1.A Study on Expression Pattern of p53, Rb Gene and Apoptosis in Ovarian Epithelial Borderline Tumors and Invasive Carcinoma.
Myeong Wan HA ; Hyeong Kweon KO ; Gi Joo KANG ; Man Soo YOON ; Mee Young SOL
Korean Journal of Obstetrics and Gynecology 2000;43(3):407-413
OBJECTIVE: The aim of this study is to evaluate the role of tumor suppressor genes, p53 and Rb gene, as well as apoptosis in the carcinogenesis of ovarian epithelial tumors. And the value of these factors as prognostic markers to tell the transformation of borderline tumors to overt carcinomas is also studied. METHOD: Thirty cases of ovarian epithelial benign and borderline tumors and invasive carcinoma were used and the expression of the p53 protein and Rb gene protein were evaluated by immunohistochemical method. The apoptosis was evaluated by TUNNEL method. RESULTS: Positive rate of p53 expression in benign, borderline and invasive tumors were 0, 28, and 94 %, respectively. And also, p53 was highly expressed in chemoresistant cases (2/3), in residual tumor (4/5) and in recurred cancer (2/2). Rb protein was partly lost in the borderline tumors, but the rate of Rb protein loss in both borderline tumors and invasive carcinomas were similar. Apoptosis were more active in overt carcinomas than in borderline and benign tumors. In borderline tumors, p53 protein was expressed as 28.6% positivity, and apoptosis was expressed as 28.6% negativity, which showed indirectly that there was apoptosis induction effect of p53. In ten cases of invasive carcinomas showing highly expressed p53, apoptosis revealed all positive reaction except 2 cases, and Rb protein revealed variously. This result supported the apoptosis imduction effect of p53, but it was difficult to find the association of expression degree between the two tumor supressor genes CONCLUSION: In conclusion, the values of p53 is a discriminating factor of malignancy from benign and the expression of p53 is related with clinical aggressivity such as recurrence and residual cancers. Apoptosis are more active in overt carcinoma than in benign & borderline tumor, and in borderline tumor the expression of p53 is related to apoptosis induction which results to carcinomatous change.
Apoptosis*
;
Carcinogenesis
;
Genes, Retinoblastoma*
;
Genes, Tumor Suppressor
;
Neoplasm, Residual
;
Recurrence
;
Retinoblastoma Protein
2.A case of uterine didelphys associated with ipsilateral renal agenesis, Gartner's duct cyst and uterine myoma.
Ha Jung KIM ; Dong Hyung LEE ; Jong Hoon PARK ; Jung Sub YOON ; Gee Joo KANG ; Man Soo YOON
Korean Journal of Obstetrics and Gynecology 2000;43(12):2315-2318
No abstract available.
Leiomyoma*
3.A Case of Wegener's Granulomatosis with Acute Renal Failure and Pneumothorax Developed during Treatment with Immunosuppressive Agent.
Sung Jae PARK ; Hi Gun HA ; Yang Wook KIM ; Joo In KIM ; Yeong Hoon KIM ; Hye Kyoung YOON
Korean Journal of Nephrology 1998;17(5):831-835
Wegener's granulomatosis is characterized by necrotizing granulomatosis lesion of the respiratory tract, glomerulonephritis and frequently vasculitis involving other organs. The basic pathophysiologic mechanism of Wegener's granulomatosis is not defined yet. However, it may be suspected an autoimmune disease. We experienced a case of Wegener's granulomatosis which are associated with acute renal failure and pneumothorax. The patient suffered from hemoptysis, fever and cough. Despite antibiotic therapy, symtoms did not improved and multiple varying sized nodules were aggravated on chest roentogenogram and serum creatinine elevated 3.4mg/dl. After diagnosis using video associated thoracoscopic surgery, the patient was treated with cyclophsphamide, glucocorticoid and sulfamethoxasole-trimethoprime. With the combination therapy, the patient felt completely well and chest roentogenogram showed lungs were improved and serum creatinine was normal. The patient was readmitted because of right pleuritic pain and dyspnea 15 day after discharge. The patient was developed a right pneumothorax. The lung was easily expanded by intercostal tube drainage with a one way valve. The patient has been treated as an out- patient with immunosuppressive agents continously.
