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1.
Psychopharmacology (Berl) ; 238(2): 399-410, 2021 Feb.
Article in English | MEDLINE | ID: mdl-33216166

ABSTRACT

INTRODUCTION: Smokers discount delayed rewards steeper than non-smokers or ex-smokers, possibly due to neuropharmacological effects of tobacco on brain circuitry, or lower abstinence rates in smokers with steep discounting. To delineate both theories from each other, we tested if temporal discounting, choice inconsistency, and related brain activity in treatment-seeking smokers (1) are higher compared to non-smokers, (2) decrease after smoking cessation, and (3) predict relapse. METHODS: At T1, 44 dependent smokers, 29 non-smokers, and 30 occasional smokers underwent fMRI while performing an intertemporal choice task. Smokers were measured before and 21 days after cessation if abstinent from nicotine. In total, 27 smokers, 28 non-smokers, and 29 occasional smokers were scanned again at T2. Discounting rate k and inconsistency var(k) were estimated with Bayesian analysis. RESULTS: First, k and var(k) in smokers in treatment were not higher than in non-smokers or occasional smokers. Second, neither k nor var(k) changed after smoking cessation. Third, k did not predict relapse, but high var(k) was associated with relapse during treatment and over 6 months. Brain activity in valuation and decision networks did not significantly differ between groups and conditions. CONCLUSION: Our data from treatment-seeking smokers do not support the pharmacological hypothesis of pronounced reversible changes in discounting behavior and brain activity, possibly due to limited power. Behavioral data rather suggest that differences between current and ex-smokers might be due to selection. The association of choice consistency and treatment outcome possibly links consistent intertemporal decisions to remaining abstinent.


Subject(s)
Brain/physiology , Choice Behavior/drug effects , Delay Discounting/drug effects , Nicotine/administration & dosage , Smoking Cessation/methods , Smoking/psychology , Adult , Bayes Theorem , Brain/diagnostic imaging , Chronic Disease , Female , Humans , Magnetic Resonance Imaging , Male , Nicotine/pharmacology , Reward , Smokers/psychology , Smoking Cessation/psychology , Surveys and Questionnaires , Tobacco Use Disorder/psychology
2.
PLoS One ; 13(7): e0199995, 2018.
Article in English | MEDLINE | ID: mdl-29979756

ABSTRACT

In agricultural landscapes honeybees and other pollinators are exposed to pesticides, often surveyed by residue analysis of bee bread. However, bee bread is a mixture of pollen pellets of different plants collected over a longer time period. Therefore, pesticide content in the hive varies with plant species and time of pollen collection. Hence, the analysis of bee bread is an approximate approach to gain information on detailed pesticide exposure during the agronomic active season. As high-resolution data is missing, we carried out a pesticide residue survey over five years (2012-2016) of daily collected pollen pellets at three agricultural distinct sites in southern Germany. 281 single day pollen samples were selected and subjected to a multi-pesticide residue analysis. Pesticide contaminations of pollen differed between the sites. Intensive pesticide exposure can be seen by high pesticide concentrations as well as a high amount of different pesticides detected. During the five years of observation 73 different pesticides were found, of which 84% are characterized as non-harmful to honeybees. To estimate pesticide risks for honeybees, the pollen hazard quotient (PHQ) was calculated. Even though pesticides were detected in sublethal concentrations, we found substances not supposed to be exposed to honey bees, indicating the necessity for further improvement of seed treatments and increasing awareness of flowering shrubs, field margins and pesticide drift. Additionally, an in-depth analysis of nine pollen samples, divided into sub-fractions dominated by single plant species, revealed even higher concentrations in single crops for some pesticides. We give precise residue data of 1,657 single pesticide detections, which should be used for realistic laboratory and field tests.


Subject(s)
Agriculture , Bees , Environmental Monitoring , Pesticide Residues/analysis , Pollen/chemistry , Animals , Germany , Surveys and Questionnaires
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