scispace - formally typeset
Search or ask a question
Institution

Emory University

EducationAtlanta, Georgia, United States
About: Emory University is a education organization based out in Atlanta, Georgia, United States. It is known for research contribution in the topics: Population & Medicine. The organization has 51959 authors who have published 122469 publications receiving 6010698 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: The primary goals of this set of studies were to develop, and initiate the construct validation of, a self-report measure that assesses the major personality traits of psychopathy in noncriminal populations and clarify the nature of these traits via an exploratory approach to test construction.
Abstract: Research on psychopathology has been hindered by persisting difficulties and controversies regarding its assessment The primary goals of this set of studies were to (a) develop, and initiate the construct validation of, a self-report measure that assesses the major personality traits of psychopathy in noncriminal populations and (b) clarify the nature of these traits via an exploratory approach to test construction This measure, the Psychopathic Personality Inventory (PPI), was developed by writing items to assess a large number of personality domains relevant to psychopathy and performing successive item-level factor analyses and revisions on three undergraduate samples The PPI total score and its eight subscales were found to possess satisfactory internal consistency and test-retest reliability In four studies with undergraduates, the PPI and its subscales exhibited a promising pattern of convergent and discriminant validity with self-report, psychiatric interview, observer rating, and family history data In addition, the PPI total score demonstrated incremental validity relative to several commonly used self-report psychopathy-related measures Future construct validation studies, unresolved conceptual issues regarding the assessment of psychopathy, and potential research uses of the PPI are outlined

1,314 citations

Journal ArticleDOI
TL;DR: Data indicate that initial antigen encounter triggers an instructive developmental program that does not require further antigenic stimulation and does not cease until memory CD8+ T cell formation.
Abstract: The rules that govern memory T cell differentiation are not well understood. This study shows that after antigenic stimulation naive CD8+ T cells become committed to dividing at least seven times and differentiating into effector and memory cells. Once the parental naive CD8+ T cell had been activated, this developmental process could not be interrupted and the daughter cells continued to divide and differentiate in the absence of further antigenic stimulation. These data indicate that initial antigen encounter triggers an instructive developmental program that does not require further antigenic stimulation and does not cease until memory CD8+ T cell formation.

1,302 citations

Journal ArticleDOI
18 Jul 2002-Neuron
TL;DR: In this article, the authors used fMRI to scan 36 women as they played an iterated Prisoner's Dilemma Game with another woman to investigate the neurobiological basis of cooperative social behavior.

1,302 citations

Journal ArticleDOI
TL;DR: Baricitinib plus remdesivir was superior to remdes Vivir alone in reducing recovery time and accelerating improvement in clinical status among patients with Covid-19, notably among those receiving high-flow oxygen or noninvasive ventilation.
Abstract: Background Severe coronavirus disease 2019 (Covid-19) is associated with dysregulated inflammation. The effects of combination treatment with baricitinib, a Janus kinase inhibitor, plus remdesivir are not known. Methods We conducted a double-blind, randomized, placebo-controlled trial evaluating baricitinib plus remdesivir in hospitalized adults with Covid-19. All the patients received remdesivir (≤10 days) and either baricitinib (≤14 days) or placebo (control). The primary outcome was the time to recovery. The key secondary outcome was clinical status at day 15. Results A total of 1033 patients underwent randomization (with 515 assigned to combination treatment and 518 to control). Patients receiving baricitinib had a median time to recovery of 7 days (95% confidence interval [CI], 6 to 8), as compared with 8 days (95% CI, 7 to 9) with control (rate ratio for recovery, 1.16; 95% CI, 1.01 to 1.32; P = 0.03), and a 30% higher odds of improvement in clinical status at day 15 (odds ratio, 1.3; 95% CI, 1.0 to 1.6). Patients receiving high-flow oxygen or noninvasive ventilation at enrollment had a time to recovery of 10 days with combination treatment and 18 days with control (rate ratio for recovery, 1.51; 95% CI, 1.10 to 2.08). The 28-day mortality was 5.1% in the combination group and 7.8% in the control group (hazard ratio for death, 0.65; 95% CI, 0.39 to 1.09). Serious adverse events were less frequent in the combination group than in the control group (16.0% vs. 21.0%; difference, -5.0 percentage points; 95% CI, -9.8 to -0.3; P = 0.03), as were new infections (5.9% vs. 11.2%; difference, -5.3 percentage points; 95% CI, -8.7 to -1.9; P = 0.003). Conclusions Baricitinib plus remdesivir was superior to remdesivir alone in reducing recovery time and accelerating improvement in clinical status among patients with Covid-19, notably among those receiving high-flow oxygen or noninvasive ventilation. The combination was associated with fewer serious adverse events. (Funded by the National Institute of Allergy and Infectious Diseases; ClinicalTrials.gov number, NCT04401579.).

1,301 citations

Proceedings ArticleDOI
11 Feb 2008
TL;DR: This paper introduces a general classification framework for combining the evidence from different sources of information, that can be tuned automatically for a given social media type and quality definition, and shows that its system is able to separate high-quality items from the rest with an accuracy close to that of humans.
Abstract: The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability of such content increases, the task of identifying high-quality content sites based on user contributions --social media sites -- becomes increasingly important. Social media in general exhibit a rich variety of information sources: in addition to the content itself, there is a wide array of non-content information available, such as links between items and explicit quality ratings from members of the community. In this paper we investigate methods for exploiting such community feedback to automatically identify high quality content. As a test case, we focus on Yahoo! Answers, a large community question/answering portal that is particularly rich in the amount and types of content and social interactions available in it. We introduce a general classification framework for combining the evidence from different sources of information, that can be tuned automatically for a given social media type and quality definition. In particular, for the community question/answering domain, we show that our system is able to separate high-quality items from the rest with an accuracy close to that of humans

1,300 citations


Authors

Showing all 52622 results

NameH-indexPapersCitations
Younan Xia216943175757
Eric J. Topol1931373151025
Bernard Rosner1901162147661
Paul G. Richardson1831533155912
Peter W.F. Wilson181680139852
Dennis S. Charney179802122408
Joseph Biederman1791012117440
Kenneth C. Anderson1781138126072
David A. Weitz1781038114182
Lei Jiang1702244135205
William J. Sandborn1621317108564
Stephen J. Elledge162406112878
Ali H. Mokdad156634160599
Michael Tomasello15579793361
Don W. Cleveland15244484737
Network Information
Related Institutions (5)
University of California, San Francisco
186.2K papers, 12M citations

98% related

University of North Carolina at Chapel Hill
185.3K papers, 9.9M citations

97% related

Duke University
200.3K papers, 10.7M citations

97% related

University of Pennsylvania
257.6K papers, 14.1M citations

97% related

Yale University
220.6K papers, 12.8M citations

97% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023195
20221,124
20218,694
20208,001
20197,033
20186,326