Stokesmohamad9521
Few previous studies have comprehensively explored the level of DNA methylation and gene expression in ccRCC. The purpose of this study was to identify the key clear cell renal cell carcinoma- (ccRCC-) related DNA methylation-driven genes (MDG) and to build a prognostic model based on the level of DNA methylation.
RNA-seq transcriptome data and DNA methylation data were obtained from The Cancer Genome Atlas. Based on the MethylMix algorithm, we obtain ccRCC-related MDG. The univariate and multivariate Cox regression analyses were employed to investigate the correlation between patient overall survival and the methylation level of each MDG. Finally, a prognosis risk score was established based on a linear combination of the regression coefficient derived from the multivariate Cox regression model (
) multiplied with the methylation level of the gene.
19 ccRCC-related MDG were identified. Three MDG (NCKAP1L, EVI2A, and BATF) were further screened and integrated into a prognostic risk score model, risk score = (3.710∗methylation level of NCKAP1L) + (-3.892∗methylation level of EVI2A) + (-3.907∗methylation level of BATF). The risk model was independent from conventional clinical characteristics as a prognostic factor for ccRCC (HR = 1.221, 95% confidence interval 1.063-1.402, and
= 0.005). The joint survival analysis showed that the gene expression and methylation levels of the prognostic genes EVI2A and BATF were significantly related with prognosis.
This study provided an important bioinformatics foundation for in-depth studies of ccRCC DNA methylation.
This study provided an important bioinformatics foundation for in-depth studies of ccRCC DNA methylation.
One of the key concerns of the clinician is to identify and manage risk factors for major adverse cardiovascular events (MACEs) in nondiabetic and diabetic patients with acute coronary syndrome (ACS) undergoing stent implantation. Mean corpuscular volume (MCV) is a marker of erythrocyte size and activity and is associated with prognosis of cardiovascular disease. However, the role of admission MCV in predicting MACEs following stent implantation in diabetes mellitus (DM), non-DM, or whole patients with ACS remains largely unknown.
A total of 437 ACS patients undergoing stent implantation, including 294 non-DM (59.08 ± 10.24 years) and 143 DM (63.02 ± 9.92 years), were analyzed. Admission MCV was higher in non-DM than DM patients. During a median of 31.93 months follow-up, Kaplan-Meier curve demonstrated that higher admission MCV level was significantly associated with increased MACEs in whole and non-DM, but not in DM patients. In Cox regression analysis, the highest MCV tertile was associated with higherg for lifestyle and clinical risk factors. However, as the follow-up period increased, the admission MCV lost its ability to predict MACEs.
Circulating long noncoding RNAs (lncRNAs) have been demonstrated to serve as diagnostic biomarkers for various cancers. We aimed to elucidate the diagnostic efficacy of eight serum lncRNAs HULC, MALAT1, Linc00152, PTENP1, PTTG3P, SPRY4-IT1, UBE2CP3, and UCA1 and their combinations for the diagnosis of hepatocellular carcinoma (HCC).
A total of 129 patients with HCC, 49 patients with liver cirrhosis, 27 patients with chronic hepatitis B, and 93 healthy controls were enrolled in this study. The levels of serum lncRNAs were assessed by quantitative real-time polymerase chain reaction. The correlations between serum lncRNAs and clinicopathological characteristics were further analyzed. The receiver operating characteristic (ROC) curve and area under curve (AUC) were utilized to estimate the diagnostic capacity of serum lncRNAs and their combination with AFP for HCC. A logistic regression model was performed to establish a multiple-lncRNA panel.
The levels of serum HULC, MALAT1, Linc00152, PTTG3P, SPRY4-IT1, HCC diagnosis.
The panel of serum Linc00152, UCA1, and AFP demonstrates a novel and noninvasive biomarker with relatively high sensitivity and specificity for HCC diagnosis.Hepatocellular carcinoma (HCC) is a malignant tumour associated with a high mortality rate and poor prognosis worldwide. Uridine diphosphate-glucose pyrophosphorylase 2 (UGP2), a key enzyme in glycogen biosynthesis, has been reported to be associated with the occurrence and development of various cancer types. However, its diagnostic value and prognostic value in HCC remain unclear. The present study observed that UGP2 expression was significantly downregulated at both the mRNA and protein levels in HCC tissues. Receiver operating characteristic (ROC) curve analysis revealed that UGP2 may be an indicator for the diagnosis of HCC. In addition, Kaplan-Meier and Cox regression multivariate analyses indicated that UGP2 is an independent prognostic factor of overall survival (OS) in patients with HCC. Furthermore, gene set enrichment analysis (GSEA) suggested that gene sets negatively correlated with the survival of HCC patients were enriched in the group with low UGP2 expression levels. More importantly, a significant correlation was identified between low UGP2 expression and fatty acid metabolism. https://www.selleckchem.com/products/abt-199.html In summary, the present study demonstrates that UGP2 may contribute to the progression of HCC, indicating a potential therapeutic target for HCC patients.A convergent strategy is reported for the construction of nitrogen-containing heterocycles from common substrates 1,4-diketones and primary amines. Indeed, by just varying the substrates, the substituents, or the heating mode, it is possible to selectively synthesize indole, indolone (1,5,6,7-tetrahydroindol-4-one), or cinnoline (5,6,7,8-tetrahydrocinnoline) derivatives in moderate to excellent yields.The catalytic conversion of (ligno)cellulose is currently subject of intense research. Isosorbide is one of the interesting products that can be produced from (ligno)cellulose as it can be used for the synthesis of a wide range of pharmaceuticals, chemicals, and polymers. Isosorbide is obtained after the hydrolysis of cellulose to glucose, followed by the hydrogenation of glucose to sorbitol that is then dehydrated to isosorbide. The one-pot process requires an acid and a hydrogenation catalyst. Several parameters are of importance during the direct conversion of (ligno)cellulose such as the acidity, the crystallinity and the particle size of cellulose as well as the nature of the feedstocks. This review highlights all these parameters and all the strategies employed to produce isosorbide from (ligno)cellulose in a one-pot process.
