Enhanced Solubility of the Support in an FDM-Based 3D Printed Structure Using Hydrogen Peroxide under Ultrasonication

Fused deposition modeling (FDM), one of the archetypal 3D printing processes, typically requires support structures matched to printed model parts that principally have undercut or overhung features. Thus, the support removal is an essential postprocessing step after the FDM process. Here, we present an efficient and rapid method to remove the support part of an FDM-manufactured product using the phenomenon of oxidative degradation of hydrogen peroxide. This mechanism was significantly effective on polyvinyl alcohol (PVA), which has been widely used as a support material in the FDM process. Compared to water, hydrogen peroxide provided a two times faster dissolution rate of the PVA material. This could be increased another two times by applying ultrasonication to the solvent. In addition to the rapidness, we confirmed that amount of the support residues removed was enhanced, which was essentially caused by the surface roughness of the FDM-fabricated part. Furthermore, we demonstrated that there was no deterioration with respect to the mechanical properties or shape geometries of the obtained 3D printed parts. Taken together, these results are expected to help enhance the productivity of FDM by reducing the postprocessing time and to allow the removal of complicated and fine support structures, thereby improving the design capability of the FDM technique

Desktop Micro Forming System for Micro Pattern on the Metal Substrate

Abstract. In this Research, the desktop micro forming manufacturing system has been developed. A micro forming system has been achieved in Japan and its developed micro press is limited to single forming process. To coincide with the purpose to be more practical, research and development is necessary about the press which the multi forming process is possible. Micro patterned metal components are used in so many precision engineering fields. This micro pattern plays an important part in the functional movement of precision module. This micro pattern on the metal component can be made by EDM(Electro Discharge Machining). But this EDM method has low productivity because EDM tools can be worn easily. If another manufacturing process is developed with high productivity, industries can product the competitive goods. So we research on the forming process and system to make micro functional pattern on the metal component

Predictors of Success of Repeated Injections of Single-dose Methotrexate Regimen for Tubal Ectopic Pregnancy

The purpose of this study is to evaluate predictors of success of repeated injections of methotrexate in the single-dose regimen for the treatment of tubal ectopic pregnancy. All patients who had ectopic tubal pregnancy and were treated with a single dose regimen were retrospectively identified. 126 patients were treated with methotrexate. Among them, 39 patients were adequate for this study. 33 were treated with the 2nd dose and 27 were successfully cured. Additionally, 6 who were injected with the 3rd dose were all cured as well. Therefore, in our study, the success rate for the repeated injections of methotrexate was found to be 84.6% (33/39). The mean initial β-hCG level was significantly lower in patients who were successfully treated than in patients who failed (3915.3±3281.3 vs. 8379.7±2604.4 IU/mL, p<0.05). The success rate is 96% when the β-hCG level is less than 6,000 IU/mL and is 58% when β-hCG is greater than 6,000 IU/mL (OR=18.57, 95% CI 1.86-185.89). The initial β-hCG level is the only factor that has significant meaning as predictor of success of repeated injections of methotrexate in the single-dose regimen. Repeated injections of methotrexate may be particularly effective when the initial β-hCG level is below 6,000 IU/mL

Co-transplantation of Human Mesenchymal Stem Cells Promotes Human CD34+ Cells Engraftment in a Dose-dependent Fashion in NOD/SCID Mice

Mesenchymal stem cells (MSCs) have recently been identified and characterized in humans. Moreover, MSC secrete cytokines that can support hematopoietic progenitor growth. In the present study, we evaluated whether the efficacy of hematopoietic stem cell transplantation is improved by their co-transplantation with MSC, and whether this is positively correlated with the dose of infused MSCs. Accordingly, irradiated NOD/SCID mice were transplanted with 1×105 human CD34+ cells in the presence or absence of culture expanded MSCs (1×106 or 5×106). We evaluated human hematopoietic cell engraftment by flow cytometry and assessed MSC tissue distributions by fluorescence in situ hybridization. We found that CD45+ and CD34+ cell levels were significantly elevated in a dose-dependent manner in cotransplanted mice 4 weeks after transplantation. The engraftments of CD33+ and CD19+ cells also increased dose-dependently. However, the engraftment of CD3+ cells did not increase after co-transplantation with MSCs. Human Y chromosome+ cells were observed in multiple tissues and were more frequently observed in mice co-transplanted with 5×106 rather than 1×106 MSCs. These results suggest that MSCs are capable of enhancing hematopoietic cell engraftment and distribution in multiple organs in a dose-dependent fashion

Endocrine Complications after Hematopoietic Stem Cell Transplantation during Childhood and Adolescence

Long-term survivors of hematopoietic stem cell transplantation (HSCT) during childhood and adolescence are at risk of developing endocrine complications. The purpose of this study was to evaluate the long-term endocrine complications and their associated risk factors among such patients. We reviewed the data from 111 patients (59 males and 52 females) who underwent HSCT at the mean age of 8.3±4.1 yr. Thirty patients (27.0%) had growth impairment, and seven (21.2%) out of 33 patients who attained final height reached final height below 2 standard deviation (SD). The final height SD score of the patients conditioned with total body irradiation (TBI) was significantly lower than that of the patients conditioned without TBI (-1.18±1.14 vs. -0.19±0.78, P=0.011). Thirteen patients (11.7%) developed hypothyroidism (11 subclinical, 2 central) 3.8±1.8 (range 1.6-6.2) yr after HSCT. Nineteen (65.5%) out of 29 females had evidence of gonadal dysfunction, and 18 (64.3%) out of 28 males had evidence of gonadal dysfunction. The risk for gonadal dysfunction was significantly higher in females conditioned with busulfan/cyclophosphamide (P=0.003). These results suggest that the majority of patients treated with HSCT during childhood and adolescence have one or more endocrine complications. Therefore, multiple endocrine functions should be monitored periodically after HSCT until they reach adult age

Detection of Stress Levels from Biosignals Measured in Virtual Reality Environments Using a Kernel-Based Extreme Learning Machine

Virtual reality (VR) is a computer technique that creates an artificial environment composed of realistic images, sounds, and other sensations. Many researchers have used VR devices to generate various stimuli, and have utilized them to perform experiments or to provide treatment. In this study, the participants performed mental tasks using a VR device while physiological signals were measured: a photoplethysmogram (PPG), electrodermal activity (EDA), and skin temperature (SKT). In general, stress is an important factor that can influence the autonomic nervous system (ANS). Heart-rate variability (HRV) is known to be related to ANS activity, so we used an HRV derived from the PPG peak interval. In addition, the peak characteristics of the skin conductance (SC) from EDA and SKT variation can also reflect ANS activity; we utilized them as well. Then, we applied a kernel-based extreme-learning machine (K-ELM) to correctly classify the stress levels induced by the VR task to reflect five different levels of stress situations: baseline, mild stress, moderate stress, severe stress, and recovery. Twelve healthy subjects voluntarily participated in the study. Three physiological signals were measured in stress environment generated by VR device. As a result, the average classification accuracy was over 95% using K-ELM and the integrated feature (IT = HRV + SC + SKT). In addition, the proposed algorithm can embed a microcontroller chip since K-ELM algorithm have very short computation time. Therefore, a compact wearable device classifying stress levels using physiological signals can be developed