Search

Abstract Despite recent advances in surgical techniques and perinatal management in obstetrics for reducing intraoperative bleeding, blood transfusion may occur during a cesarean section (CS). This study aims to identify machine learning models with an optimal diagnostic performance for intraoperative transfusion prediction in parturients undergoing a CS. Additionally, to address model performance degradation due to data imbalance, this study further investigated the variation in predictive model performance depending on the ratio of event to non-event data (1:1, 1:2, 1:3, and 1:4 model datasets and raw data).The area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC) were evaluated to compare the predictive accuracy of different machine learning algorithms, including XGBoost, K-nearest neighbor, decision tree, support vector machine, multilayer perceptron, logistic regression, random forest, and deep neural network. We compared the predictive performance of eight prediction algorithms that were applied to five types of datasets. The intraoperative transfusion in maternal CS was 7.2% (1020/14,254). XGBoost showed the highest AUROC (0.8257) and AUPRC (0.4825) among the models. The most significant predictors for transfusion in maternal CS as per machine learning models were placenta previa totalis, haemoglobin, placenta previa partialis, and platelets. In all eight prediction algorithms, the change in predictive performance based on the AUROC and AUPRC according to the resampling ratio was insignificant. The XGBoost algorithm exhibited optimal performance for predicting intraoperative transfusion. Data balancing techniques employed to alter the event data composition ratio of the training data failed to improve the performance of the prediction model.

Highlights In-depth review assesses III–V materials for efficient hydrogen generation and CO2 reduction in renewable energy technologies. Exploration of strategies for broad light absorption and increased efficiency in water splitting processes and CO2 reduction. Innovative electrode designs conclude the path for stable, large-scale implementation of clean energy systems.

Abstract This study investigates the effects of an air layer on drag reduction and turbulence dynamics in channel flow over a superhydrophobic surface (SHS). Employing the OpenFOAM platform, direct numerical simulation was conducted to investigate turbulent channel flow with an air layer over an SHS. The simulations, which take into account the interaction between water and air, analyze various parameters such as velocity distribution, drag reduction (DR), Reynolds stress, turbulent kinetic energy (TKE), and coherent structures near the water–air interface. The presence of an air layer significantly alters the velocity distribution, leading to higher velocities at the interface compared to simulations without the air layer. Notably, the thickness of the air layer emerges as an important factor, with larger thicknesses resulting in increased velocities and drag reduction. This study underscores the substantial impact of the air layer on TKE near the superhydrophobic surface, emphasizing its role in understanding and optimizing drag reduction. Furthermore, the nonlinear relationship between slip velocity, Q contours, and coherent structures near the SHS are investigated.

IntroductionHumanized mouse models to recapitulate human biological systems still have limitations, such as the onset of lethal graft-versus-host disease (GvHD), a variable success rate, and the low accessibility of total body irradiation (TBI). Recently, mice modified with the CD47-SIRPA axis have been studied to improve humanized mouse models. However, such trials have been rarely applied in NOD mice. In this study, we created a novel mouse strain, NOD-CD47nullRag2nullIL-2rγnull (RTKO) mice, and applied it to generate humanized mice.MethodsFour-week-old female NOD-Rag2nullIL-2rγnull (RID) and RTKO mice pre-conditioned with TBI or busulfan (BSF) injection were used for generating human CD34+ hematopoietic stem cell (HSC) engrafted humanized mice. Clinical signs were observed twice a week, and body weight was measured once a week. Flow cytometry for human leukocyte antigens was performed at intervals of four weeks or two weeks, and mice were sacrificed at 48 weeks after HSC injection.ResultsFor a long period from 16 to 40 weeks post transplantation, the percentage of hCD45 was mostly maintained above 25% in all groups, and it was sustained the longest and highest in the RTKO BSF group. Reconstruction of human leukocytes, including hCD3, was also most prominent in the RTKO BSF group. Only two mice died before 40 weeks post transplantation in all groups, and there were no life-threatening GvHD lesions except in the dead mice. The occurrence of GvHD has been identified as mainly due to human T cells infiltrating tissues and their related cytokines.DiscussionHumanized mouse models under all conditions applied in this study are considered suitable models for long-term experiments based on the improvement of human leukocytes reconstruction and the stable animal health. Especially, RTKO mice pretreated with BSF are expected to be a valuable platform not only for generating humanized mice but also for various immune research fields.

BackgroundTo circumvent regulatory barriers that limit medical data exchange due to personal information security concerns, we use homomorphic encryption (HE) technology, enabling computation on encrypted data and enhancing privacy. ObjectiveThis study explores whether using HE to integrate encrypted multi-institutional data enhances predictive power in research, focusing on the integration feasibility across institutions and determining the optimal size of hospital data sets for improved prediction models. MethodsWe used data from 341,007 individuals aged 18 years and older who underwent noncardiac surgeries across 3 medical institutions. The study focused on predicting in-hospital mortality within 30 days postoperatively, using secure logistic regression based on HE as the prediction model. We compared the predictive performance of this model using plaintext data from a single institution against a model using encrypted data from multiple institutions. ResultsThe predictive model using encrypted data from all 3 institutions exhibited the best performance based on area under the receiver operating characteristic curve (0.941); the model combining Asan Medical Center (AMC) and Seoul National University Hospital (SNUH) data exhibited the best predictive performance based on area under the precision-recall curve (0.132). Both Ewha Womans University Medical Center and SNUH demonstrated improvement in predictive power for their own institutions upon their respective data’s addition to the AMC data. ConclusionsPrediction models using multi-institutional data sets processed with HE outperformed those using single-institution data sets, especially when our model adaptation approach was applied, which was further validated on a smaller host hospital with a limited data set.

Abstract Proper placental development in early pregnancy ensures a positive outcome later on. The developmental relationship between the placenta and embryonic organs, such as the heart, is crucial for a normal pregnancy. However, the mechanism through which the placenta influences the development of embryonic organs remains unclear. Trophoblasts fuse to form multinucleated syncytiotrophoblasts (SynT), which primarily make up the placental materno-fetal interface. We discovered that endogenous progesterone immunomodulatory binding factor 1 (PIBF1) is vital for trophoblast differentiation and fusion into SynT in humans and mice. PIBF1 facilitates communication between SynT and adjacent vascular cells, promoting vascular network development in the primary placenta. This process affected the early development of the embryonic cardiovascular system in mice. Moreover, in vitro experiments showed that PIBF1 promotes the development of cardiovascular characteristics in heart organoids. Our findings show how SynTs organize the barrier and imply their possible roles in supporting embryogenesis, including cardiovascular development. SynT-derived factors and SynT within the placenta may play critical roles in ensuring proper organogenesis of other organs in the embryo.

