Riisedunn1377

Results Bioinformatics analysis indicated that lncRNA LBX2-AS1, RARα, FSTL3 were remarkably fostered in thyroid cancer tissue, and LBX2-AS1 was evidently correlated with clinical features. The LncMAP triplet prediction showed that LBX2-AS1 recruited TF RARα to modulate FSTL3. RIP assay confirmed that LBX2-AS1 was prominently enriched on RARα. ChIP and dual-luciferase report assays unveiled that RARα bound to the promoter region of FSTL3 and functioned as a TF. Cell function experiments uncovered that LBX2-AS1 boosted the progression of thyroid cancer. learn more The rescue experiments showed that LBX2-AS1 recruited the TF RARα to hasten the transcription activity of FSTL3 and thus promoted the development of thyroid cancer. Conclusion The integrative results demonstrated that LBX2-AS1 activated FSTL3 by binding to TF RARα to hasten proliferation, migration and invasion of thyroid cancer.Humankind has suffered many pandemics in history including measles, SARS, MERS, Ebola, and recently the novel Coronavirus disease caused by SARS-CoV-2. As of September 2021, it has affected over 200 million people and caused over 4 million deaths. India is the second most affected country in the world. Up to this date, more than 38 Lakh viral genomes have been submitted to public repositories like GISAID and NCBI to analyze the virus phylogeny and mutations. Here, we analyzed 2349 genome sequences of SARS-CoV-2 submitted in GISAID by a single institute pertaining to infections from the Gujarat state to know their variants and phylogenetic distributions with a major focus on the spike protein. More than 93% of the genomes had one or more mutations in the spike glycoprotein. The D614G variant in spike protein is reported to have a very high frequency of >95% globally followed by the L452R and P681R, thus getting significant attention. The antigenic propensity of a small peptide of 29 residues from 597 to 625 of the spike protein variants having D614 and G614 showed that G614 has a little higher antigenic propensity. Thus, the D614G is the cause for higher viral antigenicity, however, it has not been reported to be effective to be causing more deaths.Recent studies have shown that PPP1R14B was highly expressed in tumor tissues and patients with high expression of PPP1R14B had poor survival rates. However, the function and mechanisms of PPP1R14B in tumor progression remain ill defined. There was also lack of pan-cancer evidence for the relationship between PPP1R14B and various tumor types based on abundant clinical data. We used the TCGA project and GEO databases to perform pan-cancer analysis of PPP1R14B, including expression differences, correlations between expression levels and survival, genetic alteration, immune infiltration, and relevant cellular pathways, to investigate the functions and potential mechanisms of PPP1R14B in the pathogenesis or clinical prognosis of different cancers. Herein, we found that PPP1R14B was involved in the prognosis of pan-cancer and closely related to immune infiltration. Increased PPP1R14B expression correlated with poor prognosis and increased immune infiltration levels in myeloid-derived suppressor cells (MDSCs). Our studies suggest that PPP1R14B can be used as a prognostic biomarker for pan-cancer. Our findings may provide an antitumor strategy targeting PPP1R14B, including manipulation of tumor cell growth or the tumor microenvironment, especially myeloid-derived suppressor cell infiltration.Adipose tissue-derived stromal cells are promising candidates investigating the stem cell-related treatment. However, their proportion and utility in the human body decline with time, rendering stem cells incompetent to complete repair processes in vivo. The involvement of circRNAs in the aging process is poorly understood. Rat subcutaneous adipose tissue from 10-week-old and 27-month-old rats were used for hematoxylin and eosin (H and E) staining, TUNEL staining, and circRNA sequencing. Rat adipose tissue-derived stromal cells were cultured and overexpressed with circ-ATXN2. Proliferation was examined using xCELLigence real-time cell analysis, EdU staining, and cell cycle assay. Apoptosis was induced by CoCl2 and examined using flow cytometry. RT-PCR assay and Oil Red O staining were used to measure adipogenesis at 48 h and 14 days, respectively. H and E staining showed that the diameter of adipocytes increased; however, the number of cells decreased in old rats. TUNEL staining showed that the proportion of pression profile of circRNAs in the adipose tissue of old rats. We found a novel age-related circular RNA-circ-ATXN2-that inhibits proliferation and promotes cell death and adipogenesis in rat adipose tissue-derived stromal cells.Evidences increasingly indicate the involvement of gene network rewiring in disease development and cell differentiation. With the accumulation of high-throughput gene expression data, it is now possible to infer the changes of gene networks between two different states or cell types via computational approaches. However, the distribution diversity of multi-platform gene expression data and the sparseness and high noise rate of single-cell RNA sequencing (scRNA-seq) data raise new challenges for existing differential network estimation methods. Furthermore, most existing methods are purely rely on gene expression data, and ignore the additional information provided by various existing biological knowledge. In this study, to address these challenges, we propose a general framework, named weighted joint sparse penalized D-trace model (WJSDM), to infer differential gene networks by integrating multi-platform gene expression data and multiple prior biological knowledge. Firstly, a non-paranormal graphical model is employed to tackle gene expression data with missing values. Then we propose a weighted group bridge penalty to integrate multi-platform