Normics: Proteomic Normalization by Variance and Data-Inherent Correlation Structure

Several algorithms for the normalization of proteomic data are currently available, each based on a priori assumptions. Among these is the extent to which differential expression (DE) can be present in the dataset. This factor is usually unknown in explorative biomarker screens. Simultaneously, the increasing depth of proteomic analyses often requires the selection of subsets with a high probability of being DE to obtain meaningful results in downstream bioinformatical analyses. Based on the relationship of technical variation and (true) biological DE of an unknown share of proteins, we propose the “Normics” algorithm: Proteins are ranked based on their expression level–corrected variance and the mean correlation with all other proteins. The latter serves as a novel indicator of the non-DE likelihood of a protein in a given dataset. Subsequent normalization is based on a subset of non-DE proteins only. No a priori information such as batch, clinical, or replicate group is necessary. Simulation data demonstrated robust and superior performance across a wide range of stochastically chosen parameters. Five publicly available spike-in and biologically variant datasets were reliably and quantitively accurately normalized by Normics with improved performance compared to standard variance stabilization as well as median, quantile, and LOESS normalizations. In complex biological datasets Normics correctly determined proteins as being DE that had been cross-validated by an independent transcriptome analysis of the same samples. In both complex datasets Normics identified the most DE proteins. We demonstrate that combining variance analysis and data-inherent correlation structure to identify non-DE proteins improves data normalization. Standard normalization algorithms can be consolidated against high shares of (one-sided) biological regulation. The statistical power of downstream analyses can be increased by focusing on Normics-selected subsets of high DE likelihood

What children know about the source of their knowledge without reporting it as the source

We argue that, amongst 3- to 5- year-olds, failure to report the source of knowledge recently acquired in answer to “How do you know…?” is due to a specific failure to make a causal inference, in line with source monitoring theory but not fuzzy trace theory. In three Experiments, children (N = 37; 30; 59) identified a hidden toy by seeing, feeling, or by being told, having had two modes of access on each trial, one informative (e.g. seeing a toy identified by colour) and the other uninformative (e.g. being told the toy’s colour by the Experimenter who had only felt it). Children who answered the know question wrongly nevertheless reported accurately who saw and who felt the toy, and what the well-informed player had said. They also realised when the Experimenter’s uninformative access implied their own knowledge was unreliable, suggesting precocious working understanding of knowledge sources

Recognition memory, self-other source memory, and theory-of-mind in children with autism spectrum disorder.

This study investigated semantic and episodic memory in autism spectrum disorder (ASD), using a task which assessed recognition and self-other source memory. Children with ASD showed undiminished recognition memory but significantly diminished source memory, relative to age- and verbal ability-matched comparison children. Both children with and without ASD showed an “enactment effect”, demonstrating significantly better recognition and source memory for self-performed actions than other-person-performed actions. Within the comparison group, theory-of-mind (ToM) task performance was significantly correlated with source memory, specifically for other-person-performed actions (after statistically controlling for verbal ability). Within the ASD group, ToM task performance was not significantly correlated with source memory (after controlling for verbal ability). Possible explanations for these relations between source memory and ToM are considered

Relationship Between Hyperglycemia and Infection in Critically Ill Patients

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90178/1/phco.2005.25.7.963.pd

Delayed self-recognition in children with autism spectrum disorder.

This study aimed to investigate temporally extended self-awareness (awareness of one’s place in and continued existence through time) in autism spectrum disorder (ASD), using the delayed self-recognition (DSR) paradigm (Povinelli et al., Child Development 67:1540–1554, 1996). Relative to age and verbal ability matched comparison children, children with ASD showed unattenuated performance on the DSR task, despite showing significant impairments in theory-of-mind task performance, and a reduced propensity to use personal pronouns to refer to themselves. The results may indicate intact temporally extended self-awareness in ASD. However, it may be that the DSR task is not an unambiguous measure of temporally extended self-awareness and it can be passed through strategies which do not require the possession of a temporally extended self-concept

