Institution
Research Triangle Park
Nonprofit•Durham, 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.
Topics: Population, Receptor, Health care, Gene, Environmental exposure
Papers published on a yearly basis
Papers
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01 Oct 1991TL;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
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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
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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
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Dartmouth College1, University of Cambridge2, St. Jude Children's Research Hospital3, Case Western Reserve University4, Cedars-Sinai Medical Center5, University of Southern California6, Harvard University7, Johns Hopkins University8, QIMR Berghofer Medical Research Institute9, Van Andel Institute10, University of Copenhagen11, McGill University12, Princess Margaret Cancer Centre13, Huntsman Cancer Institute14, Mayo Clinic15, University of Tasmania16, Cancer Council Victoria17, University of Göttingen18, German Cancer Research Center19, University of Salzburg20, Laval University21, Institute of Cancer Research22, University of Washington23, International Agency for Research on Cancer24, Medical University of South Carolina25, Duke University26, Nanjing Medical University27, Shanghai Jiao Tong University28, University of South Florida29, Research Triangle Park30, University of Liverpool31, Seoul National University32, Memorial Sloan Kettering Cancer Center33, Memorial Hospital of South Bend34, Cornell University35, University of Southern Denmark36, Sapienza University of Rome37, University of Toronto38, University of Oxford39, Fred Hutchinson Cancer Research Center40, University of California, Davis41
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
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04 Oct 2010TL;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
Name | H-index | Papers | Citations |
---|---|---|---|
Douglas G. Altman | 253 | 1001 | 680344 |
Lewis C. Cantley | 196 | 748 | 169037 |
Ronald Klein | 194 | 1305 | 149140 |
Daniel J. Jacob | 162 | 656 | 76530 |
Christopher P. Cannon | 151 | 1118 | 108906 |
James B. Meigs | 147 | 574 | 115899 |
Lawrence Corey | 146 | 773 | 78105 |
Jeremy K. Nicholson | 141 | 773 | 80275 |
Paul M. Matthews | 140 | 617 | 88802 |
Herbert Y. Meltzer | 137 | 1148 | 81371 |
Charles J. Yeo | 136 | 672 | 76424 |
Benjamin F. Cravatt | 131 | 666 | 61932 |
Timothy R. Billiar | 131 | 838 | 66133 |
Peter Brown | 129 | 908 | 68853 |
King K. Holmes | 124 | 606 | 56192 |