This work simulates thermo-diffusion and diffusion-thermo on heat, mass transfer, and fluid flow of nano-encapsulated phase change materials (NEPCM) within a complex cavity. It is a novel study in handling the heat/mass transfer inside a highly complicated shape saturated by a partial layer porous medium. In addition, an artificial neural network (ANN) model is used in conjunction with the incompressible smoothed particle hydrodynamics (ISPH) simulation to forecast the mean Nusselt and Sherwood numbers ($ \stackrel{-}{Nu} $ and $ \stackrel{-}{Sh} $). Heat and mass transfer, as well as thermo-diffusion effects, are useful in a variety of applications, including chemical engineering, material processing, and multifunctional heat exchangers. The ISPH method is used to solve the system of governing equations for the heat and mass transfer inside a complex cavity. The scales of pertinent parameters are fusion temperature $ {\theta }_{f} = 0.05-0.95 $, Rayleigh number $ Ra = {10}^{3}-{10}^{6} $, buoyancy ratio parameter $ N = -2-1 $, Darcy number $ Da = {10}^{-2}-{10}^{-5} $, Lewis number $ Le = 1-20 $, Dufour number $ Du = 0-0.25 $, and Soret number $ Sr = 0-0.8 $. Alterations of Rayleigh number are effective in enhancing the intensity of heat and mass transfer and velocity field of NEPCM within a complex cavity. The high complexity of a closed domain reduced the influences of Soret-Dufour numbers on heat and mass transfer especially at the steady state. The fusion temperature works well in adjusting the intensity and location of a heat capacity ratio inside a complex cavity. The presence of a porous layer in a cavity's center decreases the velocity field within a complex cavity at a reduction in Darcy number. The goal values of $ \stackrel{-}{Nu} $ and $ \stackrel{-}{Sh} $ for each data point are compared to those estimated by the ANN model. It is discovered that the ANN model's $ \stackrel{-}{Nu} $ and $ \stackrel{-}{Sh} $ values correspond completely with the target values. The exact harmony of the ANN model prediction values with the target values demonstrates that the developed ANN model can forecast the $ \stackrel{-}{Nu} $ and $ \stackrel{-}{Sh} $ values precisely.

Background and Objective: Early discharge following robot-assisted kidney transplantation (RAKT) is a cost-effective strategy for reducing healthcare expenses while maintaining favorable short- and long-term prognoses. This study aims to identify predictors of postoperative delayed discharge in RAKT patients and develop a predictive model to enhance clinical outcomes. Materials and Methods: This retrospective study included 146 patients aged 18 years and older who underwent RAKT at a single tertiary medical center from August 2020 to January 2024. Data were collected on demographics, comorbidities, social and medical histories, preoperative labs, surgical information, intraoperative data, and postoperative outcomes. The primary outcome was delayed postoperative discharge (length of hospital stay > 7 days). Risk factors for delayed discharge were identified through univariate and multivariate regression analyses, leading to the development of a risk scoring system, the effectiveness of which was evaluated through receiver operating characteristic curve analysis. Results: 110 patients (74.8%) were discharged within 7 days post-transplant, while 36 (24.7%) remained hospitalized for 8 days or longer. Univariate and multivariate logistic regression analyses identified ABO incompatibility, BUN levels, anesthesia time, and vasodilator use as risk factors for delayed discharge. The RAKT score, incorporating these factors, demonstrated a predictive performance with a C-statistic of 0.789. Conclusions: This study identified risk factors for delayed discharge after RAKT and developed a promising risk scoring system for real-world clinical application, potentially improving postoperative outcome stratification in RAKT recipients.

Chat generative pre-trained transformer (ChatGPT) is a chatbot developed by OpenAI that answers questions in a human-like manner. ChatGPT is a GPT language model that understands and responds to natural language created using a transformer, which is a new artificial neural network algorithm first introduced by Google in 2017. ChatGPT can be used to identify research topics and proofread English writing and R scripts to improve work efficiency and optimize time. Attempts to actively utilize generative artificial intelligence (AI) are expected to continue in clinical settings. However, ChatGPT still has many limitations for widespread use in clinical research, owing to AI hallucination symptoms and its training data constraints. Researchers recommend avoiding scientific writing using ChatGPT in many traditional journals because of the current lack of originality guidelines and plagiarism of content generated by ChatGPT. Further regulations and discussions on these topics are expected in the future.

Purpose: The first tracheostomy tube replacement is a critical procedure that can cause various complications, but there are few studies on the optimal timing of tracheostomy tube replacement in adult patients. This study aimed to evaluate the appropriate timing to replace the first tracheostomy tube to improve outcomes in adult patients. Materials and methods: This study was a retrospective cohort study that included 3957 patients aged ≥18 years who underwent the first tracheostomy tube change from January 2010 to February 2021. The primary outcome was all-cause mortality after the first tracheostomy tube change. Results: The all-cause mortality was statistically significantly lower in group changing the first tracheostomy tube between 7 and 9 days than in other groups (42.1%, P = 0.001). After adjustments in the multivariable analyses, early first tracheostomy tube change within 6 days was independently associated with increased all-cause mortality. The hospital stay, ICU stay, and post-procedural pulmonary complications seemed to increase as the replacement time was delayed. Conclusions: The timing of the first tracheostomy tube change between 7 and 9 days after tracheostomy was associated with improved clinical outcomes, including all-cause mortality. Further prospective investigations are needed to determine whether the optimal timing of the first tracheostomy tube change can reduce mortality.

This work integrates incompressible smoothed particle hydrodynamics (ISPH) with machine learning (ML) to examine the uses of two different domain shapes, spline star-domain, and triangle star-domain, on double diffusion of nano-encapsulated phase change material (NEPCM). The effects of thermal radiation and exothermic chemical reactions are conducted in this work. The hexagonal-shaped is located inside the center of the star-shape carrying (Th&Ch). The left/right walls of the star shape are kept at (Tc&Cc) and the other walls have an adiabatic condition. It is recommended to examine the smoothness of closed curves in the heat and mass transfer by changing the triangle to spline curves. The present investigations of transmission of heat and mass of NEPCM within a complicated star shape can be employed in cooling systems of electronic/battery, heat exchangers, food processing, and chemical engineering. The ISPH simulations are executed for the pertinent parameters, Darcy number, Frank-Kamenetskii number, Rayleigh number, Dufour number, Soret number, and thermal radiation parameter. The performed simulations showed the significance of the spline star domain compared to the triangle star domain in smoothening the nanofluid flow and double-diffusive convection in an annulus. Frank-Kamenetskii number is a promising factor in the enhancement of heat transfer and controlling the phase change zone within an annulus. At a spline-star cavity, the maximum velocity rises by 32.32 % and 54.95 % when the Frank-Kamenetskii number grows from 0 to 5, and thermal radiation increases from 0 to 5. Soret number works effectively in enhancing the distribution of concentration at large temperature differences. Machine learning plays a vital role in many engineering applications. Hence, ML's powerful capabilities to predict the average Nu‾ and Sh‾. In the proposed ML model, the dimensionless time and thermal radiation parameter are used as input to the ML model, while their corresponding numeral estimated values of Nu‾ and Sh‾ are used as output targets for the ML model. The values of Nu‾ and Sh‾ are predicted by the suggested ML model with a comparatively small error less than 1 %.

Abstract Background Prediction of preoperative frailty risk in the emergency setting is a challenging issue because preoperative evaluation cannot be done sufficiently. In a previous study, the preoperative frailty risk prediction model used only diagnostic and operation codes for emergency surgery and found poor predictive performance. This study developed a preoperative frailty prediction model using machine learning techniques that can be used in various clinical settings with improved predictive performance. Methods This is a national cohort study including 22,448 patients who were older than 75 years and visited the hospital for emergency surgery from the cohort of older patients among the retrieved sample from the Korean National Health Insurance Service. The diagnostic and operation codes were one-hot encoded and entered into the predictive model using the extreme gradient boosting (XGBoost) as a machine learning technique. The predictive performance of the model for postoperative 90-day mortality was compared with those of previous frailty evaluation tools such as Operation Frailty Risk Score (OFRS) and Hospital Frailty Risk Score (HFRS) using the receiver operating characteristic curve analysis. Results The predictive performance of the XGBoost, OFRS, and HFRS for postoperative 90-day mortality was 0.840, 0.607, and 0.588 on a c-statistics basis, respectively. Conclusions Using machine learning techniques, XGBoost to predict postoperative 90-day mortality, using diagnostic and operation codes, the prediction performance was improved significantly over the previous risk assessment models such as OFRS and HFRS.

