Cellular oncogenes are expressed as an intrinsic part of the transformed or neoplastic phenotype. More than 60 of the known cellular oncogenes play a specific role in normal cellular development and differentiation. To examine the correlation between ras oncogene expression and the development of cervical cancer, this study investigated the reactivity of cervical intraepithelial neoplasia(CIN) and carcinoma of the uterine cervix by using anti-ras P21 mouse monoclonal antibody. The expression of ras oncogene significantly increased with the grade of malignancy from 11% in severe dysplasia, 30% in carcinoma in situ, 43% in microinvasive carcinoma, to 53% in invasive cancer. The expression of ras oncogene was not correlated with histologic type, tumor size, and nodal status of cervical cancer. It was concluded that expression of ras oncogene is related to early phase of carcinogenesis and tumor invasion of carcinoma of the uterine cervix.
Animals ; Carcinogenesis ; Carcinoma in Situ ; Cervix Uteri* ; Female ; Genes, ras* ; Mice ; Oncogenes ; Phenotype ; Uterine Cervical Neoplasms

BACKGROUND: Postoperative admission to the surgical intensive care unit (S-ICU) is commonly planned to prevent and treat complications, unnecessary admission to the S-ICU increases medical costs and length of hospital stay. This study aimed evaluated outcome and the predictive factors for mortality in patients admitted to the S-ICU after abdominal surgery. METHODS: The 168 patients admitted to the S-ICU immediately after abdominal surgery were reviewed retrospectively from January to December 2011. RESULTS: The mortality rate of patients admitted to the S-ICU after abdominal surgery was 8.9% (15 of 168). Two preoperative factors (body mass index [BMI] < 18.5 kg/m2 [p < 0.001] and serum albumin < 3.0 g/dL [p = 0.018]), two operative factors (the need for transfusion [p = 0.008] or vasopressors [p = 0.013] during surgery), and three postoperative variables (mechanical ventilation immediately following surgery [p < 0.001], sequential organ failure assessment [p = 0.001] and SAPS II [p = 0.001] score) were associated with mortality in univariate analysis. After adjusting for age, gender, and SAPS II by a Cox regression, which revealed that BMI < 18.5 kg/m2 (p < 0.001, hazard ratio [HR] 9.690, 95% confidence interval [CI] 2.990-25.258) and the use of mechanical ventilation on admission to S-ICU (p < 0.001, HR 34.671, 95% CI 6.440-186.649) were independent prognostic factors. CONCLUSIONS: In patients in S-ICU after abdominal surgery, low BMI and postsurgical mechanical ventilation should be considered important predictors of mortality.
Abdomen* ; Body Mass Index ; Humans ; Critical Care ; Intensive Care Units ; Length of Stay ; Mortality ; Postoperative Complications ; Prognosis* ; Respiration, Artificial ; Retrospective Studies ; Serum Albumin ; Ventilation

No abstract available.
Arteriovenous Fistula* ; Cyanosis*

Fetal bilateral renal agenesis is a lethal congenital anomaly. An early and reliable prenatal diagnosis is extremely important as it may offer options for pregnancy termination as early as possible. The criteria for the ultrasonographic diagnosis of bilateral renal agenesis are severe oligohydramnios, nonvisualization of the bladder, and the empty renal fossa. However, severe oligohydramnios makes it difficult to diagnose the disease because of poor sonographic resolution. We present two cases of bilateral renal agenesis, one is diagnosed by ultrasonography after amnioinfusion at 24 weeks gestation, the other is diagnosed postnatally after term delivery.
Diagnosis ; Female ; Oligohydramnios ; Pregnancy ; Prenatal Diagnosis ; Ultrasonography ; Urinary Bladder

No abstract available.

The final degrees of education for the third and fourth authors were mutually misplaced.

Purpose: Multi-echo gradient echo (mGRE) images are used to acquire and analyze multiple echo signals. As the number of acquired echoes increases, more information on the voxel decay changes can be obtained, facilitating myelin water fraction (MWF) mapping.However, an increase in the acquired echoes leads to an increase in scan time. In this study, we developed a workflow to reduce the scan time using a two-stage neural network approach, which extrapolates additional echo images using mGRE data. Materials and Methods: In Stage 1, a pseudo-T1 map was estimated using a U-net network combined with a simple signal model to correct the bias between two mGRE acquired with different scan parameters. The pseudo-T1 map was used to generate an initial echo time (TE) image from the mGRE images. In Stage 2, subsequent TE images were predicted from the initial echo image generated using a trained prediction network. The results were quantitatively compared with those obtained using a fitting algorithm. The MWF mapping results were then compared. Results: The proposed model exhibited better root mean square error, structural similarity index measure, and peak signal-to-noise ratio, as well as a higher correlation with the MWF analysis compared to the fitting algorithm. Conclusion These results demonstrate that the proposed network can effectively reduce the scan time for mGRE image acquisition.

