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  • 1
    Online Resource
    Online Resource
    Change in Paralytic Shellfish Toxins in the Mussel Mytilus galloprovincialis Depending on Dynamics of Harmful Alexandrium catenella (Group I) in the Geoje Coast (South Korea) during Bloom Season
    MDPI AG ; 2020
    In:  Toxins Vol. 12, No. 7 ( 2020-07-07), p. 442-
    Details
    In: Toxins, MDPI AG, Vol. 12, No. 7 ( 2020-07-07), p. 442-
    Abstract: Paralytic shellfish toxins (PSTs) produced by Alexandrium catenella (formerly A. tamarense) in Korean coastal waters caused the deaths of four people (in 1986 and 1996) who consumed contaminated mussels (Mytilus edulis). This led to more detailed consideration of the risks of PST outbreaks and incidents in Korea, including the introduction of shellfish collection bans. In this study, we investigated the relationships between A. catenella population dynamics and PST accumulation in the mussel M. galloprovincialis. Discharges from the Nakdong River affect the environmental conditions along the Geoje coast, resulting in low salinity and high nutrient levels that trigger blooms of A. catenella. At the toxin peak on 24 April 2017, the toxins detected in A. catenella cells were C1, gonyautoxin (GTX)1 and GTX2, whereas the concentrations of PSTs in M. galloprovincialis were high and in the order of GTX4 〉 GTX1 〉 GTX3 〉 saxitoxin (STX) 〉 GTX2 〉 neoSTX 〉 decarbamoylgonyautoxin (dcGTX)2 〉 dc GTX3. The PST level in mussels was also high. At 15 °C, the PSTs are constantly found to be higher (10-fold higher in 2017 and 30-fold higher in 2018) than safe levels for human consumption (80 μg STX diHCl equivalents 100 g−1).
    Type of Medium: Online Resource
    ISSN: 2072-6651
    URL: Article
    DOI: 10.3390/toxins12070442
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2518395-3
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  • 2
    Online Resource
    Online Resource
    A Study on Customized Prediction of Daily Illness Risk Using Medical and Meteorological Data
    MDPI AG ; 2022
    In:  Applied Sciences Vol. 12, No. 12 ( 2022-06-15), p. 6060-
    Details
    In: Applied Sciences, MDPI AG, Vol. 12, No. 12 ( 2022-06-15), p. 6060-
    Abstract: This study selected the most common illnesses in children and older adults and aimed to provide a customized degree of daily risk for each illness based on patient data for specific regions and illnesses. Sample medical data of one million people provided by the National Health Insurance Corporation and information regarding the meteorological environment and atmosphere from the Korea Meteorological Administration and a public data portal using application programing interface were collected. Learning and predictions were carried out with machine learning. Models with high R2 were selected and tuned to determine the optimal hyperparameter for predicting the degree of daily risk of an illness. Illnesses with an R2 value greater than 0.65 were considered significant. For children, these consisted of acute bronchitis, the common cold, rhinitis and tonsillitis, and middle ear inflammation. For older adults, they consisted of high blood pressure and heart disease, the common cold, esophageal inflammation and gastritis, acute bronchitis, eczema and dermatitis, and chronic bronchitis. This study provides the degree of daily risk for the most common illnesses in each age group. Furthermore, the results of this study are expected to raise awareness of illnesses that occur in certain climates and to help prevent them.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app12126060
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
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  • 3
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    Online Resource
    Anti-Metastatic Effect of Pyruvate Dehydrogenase Kinase 4 Inhibition in Bladder Cancer via the ERK, SRC, and JNK Pathways
    MDPI AG ; 2022
    In:  International Journal of Molecular Sciences Vol. 23, No. 21 ( 2022-10-31), p. 13240-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 23, No. 21 ( 2022-10-31), p. 13240-
    Abstract: Bladder cancer is a common global cancer with a high percentage of metastases and high mortality rate. Thus, it is necessary to identify new biomarkers that can be helpful in diagnosis. Pyruvate dehydrogenase kinase 4 (PDK4) belongs to the PDK family and plays an important role in glucose utilization in living organisms. In the present study, we evaluated the role of PDK4 in bladder cancer and its related protein changes. First, we observed elevated PDK4 expression in high-grade bladder cancers. To screen for changes in PDK4-related proteins in bladder cancer, we performed a comparative proteomic analysis using PDK4 knockdown cells. In bladder cancer cell lines, PDK4 silencing resulted in a lower rate of cell migration and invasion. In addition, a PDK4 knockdown xenograft model showed reduced bladder cancer growth in nude mice. Based on our results, PDK4 plays a critical role in the metastasis and growth of bladder cancer cells through changes in ERK, SRC, and JNK.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms232113240
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 4
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    Online Resource
    ARPNet: Antidepressant Response Prediction Network for Major Depressive Disorder
    MDPI AG ; 2019
    In:  Genes Vol. 10, No. 11 ( 2019-11-07), p. 907-
    Details
    In: Genes, MDPI AG, Vol. 10, No. 11 ( 2019-11-07), p. 907-
    Abstract: Treating patients with major depressive disorder is challenging because it takes several months for antidepressants prescribed for the patients to take effect. This limitation may result in increased risks and treatment costs. To address this limitation, an accurate antidepressant response prediction model is needed. Recently, several studies have proposed models that extract useful features such as neuroimaging biomarkers and genetic variants from patient data, and use them as predictors for predicting the antidepressant responses of patients. However, it is impossible to utilize all the different types of predictors when making a clinical decision on what drugs to prescribe for a patient. Although a machine learning-based antidepressant response prediction model has been proposed to overcome this problem, the model cannot find the most effective antidepressant for a patient. Based on a neural network, we propose an Antidepressant Response Prediction Network (ARPNet) model capturing high-dimensional patterns from useful features. Based on a literature survey and data-driven feature selection, we extract useful features from patient data, and use the features as predictors. In ARPNet, the patient representation layer captures patient features and the antidepressant prescription representation layer captures antidepressant features. Utilizing the patient and antidepressant prescription representation vectors, ARPNet predicts the degree of antidepressant response. The experimental evaluation results demonstrate that our proposed ARPNet model outperforms machine learning-based models in predicting antidepressant response. Moreover, we demonstrate the applicability of ARPNet in downstream applications in use case scenarios.
