1.Patterns of rpoC Mutations in Drug-Resistant Mycobacterium tuberculosis Isolated from Patients in South Korea.
Yeo Jun YUN ; Jong Seok LEE ; Je Chul YOO ; Eunjin CHO ; Dahee PARK ; Yoon Hoh KOOK ; Keun Hwa LEE
Tuberculosis and Respiratory Diseases 2018;81(3):222-227
BACKGROUND: Rifampicin (RFP) is one of the principal first-line drugs used in combination chemotherapies against Mycobacterium tuberculosis, and its use has greatly shortened the duration of chemotherapy for the successful treatment of drug-susceptible tuberculosis. Compensatory mutations have been identified in rpoC that restore the fitness of RFP-resistant M. tuberculosis strains with mutations in rpoB. To investigate rpoC mutation patterns, we analyzed 93 clinical M. tuberculosis isolates from patients in South Korea. METHODS: Drug-resistant mycobacterial isolates were cultured to determine their susceptibility to anti-tubercular agents. Mutations in rpoC were identified by sequencing and compared with the relevant wild-type DNA sequence. RESULTS: In total, 93 M. tuberculosis clinical isolates were successfully cultured and tested for drug susceptibilities. They included 75 drug-resistant tuberculosis species, of which 66 were RFP-resistant strains. rpoC mutations were found in 24 of the 66 RFP-resistant isolates (36.4%). Fifteen different types of mutations, including single mutations (22/24, 91.7%) and multiple mutations (2/24, 8.3%), were identified, and 12 of these mutations are reported for the first time in this study. The most frequent mutation involved a substitution at codon 452 (nt 1356) resulting in amino acid change F452L. CONCLUSION: Fifteen different types of mutations were identified and were predominantly single-nucleotide substitutions (91.7%). Mutations were found only in dual isoniazid- and RFP-resistant isolates of M. tuberculosis. No mutations were identified in any of the drug-susceptible strains.
Base Sequence
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Codon
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Drug Resistance, Multiple
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Drug Therapy
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Drug Therapy, Combination
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Humans
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Korea*
;
Mycobacterium tuberculosis*
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Mycobacterium*
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Rifampin
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Tuberculosis
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Tuberculosis, Multidrug-Resistant
2.Two Distinct Subsets Are Identified from the Peritoneal Myeloid Mononuclear Cells Expressing both CD11c and CD115
Moah SOHN ; Hye Young NA ; Seul Hye RYU ; Wanho CHOI ; Hyunju IN ; Hyun Soo SHIN ; Ji Soo PARK ; Dahee SHIM ; Sung Jae SHIN ; Chae Gyu PARK
Immune Network 2019;19(3):e15-
To this date, the criteria to distinguish peritoneal macrophages and dendritic cells (DCs) are not clear. Here we delineate the subsets of myeloid mononuclear cells in the mouse peritoneal cavity. Considering phenotypical, functional, and ontogenic features, peritoneal myeloid mononuclear cells are divided into 5 subsets: large peritoneal macrophages (LPMs), small peritoneal macrophages (SPMs), DCs, and 2 MHCII⁺CD11c⁺CD115⁺ subpopulations (i.e., MHCII⁺CD11c⁺CD115⁺CD14⁻CD206⁻ and MHCII⁺CD11c⁺CD115⁺CD14⁺CD206⁺). Among them, 2 subsets of competent Ag presenting cells are demonstrated with distinct functional characteristics, one being DCs and the other being MHCII⁺CD11c⁺CD115⁺CD14⁻CD206⁻ cells. DCs are able to promote fully activated T cells and superior in expanding cytokine producing inflammatory T cells, whereas MHCII⁺CD11c⁺CD115⁺CD14⁻CD206⁻ cells generate partially activated T cells and possess a greater ability to induce Treg under TGF-β and retinoic acid conditions. While the development of DCs and MHCII⁺CD11c⁺CD115⁺CD14⁻CD206⁻ cells are responsive to the treatment of FLT3 ligand and GM-CSF, the number of LPMs, SPMs, and MHCII⁺CD11c⁺CD115⁺CD14⁺CD206⁺ cells are only influenced by the injection of GM-CSF. In addition, the analysis of gene expression profiles among MHCII⁺ peritoneal myeloid mononuclear cells reveals that MHCII⁺CD11c⁺CD115⁺CD14⁺CD206⁺ cells share high similarity with SPMs, whereas MHCII⁺CD11c⁺CD115⁺CD14⁻CD206⁻ cells are related to peritoneal DC2s. Collectively, our study identifies 2 distinct subpopulations of MHCII⁺CD11c⁺CD115⁺ cells, 1) MHCII⁺CD11c⁺CD115⁺CD14⁻CD206⁻ cells closely related to peritoneal DC2s and 2) MHCII⁺CD11c⁺CD115⁺CD14⁺CD206⁺ cells to SPMs.