Background and Objective: Lung transplantation is the only life-extending therapy for end-stage pulmonary disease patients, but its risks necessitate an understanding of outcome predictors, with the frailty index and nutritional status being key assessment tools. This study aims to evaluate the relationship between preoperative frailty and nutritional indexes and the postoperative mortality rate in patients receiving lung transplants, and to determine which measure is a more potent predictor of outcomes. Materials and Methods: This study reviewed 185 adults who received lung transplants at a single medical center between January 2013 and May 2023. We primarily focused on postoperative 7-year overall survival. Other outcomes measured were short-term mortalities, acute rejection, kidney complications, infections, and re-transplantation. We compared the predictive abilities of preoperative nutritional and frailty indicators for survival using receiver operating characteristic curve analysis and identified factors affecting survival through regression analyses. Results: There were no significant differences in preoperative nutritional indicators between survivors and non-survivors. However, preoperative frailty indicators did differ significantly between these groups. Multivariate analysis revealed that the American Society of Anesthesiologists Class V, clinical frailty scale, and Charlson Comorbidity Index (CCI) were key predictors of 7-year overall survival. Of these, the CCI had the strongest predictive ability with an area under the curve of 0.755, followed by the modified frailty index at 0.731. Conclusions: Our study indicates that for critically ill patients undergoing lung transplantation, frailty indexes derived from preoperative patient history and functional autonomy are more effective in forecasting postoperative outcomes, including survival, than indexes related to preoperative nutritional status.

This study proposes a rectangular-shaped optical module capable of simultaneously implementing crop cultivation and solar power generation. By employing a cylindrical Fresnel lens (CFL) array plate with a size of 100 × 100 mm2, multiple focal lines are formed, where some of the incident light transmits through the module while the rest is guided laterally through the rectangular lightguide structure. This guided sunlight is then concentrated by a cylindrical compound parabolic concentrator (CCPC) structure, resulting in a 20-fold concentration ratio, onto a 5 × 100 mm2 Si photovoltaic (PV) cell. To experimentally verify feasibility, both the CFL array plate and the lightguide plate were fabricated with three-axis machine tooling equipment and assembled. The power generated experimentally by the 5 × 100 mm2 Si PV cell was 54% of the expected value from the simulation results on the light-concentrated efficiency considering experimental conditions, while the results on experimental transmittance along with rotation angles were very close to the simulation results. However, overall, the tendency of the generated power along the rotation angles is close to the tendency of the light-concentrated efficiency along the rotation angles from the simulation. Additionally, this study dealt with further consideration to enhance light-concentrated efficiency, introducing a means to adjust the trade-off relationship between transmittance and light-concentrated efficiency.

IntroductionIn clinical practice, hemodynamics-based functional indices, such as fractional flow reserve (FFR) and wall shear stress (WSS), are useful in assessing the severity and risk of rupture of atherosclerotic lesions. Computational fluid dynamics (CFD) is widely used to predict these indices noninvasively.MethodIn this study, uncertainty quantification and sensitivity analysis are performed for the computational prediction of WSS and FFR directly from 3D–0D coupled CFD simulations on idealized stenotic coronary models. Five geometric parameters (proximal, mid, and distal lengths of stenosis; reference lumen diameter; and stenosis severity) and two physiological parameters (mean aortic pressure and microcirculation resistance) are considered as uncertain input variables.ResultsWhen employing the true values of stenosis severity and mean aortic pressure, a discernible reduction of 25% and 9.5% in the uncertainty of the computed proximal WSS, respectively. In addition, degree of stenosis, reference lumen diameter, and coronary resistance contributed the uncertainty of computed FFR, accounting for 41.2%, 31.9%, and 24.6%, respectively.ConclusionThis study demonstrated that accurate measurement of the degree of stenosis and mean aortic pressure is crucial for improving the computational prediction of WSS. In contrast, the reference lumen diameter, degree of stenosis, and coronary resistance are the most impactful parameters for FFR.

Abstract Accurate prediction of postoperative mortality is important for not only successful postoperative patient care but also for information-based shared decision-making with patients and efficient allocation of medical resources. This study aimed to create a machine-learning prediction model for 30-day mortality after a non-cardiac surgery that adapts to the manageable amount of clinical information as input features and is validated against multi-centered rather than single-centered data. Data were collected from 454,404 patients over 18 years of age who underwent non-cardiac surgeries from four independent institutions. We performed a retrospective analysis of the retrieved data. Only 12–18 clinical variables were used for model training. Logistic regression, random forest classifier, extreme gradient boosting (XGBoost), and deep neural network methods were applied to compare the prediction performances. To reduce overfitting and create a robust model, bootstrapping and grid search with tenfold cross-validation were performed. The XGBoost method in Seoul National University Hospital (SNUH) data delivers the best performance in terms of the area under receiver operating characteristic curve (AUROC) (0.9376) and the area under the precision-recall curve (0.1593). The predictive performance was the best when the SNUH model was validated with Ewha Womans University Medical Center data (AUROC, 0.941). Preoperative albumin, prothrombin time, and age were the most important features in the model for each hospital. It is possible to create a robust artificial intelligence prediction model applicable to multiple institutions through a light predictive model using only minimal preoperative information that can be automatically extracted from each hospital.

Abstract Some surgical patients require an arterial or central venous catheterization intraoperatively. This decision relied solely on the experience of individual anesthesiologists; however, these decisions are not easy for clinicians who are in an emergency or inexperienced. Therefore, applying recent artificial intelligence techniques to automatically extractable data from electronic medical record (EMR) could create a very clinically useful model in this situation. This study aimed to develop a model that is easy to apply in real clinical settings by implementing a prediction model for the preoperative decision to insert an arterial and central venous catheter and that can be automatically linked to the EMR. We collected and retrospectively analyzed data from 66,522 patients, > 18 years of age, who underwent non-cardiac surgeries from March 2019 to April 2021 at the single tertiary medical center. Data included demographics, pre-operative laboratory tests, surgical information, and catheterization information. When compared with other machine learning methods, the DNN model showed the best predictive performance in terms of the area under receiver operating characteristic curve and area under the precision-recall curve. Operation code information accounted for the largest portion of the prediction. This can be applied to clinical fields using operation code and minimal preoperative clinical information.

The thermal performance of a lithium-ion battery module comprising three cells contained within a casing was investigated at discharge rates of 3C and 5C with three different cooling strategies: forced air, phase-change material (PCM), and a hybrid system using a combination of forced air and the PCM. Three levels of fan speed (5000 rpm; 7000 rpm; and 9000 rpm) for cooling air flow were considered. A numerical simulation of heat transfer was performed using the ANSYS Fluent software. The electrochemical modelling of a battery was developed based on the NTGK approach, and the phase-change phenomenon was treated as an enthesis–porosity problem. The composite PCM, aluminum metal foam embedded in n-octadecane, had better heat dissipation performance than forced air convection. The PCM is significantly more effective at heat dissipation than forced air. Interestingly, when using a hybrid cooling system that combines forced air and a PCM, although it meets the operational requirements for Li-ion batteries in regard to maximum temperature and temperature uniformity at a 3C discharge rate, the airflow appears to have a negligible effect on thermal management and yields an indiscernible change in temperature. This can be attributed to a complex flow pattern that developed in a casing as a result of the suboptimal design of the inlet and outlet. Further studies will be required for the optimal positioning of the inlet and outlet, as well as the effectiveness of combining liquid cooling methods.

