The Symmetry of Partner Modelling

© 2016, International Society of the Learning Sciences, Inc. Collaborative learning has often been associated with the construction of a shared understanding of the situation at hand. The psycholinguistics mechanisms at work while establishing common grounds are the object of scientific controversy. We postulate that collaborative tasks require some level of mutual modelling, i.e. that each partner needs some model of what the other partners know/want/intend at a given time. We use the term “some model” to stress the fact that this model is not necessarily detailed or complete, but that we acquire some representations of the persons we interact with. The question we address is: Does the quality of the partner model depend upon the modeler’s ability to represent his or her partner? Upon the modelee’s ability to make his state clear to the modeler? Or rather, upon the quality of their interactions? We address this question by comparing the respective accuracies of the models built by different team members. We report on 5 experiments on collaborative problem solving or collaborative learning that vary in terms of tasks (how important it is to build an accurate model) and settings (how difficult it is to build an accurate model). In 4 studies, the accuracy of the model that A built about B was correlated with the accuracy of the model that B built about A, which seems to imply that the quality of interactions matters more than individual abilities when building mutual models. However, these findings do not rule out the fact that individual abilities also contribute to the quality of modelling process

Multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci

Genome-wide association studies (GWASs) have identified hundreds of risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWASs, and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotypes to identify quantitative trait loci for expression (eQTLs) and splicing (sQTLs) in coronary arteries from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary artery; 19% exhibited cell-type-specific expression. Colocalization revealed subgroups of eGenes unique to CAD and blood pressure GWAS. Fine-mapping highlighted additional eGenes, including TBX20 and IL5. We also identified sQTLs for 1,690 genes, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing to accurately identify disease-relevant isoform expression. Our work provides a patient-derived coronary artery eQTL resource and exemplifies the need for diverse study populations and multifaceted approaches to characterize gene regulation in disease processes.</p

Multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci

Genome-wide association studies (GWASs) have identified hundreds of risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWASs, and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotypes to identify quantitative trait loci for expression (eQTLs) and splicing (sQTLs) in coronary arteries from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary artery; 19% exhibited cell-type-specific expression. Colocalization revealed subgroups of eGenes unique to CAD and blood pressure GWAS. Fine-mapping highlighted additional eGenes, including TBX20 and IL5. We also identified sQTLs for 1,690 genes, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing to accurately identify disease-relevant isoform expression. Our work provides a patient-derived coronary artery eQTL resource and exemplifies the need for diverse study populations and multifaceted approaches to characterize gene regulation in disease processes.</p

The Dichotomous Pattern of IL-12R and IL-23R Expression Elucidates the Role of IL-12 and IL-23 in Inflammation

IL-12 and IL-23 cytokines respectively drive Th1 and Th17 type responses. Yet, little is known regarding the biology of these receptors. As the IL-12 and IL-23 receptors share a common subunit, it has been assumed that these receptors are co-expressed. Surprisingly, we find that the expression of each of these receptors is restricted to specific cell types, in both mouse and human. Indeed, although IL-12Rβ2 is expressed by NK cells and a subset of γδ T cells, the expression of IL-23R is restricted to specific T cell subsets, a small number of B cells and innate lymphoid cells. By exploiting an IL-12- and IL-23-dependent mouse model of innate inflammation, we demonstrate an intricate interplay between IL-12Rβ2 NK cells and IL-23R innate lymphoid cells with respectively dominant roles in the regulation of systemic versus local inflammatory responses. Together, these findings support an unforeseen lineage-specific dichotomy in the in vivo role of both the IL-12 and IL-23 pathways in pathological inflammatory states, which may allow more accurate dissection of the roles of these receptors in chronic inflammatory diseases in humans

Multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci

Genome-wide association studies (GWASs) have identified hundreds of risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWASs, and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotypes to identify quantitative trait loci for expression (eQTLs) and splicing (sQTLs) in coronary arteries from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary artery; 19% exhibited cell-type-specific expression. Colocalization revealed subgroups of eGenes unique to CAD and blood pressure GWAS. Fine-mapping highlighted additional eGenes, including TBX20 and IL5. We also identified sQTLs for 1,690 genes, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing to accurately identify disease-relevant isoform expression. Our work provides a patient-derived coronary artery eQTL resource and exemplifies the need for diverse study populations and multifaceted approaches to characterize gene regulation in disease processes

