Hypoxic Culture Conditions as a Solution for Mesenchymal Stem Cell Based Regenerative Therapy

Cell-based regenerative therapies, based on in vitro propagation of stem cells, offer tremendous hope to many individuals suffering from degenerative diseases that were previously deemed untreatable. Due to the self-renewal capacity, multilineage potential, and immunosuppressive property, mesenchymal stem cells (MSCs) are considered as an attractive source of stem cells for regenerative therapies. However, poor growth kinetics, early senescence, and genetic instability during in vitro expansion and poor engraftment after transplantation are considered to be among the major disadvantages of MSC-based regenerative therapies. A number of complex inter-and intracellular interactive signaling systems control growth, multiplication, and differentiation of MSCs in their niche. Common laboratory conditions for stem cell culture involve ambient O-2 concentration (20%) in contrast to their niche where they usually reside in 2-9% O-2. Notably, O-2 plays an important role in maintaining stem cell fate in terms of proliferation and differentiation, by regulating hypoxia-inducible factor-1 (HIF-1) mediated expression of different genes. This paper aims to describe and compare the role of normoxia (20% O-2) and hypoxia (2-9% O-2) on the biology of MSCs. Finally it is concluded that a hypoxic environment can greatly improve growth kinetics, genetic stability, and expression of chemokine receptors during in vitro expansion and eventually can increase efficiency of MSC-based regenerative therapies.Article Link: http://www.hindawi.com/journals/tswj/2013/632972

Sample Size Evaluation and Comparison of K-Means Clusterings of RNA-Seq Gene Expression Data

The process by which DNA is transformed into gene products, such as RNA and proteins, is called gene expression. Gene expression profiling quantifies the expression of genes (amount of RNA) in a particular tissue at a particular time. Two commonly used high-throughput techniques for gene expression analysis are DNA microarrays and RNA-Seq, with RNA-Seq being the newer technique based on high-throughput sequencing. Statistical analysis is needed to deal with complex datasets — one commonly used statistical tool is clustering. Clustering comparison is an existing area dedicated to comparing multiple clusterings from one or more clustering algorithms. However, there has been limited application of cluster comparisons to clusterings of RNA-Seq gene expression data. In particular, cluster comparisons are useful in order to test the differences between clusterings obtained using a single algorithm when using different samples for clustering. Here we use a metric for cluster comparisons that is a variation of existing metrics. The metric is simply the minimal number of genes that need to be moved from one cluster to another in one given clustering to produce another given clustering. As the metric only has genes (or elements) as units, it is easy to interpret for RNA-Seq analysis. Moreover, three different algorithmic techniques — brute force, branch-and-bound, and maximal bipartite matching — for computing the proposed metric exactly are compared in terms of time to compute, with bipartite matching being significantly more time efficient. This metric is then applied to the important issue of understanding the effect of increasing the number of RNA-Seq samples to clusterings. Three datasets were used where a large number of samples were available: mouse embryonic stem cell tissue data, Drosophila melanogaster data from multiple tissues and micro-climates, and a mouse multi-tissue dataset. For each, a reference clustering was computed from all of the samples, and then it was compared to clusterings created from smaller subsets of the samples. All clusterings were created using a standard heuristic K-means clustering algorithm, while also systematically varying the numbers of clusters, and also using both Euclidean distance and Manhattan distance. The clustering comparisons suggest that for the three large datasets tested, there seems to be a limited impact of adding more RNA-Seq samples on K-means clusterings using both Euclidean distance and Manhattan distance (Manhattan distance gives a higher variation) beyond some small number of samples. That is, the clusterings compiled based on a limited number of samples were all either quite similar to the reference clustering or did not improve as additional samples were added. These findings were the same for different numbers of clusters. The methods developed could also be applied to other clustering comparison problems

Far-Field Plasmonic Resonance Enhanced Nano-Particle Image Velocimetry within a Micro Channel

In this paper, a novel far-field plasmonic resonance enhanced nanoparticle-seeded Particle Image Velocimetry (nPIV) has been demonstrated to measure the velocity profile in a micro channel. Chemically synthesized silver nanoparticles have been used to seed the flow in the micro channel. By using Discrete Dipole Approximation (DDA), plasmonic resonance enhanced light scattering has been calculated for spherical silver nanoparticles with diameters ranging from 15nm to 200nm. Optimum scattering wavelength is specified for the nanoparticles in two media: water and air. The diffraction-limited plasmonic resonance enhanced images of silver nanoparticles at different diameters have been recorded and analyzed. By using standard PIV techniques, the velocity profile within the micro channel has been determined from the images.Comment: submitted to Review of Scientific Instrument

