The difficult oral healthcare in intellectually disabled patients with poor behavioral control has led to debate over the cost-effectiveness and validity of implant treatment in these patients. The patient in the present report had schizophrenia that had led to poor oral care and severe dental caries in the full mouth. Tooth extraction and a removable prosthesis were planned, but the guardian wanted an implant procedure. Since the guardian showed strong will and cooperation with regard to the patient's oral healthcare, extraction followed by immediate implant placement was performed across two rounds of general anesthesia. Since the outcome appears successful, we present this case report. Immediate implant placement after tooth extraction requires fewer surgeries and rounds of general anesthesia, reduces horizontal bone resorption, and can achieve better esthetic results. Therefore, as long as a certain degree of oral care is possible, this can be a positive option for restoration of a partially edentulous mouth, even in intellectually disabled patients.
Anesthesia, General* ; Bone Resorption ; Delivery of Health Care ; Dental Caries ; Humans ; Mouth ; Mouth, Edentulous ; Outpatients* ; Prostheses and Implants ; Schizophrenia ; Tooth Extraction

The difficult oral healthcare in intellectually disabled patients with poor behavioral control has led to debate over the cost-effectiveness and validity of implant treatment in these patients. The patient in the present report had schizophrenia that had led to poor oral care and severe dental caries in the full mouth. Tooth extraction and a removable prosthesis were planned, but the guardian wanted an implant procedure. Since the guardian showed strong will and cooperation with regard to the patient's oral healthcare, extraction followed by immediate implant placement was performed across two rounds of general anesthesia. Since the outcome appears successful, we present this case report. Immediate implant placement after tooth extraction requires fewer surgeries and rounds of general anesthesia, reduces horizontal bone resorption, and can achieve better esthetic results. Therefore, as long as a certain degree of oral care is possible, this can be a positive option for restoration of a partially edentulous mouth, even in intellectually disabled patients.
Anesthesia, General* ; Bone Resorption ; Delivery of Health Care ; Dental Caries ; Humans ; Mouth ; Mouth, Edentulous ; Outpatients* ; Prostheses and Implants ; Schizophrenia ; Tooth Extraction

OBJECTIVES: The present study was conducted to evaluate the mobile transposon-like element, clone MTi7 (MTi7) expression in the mouse ovary and to determine its role(s) in the mouse oocytes by RNA interference (RNAi). METHODS: MTi7 mRNA expression was localized by in situ hybridization in day5 and adult ovaries. Double stranded RNA (dsRNA) was prepared for c-mos, a gene with known function as control, and the MTi7. Each dsRNA was microinjected into the germinal vesicle (GV) stage oocytes then oocyte maturation and intracellular changes were evaluated. RESULTS: In situ hybridization analysis revealed that MTi7 mRNA localized to the oocyte cytoplasm from primordial to preovulatory follicles. After dsRNA injection, we found 43-54% GV arrest of microinjected GV oocytes with 68%-90% decrease in targeted c-mos or MTi7 mRNA. CONCLUSIONS: This is the first report of the oocyte-specific expression of the MTi7 mRNA. From results of RNAi for MTi7, we concluded that the MTi7 is involved in the germinal vesicle breakdown in GV oocytes, and MTi7 may be implicated with c-mos for its function. We report here that RNAi provides an outstanding approach to study the function of a gene with unknown functions.
Adult ; Animals ; Clone Cells* ; Cytoplasm ; Female ; Genes, vif ; Humans ; In Situ Hybridization ; Mice ; Oocytes ; Ovary ; RNA Interference* ; RNA* ; RNA, Double-Stranded ; RNA, Messenger

BACKGROUND/AIMS: The purpose of this study was to assess the value of acoustic radiation force impulse (ARFI) for predicting the extent of radiofrequency ablation (RFA) in hepatocellular carcinoma (HCC) by correlating the elasticity of HCC and peritumoral parenchyma (as measured by ARFI) with the extent of ablation determined by computed tomography (CT). METHODS: From September 2009 to June 2011, 158 patients underwent RFA ablation for HCC (single, < or =3 cm). We evaluated the data of a total of 38 prospectively enrolled patients who underwent both ARFI imaging and contrast-enhanced CT after one session of 12 minutes of RFA without a change in needle position. The ARFI imaging indices, including the mean shear wave velocity (SWV) of HCC, mean SWV of the peritumoral parenchyma and tumor size, were evaluated to determine the statistical correlation with RFA extent after one session of 12 minutes of RFA. RESULTS: A stiffer liver parenchyma in patients with cirrhosis results in a smaller ablation zone. CONCLUSIONS: SWV of ARFI in liver parenchyma was well correlated with RFA extent. After evaluating the correlation between ARFI and RFA extent, we suggest that the SWV in liver parenchyma might be a non-invasive supplementary tool for predicting the extent of RFA.
Acoustics ; Carcinoma, Hepatocellular ; Elasticity ; Elasticity Imaging Techniques ; Fibrosis ; Humans ; Liver ; Needles ; Prospective Studies

Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet.