Myocardial infarction (MI) is an acute coronary syndrome that refers to tissue infarction of the myocardium. This study aimed to investigate the effect of long intergenic non‐protein‐coding RNA ...(lincRNA) ATPase plasma membrane Ca2+ transporting 1 antisense RNA 1 (ATP2B1‐AS1) against MI by targeting nuclear factor‐kappa‐B inhibitor alpha (NFKBIA) and mediating the nuclear factor‐kappa‐B (NF‐κB) signalling pathway. An MI mouse model was established and idenepsied by cardiac function evaluation. It was determined that ATP2B1‐AS1 was highly expressed, while NFKBIA was poorly expressed and NF‐κB signalling pathway was activated in MI mice. Cardiomyocytes were extracted from mice and introduced with a series of mouse ATP2B1‐AS1 vector, NFKBIA vector, siRNA‐mouse ATP2B1‐AS1 and siRNA‐NFKBIA. The expression of NF‐κBp50, NF‐κBp65 and IKKβ was determined to idenepsy whether ATP2B1‐AS1 and NFKBIA affect the NF‐κB signalling pathway, the results of which suggested that ATP2B1‐AS1 down‐regulated the expression of NFKBIA and activated the NF‐κB signalling pathway in MI mice. Based on the data from assessment of cell viability, cell cycle, apoptosis and levels of inflammatory cytokines, either silencing of mouse ATP2B1‐AS1 or overexpression of NFKBIA was suggested to result in reduced cardiomyocyte apoptosis and expression of inflammatory cytokines, as well as enhanced cardiomyocyte viability. Our study provided evidence that mouse ATP2B1‐AS1 silencing may have the potency to protect against MI in mice through inhibiting cardiomyocyte apoptosis and inflammation, highlighting a great promise as a novel therapeutic target for MI.
A nanocomposite consisting of gold nanoparticles (AuNP), reduced graphene oxide (rGO) and multi-walled carbon nanotubes (MWCNTs) was synthesized using a co-reduction strategy in ethylene glycol using ...sodium citrate as the reducing agent. The nanocomposite was successfully characterized using X-ray powder diffraction, scanning electron microscopy and electrochemical methods. The material was deposited on a glassy carbon electrode and then was found to have high electrocatalytic capability for the electrode process of nitrite. This is attributed to the synergic actions of rGO, MWCNTs and AuNPs. Based on this, an amperometric nitrite sensing scheme was worked out that had attractive features: (a) a wide linear range that extends from 50 nM to 2.2 mM, (b) a working potential of 0.80 V (vs.SCE) at pH 5.0, (c) a 14 nM detection limit (at an SNR of 3), and (d) an electrochemical sensitivity of 1201 μA·mM
−1
·cm
−2
. The sensor was successfully applied to the determination of nitrite in the local river water.
Graphical abstract
Schematic presentation of the fabrication of the AuNPs-rGO-MWCNTs composite modified electrode and its application for the nitrite electrochemical sensing.
We propose zero-inflated statistical models based on the generalized Hermite distribution for simultaneously modelling of excess zeros, over/underdispersion, and multimodality. These new models are ...parsimonious yet remarkably flexible allowing the covariates to be introduced directly through the mean, dispersion, and zero-inflated parameters. To accommodate the interval inequality constraint for the dispersion parameter, we present a new link function for the covariate-dependent dispersion regression model. We derive score tests for zero inflation in both covariate-free and covariate-dependent models. Both the score test and the likelihood-ratio test are conducted to examine the validity of zero inflation. The score test provides a useful tool when computing the likelihood-ratio statistic proves to be difficult. We analyse several hotel booking cancellation datasets extracted from two recently published real datasets from a resort hotel and a city hotel. These extracted cancellation datasets reveal complex features of excess zeros, over/underdispersion, and multimodality simultaneously making them difficult to analyse with existing approaches. The application of the proposed methods to the cancellation datasets illustrates the usefulness and flexibility of the models.
Pneumatic artificial muscles can move continuously under the power support of air pumps, and their flexibility also provides the possibility for applications in complex environments. However, in ...order to achieve operation in confined spaces, the miniaturization of artificial muscles becomes crucial. Since external attachment devices greatly hinder the miniaturization and use of artificial muscles, we propose a light-driven approach to get rid of these limitations. In this study, we report a miniaturized fiber-reinforced artificial muscle based on mold editing, capable of bending and axial elongation using gas-liquid conversion in visible light. The minimum volume of the artificial muscle prepared using this method was 15.7 mm
(d = 2 mm, l = 5 mm), which was smaller than those of other fiber-reinforced pneumatic actuators. This research can promote the development of non-tethered pneumatic actuators for rescue and exploration, and create the possibility of miniaturization of actuators.
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•A cGAN model is proposed to make multiaxial fatigue cyclic data augmentation.•Fourier transformation is integrated into the cGAN to preprocess fatigue data.•With data augmentation, ...the performance of machine learning models is improved by 35%-91%.•Partial Least Square is adopted to extract the features in prediction processing.
