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  1. Book ; Thesis: Einfluss von EPs 7630 auf die Adhäsionskinetik von A-Streptokokken an HEp-2-Zellen

    Jung, Irina

    2010  

    Author's details vorgelegt von Irina Jung
    Language German ; English
    Size 58 Bl., Ill., graph. Darst.
    Edition [Mikrofiche-Ausg.]
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Freiburg (Breisgau), Univ., Diss., 2011
    HBZ-ID HT017038533
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    2005 MB 643 order for loan Magazin

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  2. Book: Asian facial cosmetic surgery

    Park, Jung I.

    2007  

    Author's details ed. by Jung I. Park
    Keywords Reconstructive Surgical Procedures ; Face ; Asian Continental Ancestry Group
    Language English
    Size XII, 436 S. : zahlr. Ill.
    Publisher Saunders Elsevier
    Publishing place Philadelphia, Pa
    Publishing country United States
    Document type Book
    HBZ-ID HT014836876
    ISBN 978-1-4160-0290-1 ; 1-4160-0290-1
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    2006 A 5661 order for loan Magazin

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  3. Article ; Online: A simulation-based comparison of drug-drug interaction signal detection methods.

    Jung, Dagyeom / Jung, Inkyung

    PloS one

    2024  Volume 19, Issue 4, Page(s) e0300268

    Abstract: Several statistical methods have been proposed to detect adverse drug reactions induced by taking two drugs together. These suspected adverse drug reactions can be discovered through post-market drug safety surveillance, which mainly relies on ... ...

    Abstract Several statistical methods have been proposed to detect adverse drug reactions induced by taking two drugs together. These suspected adverse drug reactions can be discovered through post-market drug safety surveillance, which mainly relies on spontaneous reporting system database. Most previous studies have applied statistical models to real world data, but it is not clear which method outperforms the others. We aimed to assess the performance of various detection methods by implementing simulations under various conditions. We reviewed proposed approaches to detect signals indicating drug-drug interactions (DDIs) including the Ω shrinkage measure, the chi-square statistic, the proportional reporting ratio, the concomitant signal score, the additive model and the multiplicative model. Under various scenarios, we conducted a simulation study to examine the performances of the methods. We also applied the methods to Korea Adverse Event Reporting System (KAERS) data. Of the six methods considered in the simulation study, the Ω shrinkage measure and the chi-square statistic with threshold = 2 had higher sensitivity for detecting the true signals than the other methods in most scenarios while controlling the false positive rate below 0.05. When applied to the KAERS data, the two methods detected one known DDI for QT prolongation and one unknown (suspected) DDI for hyperkalemia. The performance of various signal detection methods for DDI may vary. It is recommended to use several methods together, rather than just one, to make a reasonable decision.
    MeSH term(s) Humans ; Adverse Drug Reaction Reporting Systems ; Drug Interactions ; Drug-Related Side Effects and Adverse Reactions ; Computer Simulation ; Models, Statistical ; Databases, Factual
    Language English
    Publishing date 2024-04-17
    Publishing country United States
    Document type Review ; Journal Article
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0300268
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Optimal selection of resampling methods for imbalanced data with high complexity.

    Kim, Annie / Jung, Inkyung

    PloS one

    2023  Volume 18, Issue 7, Page(s) e0288540

    Abstract: Class imbalance is a major problem in classification, wherein the decision boundary is easily biased toward the majority class. A data-level solution (resampling) is one possible solution to this problem. However, several studies have shown that ... ...

    Abstract Class imbalance is a major problem in classification, wherein the decision boundary is easily biased toward the majority class. A data-level solution (resampling) is one possible solution to this problem. However, several studies have shown that resampling methods can deteriorate the classification performance. This is because of the overgeneralization problem, which occurs when samples produced by the oversampling technique that should be represented in the minority class domain are introduced into the majority-class domain. This study shows that the overgeneralization problem is aggravated in complex data settings and introduces two alternate approaches to mitigate it. The first approach involves incorporating a filtering method into oversampling. The second approach is to apply undersampling. The main objective of this study is to provide guidance on selecting optimal resampling methods in imbalanced and complex datasets to improve classification performance. Simulation studies and real data analyses were performed to compare the resampling results in various scenarios with different complexities, imbalances, and sample sizes. In the case of noncomplex datasets, undersampling was found to be optimal. However, in the case of complex datasets, applying a filtering method to delete misallocated examples was optimal. In conclusion, this study can aid researchers in selecting the optimal method for resampling complex datasets.
    MeSH term(s) Computer Simulation ; Sample Size ; Algorithms
    Language English
    Publishing date 2023-07-27
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0288540
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Development of High-Precision Urban Flood-Monitoring Technology for Sustainable Smart Cities.

