Anti-FOS monoclonal antibody, clone 3D0

Hypoxia-inducible factor 1 (HIF1) signaling pathway plays a key role in cancer progression by enhancing glycolysis through activating the transcription of glycolytic genes. JMJD2D, a histone demethylase that specifically demethylates H3K9me2/3, can promote colorectal cancer (CRC) progression. However, it is unknown whether JMJD2D could promote CRC progression by enhancing glycolysis through activating HIF1 signaling pathway. In this study, we found that downregulation of JMJD2D inhibited the glycolysis in CRC cells through suppressing HIF1 signaling pathway to downregulate glycolytic gene expression. Restoring HIF1 signaling by enforced expression of HIF1 alpha in JMJD2D-knockdown CRC cells partially recovered CRC cell glycolysis, proliferation, migration, invasion, xenograft growth, and metastasis, suggesting that JMJD2D promotes CRC progression by enhancing glycolysis through activating HIF1 signaling pathway. JMJD2D activated HIF1 signaling pathway through three different mechanisms: JMJD2D cooperated with the transcription factor SOX9 to enhance mTOR expression and then to promote HIF1 alpha translation; JMJD2D cooperated with the transcription factor c-Fos to enhance HIF1 beta transcription; JMJD2D interacted and cooperated with HIF1 alpha to enhance the expression of glycolytic gene. The demethylase-defective mutant of JMJD2D could not induce the expression of mTOR, HIF1 alpha, HIF1 beta, and glycolytic genes, suggesting that the demethylase activity of JMJD2D is important for glycolysis through activating HIF1 signaling. Clinically, a highly positive correlation between the expression of JMJD2D and mTOR, HIF1 beta, and several glycolytic genes in human CRC specimens was identified. Collectively, our study reveals an important role of JMJD2D in CRC progression by enhancing glycolysis through activating HIF1 signaling pathway.

This study is aimed to investigate the surface eco-protection techniques for cohesive soil slopes along the selected Guthrie Corridor Expressway (GCE) stretch by way of analyzing a new set of intelligence techniques namely neuro-bee, artificial neural network (ANN) and neuro-fuzzy. Soil erosion and mass movement which induce landslides have become one of the disasters faced in Selangor, Malaysia causing enormous loss affecting human lives, destruction of property and the environment. Establishing and maintaining slope stability using mechanical structures are costly. Hence, biotechnical slope protection offers an alternative which is not only cost effective but also aesthetically pleasing. To reach the aim of the current study, a field investigations and numerical studies were conducted and a suitable database was prepared and established. By preparing factor of safety (FOS) as a single output parameter and a combination of the most important parameters on that, the desired models have been designed based on training and test patterns. In order to evaluate and compare the prediction precision of the developed models, a series of statistical indices, such as root mean squared error (RMSE), determination coefficient (R-square) and variance account for (VAF) are calculated. Many intelligence models with the most effective parameters on the mentioned models were developed to predict FOS. Based on the simulation results and the measured indices, it was found that the proposed neuro-fuzzy model with the lowest system error and highest R-square performs better as compared to other proposed ANN and neuro-bee models. Therefore, the neuro-fuzzy can provide a new applicable model to effectively predict the FOS of the slopes due to the fact that it is able to combine the advantages of the ANN and fuzzy inference system to indicate a high prediction capacity in solving problem of slope stability. (C) 2020 Elsevier B.V. All rights reserved.