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How cell-to-cell copy number alterations that underpin genomic instability

BackgroundThe advent of single cell RNA sequencing (scRNA-seq) enabled researchers to study transcriptomic activity within individual cells and identify inherent cell types in the sample. Although numerous computational tools have been developed to analyze single cell transcriptomes, there are no published studies and analytical packages available to guide experimental design and to devise suitable analysis procedure for cell type identification.ResultsWe have developed an empirical methodology to address this important gap in single cell experimental design and analysis into an easy-to-use tool called SCEED (Single Cell Empirical Experimental Design and analysis). With SCEED, user can choose a variety of combinations of tools for analysis, conduct performance analysis of analytical procedures and choose the best procedure, and estimate sample size (number of cells to be profiled) required for a given analytical procedure at varying levels of cell type rarity and other experimental parameters. Using SCEED, we examined 3 single cell algorithms using 48 simulated single cell datasets that were generated for varying number of cell types and their proportions, number of genes expressed per cell, number of marker genes and their fold change, and number of single cells successfully profiled in the experiment.ConclusionsBased on our study, we found that when marker genes are expressed at fold change of 4 or more than the rest of the genes, either Seurat or Simlr algorithm can be used to analyze single cell dataset for any number of single cells isolated (minimum 1000 single cells were tested). However, when marker genes are expected to be only up to fC 2 upregulated, choice of the single cell algorithm is dependent on the number of single cells isolated and proportion of rare cell type to be identified. In conclusion, our work allows the assessment of various single cell methods and also aids in examining the single cell experimental design.

Recent observations indicate that solar p-mode line profiles are not exactly Lorentzian but rather exhibit varying amounts of asymmetry about their peaks. We analyze p-mode line asymmetry by using both a simplified one-dimensional model and a more realistic solar model. We find that the amount of asymmetry exhibited by a given mode depends on the location of the sources exciting the mode, the mode frequency, and weakly on the mode spherical harmonic degree but not on the particular mechanism or location of the damping. We calculate the dependence of line asymmetry on source location for solar p-modes and provide physical explanations of our results in terms of the simplified model. A comparison of our results to the observations of line asymmetry in velocity spectra reported by Duvall et al. for modes of frequency ~2.3 mHz suggests that the sources for these modes are located more than 325 km beneath the photosphere. This source depth is greater than that found by Kumar for acoustic waves of frequency ~6 mHz. The difference may indicate that waves of different frequencies are excited at different depths in the convection zone. We find that line asymmetry causes the frequency obtained from a Lorentzian fit to a peak in the power spectrum to differ from the corresponding eigenfrequency by an amount proportional to a dimensionless asymmetry parameter and to the mode line width.

To establish a matrix of parameters to synthesize nanoparticles of different sizes and to investigate the cellular uptake of these nanoparticles by osteosarcoma cancer cells in order to investigate their potential as therapeutic drugdelivery carriers.Gelatin A and B were used to synthesize nanoparticles by a two-step desolvation process. Different parameters were investigated, including temperature, pH, concentration of glutaraldehyde, type of desolvating agent and nature of gelatin. For cell uptake studies, Texas Red labeled nanoparticles were incubated with 143B osteosarcoma cells and then evaluated using confocal laser scanning microscopy (CLSM).The systematic investigation of the synthesis parameters showed that it is possible to prepare gelatin-based nanoparticles with different particle sizes and a narrow size distribution. Temperature and nature of the gelatin were the most important synthesis factors. Bioimaging using CLSM showed uptake of the nanoparticles by 143B osteosarcoma cancer cells.Osteosarcoma cancer cells take up gelatin nanoparticles. This might improve the clinical effectiveness of anti-cancer treatments if nanoparticles are used as a drug delivery system and has important implications for future cancer treatment strategies.