• Journal of Microbiology and Biotechnology
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• v.29 no.8
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• pp.1281-1287
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• 2019

Nattokinase (NK, E.C. 3.4.21.62) is a serine protease produced by Bacillus subtilis natto that shows promise for the treatment of thrombotic disease. In this study, we assessed the effects of NK on the development of hepatocellular carcinoma (HCC), a principal malignancy of the liver that causes morbidity and mortality worldwide. Crude extracts of NK (NCE) were isolated from fermentation medium by centrifugation and separated into three fractions (<10 K, 100~30 K and >30K). Orthotopic HCC mouse models were established and NCE was administered by oral gavage. H&E staining was performed to examine the pathology of HCC livers. Immunohistochemistry and immunofluorescence were used to evaluate FOXM1, CD31, CD44 and vimentin expression in the liver. Compared to PBS groups, NCE increased the survival rates of HCC-bearing mice to 31% and decreased ascites. Low-intensity ultrasound imaging showed that the hypoechoic mass area was lower in NCE-treated mice and that tumor growth significantly decreased. IHC staining showed that the expression of FOXM1 was inhibited by NCE treatment. Immunofluorescence results revealed lower levels of CD31, CD44 and vimentin in the NCE groups. Taken together, these data demonstrate that NCE from Bacillus subtilis natto improves survival and inhibits tumor growth in HCC mice.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.1
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• pp.1-12
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• 2019

Objective: Significant concerns have been raised over chemical exposure and potential health risks such as increased cancer mortality among laboratory workers. The aim of this study was to investigate the overall exposure and unit task exposure levels of researchers in organic synthesis laboratories at universities. Methods: Seventy-seven personal Time-weighted average(TWA) samples and 139 task-based samples from four organic synthesis laboratories at two universities were collected over three days. The concentrations of acetone, chloroform, dichloromethane(DCM), diethyl ether, ethyl acetate, n-hexane, tetrahydrofuran(THF), benzene, toluene, and xylene were determined using the GC-FID. Results: The most frequently used chemicals in the laboratories were acetone, DCM, n-hexane, methanol, and THF. Carcinogens such as benzene, chloroform, and DCM were used in one or more laboratories. The TWA full-shift exposures of researchers to acetone was the highest(ND-59.3 ppm). Benzene was observed above the occupational exposure limit in 18-40% of the samples. The levels of exposure to organic solvents were statistically different by task(p<0.05), while washing task was the highest. Washing was not perceived as a part of the real lab tasks. Rather it was considered as simple dish-washing or experimental preparation and performed in an open sink where exposure to organic solvents was unavoidable. TWAs and task-based concentrations were compared by substance, which suggests that TWA-based assessment could not reflect short-term and high concentration exposures. Conclusions: Laboratory workers may be exposed to various organic solvents at levels of concern. TWA-based measurement alone cannot guarantee holistic exposure assessment among lab workers as their exposures are very dependent on their tasks. Further investigation and characterization for specific tasks and overall chronic exposures will help protect lab workers from unnecessary exposure to chemicals while they perform research.

• Journal of Acupuncture Research
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• v.39 no.4
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• pp.310-316
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• 2022

Background: Verbenalin is an iridoid glucoside, which is among the active components of some medicinal herbs such as Verbena officinalis Linn, and Cornus officinalis Siebold and Zucc. Previous studies have confirmed the antioxidant activity and neuroprotective potential of verbenalin. To confirm the safety of verbenalin, an approximate lethal dose was determined based on a single oral dose toxicity study. Methods: Institute of Cancer Research mice were randomly assigned to three verbenalin exposure groups (250, 500, and 1,000 mg/kg) and a control group (5% methylcellulose solution). There were (5 male and 5 female mice per group). Mortality, clinical signs, and body weight were monitored for 14 days, and necropsies were conducted. Results: No mortalities were observed in the control group or the verbenalin 250 mg/kg group, whereas mortalities were observed in the 500 mg/kg and 1,000 mg/kg verbenalin groups. During the observation period, stool abnormalities such as mucous stools were observed. Clinical signs such as loss of locomotor activity were observed in the 500 mg/kg and 1,000 mg/kg verbenalin groups. During the study period, significant changes in body weight were observed in the 500 mg/kg and 1,000 mg/kg verbenalin groups; however, no gross abnormalities were observed at necropsy. Overall, no toxicity was found in the 250 mg/kg group. Conclusion: The approximate lethal dose of verbenalin was estimated to be 500 mg/kg. For a more accurate assessment of the safety of verbenalin, other types of studies such as repeated-dose toxicity studies should also be conducted.

