Institution
University of Iowa
Education•Iowa City, Iowa, United States•
About: University of Iowa is a education organization based out in Iowa City, Iowa, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 49229 authors who have published 109171 publications receiving 5021465 citations. The organization is also known as: UI & The University of Iowa.
Topics: Population, Poison control, Large Hadron Collider, Health care, Gene
Papers published on a yearly basis
Papers
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TL;DR: Not only are oxygen radicals involved in the cause of diabetes, they also appear to play a role in some of the complications seen in long-term treatment of diabetes.
1,136 citations
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TL;DR: In this article, the authors proposed a logistic regression model with maximum likelihood estimators for solving both problems and reported on their own supportive empirical studies, and summarized the related arguments.
Abstract: Classifying an observation into one of several populations is discriminant analysis, or classification. Relating qualitative variables to other variables through a logistic cdf functional form is logistic regression. Estimators generated for one of these problems are often used in the other. If the populations are normal with identical covariance matrices, discriminant analysis estimators are preferred to logistic regression estimators for the discriminant analysis problem. In most discriminant analysis applications, however, at least one variable is qualitative (ruling out multivariate normality). Under nonnormality, we prefer the logistic regression model with maximum likelihood estimators for solving both problems. In this article we summarize the related arguments, and report on our own supportive empirical studies.
1,134 citations
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TL;DR: DNA microarrays show that gene expression in biofilm cells is similar to that in free-living cells but there are a small number of significant differences, which points to mechanisms of biofilm resistance to antibiotics.
Abstract: Bacteria often adopt a sessile biofilm lifestyle that is resistant to antimicrobial treatment. Opportunistic pathogenic bacteria like Pseudomonas aeruginosa can develop persistent infections. To gain insights into the differences between free-living P. aeruginosa cells and those in biofilms, and into the mechanisms underlying the resistance of biofilms to antibiotics, we used DNA microarrays. Here we show that, despite the striking differences in lifestyles, only about 1% of genes showed differential expression in the two growth modes; about 0.5% of genes were activated and about 0.5% were repressed in biofilms. Some of the regulated genes are known to affect antibiotic sensitivity of free-living P. aeruginosa. Exposure of biofilms to high levels of the antibiotic tobramycin caused differential expression of 20 genes. We propose that this response is critical for the development of biofilm resistance to tobramycin. Our results show that gene expression in biofilm cells is similar to that in free-living cells but there are a small number of significant differences. Our identification of biofilm-regulated genes points to mechanisms of biofilm resistance to antibiotics.
1,134 citations
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01 Jan 2008TL;DR: In this paper, the authors focus on the role of motivational processes, such as goals, attributions, selfefficacy, outcome expectations, selfconcept, self-esteem, social comparisons, emotions, values, and self-evaluations, in self-regulated learning.
Abstract: This volume focuses on the role of motivational processes - such as goals, attributions, self-efficacy, outcome expectations, self-concept, self-esteem, social comparisons, emotions, values, and self-evaluations- in self-regulated learning. It provides theoretical and empirical evidence demonstrating the role of motivation in self-regulated learning, and discusses detailed applications of the principles of motivation and self-regulation in educational contexts. Each chapter includes a description of the motivational variables, the theoretical rationale for their importance, research evidence to support their role in self-regulation, suggestions for ways to incorporate motivational variables into learning contexts to foster self-regulatory skill development, and achievement outcomes.
1,133 citations
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15 Dec 2003TL;DR: Reader's Guide Contributors About the Editors Preface Introduction Entries Volume I: A-F Volume II: G-P Volume III: Q-Z Appendix: Bibliography Index List of Entries as mentioned in this paper
Abstract: Reader's Guide Contributors About the Editors Preface Introduction Entries Volume I: A-F Volume II: G-P Volume III: Q-Z Appendix: Bibliography Index List of Entries
1,132 citations
Authors
Showing all 49661 results
Name | H-index | Papers | Citations |
---|---|---|---|
Stephen V. Faraone | 188 | 1427 | 140298 |
Jie Zhang | 178 | 4857 | 221720 |
D. M. Strom | 176 | 3167 | 194314 |
Bradley T. Hyman | 169 | 765 | 136098 |
John H. Seinfeld | 165 | 921 | 114911 |
David Jonathan Hofman | 159 | 1407 | 140442 |
Stephen J. O'Brien | 153 | 1062 | 93025 |
John T. Cacioppo | 147 | 477 | 110223 |
Mark Raymond Adams | 147 | 1187 | 135038 |
E. L. Barberio | 143 | 1605 | 115709 |
Andrew Ivanov | 142 | 1812 | 97390 |
Stephen J. Lippard | 141 | 1201 | 89269 |
Russell Richard Betts | 140 | 1323 | 95678 |
Barry Blumenfeld | 140 | 1909 | 105694 |
Marcus Hohlmann | 140 | 1356 | 94739 |