Self-prioritization and perceptual matching: The effects of temporal construal.

Recent research has revealed that self-referential processing enhances perceptual judgments - the so-called self-prioritization effect. The extent and origin of this effect remains unknown, however. Noting the multifaceted nature of the self, here we hypothesized that temporal influences on self-construal (i.e., past/future-self continuity) may serve as an important determinant of stimulus prioritization. Specifically, as representations of the self increase in abstraction as a function of temporal distance (i.e., distance from now), self-prioritization may only emerge when stimuli are associated with the current self. The results of three experiments supported this prediction. Self-relevance only enhanced performance in a standard perceptual-matching task when stimuli (i.e., geometric shapes) were connected with the current self; representations of the self in the future (Expts. 1 & 2) and past (Expt. 3) failed to facilitate decision making. To identify the processes underlying task performance, data were interrogated using a hierarchical drift diffusion model (HDDM) approach. Results of these analyses revealed that self-prioritization was underpinned by a stimulus bias (i.e., rate of information uptake). Collectively, these findings elucidate when and how self-relevance influences decisional processing

HIF1α drives chemokine factor pro-tumoral signaling pathways in acute myeloid leukemia

Approximately 80% of patients diagnosed with acute myeloid leukemia (AML) die as a consequence of failure to eradicate the tumor from the bone marrow microenvironment. We have recently shown that stroma-derived interleukin-8 (IL-8) promotes AML growth and survival in the bone marrow in response to AML-derived macrophage migration inhibitory factor (MIF). In the present study we show that high constitutive expression of MIF in AML blasts in the bone marrow is hypoxia-driven and, through knockdown of MIF, HIF1α and HIF2α, establish that hypoxia supports AML tumor proliferation through HIF1α signaling. In vivo targeting of leukemic cell HIF1α inhibits AML proliferation in the tumor microenvironment through transcriptional regulation of MIF, but inhibition of HIF2α had no measurable effect on AML blast survival. Functionally, targeted inhibition of MIF in vivo improves survival in models of AML. Here we present a mechanism linking HIF1α to a pro-tumoral chemokine factor signaling pathway and in doing so, we establish a potential strategy to target AML

Active learning and optimal climate policy

This paper develops a climate-economy model with uncertainty, irreversibility, and active learning. Whereas previous papers assume learning from one observation per period, or experiment with control variables to gain additional information, this paper considers active learning from investment in monitoring, specifically in improved observations of the global mean temperature. We find that the decision maker invests a significant amount of money in climate research, far more than the current level, in order to increase the rate of learning about climate change. This helps the decision maker make improved decisions. The level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations. As the uncertainty about climate change is smaller, active learning reduces the optimal carbon tax. The greater the risk, the larger is the effect of learning. The method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable, for instance, the precision at which we observe GDP, unemployment, or the quality of education

Year in review in Intensive Care Medicine 2009: I. Pneumonia and infections, sepsis, outcome, acute renal failure and acid base, nutrition and glycaemic control

Journal ArticleReviewSCOPUS: re.jinfo:eu-repo/semantics/publishe

Tracing the HIV-1 subtype B mobility in Europe: a phylogeographic approach

<p>Abstract</p> <p>Background</p> <p>The prevalence and the origin of HIV-1 subtype B, the most prevalent circulating clade among the long-term residents in Europe, have been studied extensively. However the spatial diffusion of the epidemic from the perspective of the virus has not previously been traced.</p> <p>Results</p> <p>In the current study we inferred the migration history of HIV-1 subtype B by way of a phylogeography of viral sequences sampled from 16 European countries and Israel. Migration events were inferred from viral phylogenies by character reconstruction using parsimony. With regard to the spatial dispersal of the HIV subtype B sequences across viral phylogenies, in most of the countries in Europe the epidemic was introduced by multiple sources and subsequently spread within local networks. Poland provides an exception where most of the infections were the result of a single point introduction. According to the significant migratory pathways, we show that there are considerable differences across Europe. Specifically, Greece, Portugal, Serbia and Spain, provide sources shedding HIV-1; Austria, Belgium and Luxembourg, on the other hand, are migratory targets, while for Denmark, Germany, Italy, Israel, Norway, the Netherlands, Sweden, Switzerland and the UK we inferred significant bidirectional migration. For Poland no significant migratory pathways were inferred.</p> <p>Conclusion</p> <p>Subtype B phylogeographies provide a new insight about the geographical distribution of viral lineages, as well as the significant pathways of virus dispersal across Europe, suggesting that intervention strategies should also address tourists, travellers and migrants.</p

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Modelling the Geographical Origin of Rice Cultivation in Asia Using the Rice Archaeological Database

We have compiled an extensive database of archaeological evidence for rice across Asia, including 400 sites from mainland East Asia, Southeast Asia and South Asia. This dataset is used to compare several models for the geographical origins of rice cultivation and infer the most likely region(s) for its origins and subsequent outward diffusion. The approach is based on regression modelling wherein goodness of fit is obtained from power law quantile regressions of the archaeologically inferred age versus a least-cost distance from the putative origin(s). The Fast Marching method is used to estimate the least-cost distances based on simple geographical features. The origin region that best fits the archaeobotanical data is also compared to other hypothetical geographical origins derived from the literature, including from genetics, archaeology and historical linguistics. The model that best fits all available archaeological evidence is a dual origin model with two centres for the cultivation and dispersal of rice focused on the Middle Yangtze and the Lower Yangtze valleys