Acute Kidney Injury*
;
Autoimmune Diseases
;
Cough
;
Creatinine
;
Diagnosis
;
Drainage
;
Dyspnea
;
Fever
;
Glomerulonephritis
;
Hemoptysis
;
Humans
;
Immunosuppressive Agents
;
Lung
;
Pneumothorax*
;
Respiratory System
;
Thoracoscopy
;
Thorax
;
Vasculitis
;
Wegener Granulomatosis*
4.Diver Death due to Underwater Explosion.
Joo Young NA ; Jeong Woo PARK ; Seok Hyun YOON ; Jong Shin PARK ; Byung Ha CHOI ; Youn Shin KIM
Korean Journal of Legal Medicine 2014;38(4):171-174
A 44-year-old man was cutting an outer plate of a ship, at a depth of 25 m below sea level. Following a sudden explosion, he was discovered unconscious and was carried to the surface by other divers. There was no evidence of vital signs upon arrival at the hospital. Postmortem computed tomography, which was performed prior to autopsy, revealed massive pneumocephalus in the brain, pneumohemothorax, diffuse lung contusions with multiple traumatic lung cysts, air-fluid level in the cardiac chamber of the chest, and pneumoperitoneum in the abdomen. Postmortem external examination showed a circular abrasion on the jaw, diffuse subcutaneous emphysema, and contusion in the right upper arm. An internal examination revealed intravascular air bubbles in all four chambers of the heart, and diffuse pulmonary trauma including contusion, laceration, and multiple traumatic cysts. Blast injury to the chest, and air embolism due to the underwater explosion were established as the underlying cause of death.
Abdomen
;
Adult
;
Arm
;
Autopsy
;
Blast Injuries
;
Brain
;
Cause of Death
;
Contusions
;
Diving
;
Embolism, Air
;
Explosions*
;
Heart
;
Humans
;
Jaw
;
Lacerations
;
Lung
;
Pneumocephalus
;
Pneumoperitoneum
;
Ships
;
Subcutaneous Emphysema
;
Thorax
;
Vital Signs
5.Effect of Torque Heel on Excessive External Rotation of Hemiplegic Foot: Three Dimensional Gait Analysis.
Byung Gyu JOO ; Jong Yoon YOO ; Sang Bae HA
Journal of the Korean Academy of Rehabilitation Medicine 1998;22(5):1114-1122
OBJECTIVE: Excessive external rotation of the hemiplegic foot is a common problem of hemiplegic gait. There has been a few report on etiological investigation and corrective measurement of an excessive external rotation of hemiplegic foot. Thus we present a newly designed Torque heel to correct the external rotation of hemiplegic foot. METHOD: Ten hemiparetic patients with an excessive external rotation of affected foot participated in this study. All of the participants were able to walk at least 10 meters with metal a ankle foot orthosis (AFO) using a single cane. Each of these patients was placed on four tries of walk: (1) on a bare foot; (2) with an AFO; (3) with an AFO and a quarter inch of lateral wedge; and (4) with an AFO and the Torque heel . Gait patterns were analysed by the Vicon 370, three dimensional motion analyser. RESULTS: The speed and stride length increased in all tries except for the bare foot walk. Those who walked with the assistive devices showed no difference in the speed and stride length. All the participants showed an increased in external rotation of pelvis and ankle. Those who walked with an AFO and Torque heel presented a decrease in the external rotation of foot and pelvis. The hip and ankle motions of the hemiplegic limbs were not affected with the AFO and Torque heel . A significant degree of correction in pelvic rotation with an AFO and Torque heel was noted. CONCLUSIONS: This study indicates that an AFO with Torque heel is beneficial to the correction of external rotation of a hemiplegic foot. And the excessive external rotation of hemiplegic foot may be due possibly to the external rotation of pelvis.
Ankle
;
Canes
;
Extremities
;
Foot Orthoses
;
Foot*
;
Gait Disorders, Neurologic
;
Gait*
;
Heel*
;
Hip
;
Humans
;
Pelvis
;
Self-Help Devices
;
Torque*
6.Prediction of intensive care unit admission using machine learning in patients with odontogenic infection
Journal of the Korean Association of Oral and Maxillofacial Surgeons 2024;50(4):216-221
Objectives:
This study aimed to develop and validate a model to predict the need for intensive care unit (ICU) admission in patients with dental infections using an automated machine learning (ML) program called H2O-AutoML.
