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Population subdivision and molecular sequence variation: Theory and analysis of Drosophila ananassae data
No full textPopulation subdivision complicates analysis of molecular variation. Even if neutrality is assumed, three evolutionary forces need to be considered: migration, mutation, and drift. Simplification can be achieved by assuming that the process of migration among and drift within subpopulations is occurring fast compared to Mutation and drift in the entire population. This allows a two-step approach in the analysis: (i) analysis of population subdivision and (ii) analysis of molecular variation in the migrant pool. We model population subdivision using an infinite island model, where we allow the migration/drift parameter Theta to vary among populations. Thus, central and peripheral populations can be differentiated. For inference of Theta, we use a coalescence approach, implemented via a Markov chain Monte Carlo (MCMC) integration method that allows estimation of allele frequencies in the migrant pool. The second step of this approach (analysis of molecular variation in the migrant pool) uses the estimated allele frequencies in the migrant pool for the study of molecular variation. We apply this method to a Drosophila ananassae sequence data set. We find little indication of isolation by distance, but large differences in the migration parameter among populations. The population as a whole seems to be expanding. A population from Bogor (Java, Indonesia) shows the highest variation and seems closest to the species center
Retablo del Padre Cosme Muñoz
No full textIglesia del Colegio de Nuestra Señora de la PiedadFondo de Recuperación Next Generation E
Additional file 1 of Body weight changes in patients with type 2 diabetes and a recent acute coronary syndrome: an analysis from the EXAMINE trial
No full textAdditional file 1: Table S1. Baselinecharacteristics of the patients by 10% weight change from baseline. Table S2. Effect of alogliptin onweight change ≥5% and ≥10%. Table S3.Association of body mass index with outcomes. Figure S1. Histogram representing the weight changes throughout thefollow-up
Effect of the inhibition of Gal-3 on general and renal parameters in AS rats.
No full textEffect of the inhibition of Gal-3 on general and renal parameters in AS rats.</p
Effect of sST2 on the IL-33/ST2 pathway in VSMCs.
No full text<p>Representative pictures of immunocytochemistry for IL-33, ST2, MyD88 and IRAK-1 are presented (<b>A</b>). mRNA levels of IL-33, sST2 and ST2L in VSMCs stimulated with sST2 (2 µg/ml) (<b>B</b>). Protein levels of IL-33, ST2-L, MyD88 and IRAK-1 are shown (<b>C</b>). All conditions were performed at least by triplicate. Histogram bars represent the mean ± SEM of 4 assays, in arbitrary units normalized to HPRT and β-actin respectively for cDNA and protein. *p<0.05 <i>vs</i>. control.</p
Effects of pharmacological inhibition of Gal-3 on renal damage in obese rats.
No full textExpression of mRNA of Gal-3 (A). Quantification of fibrotic markers expression (B). Representative microphotographs of renal sections stained with Sirius red (C). Quantification of tubulointerstitial fibrosis (D). Expression of epithelial-mesenchymal transition molecules (E). Expression of inflammatory mediators (F). Expression of kidney damage markers (G). Magnification of the microphotographs 40x. Histogram bars represent the mean ± SEM of each group of animals (n ≥ 7 per group) in arbitrary units or as a percentage of staining normalized to HPRT and β-actin for cDNA. *p$p<0.05 vs HFD group.</p
Aortic composition in HFD rats.
No full text<p>Aortas from rats fed a standard diet (3.5% fat) or a high fat diet (HFD, 33.5% fat) were analyzed. Representative pictures of slides stained for collagen and elastin are presented (magnification 40X) (<b>A</b>). mRNA expression of collagen type I, fibronectin, TGF-β, CTGF in aorta from controls and HFD rats (<b>B</b>). Protein expression of collagen type I, elastin, MMP-2, TIMP-2, TGF-β and CTGF in aorta from controls and HFD rats (<b>C</b>). All conditions were performed at least by triplicate. Scale bar 50 µm. Histogram bars represent the mean ± SEM of 6–7 animals, in arbitrary units normalized to HPRT and β-actin for cDNA and protein respectively. *p<0.05; ***p<0.001 <i>vs</i>. control group.</p
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