    Type of Medium: Online Resource
    ISSN: 2073-4425
    URL: Article
    DOI: 10.3390/genes10110907
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2527218-4
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  • 5
    Online Resource
    Online Resource
    Factors Affecting Depressive Symptoms among North Korean Adolescent Refugees Residing in South Korea
    MDPI AG ; 2017
    In:  International Journal of Environmental Research and Public Health Vol. 14, No. 8 ( 2017-08-14), p. 912-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 14, No. 8 ( 2017-08-14), p. 912-
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph14080912
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2175195-X
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  • 6
    Online Resource
    Online Resource
    Intestinal Immune Cell Populations, Barrier Function, and Microbiomes in Broilers Fed a Diet Supplemented with Chlorella vulgaris
    MDPI AG ; 2023
    In:  Animals Vol. 13, No. 14 ( 2023-07-21), p. 2380-
    Details
    In: Animals, MDPI AG, Vol. 13, No. 14 ( 2023-07-21), p. 2380-
    Abstract: This study aimed to evaluate the effects of dietary Chlorella vulgaris (CV) on the distribution of immune cells, intestinal morphology, intestinal barrier function, antioxidant markers, and the cecal microbiome in 10-day-old broiler chickens. A total of 120 day-old Ross 308 male broiler chicks were assigned to two dietary treatments using a randomized complete block design, with body weight as the blocking factor. Birds fed a diet containing CV showed an increase in CD4+ T cells (p 〈 0.05) compared to those fed the control diet. The relative mRNA expression of intestinal epithelial barrier function-related markers (occludin and avian β-defensin 5) was elevated (p 〈 0.05) in the CV-supplemented group compared to the control group. The alpha diversity indices (Chao1 and observed features) of the cecal microbiome in 10-day-old birds increased (p 〈 0.05), indicating higher richness within the cecal bacterial community. In the microbiome analysis, enriched genera abundance of Clostridium ASF356 and Coriobacteriaceae CHKCI002 was observed in birds fed the diet containing CV compared to those fed the control diet. Taken together, dietary CV supplementation might alter intestinal barrier function, immunity, and microbiomes in 10-day-old broiler chickens.
    Type of Medium: Online Resource
    ISSN: 2076-2615
    URL: Article
    DOI: 10.3390/ani13142380
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2606558-7
    SSG: 23
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  • 7
    Online Resource
    Online Resource
    Anti-Inflammatory Effect of Melittin on Porphyromonas Gingivalis LPS-Stimulated Human Keratinocytes
    MDPI AG ; 2018
    In:  Molecules Vol. 23, No. 2 ( 2018-02-05), p. 332-
    Details
    In: Molecules, MDPI AG, Vol. 23, No. 2 ( 2018-02-05), p. 332-
    Type of Medium: Online Resource
    ISSN: 1420-3049
    URL: Article
    DOI: 10.3390/molecules23020332
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2008644-1
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  • 8
    Online Resource
    Online Resource
    Evaluation of Fermented Oat and Black Soldier Fly Larva as Food Ingredients in Senior Dog Diets
    MDPI AG ; 2021
    In:  Animals Vol. 11, No. 12 ( 2021-12-09), p. 3509-
    Details
    In: Animals, MDPI AG, Vol. 11, No. 12 ( 2021-12-09), p. 3509-
    Abstract: The aim of this study was to evaluate the suitability of fermented oat (FO) and black soldier fly larva (BSFL) as food ingredients for dogs. A total of 20 spayed female dogs were divided into four treatment groups, with 5 dogs per group. The four treatment groups consisted of a control group, a diet with 10% FO, one with 5% BSFL, and one with 10% FO and 5% BSFL, and each experimental food was fed for 12 weeks. The feeding of FO and/or BSFL did not affect the daily food intake, body weight, body condition score, fecal score, or skin condition of the dogs. In all the experimental groups, no significant differences in serum IgG, IL-10, or TNF-α levels were observed upon the feeding of FO and/or BSFL. Some hematological (white blood cell and basophils) and serum biochemical parameters (phosphorous, globulin, and alkaline phosphatase) showed significant differences with FO and/or BSFL feeding compared to the control group, but they were within the normal reference range. No adverse clinical signs related to these parameters being affected by FO and BSFL were observed. The feeding of BSFL for 12 weeks reduced the serum cholesterol level (p 〈 0.05) at the end of the experiment. Our findings suggest the suitability of FO and BSFL as food materials for dogs.
