Predicting acute contact toxicity of organic binary mixtures in honey bees (A. mellifera) through innovative QSAR models.

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Bibliographic Details
Title: Predicting acute contact toxicity of organic binary mixtures in honey bees (A. mellifera) through innovative QSAR models.
Authors: Carnesecchi E; Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via la Masa 19, 20156 Milan, Italy; Institute for Risk Assessment Sciences (IRAS), Utrecht University, PO Box 80177, 3508 TD Utrecht, The Netherlands. Electronic address: edoardo.carnesecchi@marionegri.it., Toropov AA; Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via la Masa 19, 20156 Milan, Italy., Toropova AP; Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via la Masa 19, 20156 Milan, Italy., Kramer N; Institute for Risk Assessment Sciences (IRAS), Utrecht University, PO Box 80177, 3508 TD Utrecht, The Netherlands., Svendsen C; Centre for Ecology and Hydrology, Maclean Building, Benson Lane, Wallingford, Oxfordshire OX10 8BB, UK., Dorne JL; European Food Safety Authority (EFSA), Scientific Committee and Emerging Risks Unit, Via Carlo Magno 1A, 43126 Parma, Italy., Benfenati E; Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via la Masa 19, 20156 Milan, Italy.
Source: The Science of the total environment [Sci Total Environ] 2020 Feb 20; Vol. 704, pp. 135302. Date of Electronic Publication: 2019 Nov 19.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0330500 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-1026 (Electronic) Linking ISSN: 00489697 NLM ISO Abbreviation: Sci Total Environ Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-1026
DOI:10.1016/j.scitotenv.2019.135302