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High throughput modular chambers for rapid evaluation of anesthetic sensitivity

BACKGROUND: Anesthetic sensitivity is determined by the interaction of multiple genes. Hence, a dissection of genetic contributors would be aided by precise and high throughput behavioral screens. Traditionally, anesthetic phenotyping has addressed only induction of anesthesia, evaluated with dose-r...

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Autores principales: Sun, Yi, Chen, Jingqiu, Pruckmayr, Gregory, Baumgardner, James E, Eckmann, David M, Eckenhoff, Roderic G, Kelz, Max B
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1657002/
https://www.ncbi.nlm.nih.gov/pubmed/17096844
http://dx.doi.org/10.1186/1471-2253-6-13
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author Sun, Yi
Chen, Jingqiu
Pruckmayr, Gregory
Baumgardner, James E
Eckmann, David M
Eckenhoff, Roderic G
Kelz, Max B
author_facet Sun, Yi
Chen, Jingqiu
Pruckmayr, Gregory
Baumgardner, James E
Eckmann, David M
Eckenhoff, Roderic G
Kelz, Max B
author_sort Sun, Yi
collection PubMed
description BACKGROUND: Anesthetic sensitivity is determined by the interaction of multiple genes. Hence, a dissection of genetic contributors would be aided by precise and high throughput behavioral screens. Traditionally, anesthetic phenotyping has addressed only induction of anesthesia, evaluated with dose-response curves, while ignoring potentially important data on emergence from anesthesia. METHODS: We designed and built a controlled environment apparatus to permit rapid phenotyping of twenty-four mice simultaneously. We used the loss of righting reflex to indicate anesthetic-induced unconsciousness. After fitting the data to a sigmoidal dose-response curve with variable slope, we calculated the MAC(LORR )(EC(50)), the Hill coefficient, and the 95% confidence intervals bracketing these values. Upon termination of the anesthetic, Emergence time(RR )was determined and expressed as the mean ± standard error for each inhaled anesthetic. RESULTS: In agreement with several previously published reports we find that the MAC(LORR )of halothane, isoflurane, and sevoflurane in 8–12 week old C57BL/6J mice is 0.79% (95% confidence interval = 0.78 – 0.79%), 0.91% (95% confidence interval = 0.90 – 0.93%), and 1.96% (95% confidence interval = 1.94 – 1.97%), respectively. Hill coefficients for halothane, isoflurane, and sevoflurane are 24.7 (95% confidence interval = 19.8 – 29.7%), 19.2 (95% confidence interval = 14.0 – 24.3%), and 33.1 (95% confidence interval = 27.3 – 38.8%), respectively. After roughly 2.5 MAC(LORR )• hr exposures, mice take 16.00 ± 1.07, 6.19 ± 0.32, and 2.15 ± 0.12 minutes to emerge from halothane, isoflurane, and sevoflurane, respectively. CONCLUSION: This system enabled assessment of inhaled anesthetic responsiveness with a higher precision than that previously reported. It is broadly adaptable for delivering an inhaled therapeutic (or toxin) to a population while monitoring its vital signs, motor reflexes, and providing precise control over environmental conditions. This system is also amenable to full automation. Data presented in this manuscript prove the utility of the controlled environment chambers and should allow for subsequent phenotyping of mice with targeted mutations that are expected to alter sensitivity to induction or emergence from anesthesia.
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spelling pubmed-16570022006-11-22 High throughput modular chambers for rapid evaluation of anesthetic sensitivity Sun, Yi Chen, Jingqiu Pruckmayr, Gregory Baumgardner, James E Eckmann, David M Eckenhoff, Roderic G Kelz, Max B BMC Anesthesiol Technical Advance BACKGROUND: Anesthetic sensitivity is determined by the interaction of multiple genes. Hence, a dissection of genetic contributors would be aided by precise and high throughput behavioral screens. Traditionally, anesthetic phenotyping has addressed only induction of anesthesia, evaluated with dose-response curves, while ignoring potentially important data on emergence from anesthesia. METHODS: We designed and built a controlled environment apparatus to permit rapid phenotyping of twenty-four mice simultaneously. We used the loss of righting reflex to indicate anesthetic-induced unconsciousness. After fitting the data to a sigmoidal dose-response curve with variable slope, we calculated the MAC(LORR )(EC(50)), the Hill coefficient, and the 95% confidence intervals bracketing these values. Upon termination of the anesthetic, Emergence time(RR )was determined and expressed as the mean ± standard error for each inhaled anesthetic. RESULTS: In agreement with several previously published reports we find that the MAC(LORR )of halothane, isoflurane, and sevoflurane in 8–12 week old C57BL/6J mice is 0.79% (95% confidence interval = 0.78 – 0.79%), 0.91% (95% confidence interval = 0.90 – 0.93%), and 1.96% (95% confidence interval = 1.94 – 1.97%), respectively. Hill coefficients for halothane, isoflurane, and sevoflurane are 24.7 (95% confidence interval = 19.8 – 29.7%), 19.2 (95% confidence interval = 14.0 – 24.3%), and 33.1 (95% confidence interval = 27.3 – 38.8%), respectively. After roughly 2.5 MAC(LORR )• hr exposures, mice take 16.00 ± 1.07, 6.19 ± 0.32, and 2.15 ± 0.12 minutes to emerge from halothane, isoflurane, and sevoflurane, respectively. CONCLUSION: This system enabled assessment of inhaled anesthetic responsiveness with a higher precision than that previously reported. It is broadly adaptable for delivering an inhaled therapeutic (or toxin) to a population while monitoring its vital signs, motor reflexes, and providing precise control over environmental conditions. This system is also amenable to full automation. Data presented in this manuscript prove the utility of the controlled environment chambers and should allow for subsequent phenotyping of mice with targeted mutations that are expected to alter sensitivity to induction or emergence from anesthesia. BioMed Central 2006-11-10 /pmc/articles/PMC1657002/ /pubmed/17096844 http://dx.doi.org/10.1186/1471-2253-6-13 Text en Copyright © 2006 Sun et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Technical Advance
Sun, Yi
Chen, Jingqiu
Pruckmayr, Gregory
Baumgardner, James E
Eckmann, David M
Eckenhoff, Roderic G
Kelz, Max B
High throughput modular chambers for rapid evaluation of anesthetic sensitivity
title High throughput modular chambers for rapid evaluation of anesthetic sensitivity
title_full High throughput modular chambers for rapid evaluation of anesthetic sensitivity
title_fullStr High throughput modular chambers for rapid evaluation of anesthetic sensitivity
title_full_unstemmed High throughput modular chambers for rapid evaluation of anesthetic sensitivity
title_short High throughput modular chambers for rapid evaluation of anesthetic sensitivity
title_sort high throughput modular chambers for rapid evaluation of anesthetic sensitivity
topic Technical Advance
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1657002/
https://www.ncbi.nlm.nih.gov/pubmed/17096844
http://dx.doi.org/10.1186/1471-2253-6-13
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