BACKGROUND/AIMS: For laboratory diagnostics in liver diseases, many enzymes have been used for the assessment of hepatocellular function. Among them, two transaminases, alanine and aspartate aminotransferase, have been regarded as the most sensitive indicators of hepatocellular damage. However, the enhanced enzyme activities of the enzymes do not exactly indicate or represent the cause and progression of diseases in the patients with liver disease. To overcome such limitations, immunological methods have been suggested as one of the alternatives for the replacement or supplement of the conventional enzymatic analysis. METHODS: In the hope of developing a new assay system for measuring the AST concentration rather than its activity, we have developed a new assay using fluorescence labeled anti-AST monoclonal antibodies. Blood was obtained from a normal population of 234 patients and 43 liver disease patients. The linearity, limit of detection, and performance of the new assay system were tested and evaluated. The comparability of assay was examined with an ELISA and biochemical assays. RESULTS: The linearity fell in the range of 0-1 mg/L of AST (R=0.995), and the analytical detection limit was 12 microgram/L of AST. The mean recovery of the control was 102.4 % in a working range. The precision of the intra- and inter-assay in a range of 50-800 microgram/L was CVs < 7% and CVs < 6%, respectively. In the normal population, the mean AST concentration was 35.5 microgram/L. The mean AST concentration in patients with liver disease was 266.5 microgram/L. The new assay system correlated well with an ELISA and biochemical assay for quantification of AST concentration (R=0.92 and 0.88, respectively; N=43). CONCLUSIONS: We have developed a new immunological assay using generated monoclonal antibodies to human cytosolic AST and used them for the development of a fluorescent assay measuring the enzyme mass. Cytosolic AST mass in sera could be measured reproducibly by the immunological method. In conclusion, this study has provided us with a new type of tool for an accurate measurement of the enzyme amount in circulation.
Antibodies, Monoclonal ; Aspartate Aminotransferase, Cytoplasmic/*blood/immunology ; Fluorescent Antibody Technique/*methods ; Humans ; Liver Diseases/diagnosis

We investigated fifteen men and twenty one women, who were diagnosed to have asteroid hyalosis between June, 1997 and November, 1997 at Seoul National University Hospital. After obtaining their medical history a complete eye examination was performed. Specimen was examined by light microscope in one case. Funduscopic examination revealed bilateral involvement in 5 cases. Twenty six patients were diabetic and 12 were hypertensive. There was a significant association with diabetes. Light microscopic exam showed variable sized spherical structures with brown rim. Further decrease in visual acuity due to asteroid hyalosis was not observed in 35 cases in which follow-up exams were possible. In conclusion, asteroid hyalosis rarely caused visual loss and were likely to be monocular and to occur in old age.
Female ; Follow-Up Studies ; Humans ; Male ; Seoul ; Visual Acuity

Neurilemmomas are benign tumors of the nerve sheaths. They are usually painless and are most common in the upper extremities. Pathologically, neurilemmoma is encapsulated and made up of organized element: the Antoni A cells, the Antoni B cells and the Verocay bodies. According to Stout, neurilemmomas never become malignant. Two cases of neurilemmoma of tibial nerve and One case of neurilemmoma of lateral antebrachial cutaneous nerve are presented with a review of the literature. Tumors were enucleated and confirmed by pathological examination.
B-Lymphocytes ; Nerve Sheath Neoplasms ; Neurilemmoma ; Tibial Nerve ; Upper Extremity

