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D. Harper - One of the best experts on this subject based on the ideXlab platform.
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Estimation of partial agonist affinity by interaction with a full agonist: a direct Operational Model‐fitting approach
British Journal of Pharmacology, 1993Co-Authors: P. Leff, I. G. Dougall, D. HarperAbstract:Abstract 1. The Operational Model of agonism (Black & Leff, 1983) has been extended to describe the interaction between a partial agonist and a full agonist at the same receptor. The derived equation explicitly describes the interaction and allows the affinity (and efficacy) of the partial agonist to be estimated by direct fitting of raw experimental agonist concentration-effect (E/[A]) curve data. 2. The Model was used to analyse experimental E/[A] curve data generated for the interaction between pilocarpine (partial agonist) and carbachol (full agonist) at the M3-muscarinic receptor mediating contraction of the guinea-pig isolated trachea. Pilocarpine affinity estimates obtained by Operational Model-fitting were compared with those obtained by use of the null method (Stephenson, 1956). These analyses demonstrated that the two methods gave comparable results (mean pKB estimates were 5.79 and 5.86 for the Operational Model and null method respectively). 3. When multiple concentrations of partial agonist are used, simultaneous Operational Model-fitting of all the E/[A] curve data allows the competitive nature of the interaction to be studied. 4. We conclude that Operational Model-fitting is a valid and analytically simple alternative to the conventional null method of analysing full/partial agonist interactions.
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Estimation of partial agonist affinity by interaction with a full agonist: a direct Operational Model-fitting approach.
British journal of pharmacology, 1993Co-Authors: P. Leff, I. G. Dougall, D. HarperAbstract:Abstract 1. The Operational Model of agonism (Black & Leff, 1983) has been extended to describe the interaction between a partial agonist and a full agonist at the same receptor. The derived equation explicitly describes the interaction and allows the affinity (and efficacy) of the partial agonist to be estimated by direct fitting of raw experimental agonist concentration-effect (E/[A]) curve data. 2. The Model was used to analyse experimental E/[A] curve data generated for the interaction between pilocarpine (partial agonist) and carbachol (full agonist) at the M3-muscarinic receptor mediating contraction of the guinea-pig isolated trachea. Pilocarpine affinity estimates obtained by Operational Model-fitting were compared with those obtained by use of the null method (Stephenson, 1956). These analyses demonstrated that the two methods gave comparable results (mean pKB estimates were 5.79 and 5.86 for the Operational Model and null method respectively). 3. When multiple concentrations of partial agonist are used, simultaneous Operational Model-fitting of all the E/[A] curve data allows the competitive nature of the interaction to be studied. 4. We conclude that Operational Model-fitting is a valid and analytically simple alternative to the conventional null method of analysing full/partial agonist interactions.
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Estimation ofpartial agonist affinity byinteraction withafull agonist: adirect Operational Model-fitting approach
1993Co-Authors: P. Leff, I. G. Dougall, D. HarperAbstract:1 TheOperational Modelofagonism (Black & Leff, 1983) hasbeenextended todescribe theinteraction between a partial agonist anda full agonist atthesamereceptor. Thederived equation explicitly describes theinteraction andallows theaffinity (andefficacy) ofthepartial agonist tobeestimated by direct fitting ofrawexperimental agonist concentration-effect (E/[A]) curve data. 2 TheModelwasusedtoanalyse experimental E/[A] curve datagenerated fortheinteraction between pilocarpine (partial agonist) andcarbachol (full agonist) attheM3-muscarinic receptor mediating contraction oftheguinea-pig isolated trachea. Pilocarpine affinity estimates obtained byOperational Model-fitting werecompared withthose obtained byuseofthenull method(Stephenson, 1956). These analyses demonstrated that thetwomethods gavecomparable results (meanpKBestimates were5.79 and 5.86fortheOperational Modelandnullmethodrespectively). 3 Whenmultiple concentrations ofpartial agonist areused, simultaneous Operational Model-fitting of alltheE/[A] curvedataallows thecompetitive nature oftheinteraction tobestudied. 4 We conclude thatOperational Model-fitting isa valid andanalytically simple alternative tothe conventional nullmethodofanalysing full/partial agonist interactions.
