Some researchers have studied about early prediction and diagnosis of major adverse cardiovascular events (MACE), but their accuracies were not high. Therefore, this paper proposes a soft voting ...ensemble classifier (SVE) using machine learning (ML) algorithms. We used the Korea Acute Myocardial Infarction Registry dataset and selected 11,189 subjects among 13,104 with the 2-year follow-up. It was subdivided into two groups (ST-segment elevation myocardial infarction (STEMI), non ST-segment elevation myocardial infarction NSTEMI), and then subdivided into training (70%) and test dataset (30%). Third, we selected the ranges of hyper-parameters to find the best prediction model from random forest (RF), extra tree (ET), gradient boosting machine (GBM), and SVE. We generated each ML-based model with the best hyper-parameters, evaluated by 5-fold stratified cross-validation, and then verified by test dataset. Lastly, we compared the performance in the area under the ROC curve (AUC), accuracy, precision, recall, and F-score. The accuracies for RF, ET, GBM, and SVE were (88.85%, 88.94%, 87.84%, 90.93%) for complete dataset, (84.81%, 85.00%, 83.70%, 89.07%) STEMI, (88.81%, 88.05%, 91.23%, 91.38%) NSTEMI. The AUC values in RF were (98.96%, 98.15%, 98.81%), ET (99.54%, 99.02%, 99.00%), GBM (98.92%, 99.33%, 99.41%), and SVE (99.61%, 99.49%, 99.42%) for complete dataset, STEMI, and NSTEMI, respectively. Consequently, the accuracy and AUC in SVE outperformed other ML models. The performance of our SVE was significantly higher than other machine learning models (RF, ET, GBM) and its major prognostic factors were different. This paper will lead to the development of early risk prediction and diagnosis tool of MACE in ACS patients.
Two-dimensional (2D) molybdenum disulfide (MoS2) has been taken much attention for various applications, such as catalyst, energy storage, and electronics. However, the lack of effective exfoliation ...methods for obtaining 2D materials in a large quantity has been one of the technical barriers for the real applications. We report a facile liquid-phase exfoliation method to improve the exfoliation efficiency for single-layer MoS2 sheets in 1-methyl-2-pyrrolidinone (NMP) with a sodium hydroxide (NaOH) assistant. The concentration of the exfoliated MoS2 nanosheets was greatly improved compared to that achieved with conventional liquid-phase exfoliation methods using NMP solvent. We demonstrate stable operation of sodium-ion battery by using the exfoliated MoS2 and MoS2-rGO composite as anode materials.
Abstract Objective Stent graft-induced new entry (SINE) has been increasingly observed after thoracic endovascular aortic repair (TEVAR) for Stanford type B aortic dissection. SINE is often life ...threatening, and reintervention is required. This study investigated risk factors for SINE after TEVAR. Methods From July 2001 to June 2013, we retrospectively analyzed data from 79 patients who underwent TEVAR for Stanford type B aortic dissection. TEVAR was performed in 17 patients ≤2 weeks (acute) after the diagnosis of aortic dissection and in the remaining 62 patients >2 weeks (chronic) after diagnosis. Forty-two of the patients underwent TEVAR with modified stent graft with an “inwardly bent” margin, and the remaining 37 underwent TEVAR with a conventional stent graft. The maximal diameter, minimal diameter, mean diameter, circumference, and area of the true lumen were analyzed. Taper ratio and oversizing ratio were evaluated and compared between the SINE and non-SINE groups, and cutoff values of taper ratio and oversizing ratio for prediction of SINE were determined using receiver-operating characteristic curve analysis. The cumulative incidence of SINE was estimated with the Kaplan-Meier method. The multivariate Cox proportional hazards model was used to identify independent predictive variables for SINE. Results SINE occurred in 21 patients (26.5%) and occurred more frequently in patients with chronic dissection than in those with acute dissection (32.3% vs 5.9%; P = .032). The Kaplan-Meier curves were significantly different ( P = .016) between these groups. The incidence of SINE events was not significantly different between the modified stent group and nonmodified stent group (23.8% vs 36.0%; P = .284). The taper ratio and oversizing ratio by maximal diameter, mean diameter, circumference, and area were significantly higher in the SINE group than in the non-SINE group, and Kaplan-Meier curves were significantly different between groups above and below optimal cutoff value ( P < .0005 to .003). According to multivariate analysis, the hazard ratios of chronic aortic dissection were 6.30 (95% confidence interval, 0.83-47.74; P = .075) to 7.80 (95% confidence interval, 1.03-59.07; P = .047). The taper ratio and oversizing ratio calculated by maximal diameter, mean diameter, circumference, and area were independent predictors of the development of SINE. Conclusions Distal oversizing of the stent graft was an independent predictor of the development of SINE. Appropriate size selection of stent graft without distal oversizing might reduce the risk of late SINE events.
