• Journal of Microbiology and Biotechnology
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• v.29 no.9
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• pp.1444-1452
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• 2019

The conventional prophylactic vaccines for human papillomavirus (HPV) efficiently prevent infection with high-risk HPV types, but they do not promote therapeutic effects against cervical cancer. Previously, we developed HPV16 E7-expressing Lactobacillus casei (L. casei-E7) as a therapeutic vaccine candidate for cervical cancer, which induces antitumor therapeutic effects in a TC-1 murine cancer model. To improve the therapeutic effect of L. casei-E7, we performed co-treatment with poly-gamma-glutamic acid (${\gamma}-PGA$), a safe and edible biomaterial naturally secreted by Bacillus subtilis. We investigated their synergistic effect to improve antitumor efficacy in a murine cancer model. The treatment with ${\gamma}-PGA$ did not show in vitro cytotoxicity against TC-1 tumor cells; however, an enhanced innate immune response including activation of dendritic cells was observed. Mice co-administered with ${\gamma}-PGA$ and L. casei-E7 showed significantly suppressed growth of TC-1 tumor cells and an increased survival rate in TC-1 mouse models compared to those of mice vaccinated with L. casei-E7 alone. The administration of ${\gamma}-PGA$ markedly enhanced the activation of natural killer (NK) cells but did not increase the E7-specific cytolytic activity of $CD8^+$ T lymphocytes in mice vaccinated with L. casei-E7. Overall, our results suggest that oral administration of ${\gamma}-PGA$ induces a synergistic antitumor effect in combination with L. casei-E7.

• Biomolecules & Therapeutics
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• v.27 no.2
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• pp.134-144
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• 2019

The prevalence of nonalcoholic fatty liver disease (NAFLD) has increased with the incidence of obesity; however, the underlying mechanisms are unknown. In this study, high-resolution metabolomics (HRM) along with transcriptomics were applied on animal models to draw a mechanistic insight of NAFLD. Wild type (WT) and catalase knockout (CKO) mice were fed with normal fat diet (NFD) or high fat diet (HFD) to identify the changes in metabolic and transcriptomic profiles caused by catalase gene deletion in correspondence with HFD. Integrated omics analysis revealed that cholic acid and $3{\beta}$, $7{\alpha}$-dihydroxy-5-cholestenoate along with cyp7b1 gene involved in primary bile acid biosynthesis were strongly affected by HFD. The analysis also showed that CKO significantly changed all-trans-5,6-epoxy-retinoic acid or all-trans-4-hydroxy-retinoic acid and all-trans-4-oxo-retinoic acid along with cyp3a41b gene in retinol metabolism, and ${\alpha}/{\gamma}$-linolenic acid, eicosapentaenoic acid and thromboxane A2 along with ptgs1 and tbxas1 genes in linolenic acid metabolism. Our results suggest that dysregulated primary bile acid biosynthesis may contribute to liver steatohepatitis, while up-regulated retinol metabolism and linolenic acid metabolism may have contributed to oxidative stress and inflammatory phenomena in our NAFLD model created using CKO mice fed with HFD.

• Biomolecules & Therapeutics
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• v.29 no.6
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• pp.615-629
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• 2021

An active compound, triterpene saponin, astersaponin I (AKNS-2) was isolated from Aster koraiensis Nakai (AKNS) and the autophagy activation and neuroprotective effect was investigated on in vitro and in vivo Parkinson's disease (PD) models. The autophagy-regulating effect of AKNS-2 was monitored by analyzing the expression of autophagy-related protein markers in SH-SY5Y cells using Western blot and fluorescent protein quenching assays. The neuroprotection of AKNS-2 was tested by using a 1-methyl-4-phenyl-2,3-dihydropyridium ion (MPP⁺)-induced in vitro PD model in SH-SY5Y cells and an MPTP-induced in vivo PD model in mice. The compound-treated SH-SY5Y cells not only showed enhanced microtubule-associated protein 1A/1B-light chain 3-II (LC3-II) and decreased sequestosome 1 (p62) expression but also showed increased phosphorylated extracellular signal-regulated kinases (p-Erk), phosphorylated AMP-activated protein kinase (p-AMPK) and phosphorylated unc-51-like kinase (p-ULK) and decreased phosphorylated mammalian target of rapamycin (p-mTOR) expression. AKNS-2-activated autophagy could be inhibited by the Erk inhibitor U0126 and by AMPK siRNA. In the MPP⁺-induced in vitro PD model, AKNS-2 reversed the reduced cell viability and tyrosine hydroxylase (TH) levels and reduced the induced α-synuclein level. In an MPTP-induced in vivo PD model, AKNS-2 improved mice behavioral performance, and it restored dopamine synthesis and TH and α-synuclein expression in mouse brain tissues. Consistently, AKNS-2 also modulated the expressions of autophagy related markers in mouse brain tissue. Thus, AKNS-2 upregulates autophagy by activating the Erk/mTOR and AMPK/mTOR pathways. AKNS-2 exerts its neuroprotective effect through autophagy activation and may serve as a potential candidate for PD therapy.

