Can immunotherapy reinforce chemotherapy efficacy? a new perspective on colorectal cancer treatment

As one of the main threats to human life (the fourth most dangerous and prevalent cancer), colorectal cancer affects many people yearly, decreases patients’ quality of life, and causes irreparable financial and social damages. In addition, this type of cancer can metastasize and involve the liver in advanced stages. However, current treatments can’t completely eradicate this disease. Chemotherapy and subsequent surgery can be mentioned among the current main treatments for this disease. Chemotherapy has many side effects, and regarding the treatment of this type of tumor, chemotherapy can lead to liver damage, such as steatohepatitis, steatosis, and sinus damage. These damages can eventually lead to liver failure and loss of its functions. Therefore, it seems that other treatments can be used in addition to chemotherapy to increase its efficiency and reduce its side effects. Biological therapies and immunotherapy are one of the leading suggestions for combined treatment. Antibodies (immune checkpoint blockers) and cell therapy (DC and CAR-T cells) are among the immune system-based treatments used to treat tumors. Immunotherapy targets various aspects of the tumor that may lead to 1) the recruitment of immune cells, 2) increasing the immunogenicity of tumor cells, and 3) leading to the elimination of inhibitory mechanisms established by the tumor. Therefore, immunotherapy can be used as a complementary treatment along with chemotherapy. This review will discuss different chemotherapy and immunotherapy methods for colorectal cancer. Then we will talk about the studies that have dealt with combined treatment

Cholesterol in colorectal cancer: an essential but tumorigenic precursor?

Colorectal cancer (CRC) is one of the most lethal human malignancies, and with the growth of societies and lifestyle changes, the rate of people suffering from it increases yearly. Important factors such as genetics, family history, nutrition, lifestyle, smoking, and alcohol can play a significant role in increasing susceptibility to this cancer. On the other hand, the metabolism of several macromolecules is also involved in the fate of tumors and immune cells. The evidence discloses that cholesterol and its metabolism can play a role in the pathogenesis of several cancers because there appears to be an association between cholesterol levels and CRC, and cholesterol-lowering drugs may reduce the risk. Furthermore, changes or mutations of some involved genes in cholesterol metabolism, such as CYP7A1 as well as signaling pathways, such as mitogen-activated protein kinase (MAPK), can play a role in CRC pathogenesis. This review summarized and discussed the role of cholesterol in the pathogenesis of CRC as well as available cholesterol-related therapeutic approaches in CRC

Direction of Arrival Estimation and Sensor Array Error Calibration Based on Blind Signal Separation

We consider estimating the direction of arrival (DOA) in the presence of sensor array error. In the proposed method, a blind signal separation method, the Joint Approximation and Diagonalization of Eigenmatrices (JADE) algorithm, is implemented to separate the signal vector and the mixing matrix consisting of the array manifold matrix and the sensor array error matrix. Based on a new mixing matrix and the reconstruction of the array output vector of each individual signal, we propose a novel DOA estimation method and sensor array error calibration procedure. This method is independent of array phase errors and performs well against difference of SNR of signals. Numerical simulations verify the effectiveness of the proposed method

Q-Markov Cover identification and integrated MCA-OVC controller design for flexible structures

The main objective of this research is to develop methods for identification and control of flexible structures. The specific problems this research focused upon are the following, (1) applying the Q-Markov Cover theory to the identification of flexible structures, (2) developing an integrated model reduction and controller design method, (3) developing a controller design method to accommodate finite wordlength errors for flexible structure controls at fast sampling rates. This research takes a linear algebra approach to simplify the existing solutions of the Q-Markov Cover problem. The new solutions are used to develop Q-Markov Cover identification algorithm and to analyse its identification errors due to measurement noises. Under the assumption that the measurement noises have rational spectrums, analytic formulas of the errors are obtained. These formulas reveal that, under certain conditions, some system parameters (eigenvalues for example) can be correctly identified. Based upon this analytical result, a new algorithm which is capable of identifying some system parameters correctly is developed. The MCA model reduction and OVC controller design algorithms are integrated into an iterative method for low order high performance controller designs based upon high order models. The resulting integrated MCA-OVC controller design method is a heuristic method which probes the stability boundaries of the closed loop systems formed by the high order model and low order controllers and searches for the maximum accuracy of the low order controllers. This research studies the effects of the finite wordlength errors on the LQG controllers. Under the assumptions that the controls are computed by fix point computations and that the external excitations are white, the lower and upper bounds of the influences of the finite wordlength errors on control systems are analysed. An optimal control design method which is capable of accommodating the finite wordlength errors is developed. NASA\u27s ACES structure is a ground test facility for flexible space structure controls. The effectiveness of the Q-Markov Cover identification and the integrated MCA-OVC controller design algorithms are successfully demonstrated by the identification and control experiments on the ACES structure