Animals
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Antigen Presentation
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Dendritic Cells
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Granulocyte-Macrophage Colony-Stimulating Factor
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Macrophages
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Macrophages, Peritoneal
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Mice
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Peritoneal Cavity
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T-Lymphocytes
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Transcriptome
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Tretinoin
3.Construction of an Electrocardiogram Database Including 12 Lead Waveforms.
Dahee CHUNG ; Junggu CHOI ; Jong Hwan JANG ; Tae Young KIM ; JungHyun BYUN ; Hojun PARK ; Hong Seok LIM ; Rae Woong PARK ; Dukyong YOON
Healthcare Informatics Research 2018;24(3):242-246
OBJECTIVES: Electrocardiogram (ECG) data are important for the study of cardiovascular disease and adverse drug reactions. Although the development of analytical techniques such as machine learning has improved our ability to extract useful information from ECGs, there is a lack of easily available ECG data for research purposes. We previously published an article on a database of ECG parameters and related clinical data (ECG-ViEW), which we have now updated with additional 12-lead waveform information. METHODS: All ECGs stored in portable document format (PDF) were collected from a tertiary teaching hospital in Korea over a 23-year study period. We developed software which can extract all ECG parameters and waveform information from the ECG reports in PDF format and stored it in a database (meta data) and a text file (raw waveform). RESULTS: Our database includes all parameters (ventricular rate, PR interval, QRS duration, QT/QTc interval, P-R-T axes, and interpretations) and 12-lead waveforms (for leads I, II, III, aVR, aVL, aVF, V1, V2, V3, V4, V5, and V6) from 1,039,550 ECGs (from 447,445 patients). Demographics, drug exposure data, diagnosis history, and laboratory test results (serum calcium, magnesium, and potassium levels) were also extracted from electronic medical records and linked to the ECG information. CONCLUSIONS: Electrocardiogram information that includes 12 lead waveforms was extracted and transformed into a form that can be analyzed. The description and programming codes in this case report could be a reference for other researchers to build ECG databases using their own local ECG repository.
Calcium
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Cardiovascular Diseases
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Demography
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Diagnosis
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Drug-Related Side Effects and Adverse Reactions
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Electrocardiography*
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Electronic Health Records
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Hospitals, Teaching
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Korea
;
Machine Learning
;
Magnesium
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Potassium
4.An Alternative Dendritic Cell-Induced Murine Model of Asthma Exhibiting a Robust Th2/Th17-Skewed Response
Sang Chul PARK ; Hongmin KIM ; Yeeun BAK ; Dahee SHIM ; Kee Woong KWON ; Chang Hoon KIM ; Joo Heon YOON ; Sung Jae SHIN
Allergy, Asthma & Immunology Research 2020;12(3):537-555
PURPOSE: Simple and reliable animal models of human diseases contribute to the understanding of disease pathogenesis as well as the development of therapeutic interventions. Although several murine models to mimic human asthma have been established, most of them require anesthesia, resulting in variability among test individuals, and do not mimic asthmatic responses accompanied by T-helper (Th) 17 and neutrophils. As dendritic cells (DCs) are known to play an important role in initiating and maintaining asthmatic inflammation, we developed an asthma model via adoptive transfer of allergen-loaded DCs.METHODS: Ovalbumin (OVA)-loaded bone marrow-derived DCs (BMDCs) (OVA-BMDCs) were injected intravenously 3 times into non-anesthetized C57BL/6 mice after intraperitoneal OVA-sensitization.RESULTS: OVA-BMDC-transferred mice developed severe asthmatic immune responses when compared with mice receiving conventional OVA challenge intranasally. Notably, remarkable increases in systemic immunoglobulin (Ig) E and IgG1 responses, Th2/Th17-associated cytokines (interleukin [IL]-5, IL-13 and IL-17), Th2/Th17-skewed T-cell responses, and cellular components, including eosinophils, neutrophils, and goblet cells, were observed in the lungs of OVA-BMDC-transferred mice. Moreover, the asthmatic immune responses and severity of inflammation were correlated with the number of OVA-BMDCs transferred, indicating that the disease severity and asthma type may be adjusted according to the experimental purpose by this method. Furthermore, this model exhibited less variation among the test individuals than the conventional model. In addition, this DCs-based asthma model was partially resistant to steroid treatment.CONCLUSIONS: A reliable murine model of asthma by intravenous (i.v.) transfer of OVA-BMDCs was successfully established without anesthesia. This model more accurately reflects heterogeneous human asthma, exhibiting a robust Th2/Th17-skewed response and eosinophilic/neutrophilic infiltration with good reproducibility and low variation among individuals. This model will be useful for understanding the pathogenesis of asthma and would serve as an alternative tool for immunological studies on the function of DCs, T-cell responses and new drugs.
