No abstract available.
Peutz-Jeghers Syndrome*

Background: Staphylococcus aureus is a common colonizer of the nasal vestibule and is found in approximately 20%–30% of healthy adults, while Staphylococcus epidermidis appears to be the most frequent colonizer in all regions of the upper respiratory tract. Esp, aserine protease of S. epidermidis, was reported to inhibit S.aureus colonization. This study was performed to examine the nasal colonization of S. aureus and S. epidermidis and the presence of esp determinants. Methods: Nasal swab specimens from 54 patients were cultured on blood agar plates (BAP) and selective media for S. aureus (S. aureus ID, bioMerieux, France) for the isolation of S.aureus and S. epidermidis. After 48 hours of incubation of with BAP, three or four colonies suspected of being coagulase-negative staphylococci (CNS) were identified by MALDI-TOF MS (Bruker, Germany). Polymerase chain reaction (PCR) for esp was performed on all CNS isolates identified as S. epidermidis. Results: Forty-three S. epidermidis strains were isolated from 18 (33.3%) of the 54 patients.Nine (50.0%) of the 18 patients carried S. aureus, while the other nine did not. Of the 36 S. epidermidis non-carriers, 13 (36.1%) were colonized by S. aureus. All S. epidermidis strains were confirmed by PCR to have esp determinants. Conclusion S. epidermidis colonization did not affect S. aureus colonization in the nasal cavity. All S. epidermidis strains harbored the esp gene. We could not find any differences in the nasal colonization rates of S. aureus according to the presence of esp-positive S. epidermidis. Further research on the characterization of S. epidermidis in Korea is needed to understand the association between S. epidermidis and S. aureus colonization.

Background: Staphylococcus aureus is a common colonizer of the nasal vestibule and is found in approximately 20%–30% of healthy adults, while Staphylococcus epidermidis appears to be the most frequent colonizer in all regions of the upper respiratory tract. Esp, aserine protease of S. epidermidis, was reported to inhibit S.aureus colonization. This study was performed to examine the nasal colonization of S. aureus and S. epidermidis and the presence of esp determinants. Methods: Nasal swab specimens from 54 patients were cultured on blood agar plates (BAP) and selective media for S. aureus (S. aureus ID, bioMerieux, France) for the isolation of S.aureus and S. epidermidis. After 48 hours of incubation of with BAP, three or four colonies suspected of being coagulase-negative staphylococci (CNS) were identified by MALDI-TOF MS (Bruker, Germany). Polymerase chain reaction (PCR) for esp was performed on all CNS isolates identified as S. epidermidis. Results: Forty-three S. epidermidis strains were isolated from 18 (33.3%) of the 54 patients.Nine (50.0%) of the 18 patients carried S. aureus, while the other nine did not. Of the 36 S. epidermidis non-carriers, 13 (36.1%) were colonized by S. aureus. All S. epidermidis strains were confirmed by PCR to have esp determinants. Conclusion S. epidermidis colonization did not affect S. aureus colonization in the nasal cavity. All S. epidermidis strains harbored the esp gene. We could not find any differences in the nasal colonization rates of S. aureus according to the presence of esp-positive S. epidermidis. Further research on the characterization of S. epidermidis in Korea is needed to understand the association between S. epidermidis and S. aureus colonization.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Brain damage resulting from perinatal cerebral hypoxia and ischemia is a major cause of acute mortality and neurological disabilities, including cerebral palsy (CP) and cognitive dysfunction. In order to establish an experimental hypoxia-ischemia (HI) model of CP for the screening of therapeutics, we operated bilateral common carotid artery ligation (BCAO) and monolateral carotid artery occlusion (MCAO), followed by 15 min of hypoxia (8% oxygen) in 4-day-old rats, and evaluated neurobehavioral disorders. After surgery, the survival rates of male and female BCAO rats were 33.3 and 7.1%, respectively, whereas 100% and 82.4% MCAO rats survived. In neurobehavioral performances, both male and female BCAO rats showed delayed achievement of righting reflex, in contrast to a negligible effect in MACO animals. However, both BCAO and MCAO rats exhibited impairment of cliff avoidance performances, although the physical dysfunction was more severe in BCAO than in MCAO. In global locomotor activity, MCAO rats also displayed decreased fast-moving time comparable BCAO animals, and increased resting and slow-moving times. In addition, MCAO rats showed marked learning and memory deficit in passive avoidance performances, similar to BCAO animals. From immunostaining analyses, severe degradation and loss of myelin basic proteins were observed in the brain of BCAO rats, in contrast to a mild aggregation in MCAO animals. Therefore, it is suggested that MCAO should be a more suitable CP model than BCAO, based on the high survival rate, relatively-mild brain injury, and enough neurobehavioral disorders for the research on preventive and therapeutic compounds.
Achievement ; Animals ; Anoxia ; Brain ; Brain Injuries ; Carotid Arteries ; Carotid Artery, Common ; Cerebral Palsy ; Demyelinating Diseases ; Female ; Humans ; Hypoxia, Brain ; Infant ; Ischemia ; Learning ; Ligation ; Male ; Mass Screening ; Memory Disorders ; Models, Theoretical ; Motor Activity ; Myelin Basic Protein ; Rats ; Reflex, Righting ; Survival Rate

BACKGROUND: Acinetobacter baumannii causes various hospital-acquired infections, its multidrug resistance is rapidly increasing worldwide. Although colistin is used in treatments against multidrug-resistant A. baumannii, resistance to colistin has also been reported recently. Few studies have reported colistin susceptibility testing using MicroScan. In this study, we compared colistin susceptibility tests for resistant A. baumannii by MicroScan (Siemens, USA) and Etest (BioMerieux, France). METHODS: We collected 115 A. baumannii clinical isolates, showing colistin resistance (minimum inhibitory concentration [MIC] > or =4 microg/mL) by MicroScan, from July 2014 to March 2015 at Kangdong Sacred Heart Hospital. Species identification and antimicrobial susceptibility tests were performed using the MicroScan Neg Combo Panel Type 72. Additionally, Etest was also performed for comparison. RESULTS: Of the 115 isolates, Etest revealed that 103 (89.6%) were colistin-susceptible (MIC < or =I microg/mL). Moreover, 52 isolates, showing a MIC of 4 microg/mL by MicroScan, were all susceptible to colistin. Only 12 (19.0%) of 63 isolates, showing a MIC of >4 microg/mL by MicroScan were resistant to colistin according to the Etest. CONCLUSIONS: The MicroScan automated system, using the commercial broth microdilution method, exhibited some discrepancies with the Etest for colistin susceptibility in A. baumannii. Therefore, more practical and reliable susceptibility tests for colistin are required in clinical laboratories using MicroScan.
Acinetobacter baumannii* ; Acinetobacter* ; Colistin* ; Drug Resistance, Multiple ; Heart ; Microbial Sensitivity Tests