University of Pittsburgh

About: University of Pittsburgh is a education organization based out in Pittsburgh, Pennsylvania, United States. It is known for research contribution in the topics: Population & Transplantation. The organization has 87042 authors who have published 201012 publications receiving 9656783 citations. The organization is also known as: Pitt & Western University of Pennsylvania.

Type i membranes, phase resetting curves, and synchrony

Abstract: Type I membrane oscillators such as the Connor model (Connor et al. 1977) and the Morris-Lecar model (Morris and Lecar 1981) admit very low frequency oscillations near the critical applied current. Hansel et al. (1995) have numerically shown that synchrony is difficult to achieve with these models and that the phase resetting curve is strictly positive. We use singular perturbation methods and averaging to show that this is a general property of Type I membrane models. We show in a limited sense that so called Type II resetting occurs with models that obtain rhythmicity via a Hopf bifurcation. We also show the differences between synapses that act rapidly and those that act slowly and derive a canonical form for the phase interactions.

Content analysis of online discussion in an applied educational psychology course

Abstract: This study analyzed discussion in an online conferencethat supplemented class discussion using aninstructional method called the starter-wrappertechnique within a traditional graduate leveleducational psychology course. Various quantitativemeasures were recorded to compare instructor andstudent participation rates. In addition, Henri's(1992) model for content analysis of computer-mediatedcommunication was employed to qualitatively analyzethe electronic discourse. Using this model, five keyvariables were examined: (1) student participationrates; (2) electronic interaction patterns; (3) socialcues within student messages; (4) cognitive andmetacognitive components of student messages; and (5)depth of processing -- surface or deep -- within messageposting. Transcript content analyses showed that,while students tended to post just the one requiredcomment per week in the conference, their messageswere lengthy, cognitively deep, embedded with peerreferences, and indicative of a student orientedenvironment. Moreover, students were using high levelcognitive skills such as inferencing and judgment aswell as metacognitive strategies related to reflectingon experience and self-awareness. Weekly conferenceactivity graphs revealed that student electroniccomments became more interactive over time, but werehighly dependent on the directions of discussionstarter. To better understand the impact ofelectronic conferencing discourse, modifications toHenri's model as well as qualitative researchsuggestions were offered.

Mapping the Genetic Architecture of Gene Expression in Human Liver

Abstract: Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process.