• Journal of Preventive Medicine and Public Health
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• v.54 no.1
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• pp.55-62
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• 2021

Objectives: After heart disease, brain stroke (BS) is the second most common cause of death worldwide, underscoring the importance of understanding preventable and treatable risk factors for the outcomes of BS. This study aimed to model the survival of patients with BS in the presence of competing risks. Methods: This longitudinal study was conducted on 332 patients with a definitive diagnosis of BS. Demographic characteristics and risk factors were collected by a validated checklist. Patients' mortality status was investigated by telephone follow-up to identify deaths that may be have been caused by stroke or other factors (heart disease, diabetes, high cholesterol, etc.). Data were analyzed by the Lunn-McNeil approach at alpha=0.1. Results: Older age at diagnosis (59-68 years: adjusted hazard ratio [aHR], 2.19; 90% confidence interval [CI], 1.38 to 3.48; 69-75 years: aHR, 5.04; 90% CI, 3.25 to 7.80; ≥76 years: aHR, 5.30; 90% CI, 3.40 to 8.44), having heart disease (aHR, 1.65; 90% CI, 1.23 to 2.23), oral contraceptive pill use (women only) (aHR, 0.44; 90% CI, 0.24 to 0.78) and ischemic stroke (aHR, 0.52; 90% CI, 0.36 to 0.74) were directly related to death from BS. Older age at diagnosis (59-68 years: aHR, 21.42; 90% CI, 3.52 to 130.39; 75-69 years: aHR, 16.48; 90% CI, 2.75 to 98.69; ≥76 years: aHR, 26.03; 90% CI, 4.06 to 166.93) and rural residence (aHR, 2.30; 90% CI, 1.15 to 4.60) were directly related to death from other causes. Significant risk factors were found for both causes of death. Conclusions: BS-specific and non-BS-specific mortality had different risk factors. These findings could be utilized to prescribe optimal and specific treatment.

• Journal of Veterinary Science
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• v.23 no.3
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• pp.41.1-41.15
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• 2022

Background: Proliferative enteritis caused by Lawsonia intracellularis undermines the economic stability of the swine industry worldwide. The development of cost-effective animal models to study the pathophysiology of the disease will help develop strategies to counter this bacterium. Objectives: This study focused on establishing a model of gastrointestinal (GI) infection of L. intracellularis in C57BL/6 mice to evaluate the disease progression and lesions of proliferative enteropathy (PE) in murine GI tissue. Methods: We assessed the murine mucosal and cell-mediated immune responses generated in response to inoculation with L. intracellularis. Results: The mice developed characteristic lesions of the disease and shed L. intracellularis in the feces following oral inoculation with 5 × 10⁷ bacteria. An increase in L. intracellularis 16s rRNA and groEL copies in the intestine of infected mice indicated intestinal dissemination of the bacteria. The C57BL/6 mice appeared capable of modulating humoral and cell-mediated immune responses to L. intracellularis infection. Notably, the expression of genes for the vitamin B12 receptor and for secreted and membrane-bound mucins were downregulated in L. intracellularis -infected mice. Furthermore, L. intracellularis colonization of the mouse intestine was confirmed by the immunohistochemistry and western blot analyses. Conclusions: This is the first study demonstrating the contributions of bacterial chaperonin and host nutrient genes to PE using an immunocompetent mouse model. This mouse infection model may serve as a platform from which to study L. intracellularis infection and develop potential vaccination and therapeutic strategies to treat PE.

• Korean Journal of Acupuncture
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• v.39 no.2
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• pp.34-42
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• 2022

Objectives : Parkinson's disease (PD) is a neurodegenerative disease caused by dopaminergic neuronal death in the substantia nigra pars compacta. PD is known to be linked with mitochondrial dysfunction and increased oxidative stress. In this study, anti-cytotoxic and anti-oxidative effect of 12 herbal formulae were compared. Methods : According to experts' advice, 12 types of herbal formulae (Gamisoyosan, Galgeuntang, Galgeunhaegitang, Banhabaekchoolcheonmatang, Bojungikgitang, Boheotang, Sihogyejitang, Sihosogantang, Sihocheonggantang, Ojeoksan, Cheongsanggyeontongtang and Palmultang) were selected from 56 types of herbal formulae covered by the National Health Insurance Service in Korea. To detect anti-oxidative effect, 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay was performed, and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay was performed to detect anti-cytotoxic effect of 12 herbal formulae using SH-SY5Y human neuroblastoma cells. Results : In DPPH assay, anti-oxidant activity was increased in a dose-dependent manner and half maximal inhibitory concentration was highest in the order of Galgeuntang, Gamisoyosan, Galgeunhaegitang, Ojeoksan, Palmultang, Sihogyejitang, Sihosogantang, Cheongsanggyeontongtang, Sihocheonggantang, Bojungikgitang, Boheotang and Banhabaekchoolcheonmatang. In MTT assay, concentration of 80% cell survival was highest in the order of Sihosogantang, Cheongsanggyeontongtang, Sihocheonggantang, Sihogyejitang, Bojungikgitang, Galgeuntang, Ojeoksan, Boheotang, Palmultang, Galgeunhaegitang, Banhabaekchoolcheonmatang and Gamisoyosan. Formulae with more than 50% DPPH radical scavenging activity at concentrations for 80% cell survival were Sihosogantang, Cheongsanggyeontongtang, Sihogyejitang, Galgeuntang and Sihocheonggantang. Conclusions : Sihosogantang, Cheongsanggyeontongtang, Sihogyejitang, Galgeuntang and Sihocheonggantang extracts can be candidate medicines for PD, but the effect should be validated in PD models.

