Step by step analysis on gene datasets of growth phases in hematopoietic stem cells.

Background: Umbilical cord blood hematopoietic stem cells (UCB-HSCs) have important roles in the treatment of illnesses based on their self-renewal and potency characteristics. Knowing the gene profiles and signaling pathways involved in each step of the cell cycle could improve the therapeutic approaches of HSCs. The aim of this study was to predict the gene profiles and signaling pathways involved in the G0, G1, and differentiation stages of HSCs. Methods: Interventional (n = 8) and non-interventional (n = 3) datasets were obtained from the Gene Expression Omnibus (GEO) database, and were crossed and analyzed to determine the high- and low-express genes related to each of the G0, G1, and differentiation stages of HSCs. Then, the scores of STRING were annotated to the gene data. The gene networks were constructed using Cytoscape software, and enriched with the KEGG and GO databases. Results: The high- and low-express genes were determined due to inter and intra intersections of the interventional and non-interventional data. The non-interventional data were applied to construct the gene networks (n = 6) with the nodes improved using the interventional data. Several important signaling pathways were suggested in each of the G0, G1, and differentiation stages. Conclusion: The data revealed that the different signaling pathways are activated in each of the G0, G1, and differentiation stages so that their genes may be targeted to improve the HSC therapy.

Differential gene expression patterns in ST-elevation Myocardial Infarction and Non-ST-elevation Myocardial Infarction.

The ST-elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI) might occur because of coronary artery stenosis. The gene biomarkers apply to the clinical diagnosis and therapeutic decisions in Myocardial Infarction. The aim of this study was to introduce, enrich and estimate timely the blood gene profiles based on the high-throughput data for the molecular distinction of STEMI and NSTEMI. The text mining data (50 genes) annotated with DisGeNET data (144 genes) were merged with the GEO gene expression data (5 datasets) using R software. Then, the STEMI and NSTEMI networks were primarily created using the STRING server, and improved using the Cytoscape software. The high-score genes were enriched using the KEGG signaling pathways and Gene Ontology (GO). Furthermore, the genes were categorized to determine the NSTEMI and STEMI gene profiles. The time cut-off points were identified statistically by monitoring the gene profiles up to 30 days after Myocardial Infarction (MI). The gene heatmaps were clearly created for the STEMI (high-fold genes 69, low-fold genes 45) and NSTEMI (high-fold genes 68, low-fold genes 36). The STEMI and NSTEMI networks suggested the high-score gene profiles. Furthermore, the gene enrichment suggested the different biological conditions for STEMI and NSTEMI. The time cut-off points for the NSTEMI (4 genes) and STEMI (13 genes) gene profiles were established up to three days after Myocardial Infarction. The study showed the different pathophysiologic conditions for STEMI and NSTEMI. Furthermore, the high-score gene profiles are suggested to measure up to 3 days after MI to distinguish the STEMI and NSTEMI.

Beta arrestin-related signalling axes are influenced by dexamethasone and metformin in vascular smooth muscle cells cultured in high glucose condition.

BACKGROUND: Metformin (Met) and dexamethasone (Dexa) are known to reduce blood sugar levels and anti-inflammatory effects, respectively. Based on the acceleration of atherosclerosis process in diabetes, the ß-arrestin 2 (BARR2) gene and protein expression levels were evaluated in vascular smooth muscle cells (VSMCs) treated with Met and Dexa in high glucose conditions in this study. METHODS AND MATERIALS: Human VSMCs were cultured in Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 (DMEM-F12) medium and, were treated with different values of Met (1 mM, 5 mM and 7 mM) and Dexa (10-7 M, 10-6 M and 10-5 M) in 24- and 48-h periods. The BARR2 gene and protein expression levels were identified with RT-qPCR and western blotting techniques, respectively. The signalling axes were predicted from gene network made using Cytoscape software and, were annotated with Gene Ontology. RESULTS: The BARR2 gene and protein expression levels reduced in VSMCs treated with Dexa and Met after 24- and 48-h periods. These results were more changed after 48 h. Furthermore, many BARR2-related signalling axes were found from the network genes. CONCLUSION: Met and Dexa suppressed the BARR2 protein and gene expression levels in the VSMCs. Moreover, the gene network suggested some the cellular signalling axes related to BARR2 that may be affected by Met and Dexa.

