No abstract available.
DNA Fingerprinting* ; DNA* ; Humans* ; Papilloma*

No Abstract available.
Cross Infection* ; Korea*

BACKGROUND: Smoking greatly increases the risk of cancer, cardiovascular diseases and osteoporosis. Besides direct harm from smoking, some dietary pattern of smokers have been reported to increase such risk. This study aimed to analyze various nutrients by smoking status, and to find out whether smokers maintain harmful dietary patterns. METHODS: One thousand and six hundred fourteen men were selected who visited the health promotion center of an university hospital in Seoul. The inclusion criteria was the completion of dietary survey. Dietary analysis was done by calculation of amounts of each nutrients from 24-hour recall method. We compared total intake of each nutrients and total calories by smoking status with analysis of variance (ANOVA). Then we adjusted the results for exercise and education level by ANCOVA (analysis of covariance). RESULTS: The study subjects were 840 current smokers (52.0%), 479 ex-smokers (29.7%) and 295 non-smokers (18.3%). The consumption of total fat and cholesterol was significantly high in smokers than non-smokers (P=0.012, P=0.005). The alcohol intake was higher in smokers and ex-smokers than non-smokers (P <0.001, P=0.007). The smokers and ex-smokers had less calcium than non- smokers (P=0.001, P=0.044). Furthermore, the smokers exercised less than ex-smokers and non-smokers (P <0.001). CONCLUSIONS: The smokers consumed more total fat and cholesterol which increases the risk of cardiovascular diseases. They also had less calcium and drank more alcohol. Comprehensive approach which includes intervention for dietary intakes in addition to smoking cessation is desirable to decrease health risk for smokers.
Analysis of Variance ; Calcium ; Cardiovascular Diseases ; Cholesterol ; Diet ; Education ; Health Promotion* ; Humans ; Male* ; Osteoporosis ; Seoul ; Smoke* ; Smoking Cessation ; Smoking*

A fixed drug eruption is a cutaneous reaction caused by various drugs, which include phenazone derivatives, barbiturates, sulfonamides, tetracyclines and phenolphthaleins. An eruption caused by piroxicam is very rare and there have been no previous reports in Korea. A 49-year-old woman was seen with mutiple erythematous patches and some bullae that appeared after oral administration of piroxicam. The patient had had two similar episodes after oral administration of piroxicam. We performed patch test with piroxicam and could confirm a fixed drug eruption caused by this durg.
Administration, Oral ; Antipyrine ; Barbiturates ; Drug Eruptions* ; Female ; Humans ; Korea ; Middle Aged ; Patch Tests ; Phenolphthalein ; Phenolphthaleins ; Piroxicam* ; Sulfonamides ; Tetracyclines

Dermatophytes infect the human hair, skin, nail and cause the dermatophytosis. The extracellular and intracellular proteinases of the dermatophytes commonly occur in the genus Trichophyton like T. rubrum, T. mentagrophytes, and T. granulosum. These enzymes play a prominent role in growth, multiplication and infection of the host tissue. Extracellular proteinases have been purified from the species of Trichophyton and Microsporum. We purified the proteinase partially from the culture filtrate of the Trichophyton tonsurans through Mono-Q and Superose 12 column and investigated its biochemical and enzymatic characters. The molecular size of the proteinase was estimated to be 41 kDa by SDS-PAGE. And pI was 3.2. The optimal temperature and pH for an enzymatic activity were 27C and 7.5, respectively. The purified porteinase degraded the keratin, bovine serum albumin, hemoglobin. The serine proteinase inhibitor like PMSF and DFP inhibited the proteolytic activity of the purified enzyme whereas the cysteinase inhibitor did not. These results demonstrated that the purified proteinase is a serine proteinase and can contribute the tissue invasion.
Arthrodermataceae ; Electrophoresis, Polyacrylamide Gel ; Hair ; Humans ; Hydrogen-Ion Concentration ; Isoflurophate ; Microsporum ; Peptide Hydrolases ; Serine Proteases* ; Serine* ; Serum Albumin, Bovine ; Skin ; Tinea ; Trichophyton*