To meet the requirement of large experimental data for machine learning (ML) methods on multiaxial life prediction, a cyclical Generative Adversarial Network (named cGAN) integrating Fourier transformation and other semi-empirical equations, was proposed to augment data following physical knowledge. Two samples of each loading path can be augmented into hundreds of good quality samples. Consequently, the accuracy of ML methods for multiaxial fatigue life of 316L stainless steel can been improved by 35%-91%. The new method can definitely balance time cost of bigger sample size and prediction accuracy well.
Many applications in real-time signal, image, and video processing require automatic algorithms for rapid characterizations of signals and images through fast estimation of their underlying ...statistical distributions. We present fast and globally convergent algorithms for estimating the three-parameter generalized gamma distribution (G Gamma D). The proposed method is based on novel scale-independent shape estimation (SISE) equations. We show that the SISE equations have a unique global root in their semi-infinite domains and the probability that the sample SISE equations have a unique global root tends to one. The consistency of the global root, its scale, and index shape estimators is obtained. Furthermore, we establish that, with probability tending to one, Newton-Raphson (NR) algorithms for solving the sample SISE equations converge globally to the unique root from any initial value in its given domain. In contrast to existing methods, another remarkable novelty is that the sample SISE equations are completely independent of gamma and polygamma functions and involve only elementary mathematical operations, making the algorithms well suited for real-time both hardware and software implementations. The SISE estimators also allow the maximum likelihood (ML) ratio procedure to be carried out for testing the generalized Gaussian distribution (GGD) versus the G Gamma D. Finally, the fast global convergence and accuracy of our algorithms for finite samples are demonstrated by both simulation studies and real image analysis.
This paper presents a method for endoscope's autonomous positioning by a robotic endoscope holder for minimally invasive surgery. The method improves human-robot cooperation in robot-assisted surgery ...by allowing the endoscope holder to acknowledge the surgeon's view projection and navigate the camera without manual control. The real-time prediction of next desired camera location is estimated using segmented instrument's tip locations from endoscope video and surgeon's attention focus given by tracked virtual reality headset. To tackle the issue of real-time surgical instrument segmentation for more precise instrument tip localization, we propose the YOLOv3 and ResNet Combined Neural Network. The method showed an 86.6% IoU across MICCAI'17 Endovis datasets with 30 frames per second processing speed. The proposed pipeline was implemented in ROS on Ubuntu with visualization running under Windows operating system in Unity3D. The simulation demonstrates the robotic arm, endoscope, and surgical environment visualized in 3D in the virtual reality headset to provide a stable view of the endoscope and improve the surgeon's perception of the operating environment.
To improve the modeling accuracy and simulation efficiency of probabilistic creep-fatigue life evaluation, a decomposed collaborative time-variant Kriging surrogate model (DCTKS) is proposed by ...absorbing the strengths of extremum selection technique and Kriging model into decomposed collaborative strategy. The probabilistic creep-fatigue life evaluation of a typical turbine disk is considered as one case to evaluate the proposed DCTKS method with respect to fluctuation of transient loads, nonlinearity of material properties and variability of models. In respect of this study, we find that the probabilistic creep-fatigue life of the turbine disk under the reliability degree of 0.998 7 is 946 cycles, and the transient fluctuating loads (body temperature and rotor speed) are the main factors of influencing creep-fatigue life. Through the comparison of methods (DCTKS, Monte Carlo simulation method, Kriging surrogate method, decomposed collaborative response surface method), the proposed DCTKS is demonstrated to possess the computational advantages in efficiency and accuracy for probabilistic creep-fatigue life evaluation.
Introduction. Reactive oxygen species (ROS) induced by extracellular cytokines trigger the expression of inflammatory mediators in osteoarthritis (OA) chondrocyte. Peroxisome proliferator-activated ...receptor gamma (PPARγ) exerts an anti-inflammatory effect. The aim of this study was to elucidate the role of PPARγ in interleukin-1β- (IL-1β-) induced cyclooxygenase-2 (COX-2) and prostaglandin E2 (PGE2) expression through ROS generation in OA chondrocytes. Methods. IL-1β-induced ROS generation and chondrocyte apoptosis were determined by flow cytometry. Contents of NADPH oxidase (NOX), caspase-3, and caspase-9 were evaluated by biochemical detection. The involvement of NOX2 and mitogen-activated protein kinases (MAPKs) in IL-1β-induced COX-2 and PGE2 expression was investigated using pharmacologic inhibitors and further analyzed by western blotting. Activation of PPARγ was performed by using a pharmacologic agonist and was analyzed by western blotting. Results. IL-1β-induced COX-2 and PGE2 expression was mediated through NOX2 activation/ROS production, which could be attenuated by N-acetylcysteine (NAC; a scavenger of ROS), GW1929 (PPARγ agonist), DPI (diphenyleneiodonium chloride, NOX2 inhibitor), SB203580 (p38MAPK inhibitor), PD98059 (extracellular signal-regulated kinase, ERK inhibitor), and SP600125 (c-Jun N-terminal kinase, JNK inhibitor). ROS activated p38MAPK to enter the nucleus, which was attenuated by PPARγ. Conclusion. In OA chondrocytes, IL-1β induced COX-2 and PGE2 expression via activation of NOX2, which led to ROS production and MAPK activation. The activation of PPARγ exerted protective roles in the pathogenesis of OA.
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