gene expression data and various existing biological knowledge. Experiment results on synthetic data demonstrate the effectiveness of our method in inferring differential networks. We apply our method to the gene expression data of ovarian cancer and the scRNA-seq data of circulating tumor cells of prostate cancer, and infer the differential network associated with platinum resistance of ovarian cancer and anti-androgen resistance of prostate cancer. By analyzing the estimated differential networks, we find some important biological insights about the mechanisms underlying platinum resistance of ovarian cancer and anti-androgen resistance of prostate cancer.We found that SDF-1/CXCR7 axis played an important role in the growth and proliferation of gastric cancer in the previous studies. The objectives of this study were to explore the effects of SDF-1/CXCR7 on the metastatic ability of gastric cancer cells and the possible mechanisms. CXCR7 expression in SGC-7901 gastric cancer cells was stably knocked down via lentiviral vectors. The cell migration and invasion abilities were detected by transwell migration and invasion assays. The expressions of matrix metalloproteinase 2 (MMP-2), MMP-9, vascular endothelial growth factor (VEGF), epithelial-mesenchymal transition (EMT) markers and Akt phosphorylation were detected with real-time PCR and/or western blot. We found that SDF-1 markedly enhanced the migration and invasion abilities of SGC-7901 gastric cancer cells; CXCR7 knockdown inhibited these effects. SDF-1/CXCR7 increased the expressions of MMP-2, MMP-9 and VEGF. SDF-1/CXCR7 also downregulated E-cadherin expression but upregulated N-cadherin, vimentin and Snail expressions, suggesting that SDF-1/CXCR7 could promote the development of EMT in gastric cancer cells. Furthermore, SDF-1/CXCR7 could promote Akt phosphorylation. Our results indicated that SDF-1/CXCR7 enhanced the migration, invasion and EMT of gastric cancer cells and thus CXCR7 supression may be a strategy for inhibiting gastric cancer metastasis.Epigenetic regulation involves reversible changes in histones and DNA modifications that can be inherited without any changes in the DNA sequence. Dysregulation of normal epigenetic processes can lead to aberrant gene expression as observed in many diseases, notably cancer. Recent insights into the mechanisms of DNA methylation, histone modifications, and non-coding RNAs involved in altered gene expression profiles of tumor cells have caused a paradigm shift in the diagnostic and therapeutic approaches towards cancer. There has been a surge in search for compounds that could modulate the altered epigenetic landscape of tumor cells, and to exploit their therapeutic potential against cancers. Flavonoids are naturally occurring phenol compounds which are abundantly found among phytochemicals and have potentials to modulate epigenetic processes. Knowledge of the precise flavonoid-mediated epigenetic alterations is needed for the development of epigenetics drugs and combinatorial therapeutic approaches against cancers. This review is aimed to comprehensively explore the epigenetic modulations of flavonoids and their anti-tumor activities.Autoimmune diseases (ADs) are a broad range of diseases in which the immune response to self-antigens causes damage or disorder of tissues, and the genetic susceptibility is regarded as the key etiology of ADs. Accumulating evidence has suggested that there are certain commonalities among different ADs. However, the theoretical research about similarity between ADs is still limited. In this work, we first computed the genetic similarity between 26 ADs based on three measurements network similarity (NetSim), functional similarity (FunSim), and semantic similarity (SemSim), and systematically identified three significant pairs of similar ADs rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), myasthenia gravis (MG) and autoimmune thyroiditis (AIT), and autoimmune polyendocrinopathies (AP) and uveomeningoencephalitic syndrome (Vogt-Koyanagi-Harada syndrome, VKH). Then we investigated the gene ontology terms and pathways enriched by the three significant AD pairs through functional analysis. By the cluster analysis on the similarity matrix of 26 ADs, we embedded the three significant AD pairs in three different disease clusters respectively, and the ADs of each disease cluster might have high genetic similarity. We also detected the risk genes in common among the ADs which belonged to the same disease cluster. Overall, our findings will provide significant insight in the commonalities of different ADs in genetics, and contribute to the discovery of novel biomarkers and the development of new therapeutic methods for ADs.Identification of intercellular signaling changes across multiple single-cell RNA-sequencing (scRNA-seq) datasets as well as how intercellular communications affect intracellular transcription factors (TFs) to regulate target genes is crucial in understanding how distinct cell states respond to evolution, perturbations, and diseases. Here, we first generalized our previously developed tool CellChat, enabling flexible comparison analysis of cell-cell communication networks across any number of scRNA-seq datasets from interrelated biological conditions. This greatly facilitates the ready detection of signaling changes of cell-cell communication in response to any biological perturbations. We then investigated how intercellular communications affect intracellular signaling response by inferring a multiscale signaling network which bridges the intercellular communications at the population level and the cell state-specific intracellular signaling network at the molecular level. The latter is constructed by integrating receptor-TF interactions collected from public databases and TF-target gene regulations inferred from a network-regularized regression model.