OBJECTIVE: Nonstress test(NST) has become an important method of antepartum evaluation of fetal well-being. The fetal heart rate(FHR) testing is used frequently as a nonstress test(NST). However, NST highly depends on whom to interpret the result of FHR testing. Recently, for interpretation of FHR, objective decision methods using softwares have been introduced. In this study, we aim to analyse the correlation between each variable affecting FHR and fetal outcome using objective decision basis with principal component analysis and multiple regression analysis. MATERIALS AND METHODS: The clinical observation was made on 5,314 data from pregnant women who took a NST which had been collected from 1989 to 1997 at Hanyang University Hospital. For collection of data and values of each variable, we used our own FHR interpretation softwares, HYFM-I(DOS version, 1989) and HYFM-II(Window-version, 1998). Then, the principal component analysis is performed to find significant variable and multiple regression analysis using these variables. RESULTS: Each groups were divided and classified as followings ; 1 minute Apgar score-normal, 1 minute Apgar score-abnormal, 5 minute Apgar score-nomal, 5 minutes Apgar score-abnormal; there is significant difference between signal loss and 1 minute Apgar score only. And significant difference was shown between mean baseline FHR, FHR variability-amplitude, FHR variability-MMR, and fetal outcomes(body weight of newborn & Apgar score). The FHR variability-amplitude, FHR variability-MMR, and weight of baby were important values in predict of fetal well-being. CONCLUSIONS: In conclusion, there are close relation in each variable of FHRand fetal outcome. The result of this study would be useful background data in the development of objective and automated FHR analysis software, especially in the computerized FHR analysis system.
Apgar Score ; Female ; Fetal Heart* ; Heart Rate, Fetal* ; Humans ; Infant, Newborn* ; Pregnancy ; Pregnant Women ; Principal Component Analysis

BACKGROUNDS: Ischemic heart diseases has increased by more than 80% in the past 10 years among Korean and the global risk assessment of coronary heart disease(CHD) based on the relative risk factors to the probability of developing CHD became widely used for western populations. In this study we hope to provide information on the distribution and characteristics of the relative risks of CHD using the Framingham risk score. METHODS: This Study involved the subjects who visited a university hospital for health promotion from 1995 to 2000 without CHD. We surveyed medical history of the subjects, and measured their blood pressure, serum glucose, total cholesterol(total C) and HDL cholesterol(HDL C). Risk points from the Framingham chart were given to age, systolic BP, total C, HDL C, smoking, diabetes, and the global risk score was calculated from their sum. We analyzed the global risk scores and each risk points of the high risk groups. RESULTS: For younger and older men in the high risk group, the factors smoking and high blood pressure had the highest score assigned respectively. With younger women total C had the highest score assigned, and with older women diabetes took over but HDL C and high blood pressure still had a higher score. CONCLUSION: For primary prevention of CHD, younger men need active education to quit smoking and for older aggressive blood pressure control is desperately needed. For women, concern about low HDL C is highly needed and after menopause aggressive treatment for diabetes, high blood pressure, low HDL C is needed.
Blood Glucose ; Blood Pressure ; Coronary Disease* ; Education ; Female ; Health Promotion ; Heart ; Hope ; Humans ; Hyperlipidemias ; Hypertension ; Male ; Menopause ; Myocardial Ischemia ; Primary Prevention ; Risk Assessment ; Risk Factors* ; Smoke ; Smoking

PURPOSE: We proposed a new index for predicting death resulting from hemorrhagic shock, which was calculated by dividing measured lactate concentration by perfusion. METHODS: Using 24 Sprague-Dawley (S-D) rats, we induced uncontrolled hemorrhage and then measured blood lactate concentration and perfusion in addition to vital signs such as heart rate, blood pressure, respiration rate and temperature. Perfusion and lactate concentration were measured by laser Doppler flowmetry and a lactate concentration meter, respectively. We collected the data for 15 min, which consisted of 3 intervals after homeostasis, and thus obtained a new index. RESULTS: The proposed index revealed an earlier death prediction than lactate concentration alone with the same timing as perfusion. The new index showed generally better sensitivity, specificity and accuracy than lactate concentration and perfusion. Using a receiver operating characteristic curve method, the mortality prediction with the proposed index resulted in a sensitivity of 98.0%, specificity of 90.0%, and accuracy of 93.7%. The mortality prediction with the proposed index resulted in a sensitivity of 98.0%, specificity of 90.0% and accuracy of 93.7%. CONCLUSION: This index could provide physicians, in emergency situations, with early and accurate mortality predictions for cases of human hemorrhagic shock.
Animals ; Blood Pressure ; Emergencies ; Heart Rate ; Hemorrhage ; Homeostasis ; Humans ; Lactic Acid ; Laser-Doppler Flowmetry ; Perfusion ; Rats ; Respiratory Rate ; ROC Curve ; Sensitivity and Specificity ; Shock, Hemorrhagic ; Vital Signs

