Application of a Deuterium Replacement Strategy to Modulate the Pharmacokinetics of 7-(3,5-dimethyl-1H-1,2,4-triazol-1-yl)-3-(4-methoxy-2-methylphenyl)-2,6-dimethylpyrazolo[5,1-b]oxazole, a Novel CRF1 Antagonist

Rowan A. Stringer; Gareth Williams; Franck Picard; Bindi Sohal; Olivier Kretz; Jeff McKenna; Joel A. Krauser

doi:10.1124/dmd.114.057265

Application of a Deuterium Replacement Strategy to Modulate the Pharmacokinetics of 7-(3,5-dimethyl-1H-1,2,4-triazol-1-yl)-3-(4-methoxy-2-methylphenyl)-2,6-dimethylpyrazolo[5,1-b]oxazole, a Novel CRF1 Antagonist

Drug Metabolism and Disposition ◽

10.1124/dmd.114.057265 ◽

2014 ◽

Vol 42 (5) ◽

pp. 954-962 ◽

Cited By ~ 10

Author(s):

Rowan A. Stringer ◽

Gareth Williams ◽

Franck Picard ◽

Bindi Sohal ◽

Olivier Kretz ◽

...

Keyword(s):

Replacement Strategy ◽

Crf1 Antagonist

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08 / Restrictive or individualized goal-directed fluid replacement strategy in ovarian cancer cytoreductive surgery (RIGoROCS) – A prospective randomized controlled trial: An interim analysis

10.26226/morressier.5aeb0acc07b0d6001a79ac44 ◽

2018 ◽

Author(s):

Jyotsna Goswami

Keyword(s):

Ovarian Cancer ◽

Randomized Controlled Trial ◽

Cytoreductive Surgery ◽

Interim Analysis ◽

Controlled Trial ◽

Fluid Replacement ◽

Replacement Strategy ◽

Randomized Controlled ◽

Prospective Randomized Controlled Trial

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Faculty Opinions recommendation of A ubiquitin replacement strategy in human cells reveals distinct mechanisms of IKK activation by TNFalpha and IL-1beta.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1247959.716058 ◽

2009 ◽

Author(s):

Henning Walczak ◽

Stefanie Cordier

Keyword(s):

Human Cells ◽

Replacement Strategy

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A Residual Replacement Strategy for Improving the Maximum Attainable Accuracy of Communication-Avoiding Krylov Subspace Methods

10.21236/ada561766 ◽

2012 ◽

Cited By ~ 4

Author(s):

Erin Carson ◽

James Demmel

Keyword(s):

Krylov Subspace ◽

Krylov Subspace Methods ◽

Subspace Methods ◽

Replacement Strategy

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Impact of a reduced budget asset replacement strategy on the reliability of a medium voltage distribution network

3rd IEE International Conference on Reliability of Transmission and Distribution Networks (RTDN 2005) ◽

10.1049/cp:20050024 ◽

2005 ◽

Author(s):

P. Birkner

Keyword(s):

Distribution Network ◽

Voltage Distribution ◽

Replacement Strategy ◽

Medium Voltage ◽

Asset Replacement

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Steam replacement strategy using microwave resonance: A future system for continuous-flow heating applications

Applied Energy ◽

10.1016/j.apenergy.2020.116300 ◽

2020 ◽

pp. 116300

Author(s):

Huayu Yang ◽

Yuhao Zhang ◽

Wenhua Gao ◽

Bowen Yan ◽

Jianxin Zhao ◽

...

Keyword(s):

Continuous Flow ◽

Replacement Strategy ◽

Microwave Resonance ◽

Future System

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CCF-LRU: hybrid storage cache replacement strategy based on counting cuckoo filter hot-probe method

Applied Intelligence ◽

10.1007/s10489-021-02567-0 ◽

2021 ◽

Author(s):

Yinyin Wang ◽

Yuwang Yang ◽

Xiulin Qiu ◽

Yaqi Ke ◽

Qingguang Wang

Keyword(s):

Probe Method ◽

Cache Replacement ◽

Replacement Strategy ◽

Hybrid Storage ◽

Cuckoo Filter ◽

Hot Probe

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User-Driven Cache Replacement Strategy for Satellite-Terrestrial Networks Based on SDN

2020 IEEE 6th International Conference on Computer and Communications (ICCC) ◽

10.1109/iccc51575.2020.9344872 ◽

2020 ◽

Author(s):

Zhiguo Liu ◽

Yunqi Li ◽

Jie Zhu ◽

Qiaoyu Yao ◽

Xiaobo Ren

Keyword(s):

Cache Replacement ◽

Replacement Strategy ◽

Terrestrial Networks

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Intelligence Selection System for Honing Parameter Based on Genetics and Artificial Neural Networks

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.102-104.846 ◽

2010 ◽

Vol 102-104 ◽

pp. 846-850

Author(s):

Wen Yu Pu ◽

Yan Nian Rui ◽

Lian Sheng Zhao ◽

Chun Yan Zhang

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Selection System ◽

Process Data ◽

Replacement Strategy ◽

Machining Quality ◽

Main Factors ◽

Artificial Neural ◽

Neural Networks Optimization ◽

The Relationship

Appropriate selecting of process parameters influences the machining quality greatly. For honing, the main factors are product precision, material components and productivity. In view of this situation, a intelligence selection model for honing parameter based on genetics and artificial neural networks was built by using excellent robustness, fault-tolerance of artificial neural networks optimization process and excellent self-optimum of genetic algorithm. It can simulate the decision making progress of experienced operators, abstract the relationship from process data and machining incidence, realize the purpose of intelligence selection honing parameter through copying, exchanging, aberrance, replacement strategy and neural networks training. Besides, experiment was performed and the results helped optimize the theories model. Both the theory and experiment show the updated level and feasibility of this system.

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