Evidence map›Paper›PMID 26566611›Full record

ArticleEnvironmental science and pollution research international2016

Behavioral and metabolic effects of sublethal doses of two insecticides, chlorpyrifos and methomyl, in the Egyptian cotton leafworm, Spodoptera littoralis (Boisduval) (Lepidoptera: Noctuidae).

Youssef Dewer, Marie-Anne Pottier, Lisa Lalouette, Annick Maria, Matthieu Dacher, Luc P Belzunces, Guillaume Kairo, David Renault, Martine Maibeche, David Siaussat

Abstract read
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Article in Environmental science and pollution research international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

10 authors.

Youssef DewerBioassay Research Department, Central Agricultural Pesticides Laboratory (CAPL), Sabahia Research Station, Agricultural Research Center (ARC), Sabahia, Baccous, P.O. Box 21616, Alexandria, Egypt.
Marie-Anne PottierInstitute of Ecology and Environmental Sciences of Paris (iEES Paris) - Sensory Ecology Department - UMR UPMC 113, CNRS, IRD, INRA, PARIS 7, Sorbonne Universités, UPMC Univ Paris 06, UPEC - 7 Quai Saint Bernard, F-75005, Paris, France.
Lisa LalouetteInstitute of Ecology and Environmental Sciences of Paris (iEES Paris) - Sensory Ecology Department - UMR UPMC 113, CNRS, IRD, INRA, PARIS 7, Sorbonne Universités, UPMC Univ Paris 06, UPEC - 7 Quai Saint Bernard, F-75005, Paris, France.
Annick MariaInstitute of Ecology and Environmental Sciences of Paris (iEES Paris) - Sensory Ecology Department - UMR UPMC 113, CNRS, IRD, INRA, PARIS 7, Sorbonne Universités, UPMC Univ Paris 06, UPEC - 7 Quai Saint Bernard, F-75005, Paris, France.
Matthieu DacherInstitute of Ecology and Environmental Sciences of Paris (iEES Paris) - Sensory Ecology Department - UMR UPMC 113, CNRS, IRD, INRA, PARIS 7, Sorbonne Universités, UPMC Univ Paris 06, UPEC - 7 Quai Saint Bernard, F-75005, Paris, France.
Luc P BelzuncesINRA, Laboratoire de Toxicologie Environnementale, UR 406 A&E, 228 Route de l'Aérodrome, CS 40509, 84914, Avignon Cedex 9, France.
Guillaume KairoINRA, Laboratoire de Toxicologie Environnementale, UR 406 A&E, 228 Route de l'Aérodrome, CS 40509, 84914, Avignon Cedex 9, France.
David RenaultUniversité de Rennes 1, UMR CNRS 6553 Ecobio 263 Avenue du Gal Leclerc, CS 74205, 35042, Rennes, France.
Martine MaibecheInstitute of Ecology and Environmental Sciences of Paris (iEES Paris) - Sensory Ecology Department - UMR UPMC 113, CNRS, IRD, INRA, PARIS 7, Sorbonne Universités, UPMC Univ Paris 06, UPEC - 7 Quai Saint Bernard, F-75005, Paris, France.
David SiaussatInstitute of Ecology and Environmental Sciences of Paris (iEES Paris) - Sensory Ecology Department - UMR UPMC 113, CNRS, IRD, INRA, PARIS 7, Sorbonne Universités, UPMC Univ Paris 06, UPEC - 7 Quai Saint Bernard, F-75005, Paris, France. david.siaussat@upmc.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insecticides have long been used as the main method in limiting agricultural pests, but their widespread use has resulted in environmental pollution, development of resistances, and biodiversity reduction. The effects of insecticides at low residual doses on both the targeted crop pest species and beneficial insects have become a major concern. In particular, these low doses can induce unexpected positive (hormetic) effects on pest insects, such as surges in population growth exceeding what would have been observed without pesticide application. Methomyl and chlorpyrifos are two insecticides commonly used to control the population levels of the cotton leafworm Spodoptera littoralis, a major pest moth. The aim of the present study was to examine the effects of sublethal doses of these two pesticides, known to present a residual activity and persistence in the environment, on the moth physiology. Using a metabolomic approach, we showed that sublethal doses of methomyl and chlorpyrifos have a systemic effect on the treated insects. We also demonstrated a behavioral disruption of S. littoralis larvae exposed to sublethal doses of methomyl, whereas no effects were observed for the same doses of chlorpyrifos. Interestingly, we highlighted that sublethal doses of both pesticides did not induce a change in acetylcholinesterase activity in head of exposed larvae.

Indexed as

SpodopteraAcetylcholinesteraseAnimalsBehavior, AnimalBrainChlorpyrifosEgyptEnvironmental PollutantsHemolymphHormesisInsecticide ResistanceInsecticidesLarvaLethal Dose 50MethomylAcetylcholinesteraseChlorpyrifosEnvironmental PollutantsInsecticidesMethomylChlorpyrifosCrop pestInsect behaviorInsecticideMethomylOlfactionSpodoptera littoralisSublethal doses

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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.