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A general model of hormesis in biological systems and its application to pest management
Hormesis, a phenomenon whereby exposure to high levels of stressors is inhibitory but low (mild, sublethal and subtoxic) doses are stimulatory, challenges decision-making in the management of cancer, neurodegenerative diseases, nutrition and ecotoxicology. In the latter, increasing amounts of a pest...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6731494/ https://www.ncbi.nlm.nih.gov/pubmed/31431187 http://dx.doi.org/10.1098/rsif.2019.0468 |
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author | Tang, Sanyi Liang, Juhua Xiang, Changcheng Xiao, Yanni Wang, Xia Wu, Jianhong Li, Guoping Cheke, Robert A. |
author_facet | Tang, Sanyi Liang, Juhua Xiang, Changcheng Xiao, Yanni Wang, Xia Wu, Jianhong Li, Guoping Cheke, Robert A. |
author_sort | Tang, Sanyi |
collection | PubMed |
description | Hormesis, a phenomenon whereby exposure to high levels of stressors is inhibitory but low (mild, sublethal and subtoxic) doses are stimulatory, challenges decision-making in the management of cancer, neurodegenerative diseases, nutrition and ecotoxicology. In the latter, increasing amounts of a pesticide may lead to upsurges rather than declines of pests, ecological paradoxes that are difficult to predict. Using a novel re-formulation of the Ricker population equation, we show how interactions between intervention strengths and dose timings, dose–response functions and intrinsic factors can model such paradoxes and hormesis. A model with three critical parameters revealed hormetic biphasic dose and dose timing responses, either in a J-shape or an inverted U-shape, yielding a homeostatic change or a catastrophic shift and hormetic effects in many parameter regions. Such effects were enhanced by repeated pulses of low-level stimulations within one generation at different dose timings, thereby reducing threshold levels, maximum responses and inhibition. The model provides insights into the complex dynamics of such systems and a methodology for improved experimental design and analysis, with wide-reaching implications for understanding hormetic effects in ecology and in medical and veterinary treatment decision-making. We hypothesized that the dynamics of a discrete generation pest control system can be determined by various three-parameter spaces, some of which reveal the conditions for occurrence of hormesis, and confirmed this by fitting our model to both hormetic data from the literature and to a non-hormetic dataset on pesticidal control of mirid bugs in cotton. |
format | Online Article Text |
id | pubmed-6731494 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-67314942019-09-09 A general model of hormesis in biological systems and its application to pest management Tang, Sanyi Liang, Juhua Xiang, Changcheng Xiao, Yanni Wang, Xia Wu, Jianhong Li, Guoping Cheke, Robert A. J R Soc Interface Life Sciences–Mathematics interface Hormesis, a phenomenon whereby exposure to high levels of stressors is inhibitory but low (mild, sublethal and subtoxic) doses are stimulatory, challenges decision-making in the management of cancer, neurodegenerative diseases, nutrition and ecotoxicology. In the latter, increasing amounts of a pesticide may lead to upsurges rather than declines of pests, ecological paradoxes that are difficult to predict. Using a novel re-formulation of the Ricker population equation, we show how interactions between intervention strengths and dose timings, dose–response functions and intrinsic factors can model such paradoxes and hormesis. A model with three critical parameters revealed hormetic biphasic dose and dose timing responses, either in a J-shape or an inverted U-shape, yielding a homeostatic change or a catastrophic shift and hormetic effects in many parameter regions. Such effects were enhanced by repeated pulses of low-level stimulations within one generation at different dose timings, thereby reducing threshold levels, maximum responses and inhibition. The model provides insights into the complex dynamics of such systems and a methodology for improved experimental design and analysis, with wide-reaching implications for understanding hormetic effects in ecology and in medical and veterinary treatment decision-making. We hypothesized that the dynamics of a discrete generation pest control system can be determined by various three-parameter spaces, some of which reveal the conditions for occurrence of hormesis, and confirmed this by fitting our model to both hormetic data from the literature and to a non-hormetic dataset on pesticidal control of mirid bugs in cotton. The Royal Society 2019-08 2019-08-21 /pmc/articles/PMC6731494/ /pubmed/31431187 http://dx.doi.org/10.1098/rsif.2019.0468 Text en © 2019 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Life Sciences–Mathematics interface Tang, Sanyi Liang, Juhua Xiang, Changcheng Xiao, Yanni Wang, Xia Wu, Jianhong Li, Guoping Cheke, Robert A. A general model of hormesis in biological systems and its application to pest management |
title | A general model of hormesis in biological systems and its application to pest management |
title_full | A general model of hormesis in biological systems and its application to pest management |
title_fullStr | A general model of hormesis in biological systems and its application to pest management |
title_full_unstemmed | A general model of hormesis in biological systems and its application to pest management |
title_short | A general model of hormesis in biological systems and its application to pest management |
title_sort | general model of hormesis in biological systems and its application to pest management |
topic | Life Sciences–Mathematics interface |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6731494/ https://www.ncbi.nlm.nih.gov/pubmed/31431187 http://dx.doi.org/10.1098/rsif.2019.0468 |
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