Legitimacy, communication and leadership in the Turnaround game

We study the effectiveness of leaders for inducing coordinated organizational change to a more efficient equilibrium, i.e., a turnaround. We compare communication from leaders to incentive increases and also compare the effectiveness of randomly selected and elected leaders. While all interventions yield shifts to more efficient equilibria, communication from leaders has a greater effect than incentives. Moreover, leaders who are elected by followers are significantly better at improving their group's outcome than randomly selected ones. The improved effectiveness of elected leaders results from sending more performance-relevant messages. Our results are evidence that the way in which leaders are selected affects their legitimacy and the degree to which they influence followers. Finally, we observed that a combination of factors- incentive increases and elected leaders-yield near universal turnarounds to full efficiency

Heavy-ion Results of the CMS Experiment

An overview of selected heavy-ion results of the CMS experiment is presented. Jet quenching, quarkonia suppression and two-particle angular correlation results are discussed. The measurements have been performed for lead–lead, proton–lead and proton–proton data samples recorded for Run 1 of the LHC accelerator. In the correlation analysis, low pile-up proton–proton collisions at an energy of 13 TeV (from Run 2) have been used as wel

Additional file 1: Table S1. of Long-term prenatal exposure to paracetamol is associated with DNA methylation differences in children diagnosed with ADHD

Significantly methylated CpGs between long-term exposed samples with ADHD and controls. (XLSX 1646 kb

Additional file 1: Table S1. of cnvScan: a CNV screening and annotation tool to improve the clinical utility of computational CNV prediction from exome sequencing data

Statistical methods used to calculate CNV quality scores. Table S2. CNVQ ratio for common TP CNVs. Table S3. Format of the cnvScan input file. Figure S1. Overview of cnvScan algorithm. Figure S2. CNV length vs Quality score for five CNV prediction programs. Figure S3. GC % vs Quality score for five CNV prediction programs. Figure S4. Length of simple repeats internal to CNVs vs Quality score for five CNV prediction programs. Figure S5a. Coverage of duplications vs Quality score for five CNV prediction programs. Figure S5b. Coverage of deletions vs Quality score for five CNV prediction programs. Figure S6. TP and FP counts in the in-house CNV database. Figure S7. Comparison of filtration efficiency using default quality score, CNVQ, database CNV count. Figure S8. Filtration efficiency of XHMM. Text S1. In-house database creation. Text S2. Thresholds used in CoNIFER and XHMM predictions. (PDF 2191 kb

RNA-Sequencing Analysis of HepG2 Cells Treated with Atorvastatin

<div><p>The cholesterol-lowering drug atorvastatin is among the most prescribed drug in the world. Alternative splicing in a number of genes has been reported to be associated with variable statin response. RNA-seq has proven to be a powerful technique for genome-wide splice variant analysis. In the present study, we sought to investigate atorvastatin responsive splice variants in HepG2 cells using RNA-seq analysis to identify novel candidate genes implicated in cholesterol homeostasis and in the statin response. HepG2 cells were treated with 10 µM atorvastatin for 24 hours. RNA-seq and exon array analyses were performed. The validation of selected genes was performed using Taqman gene expression assays. RNA-seq analysis identified 121 genes and 98 specific splice variants, of which four were minor splice variants to be differentially expressed, 11 were genes with potential changes in their splicing patterns (<i>SYCP3, ZNF195, ZNF674, MYD88, WHSC1, KIF16B, ZNF92, AGER, FCHO1, SLC6A12</i> and <i>AKAP9</i>), and one was a gene (<i>RAP1GAP</i>) with differential promoter usage. The <i>IL21R</i> transcript was detected to be differentially expressed via RNA-seq and RT-qPCR, but not in the exon array. In conclusion, several novel candidate genes that are affected by atorvastatin treatment were identified in this study. Further studies are needed to determine the biological significance of the atorvastatin responsive splice variants that have been uniquely identified using RNA-seq.</p></div

The 11 genes uniquely identified by differential expression analysis of transcript splice variants, but not identified by differential gene expression analysis, are shown.

<p>The 11 genes uniquely identified by differential expression analysis of transcript splice variants, but not identified by differential gene expression analysis, are shown.</p

Hair cortisol concentrations (pg/mg) and depression scores (EPDS sum).

<p>The relationship between hair cortisol concentrations (pg/mg) and depression scores (EPDS sum) showed a non-significant Pearson correlation of 0.096.</p

RNA-seq and exon array expression values.

<p>A comparison of RNA-seq FPKM and exon array RMA intensity values for the 17,151 genes detected using both methods in HepG2 control cells (<i>R</i> = 0.81) is shown. Significantly differentially expressed genes identified by RNA-seq are highlighted in red.</p

Top biological functions identified by Ingenuity Pathway Analysis affected by atorvastatin treatment.

<p>The number of differentially expressed genes associated with functional categories in atorvastatin treated HegG2 cells is shown. Note that several genes are represented in more than one category. A complete list of the biological functions and associated genes is presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105836#pone.0105836.s014" target="_blank">Table S1</a>.</p

Top five canonical pathways associated with the differentially expressed genes (n = 121) in atorvastatin treated HepG2 cells identified by Ingenuity Pathway Analysis.

<p>Canonical pathways are ordered by p-value. The ratio shows the number of genes in the dataset divided by the number of genes in the pathway. A complete list of the canonical pathways and associated genes is presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105836#pone.0105836.s015" target="_blank">Table S2</a>.</p