Colonhatfield3410

Cancer stem cells (CSCs) with self-renewal play an important role in tumor initiation and progression and are associated with drug resistance in cancer therapy. Here, we investigated the characteristics of stem cell-related genes in colorectal cancer (CRC) based on datasets from The Cancer Genome Atlas (TCGA) and Oncomine. We found that the stemness indices were significantly overexpressed in CRC tissues and were associated with patient survival. Weighted gene co-expression network analysis (WGCNA) was performed to determine the modules of stemness and featured genes. Significant modules and 8 genes (BUB1, BUB1B, CHEK1, DNA2, KIF23, MCM10, PLK4, and TTK) were selected according to the inclusion criteria. Expression analyses of transcription and protein levels confirmed internal correlation and their relevance with the tumor. Functional analysis of these genes demonstrated their enrichment in pathways, including checkpoint, chromosomal region and protein serine/threonine kinase activity. These results suggested that the characteristics of the featured genes fit well with CRC pathology and could provide new strategies for individual prevention and treatment.Clonorchiasis is an important zoonotic parasitic disease worldwide. In view of the fact that parasite infection affects host metabolism, and there is an intricate relationship between metabolism and immunity. Metabolic analysis of the spleen could be helpful for understanding the pathophysiological mechanisms in clonorchiasis. A non-targeted ultra high performance liquid tandem chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF MS) approach was employed to investigate the metabolic profiles of spleen in rats at 4 and 8 weeks post infection with Clonorchis sinensis (C. sinensis). Then a targeted ultra-high performance liquid chromatography multiple reaction monitoring mass spectrometry (UHPLC-MRM-MS/MS) approach was used to further quantify amino acid metabolism. Multivariate data analysis methods, such as principal components analysis and orthogonal partial least squares discriminant analysis, were used to identify differential metabolites. Finally, a total of 396 and 242 significant differential metabolites were identified in ESI+ and ESI- modes, respectively. These metabolites included amino acids, nucleotides, carboxylic acids, lipids and carbohydrates. There were 38 significantly different metabolites shared in the two infected groups compared with the control group through the Venn diagram. The metabolic pathways analysis revealed that pyrimidine metabolism, aminoacyl-tRNA biosynthesis, purine metabolism and phenylalanine, tyrosine and tryptophan biosynthesis were significantly enriched in differential metabolites, which was speculated to be related to the disease progression of clonorchiasis. Furthermore, 15 amino acids screened using untargeted profiling can be accurately quantified and identifed by targeted metabolomics during clonrochiasis. These results preliminarily revealed the perturbations of spleen metabolism in clonorchiasis. Meanwhile, this present study supplied new insights into the molecular mechanisms of host-parasite interactions.The current global debacle of COVID-19, spelled by SARS-CoV-2 needs no elaboration. With incessant and constantly clambering number of deaths across various nations, the need of the hour is to develop readily deployable, fast, affordable detection assays and kits, yielding precise and consistent results as well as timely availability of efficacious anti-SARS-CoV-2 strategies to contain it. Conventionally employed real time PCR based technique for detection of the virus suffers from a couple of handicaps. Amongst other approaches, CRISPR based technology has ushered in new hopes. Recent efforts have been directed toward developing CRISPR/Cas based low-cost, rapid detection methods as well as development of one-pot assay platforms. The plausible application of CRISPR-Cas system to counteract the viral assault has also been assessed. The write up in this article mirrors the current status, the prospects and the practical snags of CRISPR/Cas technology for the detection and inactivation of the novel corona virus, SARS-CoV-2.The outbreak of 2019 novel coronavirus (COVID-19) has caused serious threat to public health. Discovery of new anti-COVID-19 drugs is urgently needed. Fortunately, the crystal structure of COVID-19 3CL proteinase was recently resolved. The proteinase has been identified as a promising target for drug discovery in this crisis. Here, a dataset including 2030 natural compounds was screened and refined based on the machine learning and molecular docking. The performance of six machine learning (ML) methods of predicting active coronavirus inhibitors had achieved satisfactory accuracy, especially, the AUC (Area Under ROC Curve) scores with fivefold cross-validation of Logistic Regression (LR) reached up to 0.976. Comprehensive ML prediction and molecular docking results accounted for the compound Rutin, which was approved by NMPA (National Medical Products Administration), exhibited the best AUC and the most promising binding affinity compared to other compounds. Therefore, Rutin might be a promising agent in anti-COVID-19 drugs development.Background The coronavirus disease 2019 (COVID-19) outbreak in South Korea has affected the diagnosis, treatment, and follow-up protocols of various cancers. This study investigated the patterns of delaying surgery for breast cancer during the COVID-19 outbreak in South Korea and evaluated factors that may have affected the decision to delay surgery. Methods From February 18 to April 18, 2020, which was the critical period for COVID-19 in South Korea, patients with breast cancer who were scheduled for surgery were evaluated in terms of their decision in delaying the procedure. Selleck VX-745 The patients were divided into two groups delaying and non-delaying surgery groups. The association between personal and clinicopathological factors and delaying surgery was evaluated. Results In patients belonging to the delaying surgery group, the mean delay period was 15.9 (standard deviation [SD], ±10.9) days. Patients in the non-delaying surgery group were relatively younger (p = 0.003), single (p = 0.038), had planned mastectomy (p = 0.