Silicon carbide (SiC) fibers can act not only as a load-bearing component, but also as a piezoresistive and microwave lossy material when embedded in fiber-reinforced polymer composites. By ...leveraging these multifunctional characteristics, we propose simultaneous self-sensing and microwave-absorbing composite structures based on embedded SiC fiber networks. A SiC fiber network consists of SiC fiber yarns embedded in each interlaminar of the host composite at regular intervals. The SiC fiber yarns, which do not come into contact with other SiC fiber yarns, act as independent sensing elements using their piezoresistivity. By positioning the SiC fiber yarns at regular intervals within the wavelength of the targeted microwave-absorption bandwidth, the SiC fiber network functions as a microwave lossy material. In this study, specific focus has been placed on designing a multi-functional composite that senses external impacts and also absorbs microwaves in the X-band (8.2–12.4 GHz). The simultaneous self-sensing and microwave-absorbing performance of the fabricated SiC-embedded composite was experimentally verified through microwave return loss measurements and dynamic signal acquisition tests. The proposed SiC fiber network-embedded composite structure has great potential for use in future aerospace structures.
High predation risk and food depletion lead to sexual reproduction in cyclically parthenogenetic Daphnia. Mating, the core of sexual reproduction, also occurs under these conditions. Assessment of ...the environmental conditions and alteration of mating efforts may aid in determining the success of sexual reproduction. Here, we evaluated the impacts of predation risk, food quantity, and reproductive phase of females on the mating behavior of Daphnia obtusa males including contact frequency and duration using video analysis. Mating-related behavior involved male-female contact (mating) as well as male-male contact (fighting). Mating frequency increased while unnecessary fighting decreased in the presence of predation risk. In addition, low food concentration reduced fighting between males. Males attempted to attach to sexual females more than asexual females, and fighting occurred more frequently in the presence of sexual females. Duration of mating was relatively long; however, males separated shortly after contact in terms of fighting behavior. Thus, assessment of environmental factors and primary sexing of mates were performed before actual contact, possibly mechanically, and precise sex discrimination was conducted after contact. These results suggest that mating in Daphnia is not a random process but rather a balance between predation risk and energetic cost that results in changes in mating and fighting strategies.
This study aimed to assess the relationship between the histopathological and textural features of perigastric adipose tissue (AT) on 2-deoxy-2-18Ffluoro-D-glucose (18FFDG) positron emission ...tomography/computed tomography (PET/CT) and to evaluate the prognostic significance of perigastric AT textural features in predicting recurrence-free survival (RFS) in patients with gastric cancer. Sixty-nine patients with gastric cancer who underwent staging 18FFDG PET/CT and subsequent curative surgery were retrospectively reviewed. Textural features of perigastric AT were extracted from PET images. On histopathological analysis, CD4, CD8, and CD163 cell infiltration and matrix metalloproteinase-11 and interleukin-6 (IL-6) expression in perigastric AT were graded. The degree of CD163 cell infiltration in perigastric AT was significantly correlated with the mean standardized uptake value (SUV), SUV histogram entropy, grey-level co-occurrence matrix (GLCM) energy, and GLCM entropy of perigastric AT. The degree of IL-6 expression in the perigastric AT was significantly correlated with the mean and median SUVs of perigastric AT. In multivariate survival analysis, GLCM entropy, GLCM dissimilarity, and GLCM homogeneity of perigastric AT were significant predictors of RFS. The textural features of perigastric AT on 18FFDG PET/CT significantly correlated with inflammatory response in perigastric AT and were significant prognostic factors for predicting RFS in patients with gastric cancer.
Purpose
Modern science has given much attention to the treatment of obesity by activating brown adipose tissue (BAT) and browning of white adipose tissue (WAT). Recent studies have identified ...theobromine, a derivative of cocoa, as a potent natural component actively browning white fat cells. Here, we aimed to deduce the anti-obesity effect of theobromine involving phosphodiesterase (PDE) dependent-regulatory pathway in obese animal models.
Methods
For examining activity of theobromine, C57BL/6 mice were fed with high fat diet and treated with theobromine to determine the expression levels of protein markers by immunoblot analysis and gene targets by quantitative real-time PCR. Other methods used include histopathological studies, immunofluorescence and molecular docking approaches.