OBJECTIVES: The primary objective of this study is to compare model performance of machine learning methods with that of a previous study in which a nonlinear mixed effects model was created using NONMEM(R) for the pharmacokinetic and pharmacodynamic data for propofol. The secondary objective was to evaluate if a pharmacodynamic model describing the relationship between the dose of propofol and bispectral index (BIS) outperform that describing the relationship between a pharmacokinetic model derived-predicted concentrations of propofol and BIS. METHODS: Data were collected during a study involving the infusion of propofol into healthy volunteers. Pharmacokinetic and pharmacodynamic models were constructed using artificial neural networks (ANNs), support vector machines (SVMs), and multi-method ensembles and were compared with the nonlinear mixed effects method as implemented by NONMEM(R). Model performance was assessed by goodness-of-fit statistics, paired t-tests between predicted and observed values for each model and scatterplots. RESULTS: In pharmacokinetic analysis, ensemble I, the mean of ANN and NONMEM(R) predictions, achieved minimal error and the highest correlation coefficient. SVM produced the highest error and the lowest correlation coefficient. In pharmacodynamic analysis, ANN exhibited the best performance. An ANNModel describing the relationship between the dose of propofol and BIS was not inferior to an ANN model describing the relationship between predicted concentrations of propofol derived from an ANN pharmacokinetic model and BIS. CONCLUSIONS: In pharmacokinetic analysis, ensemble combined with ANN achieved slightly better performance than NONMEM(R). The relationship between the dose of propofol and BIS can be predicted without considering pharmacokinetics of propofol.
Machine Learning ; Propofol ; Support Vector Machine

Background: Quantitative computed tomography (QCT) is essential for assessing osteoporosis and monitoring spinal deformities. “Clari-QCT,” a software that uses artificial intelligence to analyze conventional computed tomography (CT) scans and produce QCTequivalent reports. This study aims to evaluate the effectiveness of Clari-QCT by comparing its results with traditional QCT, with the goal of validating new diagnostic tools for spinal deformities. Methods: The study analyzed dual energy X-ray absorptiometry, CT, and QCT data from 18 patients at Inha University Hospital. Clari-QCT software was evaluated for its ability to generate QCT-equivalent reports from CT images. The software processes abdomen CT images, calculates bone density in designated slices, and provides bone mineral density (BMD), T-score, and Z-score values. Patients were classified into normal, mild, and severe spinal deformity groups. Intraclass correlation coefficient (ICC) analysis was used to measure the agreement between actual and predicted BMD values. Results: The study included participants with an average age of 64 and a mean body mass index of 24.88. The average BMD was 94.7 g/cm³ by QCT and 122.5 g/cm³ by Clari- QCT, with individual differences ranging from 4.9 to 61.8. T-score discrepancies ranged from 0.16 to 6.86. ICC analysis showed moderate to high agreement between methods, with ICC1 values of 0.597, ICC2 of 0.64, ICC3 of 0.81, and ICC1k, ICC2k, ICC3k values ranging from 0.748 to 0.895. Conclusions Clari-QCT demonstrates good agreement with actual QCT measurements in normal and severe spinal deformity groups but shows reduced accuracy in patients with mild deformities. If the limitations are addressed, it could become a useful tool for monitoring bone health in patients with spinal deformities.