• Nutrition Research and Practice
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• v.16 no.6
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• pp.700-715
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• 2022

BACKGROUND/OBJECTIVES: Chronic colitis is a risk factor for colorectal cancer (CRC) development in both animals and humans. Previously, we reported that a diet rich in protein (with casein as the protein source) significantly increased the risk of mouse CRC development in a dose-dependent manner. In this study, we investigated the effects of different protein sources on the risk of colitis development. MATERIALS/METHODS: Balb/c mice were divided into 7 experimental groups: 20% casein (20C), 20C-dextran sulfate sodium (DSS), 40% casein-DSS (40CD), 40% whey protein-DSS (40WD), 40% soy protein-DSS (40SD), 40% white meat-DSS (40WMD), and 40% red meat-DSS (40RMD). Mice were fed an experimental diet for 4 wk and received 3% DSS in their drinking water for 6 days during the 4th wk of the experimental period. RESULTS: Compared to other groups, the 40CD group showed the most aggravated colitis with increased disease activity and inflammatory markers. In the 40RMD group, interleukin (IL)-6 levels were the highest among all the groups. The 40SD group showed conflicting effects, for example, elevated mortality and disease activity but decreased nitric oxide (NO) levels. The 40WD group showed attenuated colitis with increased IL-10 levels and decreased NO levels. The 40WMD group showed conflicting effects, including decreased NO levels and elevated fecal lipocalin-2 and IL-6 levels. CONCLUSIONS: These results suggest that, at levels of 40% in the diet, casein and red meat exacerbate colitis, whereas whey protein mitigates it the most effectively.

• Journal of Ginseng Research
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• v.46 no.3
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• pp.337-347
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• 2022

Coronavirus disease 2019 (COVID-19) is currently a pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 are directly associated with hyper-activation of innate immune response that excessively produce pro-inflammatory cytokines and induce cytokine storm, leading to multi-organ-failure and significant morbidity/mortality. Currently, several antiviral drugs such as Paxlovid (nirmatrelvir and ritonavir) and molnupiravir are authorized to treat mild to moderate COVID-19, however, there are still no drugs that can specifically fight against challenges of SARS-CoV-2 variants. Panax ginseng, a medicinal plant widely used for treating various conditions, might be appropriate for this need due to its anti-inflammatory/cytokine/viral activities, fewer side effects, and cost efficiency. To review Panax ginseng and its pharmacologically active-ingredients as potential phytopharmaceuticals for treating cytokine storm of COVID-19, articles that reporting its positive effects on the cytokine production were searched from academic databases. Experimental/clinical evidences for the effectiveness of Panax ginseng and its active-ingredients in preventing or mitigating cytokine storm, especially for the cascade of cytokine storm, suggest that they might be beneficial as an adjunct treatment for cytokine storm of COVID-19. This review may provide a new approach to discover specific medications using Panax ginseng to control cytokine storm of COVID-19.

• Korean Journal of Clinical Pharmacy
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• v.33 no.2
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• pp.113-121
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• 2023

Background: Globally, the number of patients with aspergillosis is increasing, and the mortality rate remains high. This study aimed to investigate prescribing patterns of antifungal drugs for patients with aspergillosis in South Korea using real-world data. Methods: This retrospective cross-sectional study was performed using National Patient Sample (NPS) data collected by the Health Insurance Review and Assessment Service (HIRA) during 2011-2020. The use of antifungal drugs in patients with aspergillosis was investigated. Results:A total of 1374 patients were identified: 333 patients with invasive pulmonary aspergillosis (IPA) (24.2%), 436 patients with other PA (31.7%), 73 patients with other forms of aspergillosis (5.3%), and 532 patients with unspecified aspergillosis (38.7%). The odds of receiving an antifungal prescription were higher for IPA than for other PA (aOR, 0.233; p<0.001), and higher for hematologic malignancies than for respiratory disorders other than cancer or infections (aOR, 10.018; p<0.001). During each hospitalization period, 56.1% (97/173) and 6.4% (11/173) of IPA hospitalizations received voriconazole and itraconazole monotherapy, respectively, whereas 44.3% (27/61) and 27.9% (17/61) of other PA hospitalizations received itraconazole and voriconazole monotherapy, respectively. Among outpatients with IPA, 67.5% (85/126) and 26.2% (33/126) received voriconazole and itraconazole alone, respectively, whereas among outpatients with other PA, 86.1% (68/79) and 12.7% (10/79) received itraconazole and voriconazole alone, respectively, during the year. Conclusion: In Korea, voriconazole monotherapy was preferred in IPA inpatients, and itraconazole monotherapy was preferred in other PA inpatients. In the ambulatory care settings for IPA and other PA, itraconazole monotherapy was preferred.