• Journal of Pharmacopuncture
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• v.25 no.4
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• pp.326-343
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• 2022

Neurological disorders represent a substantial healthcare burden worldwide due to population aging. Acorus gramineus Solander (AG) and Acorus tatarinowii Schott (AT), whose major component is asarone, have been shown to be effective in neurological disorders. This review summarized current information from preclinical and clinical studies regarding the effects of extracts and active components of AG and AT (e.g., α-asarone and β-asarone) on neurological disorders and biomedical targets, as well as the mechanisms involved. Databases, including PubMed, Embase, and RISS, were searched using the following keywords: asarone, AG, AT, and neurological disorders, including Alzheimer's disease, Parkinson's disease, depression and anxiety, epilepsy, and stroke. Meta-analyses and reviews were excluded. A total of 873 studies were collected. A total of 89 studies were selected after eliminating studies that did not meet the inclusion criteria. Research on neurological disorders widely reported that extracts or active components of AG and AT showed therapeutic efficacy in treating neurological disorders. These components also possessed a wide array of neuroprotective effects, including reduction of pathogenic protein aggregates, antiapoptotic activity, modulation of autophagy, anti-inflammatory and antioxidant activities, regulation of neurotransmitters, activation of neurogenesis, and stimulation of neurotrophic factors. Most of the included studies were preclinical studies that used in vitro and in vivo models, and only a few clinical studies have been performed. Therefore, this review summarizes the current knowledge on AG and AT therapeutic effects as a basis for further clinical studies, and clinical trials are required before these findings can be applied to human neurological disorders.

• Smart Media Journal
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• v.12 no.7
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• pp.9-17
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• 2023

Plant diseases and pests affect the growth of various plants, so it is very important to identify pests at an early stage. Although many machine learning (ML) models have already been used for the inspection and classification of plant pests, advances in deep learning (DL), a subset of machine learning, have led to many advances in this field of research. In this study, disease and pest inspection of abnormal crops and maturity classification were performed for normal crops using YOLOX detector and MobileNet classifier. Through this method, various plant pest features can be effectively extracted. For the experiment, image datasets of various resolutions related to strawberries, peppers, and tomatoes were prepared and used for plant pest classification. According to the experimental results, it was confirmed that the average test accuracy was 84% and the maturity classification accuracy was 83.91% in images with complex background conditions. This model was able to effectively detect 6 diseases of 3 plants and classify the maturity of each plant in natural conditions.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.148-162
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• 2023

Classification systems can significantly assist the medical sector by allowing for the precise and quick diagnosis of diseases. As a result, both doctors and patients will save time. A possible way for identifying risk variables is to use machine learning algorithms. Non-surgical technologies, such as machine learning, are trustworthy and effective in categorizing healthy and heart-disease patients, and they save time and effort. The goal of this study is to create a medical intelligent decision support system based on machine learning for the diagnosis of heart disease. We have used a mixed feature creation (MFC) technique to generate new features from the UCI Cleveland Cardiology dataset. We select the most suitable features by using Least Absolute Shrinkage and Selection Operator (LASSO), Recursive Feature Elimination with Random Forest feature selection (RFE-RF) and the best features of both LASSO RFE-RF (BLR) techniques. Cross-validated and grid-search methods are used to optimize the parameters of the estimator used in applying these algorithms. and classifier performance assessment metrics including classification accuracy, specificity, sensitivity, precision, and F1-Score, of each classification model, along with execution time and RMSE the results are presented independently for comparison. Our proposed work finds the best potential outcome across all available prediction models and improves the system's performance, allowing physicians to diagnose heart patients more accurately.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.305-307
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• 2021

Alzheimer's Disease (AD) is a cognitive disorder characterized by memory impairment that can be assessed at early stages based on administering clinical tests. However, the AD pathophysiological mechanism is still poorly understood due to the difficulty of distinguishing different levels of AD severity, even using a variety of brain modalities. Therefore, in this study, we present a hybrid EEG-fNIRS modalities to compensate for each other's weaknesses with the help of Machine Learning (ML) techniques for classifying four subject groups, including healthy controls (HC) and three distinguishable groups of AD levels. A concurrent EEF-fNIRS setup was used to record the data from 41 subjects during Oddball and 1-back tasks. We employed both a traditional neural network (NN) and a CNN-LSTM hybrid model for fNIRS and EEG, respectively. The final prediction was then obtained by using majority voting of those models. Classification results indicated that the hybrid EEG-fNIRS feature set achieved a higher accuracy (71.4%) by combining their complementary properties, compared to using EEG (67.9%) or fNIRS alone (68.9%). These findings demonstrate the potential of an EEG-fNIRS hybridization technique coupled with ML-based approaches for further AD studies.