Abstract The role of the Epstein-Barr virus (EBV) status in the blood for predicting survival in post-transplantation lymphoproliferative disorders–diffuse large B-cell lymphoma (PTLD–DLBCL) is unknown. We evaluated the prognostic values of pre-treatment EBV-encoded small RNA (EBER) detected with in situ hybridization in tissues and EBV DNA in the whole blood (WB) and plasma in 58 patients with monomorphic PTLD–DLBCL after solid organ transplantation. There were no significant differences in the rates of overall response, complete response, and survival according to EBER EBV and WB EBV status. In contrast, patients with positive plasma EBV DNA had significantly lower rates of overall response (60.0% vs. 94.4%, P = 0.043) and complete response (40.0% vs. 88.9%, P = 0.019) as well as worse progression-free survival (PFS) (P = 0.035) and overall survival (OS) (P = 0.039) compared with patients with negative plasma EBV DNA. In multivariate analysis, plasma EBV DNA positivity was a significantly unfavorable prognostic factor for PFS [hazard ratio (HR) 4.92, 95% confidence interval (CI) 1.22–19.86, P = 0.025] and OS (HR 4.48, 95% CI 1.14–17.63, P = 0.032). Despite small number of 6 patients with plasma EBV positivity, plasma EBV DNA positivity might be more prognostic for survival than EBER or WB EBV DNA positivity in patients with monomorphic PTLD–DLBCL.

Abstract The quantitative flow ratio (QFR) is a novel angiography-based computational method assessing functional ischemia caused by coronary stenosis. This study aimed to evaluate the diagnostic performance of quantitative flow ratio (QFR) in patients with angina and acute myocardial infarction (AMI) and to identify the conditions with low diagnostic performance. We assessed the QFR for 1077 vessels under fractional flow ratio (FFR) evaluation in 915 patients with angina and AMI. The diagnostic accuracies of the QFR for identifying an FFR ≤ 0.8 were 95.98% (95% confidence interval [CI] 94.52 to 97.14%) for the angina group and 92.42% (95% CI 86.51 to 96.31%) for the AMI group. The diagnostic accuracy of the QFR in the borderline FFR zones (> 0.75, ≤ 0.85) (91.23% [95% CI 88.25 to 93.66%]) was significantly lower than that in others (difference: 4.32; p = 0.001). The condition accompanying both AMI and the borderline FFR zone showed the lowest QFR diagnostic accuracy in our data (83.93% [95% CI 71.67 to 92.38]). The diagnostic accuracy was reduced for tandem lesions (p = 0.04, not correcting for multiple testing). Our study found that the QFR method yielded a high overall diagnostic performance in real-world patients. However, low diagnostic accuracy has been observed in borderline FFR zones with AMI, and the hybrid FFR approach needs to be considered.

Abstract Transit-time flow measurement (TTFM) is frequently used to evaluate intraoperative quality control during coronary artery bypass grafting (CABG) and has the ability to assess graft failure intraoperatively. However, perioperative factors affecting TTFM during CABG remain poorly understood. Patients who underwent CABG at a single institution between July 2016 and May 2018 were prospectively evaluated. TTFM and blood viscosity were measured haemodynamically, while mean flow (mL/min), pulsatility index, and diastolic filling were recorded. Arterial blood gas was analysed immediately after left internal mammary artery to left descending artery anastomosis and before sternal closure. Factors associated with TTFM were assessed using multiple linear regression analysis. We evaluated 57 of the 62 patients who underwent CABG during the study period, including 49 who underwent off-pump and 8 who underwent on-pump surgeries. Blood viscosity was not significantly associated with TTFM (p > 0.05). However, TTFM was significantly associated with body mass index, systolic blood pressure, and cardiac index (p

Abstract Segmentation of normal organs is a critical and time-consuming process in radiotherapy. Auto-segmentation of abdominal organs has been made possible by the advent of the convolutional neural network. We utilized the U-Net, a 3D-patch-based convolutional neural network, and added graph-cut algorithm-based post-processing. The inputs were 3D-patch-based CT images consisting of 64 × 64 × 64 voxels designed to produce 3D multi-label semantic images representing the liver, stomach, duodenum, and right/left kidneys. The datasets for training, validating, and testing consisted of 80, 20, and 20 CT simulation scans, respectively. For accuracy assessment, the predicted structures were compared with those produced from the atlas-based method and inter-observer segmentation using the Dice similarity coefficient, Hausdorff distance, and mean surface distance. The efficiency was quantified by measuring the time elapsed for segmentation with or without automation using the U-Net. The U-Net-based auto-segmentation outperformed the atlas-based auto-segmentation in all abdominal structures, and showed comparable results to the inter-observer segmentations especially for liver and kidney. The average segmentation time without automation was 22.6 minutes, which was reduced to 7.1 minutes with automation using the U-Net. Our proposed auto-segmentation framework using the 3D-patch-based U-Net for abdominal multi-organs demonstrated potential clinical usefulness in terms of accuracy and time-efficiency.

The uncertainties of four-dimensional computed tomography (4DCT), also called as residual motion artefacts (RMA), induced from irregular respiratory patterns can degrade the quality of overall radiotherapy. This study aims to quantify and reduce those uncertainties. A comparative study on quantitative indicators for RMA was performed, and based on this, we proposed a new 4DCT sorting method that is applicable without disrupting the current clinical workflow. In addition to the default phase sorting strategy, both additional amplitude information from external surrogates and the quantitative metric for RMA, investigated in this study, were introduced. The comparison of quantitative indicators and the performance of the proposed sorting method were evaluated via 10 cases of breath-hold (BH) CT and 30 cases of 4DCT. It was confirmed that N-RMSD (normalised root-mean-square-deviation) was best matched to the visual standards of our institute's regime, manual sorting method, and could accurately represent RMA. The performance of the proposed method to reduce 4DCT uncertainties was improved by about 18.8% in the averaged value of N-RMSD compared to the default phase sorting method. To the best of our knowledge, this is the first study that evaluates RMA indicators using both BHCT and 4DCT with visual-criteria-based manual sorting and proposes an improved 4DCT sorting strategy based on them.

Carbon monoxide is often produced during the incomplete combustion of volatile organic carbon compounds in industry. In the combustion chamber for oxidizing carbon monoxide emissions, a penta-coaxial port device can be used to improve the process of mixing the fuel and oxidizer. In this study, the conjugate heat transfer analysis was conducted by solving both Reynolds-averaged Navier–Stokes equations with the eddy dissipation model and solid heat conduction equation in the wall using Fluent 2019R2 to simulate the reaction flow of a volatile organic carbon compound burner and heat transfer of the stack insulation layer. The mass fractions of the O2, CO2, and CO gases; the temperature; and the velocity distribution in a combustion chamber were computed to investigate how various design parameters of the combustor, including air inlet size and stack height, and air inflow conditions affected the combustion performance. Results show that the size of the air inlet had only a minor effect on combustion efficiency and that the airstream forced by a fan significantly enhanced the combustion performance. In particular, increasing the height of the stack from 2 m to 4 m greatly increased combustion efficiency from 63% to 94%, with a 50% increase in the incoming air flow rate by natural convection, which demonstrates the importance of stack height in combustor design.