Molecular evolution of PCSK family: Analysis of natural selection rate and gene loss.

Proprotein convertases subtilisin kexins are serine endoproteases, playing critical roles in the biological functions, including lipid, glucose, and bile acid metabolism, as well as cell proliferation, migration, and metastasis. Experimental studies have demonstrated the physiological functions of PCSKs and their association with diseases; however, studies on the evolutionary history and diversification of these proteins are missing. In the present research, a bioinformatics study was conducted on the molecular evolution of several PCSKs family members and gene loss events across placental mammalian. In order to detect evolutionary constraints and positive selection, the CodeML program of the PAML package was used. The results showed the positive selection to occur in PCSK1, PCSK3, PCSK5, and PCSK7. A decelerated rate of evolution was observed in PCSK7, PCSK3, and MBTPS1 in Carnivores compared to the rest of phylogeny, and an accelerated evolution of PCSK1, PCSK7, and MBTPS1 in Muridae family of rodents was found. Additionally, our results indicated pcsk9 gene loss in 12 species comprising Carnivores and bats (Chiroptera). Future studies are required to evaluate the functional relevance and selective evolutionary advantages associated with these modifications in PCSK proteins during evolution.

Molecular evolution of autophagy rate-limiting factor LAMP2 in placental mammals.

Autophagy is the cellular process of removal of misfolded or damaged macromolecules and organelles. Experimental studies have demonstrated autophagy as a major mechanism of lifespan extension in long-lived mammals such as bats and mole rat rodents. Moreover, the role of this biological process has been well documented in protection against age-associated diseases and viral infection. However, studies on the molecular adaptive changes of autophagy factors during evolution are scarce. Here, we conducted a bioinformatics study of the molecular evolution of the Lysosomal Associated Membrane Protein 2 (LAMP2), as a rate-limiting factor in the lysosomal degradation stage of autophagy (the communal step of two of autophagy types: macroautophagy and chaperone-mediated). Analyzing LAMP2 across placental mammals, our phylogenetic-based maximum likelihood analyses indicate that the majority of the coding sites undergo purifying selection. However, around 27% of sites display a relaxation of purifying constraints (average ω = 0.42128), among which, 14 particular sites undergo positive selection (ω > 1). These sites are mostly located in the first luminal domain of LAMP2 (N-domain), with a hotspot region in the 135-144 codons interval. Therefore, the N-domain may account for the functional diversity and regulation of LAMP2. In addition, the identified positive selection sites could act as key regulatory sites in the LAMP2 function. On the other hand, testing the rate of evolution in LAMP2 along different clades of placental mammals revealed a relatively relaxed evolution in LAMP2 along megabats' clade. It is not clear yet whether an expedited evolution of LAMP2 in megabats has contributed to their reported up-regulation of autophagy. Finally, our data indicate positive selection sites along the ancestral branch of the clades of rodents, mouse-related rodents, and mole-rats; and suggest the potentially important regulatory role of these sites in LAMP2. Identifying the residues under positive selection, our findings pave the way for future experimental investigations to define how these selective substitutions have functionally affected autophagy.

Diosgenin-loaded niosome as an effective phytochemical nanocarrier: physicochemical characterization, loading efficiency, and cytotoxicity assay.

BACKGROUND: The use of phytochemicals to prevent or suppress tumours is known as chemoprevention. Numerous plant-derived agents have been reported to have anticancer potentials. As one such anticancer phytochemical, diosgenin has several applications which are nevertheless limited due to its low solubility in water. METHODS: We loaded diosgenin into niosome to increase its solubility and hence efficiency. Diosgenin-niosome (diosgenin loaded into niosome) was prepared by thin-film hydration method and characterised by optical microscopy, dynamic light scattering (DLS), scanning electron microscopy (SEM), and UV-visible spectrophotometry. Also, loading efficiency, in vitro drug release, and cytotoxicity assay were performed on HepG2 cell line. RESULTS AND DISCUSSION: Diosgenin-niosome has a nanometric size with a normal size distribution and spherical morphology. The loading efficiency of diosgenin was about 89% with a sustainable and controllable release rate. Finally, the viability of free diosgenin was 61.25%, and after loading into niosomes, it was improved to 28.32%. CONCLUSION: The results demonstrated that niosomes increase the solubility of naturally derived hydrophobic chemicals and thus enhance their anticancer effect. Graphical abstract.