ABSTRACT
Metabolic reprogramming is a well-known feature of cancer that allows malignant cells to alter metabolic reactions and nutrient uptake, thereby promoting tumor growth and spread. It has been discovered that noncoding RNAs (ncRNAs), including microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA), have a role in a variety of biological functions, control physiologic and developmental processes, and even influence disease. They have been recognized in numerous cancer types as tumor suppressors and oncogenic agents. The role of ncRNAs in the metabolic reprogramming of cancer cells has recently been noticed. We examine this subject, with an emphasis on the metabolism of glucose, lipids, and amino acids, and highlight the therapeutic use of targeting ncRNAs in cancer treatment.
Subject(s)
MicroRNAs , Neoplasms , RNA, Long Noncoding , RNA, Untranslated/genetics , RNA, Long Noncoding/genetics , Biological Transport , MicroRNAs/genetics , Glucose , RNA, Circular , Neoplasms/geneticsABSTRACT
One of the main challenges in sparse signal recovery in compressed sensing framework is determining the sparsity order. Most model order selection methods introduce a penalty term for the number of parameters, however do not consider the variance of the observation and measurement noise. Minimum Noiseless Description Length (MNDL), on the other hand, considers these factors and provides a more robust results in order selection. Nevertheless, it requires noise variance (equivalently SNR) estimate for the order selection procedure. In this paper, a new method is introduced to estimate the variance of the observation noise within the MNDL order selection method. The fully automated method simultaneously provides the SNR estimate and sparsity order and does not require any prior partial knowledge or assumption on the noise variance. Simulation results for ECG compression show advantages of the proposed automated MNDL over the existing approaches in the sense of parameter estimation error and SNR improvement.
Subject(s)
Data Compression , Signal Processing, Computer-Assisted , Algorithms , Electrocardiography , Signal-To-Noise RatioABSTRACT
Interferon-gamma (IFN-γ) and P2X7 receptor are crucial for host defence against mycobacterial infections. Recent studies have indicated that IFN-γ, IFN-γ receptor 1 (IFN-γR1) andP2X7 gene polymorphisms are associated with susceptibility to pulmonary tuberculosis (TB). However, the relationship between IFN-γ and P2X7 polymorphism and TB susceptibility remains inconclusive in Iranian population. For this reason, single nucleotide polymorphisms (SNPs) in IFN-γ (G+2109A), IFN-γR1 (G-611A) and P2X7 genes (at -762, 1513 position) in patients (n = 100) were assessed using PCR-RFLP. Data were analysed with SPSS version 18. For the 2109 loci of IFN-γ gene, the frequency of mutant alleles between patients and controls were not statistically significant. However, there was a significant difference between the TB patient and controls for -611 alleles of IFN-γR1 (P = 0.01). Additionally, the frequency of P2X7 gene polymorphisms (SNP-762 and 1513) between patients and controls was statistically significant. In conclusions, our study revealed a significant association of IFN-γR1 and P2X7 genes polymorphisms with risk of developing TB in Iranian population.