Abstract The upper‐air simulator (UAS) was developed at the Korea Research Institute of Standards and Science to test commercial radiosonde sensors under representative conditions. In this framework, humidity generation is performed through a two‐temperature mode in which the temperatures of the saturator and the test chamber are controlled independently. The operation range of the UAS in terms of the temperature, dew/frost‐point temperature, and relative humidity (RH) is −70 to +20°C, −80 to +20°C, and 5%–100%, respectively. The total combined uncertainty of the UAS humidity generation is within 1.1 %RH at a coverage factor k = 2. As a proof of concept, the calibration of Vaisala RS41 humidity sensors is demonstrated. The maximum difference between the humidity measured using the RS41 sensors and UAS reference humidity is approximately 3 %RH at −67°C, which gradually decreases to approximately 1 %RH as the temperature is raised to 21°C. The repeatability of a single RS41 unit and reproducibility of three different units are 0.5 and 0.9 %RH, respectively, in terms of the standard deviation. The uncertainty of an RS41 humidity sensor is 0.9–1.4 %RH (k = 2) at −67°C. Realizing the calibration of commercial radiosondes by using the UAS can enhance the traceability to the International System of Units and emphasize the role of metrology for meteorology and climate research.

The exploration of superhydrophobic drag reduction has been and continues to be of significant interest to various industries. In the present work, direct numerical simulation (DNS) is utilized to investigate the effect of the parameters on the drag-reducing performance of superhydrophobic surfaces (SHS). Simulations with a friction Reynolds number of 180 were carried out at solid fraction values of ϕs=116,111, and 14, and three distribution shapes: aligned, staggered, and random. The top wall is the smooth one, and the bottom wall is a superhydrophobic surface (SHS). Drag reduction and Reynolds stress profiles are compared for all cases. The turbulent kinetic energy budget, including production, dissipation, and diffusion, is presented with respect to the solid fraction and type of distribution to investigate the drag reduction mechanism. The sizes of the longitudinal vortices and formation of hairpin vortices are investigated through the observation of coherent structures. The simulation of a post model is a useful method to study the drag reduction for different solid fraction values and distribution geometries. Our study demonstrates that the drag reduction could acquire 42% with the solid fraction value ϕs=116 and an aligned distribution shape for post superhydrophobic surface geometry. Our study also showed the relationship of the Reynolds stress component (R11, R22, and R33) to the drag reduction with the differences in the solid fraction values and distribution geometry. In which, the R11 component has the most change between an aligned distribution and a random one. The peak value of R11 tends to shift away from the SHS wall. In addition, the analysis of the TKE budget over the superhydrophobic surface was performed, which can be adopted as a useful resource in turbulence modeling based on RANS methodology.

BackgroundExtranodal natural killer T cell lymphoma (ENKTL) is a rare subtype of non-Hodgkin lymphoma with invariable infection of lymphoma cells with Epstein-Barr virus (EBV), and the presence of EBV-DNA in the blood is a well-known prognosticator. However, there is no consensus on which blood compartment is more optimal for predicting survival outcomes.MethodsWe analyzed 60 patients who were newly diagnosed with ENKTL from a prospectively collected database. EBV-DNA was measured in the whole-blood (WB) and plasma at the time of diagnosis and after treatment completion.ResultsEBV-DNA was detected in pre-treatment WB and plasma in 37 (61.7%) and 23 (38.3%) patients, respectively. The presence of pre-treatment plasma EBV-DNA was significantly associated with advanced stage while presence of WB EBV-DNA did not. Positivity of pre-treatment plasma-EBV, but not WB EBV-DNA, was independently associated with poor PFS (HR, 4.22;95% CI, 1.79–9.97; P=0.001) and OS (HR, 8.38; 95% CI, 3.03–23.19; P

One of the biggest challenges of nuclear industries is to fabricate safe, stable and efficient materials for the storage and transportation of spent nuclear fuels (SNFs), these materials are known as neutron shielding and absorbing materials. Recently, Gd has received much attention as a neutron absorbing material in SNF applications owing to its high neutron absorption capability. Herein, we propose novel FeGd alloys as binary alloys and master alloys for potential materials in nuclear applications. FeGd alloys with 20, 55 and 80 wt% Gd were selected based on the FeGd phase diagram. All fabricated FeGd alloys had higher hardnesses than pure Fe due to the formed FeGd phases, and the Fe-rich phase had a higher hardness than the Gd-rich phase. On the other hand, corrosion resistance of the FeGd alloys decreased as the Gd content increased. Satisfactory Gd-based intermetallic dispersion and modifying effects were obtained by casting Fe and stainless-steel alloy with Fe80Gd. The average intermetallic size in the stainless-steel alloy remarkably decreased with a decrease in the average distance between Gd-based intermetallics. FeGd alloys possess requisite hardness, thermal conductivity, and corrosion resistance as well as dispersion ability of intermetallics; hence, they show potential as promising candidates for SNF applications.

Abstract For the accurate measurement of temperature in the upper air by using radiosondes, one prerequisite is the compensation of solar radiation effects that cause sensor heating. The development at the Korea Research Institute of Standards and Science (KRISS) of an upper air simulator (UAS) that can simulate radiation effects is reported. The UAS can independently control four environmental parameters: irradiance, temperature, pressure and air speed. An entire radiosonde can be installed in the test chamber and the measurement data transmitted remotely via an antenna. Solar irradiance is mimicked by using a solar simulator that irradiates the radiosonde sensor. The temperature of the test chamber is controlled from −70 to 20°C by placing it inside a climatic chamber. The pressure and ventilation speed in the test chamber are modulated using combinations of sonic nozzles, a mass flow controller and a vacuum pump. A ventilation speed of 5 m·s−1, which mimics the speed of ascent of the radiosondes when lifted using a balloon, is achieved at pressures as low as 7 hPa. The capability of controlling the environmental parameters independently and the stability of each parameter are presented. As a proof of concept, the radiation‐induced bias on the temperature sensor of a commercial radiosonde Vaisala RS41 is measured. The effect of each parameter is investigated by varying it while keeping the other parameters fixed. Radiosonde calibration using the UAS at the KRISS will help improve the traceability of upper air measurements to the International System of Units.

Abstract Background The 2-week schedule of hypofractionated radiotherapy as a salvage treatment for hepatocellular carcinoma (HCC) has previously exhibited promising results; this study aimed to assess its long-term clinical outcomes in patients with recurrent HCC ineligible for curative treatments. Methods We retrospectively enrolled 77 patients (84 lesions) with HCC who were treated with hypofractionated radiotherapy between December 2008 and July 2013. Primary inclusion criteria were HCC unsuitable for curative treatments and HCC located within 2 cm of a critical normal organ. We administered 3.5–5 Gy/fraction for 2 weeks, resulting in a total dose of 35–50 Gy. Results The median follow-up period was 33.6 (range, 4.8–78.3) months. The 3- and 5-year overall survival rates were 52.3% and 40.9%, respectively, and local control rates were 79.5% and 72.6% in all treated lesions, respectively. The 5-year local control rate was better in the higher radiation dose group than in the lower radiation dose group (50 Gy: 79.7% vs.

