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Institution

Research Triangle Park

NonprofitDurham, North Carolina, United States
About: Research Triangle Park is a nonprofit organization based out in Durham, North Carolina, United States. It is known for research contribution in the topics: Population & Receptor. The organization has 24961 authors who have published 35800 publications receiving 1684504 citations. The organization is also known as: RTP.


Papers
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Patent
01 Oct 1991
TL;DR: A medical capsule device for releasing a substance at a defined location in the gastrointestinal tract is described in this article, which has a capsule body defining one or more apertures in the circumferential wall of the colon and a sleeve valve rotatably positioned therein.
Abstract: A medical capsule device for releasing a substance at a defined location in the gastrointestinal tract. The device has a capsule body defining one or more apertures in the circumferential wall thereof and a sleeve valve rotatably positioned therein having one or more corresponding apertures in the circumferential wall thereof. The sleeve valve comprises a coil and electrically connected heatable resistor which are operatively associated with an actuator member formed of a shape memory alloy responsive to heat and which will move from a non-heated first shape to a heated second shape. Actuator stop means are provided in the capsule body for being engaged by the actuator member during movement from the non-heated first shape to the heated second shape so that the actuator member movement will serve to rotate the sleeve valve to an open position.

287 citations

Journal ArticleDOI
TL;DR: A specific, sensitive estrogen-responsive gene expression assay in a stable cell line that could possibly be adapted for high throughput screening of large numbers of chemicals for estrogenic and antiestrogenic activity is developed.

287 citations

Journal ArticleDOI
TL;DR: The intent is to define a minimal best practice for in vitro and in vivo pharmacokinetic drug‐drug interaction studies targeted to development (not discovery support) and to defined a data package that can be expected by regulatory agencies in compound registration dossiers.
Abstract: Current regulatory guidances do not address specific study designs for in vitro and in vivo drug-drug interaction studies. There is a common desire by regulatory authorities and by industry sponsors to harmonize approaches to allow for a better assessment of the significance of findings across different studies and drugs. There is also a growing consensus for the standardization of cytochrome P450 (CYP) probe substrates, inhibitors, and inducers and for the development of classification systems to improve the communication of risk to health care providers and patients. While existing guidances cover mainly CYP-mediated drug interactions, the importance of other mechanisms, such as transporters, has been recognized more recently and should also be addressed. This paper was prepared by the Pharmaceutical Research and Manufacturers of America (PhRMA) Drug Metabolism and Clinical Pharmacology Technical Working Groups and represents the current industry position. The intent is to define a minimal best practice for in vitro and in vivo pharmacokinetic drug-drug interaction studies targeted to development (not discovery support) and to define a data package that can be expected by regulatory agencies in compound registration dossiers.