Deformation of a Trapped Fermi Gas with Unequal Spin Populations

The real-space densities of a polarized strongly-interacting two-component Fermi gas of $^6$Li atoms reveal two low temperature regimes, both with a fully-paired core. At the lowest temperatures, the unpolarized core deforms with increasing polarization. Sharp boundaries between the core and the excess unpaired atoms are consistent with a phase separation driven by a first-order phase transition. In contrast, at higher temperatures the core does not deform but remains unpolarized up to a critical polarization. The boundaries are not sharp in this case, indicating a partially-polarized shell between the core and the unpaired atoms. The temperature dependence is consistent with a tricritical point in the phase diagram.Comment: Accepted for publication in Physical Review Letter

Angiogenic Host Defense Peptide Ag-30/5C and Bradykinin B 2 receptor Antagonist Icatibant are G Protein Biased Agonists for MRGPRX2 in Mast Cells

AG-30/5C is an angiogenic host defense peptide that activates human mast cells (MC) via an unknown mechanism. Using short hairpin RNA–silenced human MC line LAD2 and stably transfected RBL-2H3 cells, we demonstrate that AG-30/5C induces MC degranulation via Mas-related G protein–coupled receptor X2 (MRGPRX2). Most G protein–coupled receptors signal via parallel and independent pathways mediated by G proteins and b-arrestins. AG-30/5C and compound 48/80 induced similar maximal MC degranulation via MRGPRX2, which was abolished by pertussis toxin. However, compound 48/80 induced a robust b-arrestin activation as determined by transcriptional activation following arrestin translocation (Tango), but AG-30/5C did not. Overnight culture of MC with compound 48/80 resulted in reduced cell surface MRGPRX2 expression, and this was associated with a significant decrease in subsequent MC degranulation in response to compound 48/80 or AG-30/5C. However, AG-30/5C pretreatment had no effect on cell surface MRGPRX2 expression or degranulation in response to compound 48/80 or AG-30/5C. Icatibant, a bradykinin B 2 receptor antagonist, promotes MC degranulation via MRGPRX2 and causes pseudoallergic drug reaction. Icatibant caused MC degranulation via a pertussis toxin–sensitive G protein but did not activate b-arrestin. A screen of the National Institutes of Health Clinical Collection library led to the identification of resveratrol as an inhibitor of MRGPRX2. Resveratrol inhibited compound 48/80–induced Tango and MC degranulation in response to compound 48/80, AG-30/5C, and Icatibant. This study demonstrates the novel finding that AG-30/5C and Icatibant serve as G protein–biased agonists for MRGPRX2, but compound 48/80 signals via both G protein and b-arrestin with distinct differences in receptor regulation. Copyright © 2019 by The American Association of Immunologists, Inc. All rights reserve

Elastic scattering of electrons and positrons from In-115 atoms over the energy range 1 eV-0.5 GeV

We present a theoretical study on the calculations of various cross sections related to the scattering of electrons and positrons from indium atoms. Our calculations cover the energy range 1 eV <= E-i <= 0.5 GeV. We have employed two approaches, applicable for two domains of energy, based on the Dirac partial-wave analysis. In one approach, we have used both the atomic and nuclear potentials to calculate the cross sections for the low and intermediate energies. The other approach, valid for the high-energy scattering, utilizes only the nuclear potential for the phase-shift analysis, and considers the magnetic scattering from the nucleus too. We report the calculations of differential, integral, momentum-transfer and viscosity cross sections along with the spin asymmetries for the elastic scattering of electrons and positrons. Moreover, we have analyzed the critical minima in the elastic differential cross sections, and also computed the absorption and total cross sections. Our results agree reasonably with the available experimental data and other calculations

Neglected Heterogeneity and Dynamics in Cross-country Savings Regressions

This paper examines the extent to which the conclusions of cross-country studies of private savings are robust to allowing for the possible heterogeneity of savings behaviour across countries and for the inclusion of dynamics. It reviews the econometric implications of neglected slope heterogeneity and dynamics for the fixed effects estimators routinely used in such studies, and illustrates the nature and extent of the biases involved by a re-examination of time series data from 21 OECD countries. The paper shows that neglecting heterogeneity and dynamics in cross-country savings regressions can lead to misleading inferences about the key determinants of savings behaviour. The results indicate that among the many variables considered in the literature only the fiscal variables - the general government surplus as a proportion of GDP and the ratio of government consumption to GDP - seem to be the key determinants of private savings rates in the industrial countries in the post-World War II periodSavings behaviour, Cross-country studies. Slope heterogeneity, Dynamics, Panel data models