Accurate and timely visualization of apoptotic status in response to radiation is necessary for deciding whether to continue radiation or change to another mode of treatment. This is especially critical in patients with colorectal cancer, which requires a delicate combination of surgery, radiation, and chemotherapy in order to achieve optimal outcome. In this study, we investigated the potential of phosphatidylserine-recognizing peptide 1 (PSP1) as an apoptosis-targeting probe, which identifies phosphatidylserine on cell surfaces. We first screened colon cancer cell lines for their sensitivity to radiation and selected two cell lines: HCT116 and HT29. Cell binding assay using fluorescence-activated cell sorting and optical imaging showed that HCT116 cells had better binding to PSP1 than HT29 cells. Thus, mouse xenograft model using HCT116 cells was generated and was topically irradiated with either single or fractionated dose of radiation followed by systemic administration of PSP1 for subsequent molecular optical imaging. We confirmed that the PSP1 probe was selectively bound to apoptosis-induced tumor in a radiation dose-dependent manner. We also observed that fractionated radiation regimen, which is recently being used in clinical situation, was more effective in inducing tumor apoptosis than corresponding single-dose radiation treatment. We then evaluated the correlation between tumor targeting of PSP1 and suppression effect of tumor development and found that tumor volume and fluorescence intensity were correlated before (correlation coefficient r2 = 0.534) and after (r2 = 0.848) radiation therapy. Our study shows that PSP1 peptide is an efficient index probe for deciding “go or no-go” for radiation therapy in colorectal cancer.

The thermal performance of a large-format (52.3 Ah) Li-ion pouch battery with an n-octadecane PCM was investigated. A simplified 1D model was employed to estimate the transient thermal behavior. Two design parameters, the thickness and the thermal conductivity of the PCM, were considered. A 0.5 mm thick n-octadecane PCM integrated with aluminum foam reduced the battery temperature to 34.3 °C and 50.7 °C at the end stage of discharging under 3C and 5C discharge rates, respectively. The 1D results compared to the 3D results were able to predict the temperature dissipation by the PCM method at the end of discharging. The 1D approach clearly produced reliable results in predicting the thermal behavior of the PCM cooling and was superior in practical applications with its low cost and time consumption. A 3D CFD simulation was able to describe the detailed temperature uniformity in the cell, which is an important factor in the design and evaluation of a battery cooling system.

Abstract Background Treatment of tonsil cancer, a subset of oropahryngeal cancer, varies between surgery and radiotherapy. Well-designed studies in tonsil cancer have been rare and it is still controversial which treatment is optimal. This study aimed to assess the outcome and failure patterns in tonsil cancer patients treated with either approaches. Methods We retrospectively reviewed medical records of 586 patients with tonsil cancer, treated between 1998 and 2010 at 16 hospitals in Korea. Two hundred and one patients received radiotherapy and chemotherapy (CRT), while 385 patients received surgery followed by radiotherapy and/or chemotherapy (SRT). Compared with the SRT group, patients receiving CRT were older, with more advanced T stage and received higher radiotherapy dose given by intensity modulation techniques. Overall survival (OS), disease-free survival (DFS), locoregional recurrence-free survival (LRRFS), distant metastasis-free survival (DMFS), and clinicopathologic factors were analyzed. Results At follow-up, the 5-year OS, DFS, LRRFS and DMFS rates in the CRT group were 82, 78, 89, and 94%, respectively, and in the SRT group were 81, 73, 87, and 89%, respectively. Old age, current smoking, poor performance status, advanced T stage, nodal involvement, and induction chemotherapy were associated with poor OS. Induction chemotherapy had a negative prognostic impact on OS in both treatment groups (p = 0.001 and p = 0.033 in the CRT and SRT groups, respectively). Conclusions In our multicenter, retrospective study of tonsil cancer patients, the combined use of radiotherapy and chemotherapy resulted in comparable oncologic outcome to surgery followed by postoperative radiotherapy, despite higher-risk patients having been treated with the definitive radiotherapy. Induction chemotherapy approaches combined with either surgery or definitive radiotherapy were associated with unfavorable outcomes.

Background Basaloid squamous cell carcinoma (BSCC) is a rare variant of squamous cell carcinoma with distinct pathologic characteristics. The histogenesis of BSCC is not fully understood, and the cancer has been suggested to originate from a totipotent primitive cell in the basal cell layer of the surface epithelium or in the proximal duct of secretory glands. Methods Twenty-six cases of head and neck BSCC from Asan Medical Center, Seoul, Korea, reported during a 14-year-period were subclassified into basal, ductal, and mixed subtypes according to the expression of basal (cytokeratin [CK] 5/6, p63) or ductal markers (CK7, CK8/18). The cases were also subject to immunohistochemical study for CK19, p53, cyclin D1, epidermal growth factor receptor (EGFR), and p16 and to in situ hybridization for human papillomavirus (HPV), and the results were clinico-pathologically compared. Results Mixed subtype (12 cases) was the most common, and these cases showed hypopharyngeal predilection, older age, and higher expression of CK19, p53, and EGFR than other subtypes. The basal subtype (nine cases) showed frequent comedo-necrosis and high expression of cyclin D1. The ductal subtype (five cases) showed the lowest expression of p53, cyclin D1, and EGFR. A small number of p16- and/or HPV-positive cases were not restricted to one subtype. BSCC was the cause of death in 19 patients, and the average follow-up period for all patients was 79.5 months. Overall survival among the three subtypes was not significantly different. Conclusions The results of this study suggest a heterogeneous pathogenesis of head and neck BSCC. Each subtype showed variable histology and immunoprofiles, although the clinical implication of heterogeneity was not determined in this study.

Type I interferon (IFN-I) plays a critical role in the antitumor immune response. In our previous study, we showed that IFN-I-inducible 2′-5′ oligoadenylate synthetase-like 1 (OASL1) negatively regulated IFN-I production upon tumor challenge similar to that of viral infection. Thus, OASL1-deficient (Oasl1−/−) mice were more resistant to implanted tumor growth than wild-type (WT) mice. In this study, we investigated whether targeting or suppressing OASL1 could show synergistic effects on tumor clearance with conventional cancer therapies (such as chemotherapy and radiotherapy) using Oasl1−/− mice and a transplantable lung metastatic tumor cell model. Upon treatment with the anticancer drug cisplatin, we found that Oasl1−/− mice showed enhanced resistance to injected tumors compared to untreated Oasl1−/− mice. Similarly, irradiated Oasl1−/− mice showed better resistance to tumor challenge than untreated Oasl1−/− mice. Additionally, we found that Oasl1−/− mice applied with both types of the cancer therapies contained more cytotoxic effector cells, such as CD8+ T cells and NK cells, and produced more cytotoxic effector cytokine IFN-γ as well as IFN-I in their tumor-containing lungs compared to untreated Oasl1−/− mice. Collectively, these results show that targeting OASL1 together with conventional cancer therapies could be an effective strategy to enhance treatment efficacy.

In this paper, we propose a methodology for calculating the necessary spectrum requirements of aeronautical mobile airport communication system (AeroMACS) to provide various airport communication services. To accurately calculate the spectrum requirement, it is necessary to evaluate the AeroMACS traffic demand of the peak time and statistical data on the packet traffic generated at the airport. Because there is no AeroMACS traffic model and real trace data, we have developed the AeroMACS traffic simulator based on the report of Single European Sky Air Traffic Management Research (SESAR). To calculate the spectrum requirements, the AeroMACS traffic simulator is combined with the methodology of ITU-R M.1768-1. The developed traffic simulator reflects AeroMACS traffic priorities and can generate the required traffic according to its location in the airport. We observed the spectrum requirement by changing the number of sectors and the spectral efficiency. To show the feasibility of our methodology, we applied it to the case of Incheon International Airport in Korea. The simulation results show that the average bandwidth of 0.94 MHz is required in the ground area and 8.59 MHz is required in the entire airport.