    Jang, Bong-Joo / Jung, Intaek

    Sensors (Basel, Switzerland)

    2023  Volume 23, Issue 22

    Abstract: Owing to rapid climate change, large-scale floods have occurred yearly in cities worldwide, causing serious damage. We propose a real-time urban flood-monitoring technology as an urban disaster prevention technology for sustainable and secure smart ... ...

    Abstract Owing to rapid climate change, large-scale floods have occurred yearly in cities worldwide, causing serious damage. We propose a real-time urban flood-monitoring technology as an urban disaster prevention technology for sustainable and secure smart cities. Our method takes advantage of the characteristic that water flow is regularly detected at a certain distance with a constant Doppler velocity within the radar observation area. Therefore, a pure flow energy detection algorithm in this technology can accurately and immediately detect water flow due to flooding by effectively removing dynamic obstacles such as cars, people, and animals that cause changes in observation distance, and static obstacles that do not cause Doppler velocities. Specifically, in this method, the pure flow energy is detected by generating a two-dimensional range-Doppler relation map using 1 s periodic radar observation data and performing statistical analysis on the energy detected on the successive maps. Experiments to verify the proposed technology are conducted indoors and in real river basins. As a result of conducting experiments in a narrow indoor space that could be considered an urban underpass or underground facility, it was found that this method can detect flooding situations with centimeter-level accuracy by measuring water level and flow velocity in real time from the time of flood occurrence. And the experimental results in various river environments showed that our technology could accurately detect changes in distance and flow speed from the river surface. We also confirmed that this method could effectively eliminate moving obstacles within the observation range and detect only pure flow energy. Finally, we expect that our method will be able to build a high-density urban flood-monitoring network and a high-precision digital flood twin.
    Language English
    Publishing date 2023-11-14
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s23229167
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Exon Junction Complex Is a Molecular Compass of N

    Jung, Inhong / Kim, Yoon Ki

    Molecules and cells

    2023  Volume 46, Issue 10, Page(s) 589–591

    MeSH term(s) Histones/metabolism ; Methylation ; Cell Nucleus/metabolism ; Exons
    Chemical Substances N-methyladenosine (CLE6G00625) ; Histones
    Language English
    Publishing date 2023-09-11
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1148964-9
    ISSN 0219-1032 ; 1016-8478
    ISSN (online) 0219-1032
    ISSN 1016-8478
    DOI 10.14348/molcells.2023.0101
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4713: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  7. Article ; Online: Functional effects of gut microbiota-derived metabolites in Alzheimer's disease.

    Choi, Hyunjung / Mook-Jung, Inhee

    Current opinion in neurobiology

    2023  Volume 81, Page(s) 102730

    Abstract: The precise causation of Alzheimer's disease (AD) is unknown, and the factors that contribute to its etiology are highly complicated. Numerous research has been conducted to investigate the potential impact of various factors to the risk of AD ... ...

    Abstract The precise causation of Alzheimer's disease (AD) is unknown, and the factors that contribute to its etiology are highly complicated. Numerous research has been conducted to investigate the potential impact of various factors to the risk of AD development or prevention against it. A growing body of evidence suggests to the importance of the gut microbiota-brain axis in the modulation of AD, which is characterized by altered gut microbiota composition. These changes can alter the production of microbial-derived metabolites, which may play a detrimental role in disease progression by being involved in cognitive decline, neurodegeneration, neuroinflammation, and accumulation of Aβ and tau. The focus of this review is on the relationship between the key metabolic products of the gut microbiota and AD pathogenesis in the brain. Understanding the action of microbial metabolites can open up new avenues for the development of AD treatment targets.
    MeSH term(s) Humans ; Gastrointestinal Microbiome ; Alzheimer Disease ; Microbiota ; Brain/metabolism ; Disease Progression
    Language English
    Publishing date 2023-05-24
    Publishing country England
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't
    ZDB-ID 1078046-4
    ISSN 1873-6882 ; 0959-4388
    ISSN (online) 1873-6882
    ISSN 0959-4388
    DOI 10.1016/j.conb.2023.102730
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 3260: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article ; Online: Clinical and immunological signatures of severe COVID-19 in previously healthy patients with clonal hematopoiesis

    Jung, Inkyung

    bioRxiv

    Abstract: Identifying additional risk factors for COVID-19 severity in numerous previously healthy patients without canonical clinical risk factors remains challenging. In this study, we investigate whether clonal hematopoiesis of indeterminate potential (CHIP), a ...