Materials and Methods:
Two models were created using only the information available at the initial examination. Model 1 was parameterized with only clinical symptoms and blood tests, excluding contrast-enhanced multi-detector computed tomography (MDCT) images available at the initial visit, whereas model 2 was created with the addition of the MDCT information to the model 1 parameters. Although model 2 was expected to be superior to model 1, we wanted to independently determine this conclusion. A total of 210 patients who visited the Department of Oral and Maxillofacial Surgery at the Dankook University Dental Hospital from March 2013 to August 2023 was included in this study. The patients’ demographic characteristics (sex, age, and place of residence), systemic factors (hypertension, diabetes mellitus [DM], kidney disease, liver disease, heart disease, anticoagulation therapy, and osteoporosis), local factors (smoking status, site of infection, postoperative wound infection, dysphagia, odynophagia, and trismus), and factors known from initial blood tests were obtained from their medical charts and retrospectively reviewed.
Results:
The generalized linear model algorithm provided the best diagnostic accuracy, with an area under the receiver operating characteristic values of 0.8289 in model 1 and 0.8415 in model 2. In both models, the C-reactive protein level was the most important variable, followed by DM.
Conclusion
This study provides unprecedented data on the use of ML for successful prediction of ICU admission based on initial examination results. These findings will considerably contribute to the development of the field of dentistry, especially oral and maxillofacial surgery.
7.Prediction of intensive care unit admission using machine learning in patients with odontogenic infection
Journal of the Korean Association of Oral and Maxillofacial Surgeons 2024;50(4):216-221
Objectives:
This study aimed to develop and validate a model to predict the need for intensive care unit (ICU) admission in patients with dental infections using an automated machine learning (ML) program called H2O-AutoML.
Materials and Methods:
Two models were created using only the information available at the initial examination. Model 1 was parameterized with only clinical symptoms and blood tests, excluding contrast-enhanced multi-detector computed tomography (MDCT) images available at the initial visit, whereas model 2 was created with the addition of the MDCT information to the model 1 parameters. Although model 2 was expected to be superior to model 1, we wanted to independently determine this conclusion. A total of 210 patients who visited the Department of Oral and Maxillofacial Surgery at the Dankook University Dental Hospital from March 2013 to August 2023 was included in this study. The patients’ demographic characteristics (sex, age, and place of residence), systemic factors (hypertension, diabetes mellitus [DM], kidney disease, liver disease, heart disease, anticoagulation therapy, and osteoporosis), local factors (smoking status, site of infection, postoperative wound infection, dysphagia, odynophagia, and trismus), and factors known from initial blood tests were obtained from their medical charts and retrospectively reviewed.
Results:
The generalized linear model algorithm provided the best diagnostic accuracy, with an area under the receiver operating characteristic values of 0.8289 in model 1 and 0.8415 in model 2. In both models, the C-reactive protein level was the most important variable, followed by DM.
Conclusion
This study provides unprecedented data on the use of ML for successful prediction of ICU admission based on initial examination results. These findings will considerably contribute to the development of the field of dentistry, especially oral and maxillofacial surgery.
8.Prediction of intensive care unit admission using machine learning in patients with odontogenic infection
Journal of the Korean Association of Oral and Maxillofacial Surgeons 2024;50(4):216-221
Objectives:
This study aimed to develop and validate a model to predict the need for intensive care unit (ICU) admission in patients with dental infections using an automated machine learning (ML) program called H2O-AutoML.
Materials and Methods:
Two models were created using only the information available at the initial examination. Model 1 was parameterized with only clinical symptoms and blood tests, excluding contrast-enhanced multi-detector computed tomography (MDCT) images available at the initial visit, whereas model 2 was created with the addition of the MDCT information to the model 1 parameters. Although model 2 was expected to be superior to model 1, we wanted to independently determine this conclusion. A total of 210 patients who visited the Department of Oral and Maxillofacial Surgery at the Dankook University Dental Hospital from March 2013 to August 2023 was included in this study. The patients’ demographic characteristics (sex, age, and place of residence), systemic factors (hypertension, diabetes mellitus [DM], kidney disease, liver disease, heart disease, anticoagulation therapy, and osteoporosis), local factors (smoking status, site of infection, postoperative wound infection, dysphagia, odynophagia, and trismus), and factors known from initial blood tests were obtained from their medical charts and retrospectively reviewed.