High levels of soluble VEGF receptor 1 early after trauma are associated with shock, sympathoadrenal activation, glycocalyx degradation and inflammation in severely injured patients: a prospective study

<p>Abstract</p> <p>Background</p> <p>The level of soluble vascular endothelial growth factor receptor 1 (sVEGFR1) is increased in sepsis and strongly associated with disease severity and mortality. Endothelial activation and damage contribute to both sepsis and trauma pathology. Therefore, this study measured sVEGFR1 levels in trauma patients upon hospital admission hypothesizing that sVEGFR1 would increase with higher injury severity and predict a poor outcome.</p> <p>Methods</p> <p>Prospective observational study of 80 trauma patients admitted to a Level I Trauma Centre. Data on demography, biochemistry, Injury Severity Score (ISS), transfusions and 30-day mortality were recorded and plasma/serum (sampled a median of 68 min (IQR 48-88) post-injury) was analyzed for sVEGFR1 and biomarkers reflecting sympathoadrenal activation (adrenaline, noradrenaline), tissue injury (histone-complexed DNA fragments, hcDNA), endothelial activation and damage (von Willebrand Factor Antigen, Angiopoietin-2, soluble endothelial protein C receptor, syndecan-1, soluble thrombomodulin (sTM)), coagulation activation/inhibition and fibrinolysis (prothrombinfragment 1 + 2, protein C, activated Protein C, tissue-type plasminogen activator, plasminogen activator inhibitor-1, D-dimer) and inflammation (interleukin-6). Spearman correlations and regression analyses to identify variables associated with sVEGFR1 and its predictive value.</p> <p>Results</p> <p>Circulating sVEGFR1 correlated with injury severity (ISS, rho = 0.46), shock (SBE, rho = -0.38; adrenaline, rho = 0.47), tissue injury (hcDNA, rho = 0.44) and inflammation (IL-6, rho = 0.54) (all p < 0.01) but by multivariate linear regression analysis only lower SBE and higher adrenaline and IL-6 were independent predictors of higher sVEGFR1. sVEGFR1 also correlated with biomarkers indicative of endothelial glycocalyx degradation (syndecan-1, rho = 0.67), endothelial cell damage (sTM, rho = 0.66) and activation (Ang-2, rho = 0.31) and hyperfibrinolysis (tPA, rho = 0.39; D-dimer, rho = 0.58) and with activated protein C (rho = 0.31) (all p < 0.01). High circulating sVEGFR1 correlated with high early and late transfusion requirements (number of packed red blood cells (RBC) at 1 h (rho = 0.27, p = 0.016), 6 h (rho = 0.27, p = 0.017) and 24 h (rho = 0.31, p = 0.004) but was not associated with mortality.</p> <p>Conclusions</p> <p>sVEGFR1 increased with increasing injury severity, shock and inflammation early after trauma but only sympathoadrenal activation, hypoperfusion, and inflammation were independent predictors of sVEGFR1 levels. sVEGFR1 correlated strongly with other biomarkers of endothelial activation and damage and with RBC transfusion requirements. Sympathoadrenal activation, shock and inflammation may be critical drivers of endothelial activation and damage early after trauma.</p

Size-Dependent Surface Plasmon Dynamics in Metal Nanoparticles

We study the effect of Coulomb correlations on the ultrafast optical dynamics of small metal particles. We demonstrate that a surface-induced dynamical screening of the electron-electron interactions leads to quasiparticle scattering with collective surface excitations. In noble-metal nanoparticles, it results in an interband resonant scattering of d-holes with surface plasmons. We show that this size-dependent many-body effect manifests itself in the differential absorption dynamics for frequencies close to the surface plasmon resonance. In particular, our self-consistent calculations reveal a strong frequency dependence of the relaxation, in agreement with recent femtosecond pump-probe experiments.Comment: 8 pages + 4 figures, final version accepted to PR