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Institution

University of Virginia

EducationCharlottesville, Virginia, United States
About: University of Virginia is a education organization based out in Charlottesville, Virginia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 52543 authors who have published 113268 publications receiving 5220506 citations. The organization is also known as: U of V & UVa.


Papers
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Journal ArticleDOI
25 Aug 2006-Cell
TL;DR: The dynamic but coordinated changes in nuclear receptor expression, along with their key target genes, offers a logical explanation for known cyclic behavior of lipid and glucose metabolism and suggests novel roles for endocrine and orphan receptors in coupling the peripheral circadian clock to divergent metabolic outputs.

900 citations

Journal ArticleDOI
TL;DR: This review focuses on recent literature that describes how CNT-based electrochemical sensors are being developed to detect neurotransmitters, proteins, small molecules such as glucose, and DNA.

899 citations

Journal ArticleDOI
TL;DR: In this article, the monotonic and cyclic mechanical behavior of O-temper AZ31B Mg sheet was measured in large-strain tension/compression and simple shear.

897 citations

Journal ArticleDOI
TL;DR: The authors argue that individual performance in knowledge-intensive work is associated with properties of both networks and ties, and that such properties are associated with relationships crossing organizational boundaries, physical barriers, or physical barriers.
Abstract: We argue that individual performance in knowledge-intensive work is associated with properties of both networks and ties. Relationships crossing organizational boundaries, physical barriers, or hie...

896 citations

Journal ArticleDOI
20 May 2012-Spine
TL;DR: Data from this study show that there is excellent inter- and intra- rater reliability and inter-rater agreement for curve type and each modifier and the high degree of reliability demonstrates that applying the classification system is easy and consistent.
Abstract: Study design Inter- and intra-rater variability study. Objective On the basis of a Scoliosis Research Society effort, this study seeks to determine whether the new adult spinal deformity (ASD) classification system is clear and reliable. Summary of background data A classification of adult ASD can serve several purposes, including consistent characterization of a clinical entity, a basis for comparing different treatments, and recommended treatments. Although pediatric scoliosis classifications are well established, an ASD classification is still being developed. A previous classification developed by Schwab et al has met with clinical relevance but did not include pelvic parameters, which have shown substantial correlation with health-related quality of life measures in recent studies. Methods Initiated by the Scoliosis Research Society Adult Deformity Committee, this study revised a previously published classification to include pelvic parameters. Modifier cutoffs were determined using health-related quality of life analysis from a multicenter database of adult deformity patients. Nine readers graded 21 premarked cases twice each, approximately 1 week apart. Inter- and intra-rater variability and agreement were determined for curve type and each modifier separately. Fleiss' kappa was used for reliability measures, with values of 0.00 to 0.20 considered slight, 0.21 to 0.40 fair, 0.41 to 0.60 moderate, 0.61 to 0.80 substantial, and 0.81 to 1.00 almost perfect agreement. Results Inter-rater kappa for curve type was 0.80 and 0.87 for the 2 readings, respectively, with modifier kappas of 0.75 and 0.86, 0.97 and 0.98, and 0.96 and 0.96 for pelvic incidence minus lumbar lordosis (PI-LL), pelvic tilt (PT), and sagittal vertical axis (SVA), respectively. By the second reading, curve type was identified by all readers consistently in 66.7%, PI-LL in 71.4%, PT in 95.2%, and SVA in 90.5% of cases. Intra-rater kappa averaged 0.94 for curve type, 0.88 for PI-LL, 0.97 for PT, and 0.97 for SVA across all readers. Conclusion Data from this study show that there is excellent inter- and intra-rater reliability and inter-rater agreement for curve type and each modifier. The high degree of reliability demonstrates that applying the classification system is easy and consistent.

892 citations


Authors

Showing all 53083 results

NameH-indexPapersCitations
Joan Massagué189408149951
Michael Rutter188676151592
Gordon B. Mills1871273186451
Ralph Weissleder1841160142508
Gonçalo R. Abecasis179595230323
Jie Zhang1784857221720
John R. Yates1771036129029
John A. Rogers1771341127390
Bradley Cox1692150156200
Mika Kivimäki1661515141468
Hongfang Liu1662356156290
Carl W. Cotman165809105323
Ralph A. DeFronzo160759132993
Elio Riboli1581136110499
Dan R. Littman157426107164
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023189
2022783
20215,565
20205,600
20195,001
20184,586