Background and Objectives: We examined the association between the baseline perfusion index (PI) and changes in intraoperative body temperature during general anesthesia. The PI reflects the peripheral perfusion state. The PI may be associated with changes in body temperature during general anesthesia because the degree of redistribution of body heat from the central to the peripheral compartment varies depending on the peripheral perfusion state. Materials and Methods: Thirty-eight patients who underwent brain surgery were enrolled in this study. The baseline PI and body temperature of the patients were measured on entering the operating room. Body temperature was recorded every 15 min after induction of anesthesia using an esophageal temperature probe. Univariate and multivariate logistic regression analyses were performed to identify the risk factors for intraoperative hypothermia. Results: Eighteen patients (47 %) developed hypothermia intraoperatively. The baseline PI was significantly lower among patients in the hypothermia group (1.8 ± 0.7) than among those in the normothermia group (3.0 ± 1.2) (P < 0.001). The baseline PI and body temperature were independently associated with intraoperative hypothermia (PI: odds ratio [OR], 0.270; 95% confidence interval [CI], 0.105–0.697; P = 0.007, baseline body temperature: OR, 0.061; 95% CI, 0.005–0.743; P = 0.028). Conclusions: This study showed that low baseline PI was the factor most related to the development of intraoperative hypothermia. Future studies should consider the PI as a predictor of intraoperative hypothermia.

PurposeThis study aimed to evaluate the dosimetric accuracy of respiratory gated volumetric modulated arc therapy (VMAT) for lung stereotactic body radiation therapy (SBRT) under simulation conditions similar to the actual clinical situation using patient-specific lung phantoms and realistic target movements.MethodsSix heterogeneous lung phantoms were fabricated using a 3D-printer (3DISON, ROKIT, Seoul, Korea) to be dosimetrically equivalent to actual target regions of lung SBRT cases treated via gated VMAT. They were designed to move realistically via a motion device (QUASAR, Modus Medical Devices, Canada). Using the lung phantoms and a homogeneous phantom (model 500-3315, Modus Medical Devices), film dosimetry was performed with and without respiratory gating for VMAT delivery (TrueBeam STx; Varian Medical Systems, Palo Alto, CA, USA). The measured results were analyzed with the gamma passing rates (GPRs) of 2%/1 mm criteria, by comparing with the calculated dose via the AXB and AAA algorithms of the Eclipse Treatment Planning System (version 10.0.28; Varian Medical Systems).ResultsGPRs were greater than the acceptance criteria 80% for all film measurements with the stationary and homogeneous phantoms in conventional QAs. Regardless of the heterogeneity of phantoms, there were no significant differences (p > 0.05) in GPRs obtained with and without target motions; the statistical significance (p = 0.031) was presented between both algorithms under the utilization of heterogeneous phantoms.ConclusionsDosimetric verification with heterogeneous patient-specific lung phantoms could be successfully implemented as the evaluation method for gated VMAT delivery. In addition, it could be dosimetrically confirmed that the AXB algorithm improved the dose calculation accuracy under patient-specific simulations using 3D printed lung phantoms.

The cell nucleus is a three-dimensional, dynamic organelle organized into subnuclear compartments such as chromatin and nucleoli. The structure and function of these compartments are maintained by diffusion and interactions between related factors as well as by dynamic and structural changes. Recent studies using fluorescent microscopic techniques suggest that protein factors can access and are freely mobile in heterochromatin and in mitotic chromosomes, despite their densely packed structure. However, the physicochemical properties of the chromosome during cell division are not fully understood. In the present study, characteristic properties such as the refractive index (RI), volume of the mitotic chromosomes, and diffusion coefficient (D) of fluorescent probes inside the chromosome were quantified using an approach combining label-free optical diffraction tomography with complementary confocal laser-scanning microscopy and fluorescence correlation spectroscopy. Variations in these parameters correlated with osmotic conditions, suggesting that changes in RI are consistent with those of the diffusion coefficient for mitotic chromosomes and cytosol. Serial RI tomography images of chromosomes in live cells during mitosis were compared with three-dimensional confocal micrographs to demonstrate that compaction and decompaction of chromosomes induced by osmotic change were characterized by linked changes in chromosome RI, volume, and the mobilities of fluorescent proteins.

PurposeImage-based computational models with fluid-structure interaction (FSI) can be used to perform plaque mechanical analysis in intracranial artery stenosis. We described a process in FSI study applied to symptomatic severe intracranial (M1) stenosis before and after stenting.Materials and MethodsReconstructed 3D angiography in STL format was transferred to Magics for smoothing of vessel surface and trimming of branch vessels and to HyperMesh for generating tetra volume mesh from triangular surface-meshed 3D angiogram. Computational analysis of blood flow in the blood vessels was performed using the commercial finite element software ADINA Ver 8.5. The distribution of wall shear stress (WSS), peak velocity and pressure was analyzed before and after intracranial stenting.ResultsThe wall shear stress distributions from Computational fluid dynamics (CFD) simulation with rigid wall assumption as well as FSI simulation before and after stenting could be compared. The difference of WSS between rigid wall and compliant wall model both in pre- and post-stent case is only minor except at the stenosis region. These WSS values were greatly reduced after stenting to 15~20 Pa at systole and 3~5 Pa at end-diastole in CFD simulation, which are similar in FSI simulations.ConclusionOur study revealed that FSI simulation before and after intracranial stenting was feasible despite of limited vessel wall dimension and could reveal change of WSS as well as flow velocity and wall pressure.

Steady and unsteady natural convection heat transfer in a nanofluid-filled square enclosure cavity with various heat source configurations at the bottom were numerically studied using a characteristic-based split scheme finite element method. A wide range of Rayleigh numbers ( 10 3 ≤ Ra ≤ 10 7 ) , solid volume fractions of nanoparticles ( 0 ≤ ϕ ≤ 0 . 2 ) , the lengths ( 0 . 2 L ≤ B ≤ 0 . 8 L ) , and locations ( 0 . 2 L ≤ D ≤ 0 . 5 L ) of heat sources as well as different types of nanoparticles were considered. Results showed that addition of nanoparticles into the base fluid leads to evident enhancement of heat transfer, particularly at low Rayleigh numbers and that cooling performance is strongly influenced by thermo-physical properties of the nanoparticles. Temporal development of thermal layer in a nanofluid-filled cavity was demonstrated from initial to steady stage through unsteady analysis. We found that the maximum temperature and the average Nusselt number started to oscillate, which is a typical characteristics of high Rayleigh number flow, at higher Rayleigh number in nanofluid than in pure water.

