan parasite, which is now present in most industrialized countries. About 40% of T. cruzi infected individuals will develop severe, incurable cardiovascular, gastrointestinal, or neurological disorders. The molecular mechanisms by which T. cruzi induces cardiopathogenesis remain to be determined. Previous studies showed that increased IL-6 expression in T. cruzi patients was associated with disease severity. IL-6 signaling was suggested to induce pro-inflammatory and pro-fibrotic responses, however, the role of this pathway during early infection remains to be elucidated. We reported that T. cruzi can dysregulate the expression of host PIWI-interacting RNAs (piRNAs) during early infection. Here, we aim to evaluate the dysregulation of IL-6 signaling and the piRNAs computationally predicted to target IL-6 molecules during early T. cruzi infection of primary human cardiac fibroblasts (PHCF). Using in silico analysis, we predict that piR_004506, piR_001356, and piR_017716 target IL6 and SOCS3 genes, respectively. We validated the piRNAs and target gene expression in T. cruzi challenged PHCF. Secreted IL-6, soluble gp-130, and sIL-6R in condition media were measured using a cytokine array and western blot analysis was used to measure pathway activation. We created a network of piRNAs, target genes, and genes within one degree of biological interaction. Our analysis revealed an inverse relationship between piRNA expression and the target transcripts during early infection, denoting the IL-6 pathway targeting piRNAs can be developed as potential therapeutics to mitigate T. cruzi cardiomyopathies.

• 생물정신의학
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• 제22권2호
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• pp.40-46
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• 2015

Neuroglial cells are fundamental for brain homeostasis and defense to intrinsic or extrinsic changes. Loss of their function and over-reactivity to stimuli contribute to the aging of brain. Alzheimer's disease (AD) could be caused by more dramatic response in neuroglia associated with various chemokines and cytokines. Neuroglia of the AD brain shares some phenotypes with aging neuroglia. In addition, neuroglial activation and neuroinflammation are commonly showed in neurodegeneration. Thus neuroglia would be a promising target for therapeutics of AD.

• 셀메드
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• 제3권2호
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• pp.12.1-12.4
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• 2013

Identification of target protein is an important procedure in the course of drug discovery. Because of complexity, action mechanisms of herbal medicine are rather obscure, unlike small-molecular drugs. Inverse docking simulation is a reverse use of molecular docking involving multiple target searches for known chemical structure. This methodology can be applied in the field of target fishing and toxicity prediction for herbal compounds as well as known drug molecules. The aim of this review is to introduce a series of in silico works for predicting potential drug targets and side-effects based on inverse docking simulations.