Men with castration-resistant prostate cancer (CRPC) face poor prognosis and increased risk of treatment-incurred adverse effects resulting in one of the highest mortalities among patient population globally. Immune cells act as double-edged sword depending on the tumor microenvironment, which leads to increased infiltration of pro-tumor (M2) macrophages. Development of new immunomodulatory therapeutic agents capable of targeting the tumor microenvironment, and hence orchestrating the differentiation of pro-tumor M2 macrophages to anti-tumor M1, would substantially improve treatment outcomes of CRPC patients. We report, herein, Mangiferin functionalized gold nanoparticles (MGF-AuNPs) and its immunomodulatory characteristics in treating prostate cancer. We provide evidence of immunomodulatory intervention of MGF-AuNPs in prostate cancers through observations of enhanced levels of anti-tumor cytokines (IL-12 and TNF-α) with concomitant reductions in the levels of pro-tumor cytokines (IL-10 and IL-6). In the treated groups, IL-12 was elevated to ten-fold while TNF-α was elevated to about fifty-fold; while IL-10 and IL-6 were reduced by two-fold. Ability of MGF-AuNPs to target splenic macrophages is invoked via targeting of NF-kB signaling pathway. Finally, therapeutic efficacy of MGF-AuNPs, in treating prostate cancer in vivo in tumor bearing mice, is described taking into consideration various immunomodulatory interventions triggered by this green nanotechnology-based nanomedicine agent.
In this paper, wavelets were used to study the multivariate fractional Brownian motion through the deviations of the random process to find an efficient estimation of Hurst exponent. The results of simulations experiments were shown that the performance of the proposed estimator was efficient. The estimation process was made by taking advantage of the detail coefficients stationarity from the wavelet transform, as the variance of this coefficient showed the power-low behavior. We use two wavelet filters (Haar and db5) to manage minimizing the mean square error of the model.
Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and aft
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreThis paper proposes a novel finite-time generalized proportional integral observer (FTGPIO) based a sliding mode control (SMC) scheme for the tracking control problem of high order uncertain systems subject to fast time-varying disturbances. For this purpose, the construction of the controller consists of two consecutive steps. First, the novel FTGPIO is designed to observe unmeasurable plant dynamics states and disturbance with its higher time derivatives in finite time rather than infinite time as in the standard GPIO. In the FTGPO estimator, the finite time convergence rate of estimations is well achieved, whereas the convergence rate of estimations by classical GPIO is asymptotic and slow. Secondly, on the basis of the finite and fast e
... Show MoreLower extremity exoskeletons can assist with performing particular functions such as gait assistance, and physical therapy support for subjects who have lost the ability to walk. This paper presents the analysis and evaluation of lightweight and adjustable two degrees of freedom, quasi-passive lower limb device to improve gait rehabilitation. The exoskeleton consists of a high torque DC motor mounted on a metal plate above the hip joint, and a link that transmits assistance torque from the motor to the thigh. The knee joint is passively actuated by spring installed parallel with the joint. The action of the passive component (spring) is combined with mechanical output of the motor to provide a good control on the designed exoskeleton whi
... Show MoreFriction stir spot welding (FSSW) is a relatively new welding process that may have significant advantages compared to the fusion processes as follows joining of conventionally non-fusion weldable alloys, reduced distortion and improved mechanical properties of weldable alloys joints due to the pure solidstate joining of metals. In this paper, a three-dimensional model based on finite element analysis is used to study the thermal history in the spot-welding of aluminum alloy 2024. The model take place the thermomechanical property on the process of the welded metals. The thermal history and the evolution results with numerical model at the measured point in the friction stirred spot weld have a good matching, then the prediction of the t
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