    Abstract Identifying additional risk factors for COVID-19 severity in numerous previously healthy patients without canonical clinical risk factors remains challenging. In this study, we investigate whether clonal hematopoiesis of indeterminate potential (CHIP), a common aging-related process that predisposes various inflammatory responses, may exert COVID-19 severity. We examine the clinical impact of CHIP in 143 laboratory-confirmed COVID-19 patients. Both stratified analyses and logistic regression including the interaction between canonical risk factors and CHIP show that CHIP is an independent risk factor for severe COVID-19, especially in previously healthy patients. Analyses of 60,310 single-cell immune transcriptome profiles identify distinct immunological signatures for CHIP (+) severe COVID-19 patients, particularly in classical monocytes, with a marked increase in pro-inflammatory cytokine responses and potent IFN-γ mediated hyperinflammation signature. We further demonstrate that enhanced expression of CHIP (+) specific IFN-γ response genes is attributed to the CHIP mutation-dependent epigenetic reprogramming of poised or bivalent cis-regulatory elements. Our results highlight a unique immunopathogenic mechanism of CHIP in the progression of severe COVID-19, which could be extended to elucidate how CHIP contributes to a variety of human infectious diseases.
    Keywords covid19
    Language English
    Publishing date 2021-10-06
    Publisher Cold Spring Harbor Laboratory
    Document type Article ; Online
    DOI 10.1101/2021.10.05.463271
    Database COVID19

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  9. Article ; Online: Insulin Resistance, Non-Alcoholic Fatty Liver Disease and Type 2 Diabetes Mellitus: Clinical and Experimental Perspective.

    Jung, Inha / Koo, Dae-Jeong / Lee, Won-Young

    Diabetes & metabolism journal

    2024  

    Abstract: It has been generally accepted that insulin resistance (IR) and reduced insulin secretory capacity are the basic pathogenesis of type 2 diabetes mellitus (T2DM). In addition to genetic factors, the persistence of systemic inflammation caused by obesity ... ...

    Abstract It has been generally accepted that insulin resistance (IR) and reduced insulin secretory capacity are the basic pathogenesis of type 2 diabetes mellitus (T2DM). In addition to genetic factors, the persistence of systemic inflammation caused by obesity and the associated threat of lipotoxicity increase the risk of T2DM. In particular, the main cause of IR is obesity and subjects with T2DM have a higher body mass index (BMI) than normal subjects according to recent studies. The prevalence of T2DM with IR has increased with increasing BMI during the past three decades. According to recent studies, homeostatic model assessment of IR was increased compared to that of the 1990s. Rising prevalence of obesity in Korea have contributed to the development of IR, non-alcoholic fatty liver disease and T2DM and cutting this vicious cycle is important. My colleagues and I have investigated this pathogenic mechanism on this theme through clinical and experimental studies over 20 years and herein, I would like to summarize some of our studies with deep gratitude for receiving the prestigious 2023 Sulwon Award.
    Language English
    Publishing date 2024-02-02
    Publishing country Korea (South)
    Document type Journal Article
    ZDB-ID 2602402-0
    ISSN 2233-6087 ; 2233-6087
    ISSN (online) 2233-6087
    ISSN 2233-6087
    DOI 10.4093/dmj.2023.0350
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Spatial scan statistics for matched case-control data.

    Jung, Inkyung

    PloS one

    2019  Volume 14, Issue 8, Page(s) e0221225

    Abstract: Spatial scan statistics are widely used for cluster detection analysis in geographical disease surveillance. While this method has been developed for various types of data such as binary, count, and continuous data, spatial scan statistics for matched ... ...

    Abstract Spatial scan statistics are widely used for cluster detection analysis in geographical disease surveillance. While this method has been developed for various types of data such as binary, count, and continuous data, spatial scan statistics for matched case-control data, which often arise in spatial epidemiology, have not been considered. We propose spatial scan statistics for matched case-control data. The proposed test statistics consider the correlations between matched pairs. We evaluate the statistical power and cluster detection accuracy of the proposed methods through simulations compared to the Bernoulli-based method. We illustrate the proposed methods using a real data example. The simulation study clearly revealed that the proposed methods had higher power and higher accuracy for detecting spatial clusters for matched case-control data than the Bernoulli-based spatial scan statistic. The cluster detection result of the real data example also appeared to reflect a higher power of the proposed methods. The proposed methods are very useful for spatial cluster detection for matched case-control data.
    MeSH term(s) Binomial Distribution ; Case-Control Studies ; Cluster Analysis ; Computer Simulation ; Datasets as Topic ; Disease Outbreaks/statistics & numerical data ; Models, Statistical ; Topography, Medical/methods
    Language English
    Publishing date 2019-08-16
    Publishing country United States
    Document type Comparative Study ; Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1932-6203
    ISSN (online) 1932-6203
    DOI 10.1371/journal.pone.0221225
    Database MEDical Literature Analysis and Retrieval System OnLINE

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