Results
Theobromine alleviated diet-induced obesity in mice by browning of iWAT and activating BAT. Further, theobromine actively interacted with PDE4D and inhibited its activity in adipose tissues and cells potentiating energy expenditure. Moreover, the regulatory action of theobromine via inhibition of PDE4D was mediated by β3-AR signaling pathway.
Conclusion
Altogether, the current results signifies critical role of theobromine in reducing obesity by regulation of lipid metabolism through inhibition of PDE4, indicating its potential as a major therapeutic medicinal compound.
The nonsteroidal anti-inflammatory drug (NSAID) ketoprofen is commonly used as a pain reliever, but its role in mediating the energy metabolism in lipids is unclear. This paper reports for the first ...time the critical role of ketoprofen in ameliorating white fat browning and alleviating diet-induced obesity. The effects of ketoprofen were evaluated using C57BL/6 mice fed a high fat diet and the expression levels of the target genes and proteins in the lipid metabolisms were determined by quantitative real-time PCR, immunoblot analysis, histopathology study, immunofluorescence, and molecular docking techniques. Ketoprofen induced browning in cultured 3T3-L1 white adipocytes and inguinal white adipose tissue by increasing the expression of core fat browning marker proteins as well as beige-specific genes through COX-2 activation. Ketoprofen also led to the robust activation of brown adipocytes and enhanced brown fat adipogenesis. In addition, ketoprofen elevated lipolysis, thereby increasing mitochondrial biogenesis resulting in higher fat oxidation. Furthermore, the molecular docking and mechanistic study demonstrated the recruitment of beige fat by ketoprofen via mTORC1-p38-mediated activation of the COX-2 pathway. Overall, these results indicate the unique role of ketoprofen in body weight reduction by enhancing thermogenesis, suggesting its therapeutic potential in the treatment of obesity.
α‐In2Se3 semiconductor crystals realize artificial synapses by tuning in‐plane and out‐of‐plane ferroelectricity with diverse avenues of electrical and optical pulses. While the electrically induced ...ferroelectricity of α‐In2Se3 shows synaptic memory operation, the optically assisted synaptic plasticity in α‐In2Se3 has also been preferred for polarization flipping enhancement. Here, the synaptic memory behavior of α‐In2Se3 is demonstrated by applying electrical gate voltages under white light. As a result, the induced internal electric field is identified at a polarization flipped conductance channel in α‐In2Se3/hexagonal boron nitride (hBN) heterostructure ferroelectric field effect transistors (FeFETs) under white light and discuss the contribution of this built‐in electric field on synapse characterization. The biased dipoles in α‐In2Se3 toward potentiation polarization direction by an enhanced internal built‐in electric field under illumination of white light lead to improvement of linearity for long‐term depression curves with proper electric spikes. Consequently, upon applying appropriate electric spikes to α‐In2Se3/hBN FeFETs with illuminating white light, the recognition accuracy values significantly through the artificial learning simulation is elevated for discriminating hand‐written digit number images.
White‐light illumination into α‐In2Se3‐based ferroelectric memories generates the enhanced downward built‐in electric field (Fbi) within the α‐In2Se3 channel due to the upward shift of α‐In2Se3 Fermi level. This intensification of downward Fbi, causing preferential downward reorientation of α‐In2Se3 ferroelectric domains, improved the linearity of long‐term‐depression characteristics. White‐light‐assisted artificial neural networks have significantly improved the recognition accuracy for hand‐written digit numbers.
Cardiovascular disease is the leading cause of death worldwide so, early prediction and diagnosis of cardiovascular disease is essential for patients affected by this fatal disease. The goal of this ...article is to propose a machine learning–based 1-year mortality prediction model after discharge in clinical patients with acute coronary syndrome. We used the Korea Acute Myocardial Infarction Registry data set, a cardiovascular disease database registered in 52 hospitals in Korea for 1 November 2005–30 January 2008 and selected 10,813 subjects with 1-year follow-up traceability. The ranges of hyperparameters to find the best prediction model were selected from four different machine learning models. Then, we generated each machine learning–based mortality prediction model with hyperparameters completed the range fitness via grid search using training data and was evaluated by fourfold stratified cross-validation. The best prediction model with the highest performance was found, and its hyperparameters were extracted. Finally, we compared the performance of machine learning–based mortality prediction models with GRACE in area under the receiver operating characteristic curve, precision, recall, accuracy, and F-score. The area under the receiver operating characteristic curve in applied machine learning algorithms was averagely improved up to 0.08 than in GRACE, and their major prognostic factors were different. This implementation would be beneficial for prediction and early detection of major adverse cardiovascular events in acute coronary syndrome patients.
PDF
