Evidence map›Paper›PMID 31431187›Full record

ArticleJournal of the Royal Society, Interface2019

A general model of hormesis in biological systems and its application to pest management.

Sanyi Tang, Juhua Liang, Changcheng Xiang, Yanni Xiao, Xia Wang, Jianhong Wu, Guoping Li, Robert A Cheke

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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  10. A Universal Delayed Difference Model Fitting Dose-response Curves.Dose-response : a publication of International Hormesis Society
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sanyi TangSchool of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710119, People's Republic of China.
Juhua LiangSchool of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710119, People's Republic of China.
Changcheng XiangDepartment of Mathematics, Hubei University for Nationalities, Enshi 445000, People's Republic of China.
Yanni XiaoDepartment of Applied Mathematics, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China.
Xia WangSchool of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710119, People's Republic of China.
Jianhong WuLaboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario, Canada M3J1P3.
Guoping LiInstitute of Plant Protection, Henan Academy of Agricultural Sciences, 116 Huayuan Road, Zhengzhou 450002, People's Republic of China.
Robert A ChekeNatural Resources Institute, University of Greenwich at Medway, Central Avenue, Chatham Maritime, Kent ME4 4TB, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Models, BiologicalAnimalsGossypiumHeteropteraHormesisHumansPest ControlPesticidesPesticidesApolygus lucorumcomplex dynamicsecological paradoxpest controlRicker equationstability

Identifiers

PMID31431187
PMCPMC6731494

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.