286 citations

Journal ArticleDOI
Christopher I. Amos1, Joe Dennis2, Zhaoming Wang3, Jinyoung Byun1, Fredrick R. Schumacher4, Simon A. Gayther5, Graham Casey6, David J. Hunter7, Thomas A. Sellers, Stephen B. Gruber6, Alison M. Dunning2, Kyriaki Michailidou2, Laura Fachal2, Kimberly F. Doheny8, Amanda B. Spurdle9, Yafang Li1, Xiangjun Xiao1, Jane Romm8, Elizabeth W. Pugh8, Gerhard A. Coetzee10, Dennis J. Hazelett5, Stig E. Bojesen11, Charlisse Caga-Anan, Christopher A. Haiman5, Ahsan Kamal1, Craig Luccarini2, Daniel C. Tessier12, Daniel Vincent12, Francois Bacot12, David Van Den Berg6, Stefanie A. Nelson, Stephen Demetriades13, David E. Goldgar14, Fergus J. Couch15, Judith L. Forman1, Graham G. Giles16, Graham G. Giles17, David V. Conti6, Heike Bickeböller18, Angela Risch19, Angela Risch20, Melanie Waldenberger, Irene Brüske-Hohlfeld, Belynda Hicks, Hua Ling8, Lesley McGuffog17, Lesley McGuffog16, Andy C. H. Lee2, Karoline Kuchenbaecker2, Penny Soucy21, Judith Manz, Julie M. Cunningham15, Katja Butterbach19, Zsofia Kote-Jarai22, Peter Kraft7, Liesel M. FitzGerald17, Liesel M. FitzGerald16, Sara Lindström23, Sara Lindström7, Marcia Adams8, James McKay24, Catherine M. Phelan, Sara Benlloch2, Linda E. Kelemen25, Paul Brennan24, Marjorie J. Riggan26, Tracy A. O'Mara9, Hongbing Shen27, Yongyong Shi28, Deborah J. Thompson2, Marc T. Goodman5, Sune F. Nielsen11, Andrew Berchuck26, Sylvie Laboissiere12, Stephanie L. Schmit29, Tameka Shelford8, Christopher K. Edlund6, Jack A. Taylor30, John K. Field31, Sue K. Park32, Kenneth Offit33, Kenneth Offit34, Kenneth Offit35, Mads Thomassen36, Rita K. Schmutzler, Laura Ottini37, Rayjean J. Hung38, Jonathan Marchini39, Ali Amin Al Olama2, Ulrike Peters40, Rosalind A. Eeles22, Michael F. Seldin41, Elizabeth M. Gillanders, Daniela Seminara, Antonis C. Antoniou2, Paul D.P. Pharoah2, Georgia Chenevix-Trench9, Stephen J. Chanock, Jacques Simard21, Douglas F. Easton2 
TL;DR: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures.
Abstract: BACKGROUND: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. METHODS: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. RESULTS: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. CONCLUSIONS: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. IMPACT: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR.

286 citations

Proceedings ArticleDOI
04 Oct 2010
TL;DR: A key contribution of HyperSentry is the set of novel techniques that overcome SMM's limitation, providing an integrity measurement agent with the same contextual information available to the hypervisor, completely protected execution, and attestation to its output.
Abstract: This paper presents HyperSentry, a novel framework to enable integrity measurement of a running hypervisor (or any other highest privileged software layer on a system). Unlike existing solutions for protecting privileged software, HyperSentry does not introduce a higher privileged software layer below the integrity measurement target, which could start another race with malicious attackers in obtaining the highest privilege in the system. Instead, HyperSentry introduces a software component that is properly isolated from the hypervisor to enable stealthy and in-context measurement of the runtime integrity of the hypervisor. While stealthiness is necessary to ensure that a compromised hypervisor does not have a chance to hide the attack traces upon detecting an up-coming measurement, in-context measurement is necessary to retrieve all the needed inputs for a successful integrity measurement.HyperSentry uses an out-of-band channel (e.g., Intelligent Platform Management Interface (IPMI), which is commonly available on server platforms) to trigger the stealthy measurement, and adopts the System Management Mode (SMM) to protect its base code and critical data. A key contribution of HyperSentry is the set of novel techniques that overcome SMM's limitation, providing an integrity measurement agent with (1) the same contextual information available to the hypervisor, (2) completely protected execution, and (3) attestation to its output. To evaluate HyperSentry, we implement a prototype of the framework along with an integrity measurement agent for the Xen hypervisor. Our experimental evaluation shows that HyperSentry is a low-overhead practical solution for real world systems.

286 citations


Authors

Showing all 25006 results

NameH-indexPapersCitations
Douglas G. Altman2531001680344
Lewis C. Cantley196748169037
Ronald Klein1941305149140
Daniel J. Jacob16265676530
Christopher P. Cannon1511118108906
James B. Meigs147574115899
Lawrence Corey14677378105
Jeremy K. Nicholson14177380275
Paul M. Matthews14061788802
Herbert Y. Meltzer137114881371
Charles J. Yeo13667276424
Benjamin F. Cravatt13166661932
Timothy R. Billiar13183866133
Peter Brown12990868853
King K. Holmes12460656192
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202317
202277
2021988
20201,001
20191,035
20181,051