Background: Quantitative computed tomography (QCT) is essential for assessing osteoporosis and monitoring spinal deformities. “Clari-QCT,” a software that uses artificial intelligence to analyze conventional computed tomography (CT) scans and produce QCTequivalent reports. This study aims to evaluate the effectiveness of Clari-QCT by comparing its results with traditional QCT, with the goal of validating new diagnostic tools for spinal deformities. Methods: The study analyzed dual energy X-ray absorptiometry, CT, and QCT data from 18 patients at Inha University Hospital. Clari-QCT software was evaluated for its ability to generate QCT-equivalent reports from CT images. The software processes abdomen CT images, calculates bone density in designated slices, and provides bone mineral density (BMD), T-score, and Z-score values. Patients were classified into normal, mild, and severe spinal deformity groups. Intraclass correlation coefficient (ICC) analysis was used to measure the agreement between actual and predicted BMD values. Results: The study included participants with an average age of 64 and a mean body mass index of 24.88. The average BMD was 94.7 g/cm³ by QCT and 122.5 g/cm³ by Clari- QCT, with individual differences ranging from 4.9 to 61.8. T-score discrepancies ranged from 0.16 to 6.86. ICC analysis showed moderate to high agreement between methods, with ICC1 values of 0.597, ICC2 of 0.64, ICC3 of 0.81, and ICC1k, ICC2k, ICC3k values ranging from 0.748 to 0.895. Conclusions Clari-QCT demonstrates good agreement with actual QCT measurements in normal and severe spinal deformity groups but shows reduced accuracy in patients with mild deformities. If the limitations are addressed, it could become a useful tool for monitoring bone health in patients with spinal deformities.

Background: Quantitative computed tomography (QCT) is essential for assessing osteoporosis and monitoring spinal deformities. “Clari-QCT,” a software that uses artificial intelligence to analyze conventional computed tomography (CT) scans and produce QCTequivalent reports. This study aims to evaluate the effectiveness of Clari-QCT by comparing its results with traditional QCT, with the goal of validating new diagnostic tools for spinal deformities. Methods: The study analyzed dual energy X-ray absorptiometry, CT, and QCT data from 18 patients at Inha University Hospital. Clari-QCT software was evaluated for its ability to generate QCT-equivalent reports from CT images. The software processes abdomen CT images, calculates bone density in designated slices, and provides bone mineral density (BMD), T-score, and Z-score values. Patients were classified into normal, mild, and severe spinal deformity groups. Intraclass correlation coefficient (ICC) analysis was used to measure the agreement between actual and predicted BMD values. Results: The study included participants with an average age of 64 and a mean body mass index of 24.88. The average BMD was 94.7 g/cm³ by QCT and 122.5 g/cm³ by Clari- QCT, with individual differences ranging from 4.9 to 61.8. T-score discrepancies ranged from 0.16 to 6.86. ICC analysis showed moderate to high agreement between methods, with ICC1 values of 0.597, ICC2 of 0.64, ICC3 of 0.81, and ICC1k, ICC2k, ICC3k values ranging from 0.748 to 0.895. Conclusions Clari-QCT demonstrates good agreement with actual QCT measurements in normal and severe spinal deformity groups but shows reduced accuracy in patients with mild deformities. If the limitations are addressed, it could become a useful tool for monitoring bone health in patients with spinal deformities.

The global emergence and spread of multidrug resistant bacterial infections in communities and hospitals has become an important issue in public health. The resistance rate of gram-positive cocci to vancomycin and the resistance rate of several gram-negative bacilli against cefotaxime and carbapenem have been continuously increasing. Surveillance of antimicrobial resistance is essential for providing information on the magnitude of and trend in multidrug resistance. Therefore, beginning 2011, more robust and effective management is to be legally required for six multidrug-resistant bacteria that have been linked to healthcare-related infections: vancomycin-resistant Staphylococcus aureus (VRSA), vancomycin-resistant enterococci (VRE), methicillin-resistant S. aureus (MRSA), multidrug-resistant Pseudomonas aeruginosa (MRPA), multidrug-resistant Acinetobacter baumannii (MRAB), and carbapenem-resistant Enterobactericeae (CRE). We have also performed laboratory-based sentinel surveillance for VRSA/VISA since 2002 and carbapenemase-producing Enterobacteriaceae since November, 2010. This article reviews the national surveillance programs, and molecular epidemiology of multidrug-resistant bacteria.
Acinetobacter baumannii ; Bacteria ; Bacterial Infections ; Cefotaxime ; Drug Resistance, Multiple ; Enterobacteriaceae ; Gram-Positive Cocci ; Methicillin Resistance ; Molecular Epidemiology ; Nitriles ; Pseudomonas aeruginosa ; Public Health ; Pyrethrins ; Sentinel Surveillance ; Staphylococcus aureus ; Vancomycin