Protein arginine methyltransferases (PRMTs) play important roles in transcription, splicing, DNA damage repair, RNA biology, and cellular metabolism. Thus, PRMTs have been attractive targets for various diseases. In this study, we reported the design and synthesis of a potent pan-inhibitor for PRMTs that tethers a thioadenosine and various substituted guanidino groups through a propyl linker. Compound II757 exhibits a half-maximal inhibition concentration (IC50) value of 5 to 555 nM for eight tested PRMTs, with the highest inhibition for PRMT4 (IC50 = 5 nM). The kinetic study demonstrated that II757 competitively binds at the SAM binding site of PRMT1. Notably, II757 is selective for PRMTs over a panel of other methyltransferases, w

 Let  be a metric space and  be a continuous map. The notion of the  -average shadowing property ( ASP )  for a continuous map on  â€“space is introduced  and the relation between the ASP and average shadowing property(ASP)is investigated. We show that if  has ASP, then   has ASP for every . We prove that if a map  be pseudo-equivariant with dense set of periodic points and has the ASP,  then  is weakly mixing. We also show that if   is a expansive pseudo-equivariant homeomorphism that has the ASP and  is topologically mixing,  then  has a  -specification. We obtained that the identity map  on  has the ASP  if and only if th

  In this paper, the concept of contraction mapping on a -metric space is extended with a consideration on local contraction.  As a result, two fixed point theorems were proved for contraction on a closed ball in a complete -metric space.

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Background: Colorectal adenocarcinoma is the most common type of gastrointestinal cancer, with about 150,000 cases each year in the United States and about 56,730 deaths from colorectal cancer risk. In Iraq and according to the Iraqi cancer registry (ICR) reports, the incidence of colorectal carcinoma was 4.55% of whole body malignancy, & it is the seventh cause of death from cancer (ICR 2005). In males, it’s the 7th common cancer while in females it’s the 4th most common cancer. The estrogen and progesterone receptors belong to a super- family of nuclear hormone receptors. These receptor proteins function as transcription factors when they are bound to their respective ligands, these receptors shares a common st

In this paper, a new hybridization of supervised principal component analysis (SPCA) and stochastic gradient descent techniques is proposed, and called as SGD-SPCA, for real large datasets that have a small number of samples in high dimensional space. SGD-SPCA is proposed to become an important tool that can be used to diagnose and treat cancer accurately. When we have large datasets that require many parameters, SGD-SPCA is an excellent method, and it can easily update the parameters when a new observation shows up. Two cancer datasets are used, the first is for Leukemia and the second is for small round blue cell tumors. Also, simulation datasets are used to compare principal component analysis (PCA), SPCA, and SGD-SPCA. The results sh

A theoretical model is developed to determine time evolution of temperature at the surface of an opaque target placed in air for cases characterized by the formation of laser supported absorption waves (LSAW) plasmas. The model takes into account the power temporal variation throughout an incident laser pulse, (i.e. pulse shape, or simply: pulse profile).
Three proposed profiles are employed and results are compared with the square pulse approximation of a constant power.

The features of strategic thought transformation in Russia based on attempt confirm the Russian influenced on Region of Eastern Europe through series of common defense treaties and mutual security between USSR and another states this treaties emphasis size on direct Russian supervision on these states in addition, Russia in trusted to formation communism regimes in its vital space, Russia inherited the status of former USSR in political and economic levels.

           Shortly we can see that Russia witnessed large Transformation in political strategic thought as a result of change in internal strategic environment and change of nature understanding which influenced on Russia. This

This study was conducted in the specialized center of endocrinology and diabetic (AlKindy hospital from June 2004 to April 2005). Sera of 80 women (include 40 diagnosed Hyperprolactinemia (HPro) and 40 healthy women as control) were used to estimate some biochemical parameters which include prolactin (PRL),total fucose (TF), total protein (TP) and protein bound fucose (PBF), and protein bound hexose (PBHex),  also TP TF , TP PBF and TP PBHex   ratios. A significant elevation in TP and  PBHex, in sera of HPro patients compared to control was found while PBHex/TP ratio showed a slight non significant increase in sera of patients compared to control. On the other hand a significant decrease in TF, TF/TP and PBF/TP in ser