P. Leff - One of the best experts on this subject based on the ideXlab platform.
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Estimation of partial agonist affinity by interaction with a full agonist: a direct Operational Model‐fitting approach
British Journal of Pharmacology, 1993Co-Authors: P. Leff, I. G. Dougall, D. HarperAbstract:Abstract 1. The Operational Model of agonism (Black & Leff, 1983) has been extended to describe the interaction between a partial agonist and a full agonist at the same receptor. The derived equation explicitly describes the interaction and allows the affinity (and efficacy) of the partial agonist to be estimated by direct fitting of raw experimental agonist concentration-effect (E/[A]) curve data. 2. The Model was used to analyse experimental E/[A] curve data generated for the interaction between pilocarpine (partial agonist) and carbachol (full agonist) at the M3-muscarinic receptor mediating contraction of the guinea-pig isolated trachea. Pilocarpine affinity estimates obtained by Operational Model-fitting were compared with those obtained by use of the null method (Stephenson, 1956). These analyses demonstrated that the two methods gave comparable results (mean pKB estimates were 5.79 and 5.86 for the Operational Model and null method respectively). 3. When multiple concentrations of partial agonist are used, simultaneous Operational Model-fitting of all the E/[A] curve data allows the competitive nature of the interaction to be studied. 4. We conclude that Operational Model-fitting is a valid and analytically simple alternative to the conventional null method of analysing full/partial agonist interactions.
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Estimation of partial agonist affinity by interaction with a full agonist: a direct Operational Model-fitting approach.
British journal of pharmacology, 1993Co-Authors: P. Leff, I. G. Dougall, D. HarperAbstract:Abstract 1. The Operational Model of agonism (Black & Leff, 1983) has been extended to describe the interaction between a partial agonist and a full agonist at the same receptor. The derived equation explicitly describes the interaction and allows the affinity (and efficacy) of the partial agonist to be estimated by direct fitting of raw experimental agonist concentration-effect (E/[A]) curve data. 2. The Model was used to analyse experimental E/[A] curve data generated for the interaction between pilocarpine (partial agonist) and carbachol (full agonist) at the M3-muscarinic receptor mediating contraction of the guinea-pig isolated trachea. Pilocarpine affinity estimates obtained by Operational Model-fitting were compared with those obtained by use of the null method (Stephenson, 1956). These analyses demonstrated that the two methods gave comparable results (mean pKB estimates were 5.79 and 5.86 for the Operational Model and null method respectively). 3. When multiple concentrations of partial agonist are used, simultaneous Operational Model-fitting of all the E/[A] curve data allows the competitive nature of the interaction to be studied. 4. We conclude that Operational Model-fitting is a valid and analytically simple alternative to the conventional null method of analysing full/partial agonist interactions.
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Estimation ofpartial agonist affinity byinteraction withafull agonist: adirect Operational Model-fitting approach
1993Co-Authors: P. Leff, I. G. Dougall, D. HarperAbstract:1 TheOperational Modelofagonism (Black & Leff, 1983) hasbeenextended todescribe theinteraction between a partial agonist anda full agonist atthesamereceptor. Thederived equation explicitly describes theinteraction andallows theaffinity (andefficacy) ofthepartial agonist tobeestimated by direct fitting ofrawexperimental agonist concentration-effect (E/[A]) curve data. 2 TheModelwasusedtoanalyse experimental E/[A] curve datagenerated fortheinteraction between pilocarpine (partial agonist) andcarbachol (full agonist) attheM3-muscarinic receptor mediating contraction oftheguinea-pig isolated trachea. Pilocarpine affinity estimates obtained byOperational Model-fitting werecompared withthose obtained byuseofthenull method(Stephenson, 1956). These analyses demonstrated that thetwomethods gavecomparable results (meanpKBestimates were5.79 and 5.86fortheOperational Modelandnullmethodrespectively). 3 Whenmultiple concentrations ofpartial agonist areused, simultaneous Operational Model-fitting of alltheE/[A] curvedataallows thecompetitive nature oftheinteraction tobestudied. 4 We conclude thatOperational Model-fitting isa valid andanalytically simple alternative tothe conventional nullmethodofanalysing full/partial agonist interactions.
I. G. Dougall - One of the best experts on this subject based on the ideXlab platform.
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Estimation of partial agonist affinity by interaction with a full agonist: a direct Operational Model‐fitting approach
British Journal of Pharmacology, 1993Co-Authors: P. Leff, I. G. Dougall, D. HarperAbstract:Abstract 1. The Operational Model of agonism (Black & Leff, 1983) has been extended to describe the interaction between a partial agonist and a full agonist at the same receptor. The derived equation explicitly describes the interaction and allows the affinity (and efficacy) of the partial agonist to be estimated by direct fitting of raw experimental agonist concentration-effect (E/[A]) curve data. 2. The Model was used to analyse experimental E/[A] curve data generated for the interaction between pilocarpine (partial agonist) and carbachol (full agonist) at the M3-muscarinic receptor mediating contraction of the guinea-pig isolated trachea. Pilocarpine affinity estimates obtained by Operational Model-fitting were compared with those obtained by use of the null method (Stephenson, 1956). These analyses demonstrated that the two methods gave comparable results (mean pKB estimates were 5.79 and 5.86 for the Operational Model and null method respectively). 3. When multiple concentrations of partial agonist are used, simultaneous Operational Model-fitting of all the E/[A] curve data allows the competitive nature of the interaction to be studied. 4. We conclude that Operational Model-fitting is a valid and analytically simple alternative to the conventional null method of analysing full/partial agonist interactions.
