Literature DB >> 28118146

An open-sourced statistical application for identifying complex toxicological interactions of environmental pollutants.

Jordan T Perkins, Michael C Petriello, Li Xu, Arnold Stromberg, Bernhard Hennig.   

Abstract

The rising number of chemicals that humans are exposed to on a daily basis, as well as advances in biomonitoring and detection technologies have highlighted the diversity of individual exposure profiles (complex body burdens). To address this, the toxicological sciences have begun to shift away from examining toxic agents or stressors individually to focusing on more complex models with multiple agents or stressors present. Literature on interactions between chemicals is fairly limited in comparison with dose-response studies on individual toxicants, which is largely due to experimental and statistical challenges. Experimental designs capable of identifying these complex interactions are often avoided or not evaluated to their fullest potential because of the difficulty associated with appropriate analysis as well as logistical factors. To assist with statistical analysis of these types of experiments, an online, open-sourced statistical application was created for investigators to use to analyze and interpret potential toxicant interactions in laboratory experimental data using a full-factorial three-way analysis of variance (ANOVA). This model utilizes backward selection on interaction terms to model main effects and interactions.

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Year:  2017        PMID: 28118146      PMCID: PMC5489228          DOI: 10.1515/reveh-2016-0044

Source DB:  PubMed          Journal:  Rev Environ Health        ISSN: 0048-7554            Impact factor:   3.458


  10 in total

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Journal:  Arch Environ Health       Date:  2001 Mar-Apr

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Authors:  Thomas Backhaus; Michael Faust; Andreas Kortenkamp
Journal:  Integr Environ Assess Manag       Date:  2013-10       Impact factor: 2.992

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Authors:  M C Berenbaum
Journal:  J Theor Biol       Date:  1985-06-07       Impact factor: 2.691

5.  Mixtures research at NIEHS: an evolving program.

Authors:  Cynthia V Rider; Danielle J Carlin; Micheal J Devito; Claudia L Thompson; Nigel J Walker
Journal:  Toxicology       Date:  2012-11-09       Impact factor: 4.221

6.  Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro.

Authors:  Niels Hadrup; Camilla Taxvig; Mikael Pedersen; Christine Nellemann; Ulla Hass; Anne Marie Vinggaard
Journal:  PLoS One       Date:  2013-08-22       Impact factor: 3.240

7.  Maximum cumulative ratio (MCR) as a tool for assessing the value of performing a cumulative risk assessment.

Authors:  Paul S Price; Xianglu Han
Journal:  Int J Environ Res Public Health       Date:  2011-06-16       Impact factor: 3.390

8.  Dose-additive carcinogenicity of a defined mixture of "dioxin-like compounds".

Authors:  Nigel J Walker; Patrick W Crockett; Abraham Nyska; Amy E Brix; Michael P Jokinen; Donald M Sells; James R Hailey; Micheal Easterling; Joseph K Haseman; Ming Yin; Michael E Wyde; John R Bucher; Christopher J Portier
Journal:  Environ Health Perspect       Date:  2005-01       Impact factor: 9.031

9.  Chemical mixtures research: significance and future perspectives.

Authors:  William A Suk; Kenneth Olden; Raymond S H Yang
Journal:  Environ Health Perspect       Date:  2002-12       Impact factor: 9.031

10.  Unraveling the health effects of environmental mixtures: an NIEHS priority.

Authors:  Danielle J Carlin; Cynthia V Rider; Rick Woychik; Linda S Birnbaum
Journal:  Environ Health Perspect       Date:  2013-01       Impact factor: 9.031

  10 in total
  1 in total

Review 1.  The State-of-the Art of Environmental Toxicogenomics: Challenges and Perspectives of "Omics" Approaches Directed to Toxicant Mixtures.

Authors:  Carla Martins; Kristian Dreij; Pedro M Costa
Journal:  Int J Environ Res Public Health       Date:  2019-11-26       Impact factor: 3.390

  1 in total

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