Results:
The generalized linear model algorithm provided the best diagnostic accuracy, with an area under the receiver operating characteristic values of 0.8289 in model 1 and 0.8415 in model 2. In both models, the C-reactive protein level was the most important variable, followed by DM.
Conclusion
This study provides unprecedented data on the use of ML for successful prediction of ICU admission based on initial examination results. These findings will considerably contribute to the development of the field of dentistry, especially oral and maxillofacial surgery.
9.Prediction of intensive care unit admission using machine learning in patients with odontogenic infection
Journal of the Korean Association of Oral and Maxillofacial Surgeons 2024;50(4):216-221
Objectives:
This study aimed to develop and validate a model to predict the need for intensive care unit (ICU) admission in patients with dental infections using an automated machine learning (ML) program called H2O-AutoML.
Materials and Methods:
Two models were created using only the information available at the initial examination. Model 1 was parameterized with only clinical symptoms and blood tests, excluding contrast-enhanced multi-detector computed tomography (MDCT) images available at the initial visit, whereas model 2 was created with the addition of the MDCT information to the model 1 parameters. Although model 2 was expected to be superior to model 1, we wanted to independently determine this conclusion. A total of 210 patients who visited the Department of Oral and Maxillofacial Surgery at the Dankook University Dental Hospital from March 2013 to August 2023 was included in this study. The patients’ demographic characteristics (sex, age, and place of residence), systemic factors (hypertension, diabetes mellitus [DM], kidney disease, liver disease, heart disease, anticoagulation therapy, and osteoporosis), local factors (smoking status, site of infection, postoperative wound infection, dysphagia, odynophagia, and trismus), and factors known from initial blood tests were obtained from their medical charts and retrospectively reviewed.
Results:
The generalized linear model algorithm provided the best diagnostic accuracy, with an area under the receiver operating characteristic values of 0.8289 in model 1 and 0.8415 in model 2. In both models, the C-reactive protein level was the most important variable, followed by DM.
Conclusion
This study provides unprecedented data on the use of ML for successful prediction of ICU admission based on initial examination results. These findings will considerably contribute to the development of the field of dentistry, especially oral and maxillofacial surgery.
10.Preoperative Tract Dilatation for Percutaneous Nephrolithotomy.
Dong Sik CHOI ; Joo Hyeong OH ; Yup YOON ; Bum Ha YI ; Hong Seop SHIN ; Joo Won LIM ; Sung Koo CHANG
Journal of the Korean Radiological Society 1998;39(3):517-522
PURPOSE: The purpose of this study was to understand the principle of percutaneous nephrolithotomy(PNL), toincrease its success rate, and to base the radiologic approach on preoperative interventional tract dilatation. MATERIALS AND METHODS: Twenty-six patients(male, 19, female, 7) with staghorn or pelviocalyceal calculi who hadundergone PNL were included in this study. After percutaneous nephrostomy(PCN) was performed in each patient, thetract was dilated to 30F with Amplatz dilators using coaxial techniques or a 30F, 10cm high-pressure tractdilatation balloon. One day before the calculi were fragmented and removed by PNL, a 30F Amplatz sheath wasinserted under local anesthesia. The time required for tract dilatation, complications, and surgery was analyzed. RESULTS: Percutaneous tract dilatation were successful in all patients, and forceps, a nephrolithotome and anephroscope were successfully introduced into the pelvocalyceal system. The average procedure time was 19.5minutes ; a double J stent was replaced in the pelvocalyceal system of 13 of 26 patients (50%) ; because ofimproper catheter direction or/and bleeding, the Amplatz sheath was replaced in three. After PNL, complicationsinvolving renal hematoma occurred in one patient. This did not affect the patient's prognosis, however. CONCLUSION:Owing to its short procedure time and low complication rate, interventional preoperative tract dilatation forPNL is thought to be an effective technique for patients with staghorn or pelvocalceal calculi.
Anesthesia, Local
;
Calculi
;
Catheters
;
Dilatation*
;
Female
;
Hematoma
;
Hemorrhage
;
Humans
;
Nephrostomy, Percutaneous*
;
Prognosis
;
Stents
;
Surgical Instruments