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Estimation of partial agonist affinity by interaction with a full agonist: a direct Operational Model-fitting approach.
British journal of pharmacology, 1993Co-Authors: P. Leff, I. G. Dougall, D. HarperAbstract:Abstract 1. The Operational Model of agonism (Black & Leff, 1983) has been extended to describe the interaction between a partial agonist and a full agonist at the same receptor. The derived equation explicitly describes the interaction and allows the affinity (and efficacy) of the partial agonist to be estimated by direct fitting of raw experimental agonist concentration-effect (E/[A]) curve data. 2. The Model was used to analyse experimental E/[A] curve data generated for the interaction between pilocarpine (partial agonist) and carbachol (full agonist) at the M3-muscarinic receptor mediating contraction of the guinea-pig isolated trachea. Pilocarpine affinity estimates obtained by Operational Model-fitting were compared with those obtained by use of the null method (Stephenson, 1956). These analyses demonstrated that the two methods gave comparable results (mean pKB estimates were 5.79 and 5.86 for the Operational Model and null method respectively). 3. When multiple concentrations of partial agonist are used, simultaneous Operational Model-fitting of all the E/[A] curve data allows the competitive nature of the interaction to be studied. 4. We conclude that Operational Model-fitting is a valid and analytically simple alternative to the conventional null method of analysing full/partial agonist interactions.
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Estimation ofpartial agonist affinity byinteraction withafull agonist: adirect Operational Model-fitting approach
1993Co-Authors: P. Leff, I. G. Dougall, D. HarperAbstract:1 TheOperational Modelofagonism (Black & Leff, 1983) hasbeenextended todescribe theinteraction between a partial agonist anda full agonist atthesamereceptor. Thederived equation explicitly describes theinteraction andallows theaffinity (andefficacy) ofthepartial agonist tobeestimated by direct fitting ofrawexperimental agonist concentration-effect (E/[A]) curve data. 2 TheModelwasusedtoanalyse experimental E/[A] curve datagenerated fortheinteraction between pilocarpine (partial agonist) andcarbachol (full agonist) attheM3-muscarinic receptor mediating contraction oftheguinea-pig isolated trachea. Pilocarpine affinity estimates obtained byOperational Model-fitting werecompared withthose obtained byuseofthenull method(Stephenson, 1956). These analyses demonstrated that thetwomethods gavecomparable results (meanpKBestimates were5.79 and 5.86fortheOperational Modelandnullmethodrespectively). 3 Whenmultiple concentrations ofpartial agonist areused, simultaneous Operational Model-fitting of alltheE/[A] curvedataallows thecompetitive nature oftheinteraction tobestudied. 4 We conclude thatOperational Model-fitting isa valid andanalytically simple alternative tothe conventional nullmethodofanalysing full/partial agonist interactions.
Matt Sims - One of the best experts on this subject based on the ideXlab platform.
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An Operational Model of quickpay : Extended abstract
Lecture Notes in Computer Science, 2000Co-Authors: Pieter H. Hartel, J. Hill, Matt SimsAbstract:QuickPay is a system for micro payments aiming to avoid the cost of cryptographic operations during payments. An Operational Model of the system has been built to assist in the search for weaknesses in the protocols. As a result of this Model building activity, one minor weakness has been found. Another more serious weakness has been re-discovered and a number of solutions are proposed. The full paper gives the details of the Model.
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An Operational Model of QuickPay
Lecture Notes in Computer Science, 1998Co-Authors: Pieter H. Hartel, J. Hill, Matt SimsAbstract:QuickPay is a system for micro payments aiming to avoid the cost of cryptographic operations during payments. An Operational Model of the system has been built to assist in the search for weaknesses in the protocols. As a result of this Model building activity, one minor weakness has been found. Another more serious weakness has been re-discovered and a number of solutions are proposed.
Ian Moffatt - One of the best experts on this subject based on the ideXlab platform.
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Sustainable development: conceptual issues, an Operational Model and its implications for Australia
Landscape and Urban Planning, 1993Co-Authors: Ian MoffattAbstract:Abstract This paper describes an Operational Model of sustainable development in an attempt to clarify some of the conceptual issues which surround the term. Despite the plethora of papers that make reference to sustainable development it is becoming increasingly clear that very few studies have progressed to the point wheresome of the ideas underpinning sustainable development can be put into an Operational format. Yet, if the concept is to be useful for planning and managing landscapes in a sustainable way it is essential that Operational Models of the conceptare produced. After discussing some of the conceptual issues that surround the term ‘sustainable development’, a description of a dynamic simulation Model of sustainable development is proposed. Although the Model is in its early stages of developement it has been applied in several national case studies, including Australia. Some implications of further development of the Model for its application to northern Australia are also suggested.