A new method for image classification and image retrieval using convolutional neural networks

This article proposes a new method for image classification and image retrieval. The advantages of the proposed method are its high performance and requiring less memory compared to other methods. In order to extract image features, a Convolutional Neural Network (CNN), AlexNet, has been used. For image classification, we design a committee of four classifiers trained on graphics cards, narrowing the gap to human performance. For image retrieval, the similarity between extracted features from dataset images and features of the query image is calculated and the final results are visualized. Comprehensive experiments on Corel-1k, Corel-10k, Caltech-101 object and Scene-67 datasets have been investigated to find optimal parameters of the proposed method. The experiments demonstrate the high performance of the proposed method in comparison with the state-of-the-art in the field

Innate immune response in systemic autoimmune diseases: a potential target of therapy

Innate immunity refers to defense mechanisms that are always present, ready to combat microbes and other offending agents. Innate immunity acts as a first-line defense and activates the conventional immune responses; however, it has been speculated that the importance of innate immunity in initiation and development of some disorders is more than just the �first line of defense�. Autoimmune diseases, caused by immune system overactivation, are among the most challenging scientific and clinical problems, and there is still much to be learned about their pathogenesis. We aimed to provide a comprehensive overview of available documents about the role of innate immunity in systemic autoimmune diseases including rheumatoid arthritis, systemic lupus erythematosus, Sjögren�s syndrome, polymyositis, and systemic sclerosis. This study highlights the innate immunity pathways or molecules that are under investigation for therapy of these diseases. © 2020, Springer Nature Switzerland AG

GPCR-CARMA3-NF-kappaB Signaling Axis: A Novel Drug Target for Cancer Therapy

G protein-coupled receptors (GPCRs) play pivotal roles in regulating various cellular functions. It has been well established that GPCR activates NF-κB and aberrant regulation of GPCR-NF-κB signaling axis leads to cancers. However, how GPCRs induce NF-κB activation remains largely elusive. Recently, it has been shown that a novel scaffold protein, CARMA3, is indispensable in GPCR-induced NF-κB activation. In CARMA3-deficient mouse embryonic fibroblast cells, some GPCR ligand-, like lysophosphatidic acid (LPA), induced NF-κB activation is completely abolished. Mechanistically, upon GPCR activation, CARMA3 is linked to the membrane by β-arrestin 2 and phosphorylated by some PKC isoform. Phosphorylation of CARMA3 unfolds its steric structure and recruits its downstream effectors, which in turn activate the IKK complex and NF-κB. Interestingly, GPCR (LPA)-CARMA3-NF-κB signaling axis also exists in ovarian cancer cells, and knockdown of CARMA3 results in attenuation of ovarian cancer migration and invasion, suggesting a novel target for cancer therapy. In this review, we summarize the biology of CARMA3, discuss the GPCR (LPA)-CARMA3-NF-κB signaling axis in ovarian cancer and speculate its potential role in other types of cancers. With a strongly increasing tendency to identify more LPA-like ligands, such as endothelin-1 and angiotensin II, which also activate NF-κB through CARMA3 and contribute to myriad diseases, GPCR- CARMA3-NF-κB signaling axis is emerging as a novel drug target for various types of cancer and other myriad diseases