Adoptive Transfer
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Anesthesia
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Animals
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Asthma
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Cytokines
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Dendritic Cells
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Eosinophils
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Goblet Cells
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Humans
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Immunoglobulin G
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Immunoglobulins
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Inflammation
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Interleukin-13
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Lung
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Methods
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Mice
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Models, Animal
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Neutrophils
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Ovalbumin
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Ovum
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T-Lymphocytes
5.Source Analysis and Effective Control of a COVID-19 Outbreak in a University Teaching Hospital during a Period of Increasing Community Prevalence of COVID-19
Unhee LEE ; Seong Eun KIM ; Seung Yeob LEE ; Hang Nam WI ; Okja CHOI ; Ji-Won PARK ; Dahee KIM ; You Jung KIM ; Hwa Young SHIN ; Mihee KIM ; Eun Ji KIM ; Seung-Ji KANG ; Sook-In JUNG ; Kyung-Hwa PARK
Journal of Korean Medical Science 2021;36(24):e179-
Background:
South Korea has been experiencing a third wave of coronavirus disease 2019 (COVID-19) since mid-November 2020. Our hospital in Gwangju metropolitan city experienced a healthcare-associated COVID-19 outbreak early in the third wave. The first confirmed COVID-19 patient was a symptomatic neurosurgery resident with high mobility throughout the hospital. We analyzed the transmission routes of nosocomial COVID-19 and discussed infection control strategies.
Methods:
We retrospectively analyzed the severe acute respiratory syndrome coronavirus 2 reverse transcription-polymerase chain reaction (RT-PCR) testing results according to time point and evaluated transmission routes.
Results:
Since COVID-19 was first confirmed in a healthcare worker (HCW) on 11/13/2020, we performed RT-PCR tests for all patients and caregivers and four complete enumeration surveys for all HCWs. We detected three clusters of nosocomial spread and several sporadic cases. The first cluster originated from the community outbreak spot, where an asymptomatic HCW visited, which led to a total of 22 cases. The second cluster, which included patient-to-patient transmission, originated from a COVID-19 positive caregiver before diagnosis and the third cluster involved a radiologist and a banker. We took measures to isolate Building 1 of the hospital for 17 days and controlled the outbreak during a period of increasing community COVID-19 prevalence. Universal screening of all inpatients upon admission and resident caregivers was made mandatory and hospital-related employees are now screened monthly.
Conclusion
Infection control strategies to prevent the nosocomial transmission of emerging infectious diseases must correspond with community disease prevalence. Our data reinforce the importance of multi-time point surveillance of asymptomatic HCWs and routine surveillance of patients and caregivers during an epidemic.
6.Source Analysis and Effective Control of a COVID-19 Outbreak in a University Teaching Hospital during a Period of Increasing Community Prevalence of COVID-19
Unhee LEE ; Seong Eun KIM ; Seung Yeob LEE ; Hang Nam WI ; Okja CHOI ; Ji-Won PARK ; Dahee KIM ; You Jung KIM ; Hwa Young SHIN ; Mihee KIM ; Eun Ji KIM ; Seung-Ji KANG ; Sook-In JUNG ; Kyung-Hwa PARK
Journal of Korean Medical Science 2021;36(24):e179-
Background:
South Korea has been experiencing a third wave of coronavirus disease 2019 (COVID-19) since mid-November 2020. Our hospital in Gwangju metropolitan city experienced a healthcare-associated COVID-19 outbreak early in the third wave. The first confirmed COVID-19 patient was a symptomatic neurosurgery resident with high mobility throughout the hospital. We analyzed the transmission routes of nosocomial COVID-19 and discussed infection control strategies.
Methods:
We retrospectively analyzed the severe acute respiratory syndrome coronavirus 2 reverse transcription-polymerase chain reaction (RT-PCR) testing results according to time point and evaluated transmission routes.
Results:
Since COVID-19 was first confirmed in a healthcare worker (HCW) on 11/13/2020, we performed RT-PCR tests for all patients and caregivers and four complete enumeration surveys for all HCWs. We detected three clusters of nosocomial spread and several sporadic cases. The first cluster originated from the community outbreak spot, where an asymptomatic HCW visited, which led to a total of 22 cases. The second cluster, which included patient-to-patient transmission, originated from a COVID-19 positive caregiver before diagnosis and the third cluster involved a radiologist and a banker. We took measures to isolate Building 1 of the hospital for 17 days and controlled the outbreak during a period of increasing community COVID-19 prevalence. Universal screening of all inpatients upon admission and resident caregivers was made mandatory and hospital-related employees are now screened monthly.
Conclusion
Infection control strategies to prevent the nosocomial transmission of emerging infectious diseases must correspond with community disease prevalence. Our data reinforce the importance of multi-time point surveillance of asymptomatic HCWs and routine surveillance of patients and caregivers during an epidemic.