Routine gastric residual volume measurement and energy target achievement in the PICU: A comparison study

Critically ill children frequently fail to achieve adequate energy intake and some care practices, such as the measurement of gastric residual volume (GRV) may contribute to this problem. We compared outcomes in two similar European Pediatric Intensive Care Units (PICUs): one which routinely measures GRV (PICU-GRV) to one unit that does not (PICU-noGRV). An observational pilot comparison study was undertaken. 87 children were included in the study, 42 (PICU-GRV) and 45 (PICU-noGRV). There were no significant differences in the percentage of energy targets achieved in the first four days of PICU admission although PICU-noGRV showed more consistent delivery of median (and IQR) energy targets, and less under and over feeding for PICU-GRV and PICU-noGRV Day 1 37 (14-72) vs 44 (0-100); Day 2 97 (53-126) vs 100 (100-100), Day 3 84 (45-112) vs 100 (100-100) , Day 4 101 (63-124) vs 100 (100-100). The incidence of vomiting was higher in PICU-GRV. No necrotising enterocolitis was confirmed in either unit and ventilator acquired pneumonia rates were not significantly different (7.01 vs 12 5.31 per 1000 ventilator days; p=0.70) between PICU-GRV and PICU-noGRV units. Conclusions: The practice of routine gastric residual measurement did not significantly impair energy targets in the first four days of PICU admission. However, not measuring GRV did not increase vomiting, ventilator acquired pneumonia or necrotising enterocolitis, which is the main reason clinicians cite for measuring GRV. What is known?•The practice of routinely measuring gastric residual volume is widespread in critical care units•This practice is increasingly being questioned in critically ill patients, both as a practice that increases •the likelihood of delivering inadequate enteral nutrition amounts and as a tool to assess feeding tolerance What is new? •Not routinely measuring gastric residual volume did not increase adverse events of ventilator acquired pneumonia, necrotising enterocolitis or vomiting •In the first four days of PICU stay, energy target achievement was not significantly different, but the rates of under and over feeding were higher in the routine GRV measurement uni

IL-12Rβ2+ and IL-23R+ innate immune cells both contribute to the systemic inflammatory response.

<p>C57BL/6.Rag1^−/−, IL-23R^−/−.Rag1^−/−, and IL-12Rβ2^−/−.Rag1^−/− mice were injected with anti-CD40 antibody or PBS (6 to 11 mice per group). (A) Mouse weight relative to the initial weight is shown. a, b p<0.05. (B) Day 7 serum concentrations of IFN-γ, IL-1β, IL-6, IL-12p70, IL-18, IL-23p19, TNF-α, CCL-2 and CXCL1 were quantified. Each symbol represents data for one mouse. *<i>p</i><0.05, **<i>p</i><0.01.</p

<i>Il23r</i> expressing cells exhibit a mixed Th1/Th17 signature profile.

<p>(A) The relative mRNA transcription level of <i>Rorc</i>, <i>Il17a</i>, <i>Il22</i>, <i>Tbx21</i>, and <i>Ifng</i> in sorted murine spleen cells is shown. (B) The relative mRNA transcription level of <i>Il23r</i>, <i>Il12rb1</i>, <i>Il12rb2</i>, <i>Rorc</i>, <i>Il17a</i>, <i>Tbx21</i> and <i>Ifng</i> in γδ T cells from RORγt^−/− mice is shown. (C) The relative mRNA transcription level of <i>Il23r</i>, <i>Il12rb1</i>, <i>Il12rb2</i>, <i>Rorc</i>, <i>Il17a</i>, <i>Il22</i>, <i>Tbx21</i> and <i>Ifng</i> in IL23R-eGFP sorted spleen cells and NK cells is shown. For all panels, the horizontal bar represents the mean of each group and each symbol represents one sample.*, <i>p</i><0.05 compared to each group.</p