Purpose: Multi-echo gradient echo (mGRE) images are used to acquire and analyze multiple echo signals. As the number of acquired echoes increases, more information on the voxel decay changes can be obtained, facilitating myelin water fraction (MWF) mapping.However, an increase in the acquired echoes leads to an increase in scan time. In this study, we developed a workflow to reduce the scan time using a two-stage neural network approach, which extrapolates additional echo images using mGRE data. Materials and Methods: In Stage 1, a pseudo-T1 map was estimated using a U-net network combined with a simple signal model to correct the bias between two mGRE acquired with different scan parameters. The pseudo-T1 map was used to generate an initial echo time (TE) image from the mGRE images. In Stage 2, subsequent TE images were predicted from the initial echo image generated using a trained prediction network. The results were quantitatively compared with those obtained using a fitting algorithm. The MWF mapping results were then compared. Results: The proposed model exhibited better root mean square error, structural similarity index measure, and peak signal-to-noise ratio, as well as a higher correlation with the MWF analysis compared to the fitting algorithm. Conclusion These results demonstrate that the proposed network can effectively reduce the scan time for mGRE image acquisition.

Purpose: Multi-echo gradient echo (mGRE) images are used to acquire and analyze multiple echo signals. As the number of acquired echoes increases, more information on the voxel decay changes can be obtained, facilitating myelin water fraction (MWF) mapping.However, an increase in the acquired echoes leads to an increase in scan time. In this study, we developed a workflow to reduce the scan time using a two-stage neural network approach, which extrapolates additional echo images using mGRE data. Materials and Methods: In Stage 1, a pseudo-T1 map was estimated using a U-net network combined with a simple signal model to correct the bias between two mGRE acquired with different scan parameters. The pseudo-T1 map was used to generate an initial echo time (TE) image from the mGRE images. In Stage 2, subsequent TE images were predicted from the initial echo image generated using a trained prediction network. The results were quantitatively compared with those obtained using a fitting algorithm. The MWF mapping results were then compared. Results: The proposed model exhibited better root mean square error, structural similarity index measure, and peak signal-to-noise ratio, as well as a higher correlation with the MWF analysis compared to the fitting algorithm. Conclusion These results demonstrate that the proposed network can effectively reduce the scan time for mGRE image acquisition.

BACKGROUND: Liver transplantation (LT) is a complicated procedure with a high incidence of postoperative acute kidney injury (AKI). Previous studies indicate that even transient or mild post-LT AKI can result in critical conditions, including prolonged stays in hospitals and intensive care units and increased morbidity and mortality. The aim of this study was to investigate the association between body mass index (BMI) and occurrence of AKI in LT recipients. METHODS: Medical data from 203 patients who received LT surgery from January 2010 to August 2016 in a single university hospital setting were retrospectively collected and analyzed. Patients were classified as either underweight (BMI <20 kg/m²) or normal weight (20 ≤ BMI < 30 kg/m²). Demographic data, anesthetic methods, complications, and perioperative laboratory test values of each patient were assessed. Propensity analyses and logistic regression were performed to evaluate the association between BMI and post-LT AKI. RESULTS: There was no significant difference in occurrence of post-LT AKI between underweight and normal weight patients. The underweight patient group had significantly longer hospital stay compared with the normal weight patient group (P = 0.023). CONCLUSIONS: BMI classification was neither a positive nor negative predictor of postoperative AKI occurrence. However, patients with lower BMI had significantly longer hospital stay compared with their counterparts. Although our study was limited by its retrospective design, our observations suggest that lower BMI might play a role in post-LT AKI.
Acute Kidney Injury* ; Body Mass Index* ; Classification ; Humans ; Incidence ; Intensive Care Units ; Length of Stay ; Liver Transplantation* ; Liver* ; Logistic Models ; Mortality ; Retrospective Studies* ; Thinness