    Type of Medium: Online Resource
    ISSN: 2076-2615
    URL: Article
    DOI: 10.3390/ani11123509
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2606558-7
    SSG: 23
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  • 9
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    Online Resource
    Adverse Events Following Immunization Associated with the First and Second Doses of the ChAdOx1 nCoV-19 Vaccine among Healthcare Workers in Korea
    MDPI AG ; 2021
    In:  Vaccines Vol. 9, No. 10 ( 2021-09-28), p. 1096-
    Details
    In: Vaccines, MDPI AG, Vol. 9, No. 10 ( 2021-09-28), p. 1096-
    Abstract: As worldwide large-scale inoculation of novel vaccines is on the way, the importance of real-world data on safety cannot be overemphasized. We aimed to investigate the adverse events following immunization (AEFIs) associated with the ChAdOx1 nCoV-19 vaccine among healthcare workers (HCWs). We investigated the systemic and local adverse events reported within seven days following the first and second doses of vaccination, using the mobile vaccine adverse events reporting system (MVAERS) developed by our hospital. The response rates were 71.8% (994/1384) and 52.9% (727/1375) after the first and second doses, respectively. The most commonly reported AEFIs were tenderness and pain at the injection site and fatigue after the first and second doses. In comparison to the first dose, the incidence and severity of AEFIs were lower following the second dose. Since the Korean government does not recommend the ChAdOx1 nCoV-19 vaccination for those under 30 years of age, with greater risk than benefit, we additionally compared the AEFIs of age groups under and above 30 years of age. The overall incidence of AEFIs was similar in both the under and over 30 age groups. In conclusion, AEFIs associated with the ChAdOx1 nCoV-19 vaccine were found to be tolerable, and AEFIs associated with the second dose were less common and severe compared to the first dose. Further safety surveillance studies on COVID-19 vaccines are required to validate our findings.
    Type of Medium: Online Resource
    ISSN: 2076-393X
    URL: Article
    DOI: 10.3390/vaccines9101096
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2703319-3
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  • 10
    Online Resource
    Online Resource
    Polyphenol-Rich Black Elderberry Extract Stimulates Transintestinal Cholesterol Excretion
    MDPI AG ; 2021
    In:  Applied Sciences Vol. 11, No. 6 ( 2021-03-21), p. 2790-
    Details
    In: Applied Sciences, MDPI AG, Vol. 11, No. 6 ( 2021-03-21), p. 2790-
    Abstract: Hypercholesterolemia is the primary risk factor for cardiovascular disease (CVD). Recent studies reported that the stimulation of transintestinal cholesterol excretion (TICE), a nonbiliary cholesterol excretion, can be a strategy for preventing CVD. Black elderberry (Sambucus nigra) has been reported to reduce the risk of CVD via its antioxidant, anti-inflammatory, and hypocholesterolemic effects. However, little is known about the role of black elderberry in intestinal cholesterol metabolism despite its well-known effects on cholesterol homeostasis regulation. To investigate the effects of polyphenol-rich black elderberry extract (BEE) on intestinal cholesterol metabolism, we measured the expression of genes involved in cholesterol biosynthesis and flux in Caco-2 cells. BEE significantly decreased the messenger RNA (mRNA) and protein levels of genes for cholesterol absorption, such as Niemann–Pick C1 Like 1 and ATP-binding cassette transporter A1 (ABCA1). In contrast, there was marked induction of low-density lipoprotein receptor, ABCG5/G8, and ABCB1 in BEE-treated Caco-2 cells. Furthermore, BEE decreased the expression of genes for lipogenesis and altered the mRNA levels of sirtuins. All of the genes altered by BEE were in the direction of flux cholesterol from the basolateral to apical side of enterocytes, indicating stimulation of TICE. These results support the hypocholesterolemic effects of BEE for the prevention of CVD.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app11062790
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2704225-X
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