• Archives of Craniofacial Surgery
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• v.24 no.5
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• pp.211-217
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• 2023

Background: Oral cavity cancers, the second most common type in India, are responsible for 10% of the overall cancer burden. With a recurrence rate of 30% to 40% and a 5-year survival rate of 50%, these malignancies account for substantial morbidity and mortality. Despite advances in treatment modalities, survival rates following treatment completion have not improved significantly. The present study aimed to establish specific epidemiological and pathological factors responsible for recurrence after treatment completion in buccal mucosa cancers. Methods: A retrospective analysis of the data of 116 patients treated for biopsy-proven cancers of the buccal mucosa was undertaken 1 year after treatment completion. Factors such as age, sex, education, lymphovascular invasion, extranodal extension (ENE), perineural invasion, depth of invasion, and pathological margin status were compared between patients who presented with recurrence and those who did not. Statistical significance was set at p< 0.05. Results: Of the 116 patients, 40 (34.5%) developed a recurrent disease within 1 year. The mean age of the study population was 43.3 years, and males constituted 91.4% of the included patients. Ipsilateral buccal mucosa was the commonest site of disease recurrence. Neck node metastasis, ENE, and margins of resection < 5 mm were significantly related to the recurrence of disease. However, surprisingly, lymphovascular invasion, perineural invasion, and depth of invasion > 10 mm did not show statistically significant associations. Conclusion: Neck node metastasis, ENE, and margins of resection < 5 mm were the histopathological factors associated with recurrence in cancers of the buccal mucosa.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2021.04a
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• pp.65-66
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• 2021

Glycyrrhiza species (Licorice) are one of the most commonly used medicinal plants in Asian countries such as China, India and Korea. It has been traditionally used to treat many disease including cough, cold, asthma, fatigue, gastritis and respiratory tract infections. Glycyrrhiza new variety, Wongam (WG), have been developed by Korea Rural Development Administration and revealed several pharmacological effects. However, limited data are available on the potential adverse effects of the WG. Here, we evaluated the general toxicity of the WG extract through single oral dose toxicity study in Sprague-Dawley rats. After single oral dose administration, there was no mortality up to 5000 mg/kg during experiment period. In addition, there was no clinical signs including body weight change, gross findings and necropsy findings up to 5000 mg/kg during experiment period. To conclude, the no-observed-adverse-effect level (NOAEL) of WG was higher than 5000 mg/kg and no target organs were identified in male and female Sprague-Dawley rats.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.101-106
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• 2023

Chronic illnesses are among the most common serious problems affecting human health. Early diagnosis of chronic diseases can assist to avoid or mitigate their consequences, potentially decreasing mortality rates. Using machine learning algorithms to identify risk factors is an exciting strategy. The issue with existing feature selection approaches is that each method provides a distinct set of properties that affect model correctness, and present methods cannot perform well on huge multidimensional datasets. We would like to introduce a novel model that contains a feature selection approach that selects optimal characteristics from big multidimensional data sets to provide reliable predictions of chronic illnesses without sacrificing data uniqueness.[1] To ensure the success of our proposed model, we employed balanced classes by employing hybrid balanced class sampling methods on the original dataset, as well as methods for data pre-processing and data transformation, to provide credible data for the training model. We ran and assessed our model on datasets with binary and multivalued classifications. We have used multiple datasets (Parkinson, arrythmia, breast cancer, kidney, diabetes). Suitable features are selected by using the Hybrid feature model consists of Lassocv, decision tree, random forest, gradient boosting,Adaboost, stochastic gradient descent and done voting of attributes which are common output from these methods.Accuracy of original dataset before applying framework is recorded and evaluated against reduced data set of attributes accuracy. The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy on multi valued class datasets than on binary class attributes.[1]

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.2
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• pp.195-200
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• 2023

Backgrounds/Aims: We aimed to build a machine learning tool to help predict low-grade intraductal papillary mucinous neoplasms (IPMNs) in order to avoid unnecessary surgical resection. IPMNs are precursors to pancreatic cancer. Surgical resection remains the only recognized treatment for IPMNs yet carries some risks of morbidity and potential mortality. Existing clinical guidelines are imperfect in distinguishing low-risk cysts from high-risk cysts that warrant resection. Methods: We built a linear support vector machine (SVM) learning model using a prospectively maintained surgical database of patients with resected IPMNs. Input variables included 18 demographic, clinical, and imaging characteristics. The outcome variable was the presence of low-grade or high-grade IPMN based on post-operative pathology results. Data were divided into a training/validation set and a testing set at a ratio of 4:1. Receiver operating characteristics analysis was used to assess classification performance. Results: A total of 575 patients with resected IPMNs were identified. Of them, 53.4% had low-grade disease on final pathology. After classifier training and testing, a linear SVM-based model (IPMN-LEARN) was applied on the validation set. It achieved an accuracy of 77.4%, with a positive predictive value of 83%, a specificity of 72%, and a sensitivity of 83% in predicting low-grade disease in patients with IPMN. The model predicted low-grade lesions with an area under the curve of 0.82. Conclusions: A linear SVM learning model can identify low-grade IPMNs with good sensitivity and specificity. It may be used as a complement to existing guidelines to identify patients who could avoid unnecessary surgical resection.