To assess the potential dosimetric benefits associated with the CyberKnife (CK) tumor tracking capability, wherein an extra margin for respiratory tumor motion is not required, when compared to respiratory-gated volumetric-modulated arc therapy (VMAT) for hepatocellular carcinoma (HCC).Twenty-nine HCC patients previously treated with double-arc VMAT were enrolled. In each VMAT plan, the individual internal target volume (ITV) margin around the tumor was determined by measuring its motion over 30-70% of respiratory phases using four-dimensional computed tomography, followed by a 5-mm isotropic margin for the planning target volume (PTV). For each VMAT plan, two CK plans were generated using the original (CKoriginal, ITV included) and modified PTVs (CKmodified, ITV excluded) for comparison. In each case, the CKoriginal and CKmodified plans were compared to the original VMAT plan in terms of the dosimetric parameters including the conformity index (CI), PTV coverage (CO), organs at risk (OAR) doses, and normal liver tissue sparing.The original PTVs with median 24 cc (range, 9-65 cc) were significantly reduced to median 12 cc (range, 5-41 cc) in the CKmodified plans. Statistically significant differences in plan qualities were observed between the VMAT and the CK plans: mean CI, 1.05 in VMAT vs. 1.17 in both CK plans (p < 0.001); and mean CO, 93.0% in VMAT vs. 96.6% in CKoriginal and 96.9% in CKmodified (p < 0.001). The average volume of normal liver tissue receiving > 15 Gy was significantly decreased in the CKmodified plan, as compared to that in the VMAT and CKoriginal plans, by 1.75- and 1.61-fold, respectively.The tumor tracking capability of the CK system can significantly decrease the volume of normal liver tissue receiving > 15 Gy, while maintaining high precision in target localization, conformity, tumor coverage, and dose sparing of the OAR. Therefore, it can be a valuable SBRT option, particularly for HCC patients with poor liver function.

Multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) are an adult-onset progressive neurodegenerative disorder that are known to display diverse clinical features and disease progression. We aim to characterize the clinical features and disease progression in patients with MSA and PSP by using a number of relevant disability milestones in Koreans. Forty-one patients with MSA and 14 patients with PSP had been enrolled. The mean age at onset of MSA-C, MSA-P and PSP was 56.7 ± 7.8, 62.5 ± 8.0, 68.9 ± 6.1 years respectively. The most commonly reported symptom at disease onset is disequilibrium/dizziness in MSA-C, tremor in MSA-P and frequent falling in PSP. The mean duration of reaching milestones after disease onset in MSA-C were as followings: 20.8 (urinary incontinence), 22.9 (frequent falling), 27.8 (wheelchair bound), 31.8 (dysarthria) and 35.8 months (diagnosis). The mean duration of reaching milestones after disease onset were 22.0 (urinary incontinence), 32.6 (frequent falling and diagnosis), 41.2 (dysarthria), 61.4 months (wheelchair bound) in MSA-P and 16.8 (dysarthria), 21.6 (diagnosis), 21.7 (frequent falling), 24.0 months (wheel chair bound) in PSP. In the case of MSA, dizziness may occur for the first time. Thus, when the patient complains of non-specific dizziness, a follow-up examination to distinguish it from MSA can be helpful. There was a trend for patients with MSA-C to reach more disability milestones than in MSA-P and PSP before diagnosis. It may explain why patients with MSA-C are required more detail history taking and neurologic examination at an earlier stage.

Super duplex stainless steels (SDSSs), exhibiting excellent strength and corrosion resistance, serve as the attractive materials in a variety of industries. However, improvements in their ductility and impact-toughness are required in extreme environments. In this study, the effects of gadolinium on the microstructures and Charpy impact properties of super duplex stainless steels were investigated. A base super duplex stainless steel (BDSS) and a gadolinium-added super duplex stainless steel (GDSS) were successfully fabricated using an air casting method. The oxygen content and grain size of SDSSs were found to decrease because of high reactivity of gadolinium with oxygen. Moreover, the average inclusion size and area of GDSS also decreased even with a slight decrease in the average distance between inclusions. Both the BDSS and GDSS exhibited typical Charpy impact transition behavior from −196 °C to 200 °C. Moreover, the GDSS impact energies using Charpy test were higher than those of BDSS over the entire temperature range. Moreover, the ductile-to-brittle transition temperature (DBTT) of SDSSs calculated from the fracture appearance transition temperature (FATT) significantly decreased by over 20 °C with the addition of gadolinium.

A stabilized incompressible smoothed particle hydrodynamics (ISPH) method with the addition of a density invariant relaxation condition in the pressure calculations is applied to simulations of highly nonlinear liquid sloshing problems. By applying the Neumann boundary condition when solving pressure, the performance of the present ISPH method is enhanced significantly. Two large-amplitude free sloshing problems under a resonance sway excitation were carried out in a square and a rectangular tank with filling-depths ratios of 20% and 50% of tank height, respectively, and compared with the available published experimental results. To extend the validation of the method, numerical simulations for sloshing problems with the varying density of a floating body as well as a middle baffle, which also generates strongly nonlinear free surface flow, were conducted. The results showed that the present ISPH method produces smooth pressure distribution and significantly reduces spurious oscillation. The proposed ISPH method was shown to be robust and accurate in long time simulation of highly nonlinear sloshing problems.

To investigate the value of changes in alpha-fetoprotein (AFP) levels for the prediction of radiologic response and survival outcomes in hepatocellular carcinoma (HCC) patients with portal vein tumor thrombus (PVTT) who received combined treatment of 3-dimensional conformal radiotherapy (3D-CRT) and transarterial chemoembolization (TACE).A database of 154 HCC patients with PVTT and elevated AFP levels (>20 ng/mL) treated with 3D-CRT and TACE as an initial treatment between August 2002 and August 2008 was retrospectively reviewed. AFP levels were determined 1 month after radiotherapy, and AFP response was defined as an AFP level reduction of >20% from the initial level. Radiologic response, overall survival (OS), and progression-free survival (PFS) rates were compared between AFP responders and non-responders. Propensity-score based matching analysis was performed to minimize the effect of potential confounding bias.The median follow-up period was 11.1 months (range, 3.1-82.7 months). In the propensity-score matching cohort (92 pairs), a best radiologic response of CR or PR occurred in more AFP responders than AFP non-responders (41.3% vs. 10.9%, p < 0.001). OS and PFS were also longer in AFP responders than in non-responders (median OS 13.2 months vs. 5.6 months, p < 0.001; median PFS 8.7 months vs. 3.5 months, p < 0.001).AFP response is a significant predictive factor for radiologic response. Furthermore, AFP response is significant for OS and PFS outcomes. AFP evaluation after combined radiotherapy and TACE appears to be a useful predictor of clinical outcomes in HCC patients with PVTT.

Genomic changes frequently occur in cancer cells during tumorigenesis from normal cells. Using the Illumina Human NS-12 single-nucleotide polymorphism (SNP) chip to screen for gene copy number changes in primary hepatocellular carcinomas (HCCs), we initially detected amplification of 35 genes from four genomic regions (1q21-41, 6p21.2-24.1, 7p13 and 8q13-23). By integrated screening of these genes for both DNA copy number and gene expression in HCC and colorectal cancer, we selected CENPF (centromere protein F/mitosin), GMNN (geminin, DNA replication inhibitor), CDK13 (cyclin-dependent kinase 13), and FAM82B (family with sequence similarity 82, member B) as common cancer genes. Each gene exhibited an amplification frequency of ~30% (range, 20-50%) in primary HCC (n = 57) and colorectal cancer (n = 12), as well as in a panel of human cancer cell lines (n = 70). Clonogenic and invasion assays of NIH3T3 cells transfected with each of the four amplified genes showed that CENPF, GMNN, and CDK13 were highly oncogenic whereas FAM82B was not. Interestingly, the oncogenic activity of these genes (excluding FAM82B) was highly correlated with gene-copy numbers in tumor samples (correlation coefficient, r>0.423), indicating that amplifications of CENPF, GMNN, and CDK13 genes are tightly linked and coincident in tumors. Furthermore, we confirmed that CDK13 gene copy number was significantly associated with clinical onset age in patients with HCC (P = 0.0037). Taken together, our results suggest that coincidently amplified CDK13, GMNN, and CENPF genes can play a role as common cancer-driver genes in human cancers.