PURPOSE: We proposed a new index for predicting death resulting from hemorrhagic shock, which was calculated by dividing measured lactate concentration by perfusion. METHODS: Using 24 Sprague-Dawley (S-D) rats, we induced uncontrolled hemorrhage and then measured blood lactate concentration and perfusion in addition to vital signs such as heart rate, blood pressure, respiration rate and temperature. Perfusion and lactate concentration were measured by laser Doppler flowmetry and a lactate concentration meter, respectively. We collected the data for 15 min, which consisted of 3 intervals after homeostasis, and thus obtained a new index. RESULTS: The proposed index revealed an earlier death prediction than lactate concentration alone with the same timing as perfusion. The new index showed generally better sensitivity, specificity and accuracy than lactate concentration and perfusion. Using a receiver operating characteristic curve method, the mortality prediction with the proposed index resulted in a sensitivity of 98.0%, specificity of 90.0%, and accuracy of 93.7%. The mortality prediction with the proposed index resulted in a sensitivity of 98.0%, specificity of 90.0% and accuracy of 93.7%. CONCLUSION: This index could provide physicians, in emergency situations, with early and accurate mortality predictions for cases of human hemorrhagic shock.
Animals ; Blood Pressure ; Emergencies ; Heart Rate ; Hemorrhage ; Homeostasis ; Humans ; Lactic Acid ; Laser-Doppler Flowmetry ; Perfusion ; Rats ; Respiratory Rate ; ROC Curve ; Sensitivity and Specificity ; Shock, Hemorrhagic ; Vital Signs

PURPOSE: A number of clinical decision tools for osteoporosis risk assessment have been developed to select postmenopausal women for the measurement of bone mineral density. We developed and validated machine learning models with the aim of more accurately identifying the risk of osteoporosis in postmenopausal women compared to the ability of conventional clinical decision tools. MATERIALS AND METHODS: We collected medical records from Korean postmenopausal women based on the Korea National Health and Nutrition Examination Surveys. The training data set was used to construct models based on popular machine learning algorithms such as support vector machines (SVM), random forests, artificial neural networks (ANN), and logistic regression (LR) based on simple surveys. The machine learning models were compared to four conventional clinical decision tools: osteoporosis self-assessment tool (OST), osteoporosis risk assessment instrument (ORAI), simple calculated osteoporosis risk estimation (SCORE), and osteoporosis index of risk (OSIRIS). RESULTS: SVM had significantly better area under the curve (AUC) of the receiver operating characteristic than ANN, LR, OST, ORAI, SCORE, and OSIRIS for the training set. SVM predicted osteoporosis risk with an AUC of 0.827, accuracy of 76.7%, sensitivity of 77.8%, and specificity of 76.0% at total hip, femoral neck, or lumbar spine for the testing set. The significant factors selected by SVM were age, height, weight, body mass index, duration of menopause, duration of breast feeding, estrogen therapy, hyperlipidemia, hypertension, osteoarthritis, and diabetes mellitus. CONCLUSION: Considering various predictors associated with low bone density, the machine learning methods may be effective tools for identifying postmenopausal women at high risk for osteoporosis.
Aged ; *Artificial Intelligence ; Bone Density/*physiology ; Female ; Humans ; Middle Aged ; Osteoporosis, Postmenopausal

No abstract available.
Nicotine* ; Smoke* ; Smoking Cessation* ; Smoking* ; Tobacco Use Cessation Products*

No abstract available.
Hydronephrosis*