Stacking transgenic event DAS-Ø15Ø7-1 alters maize composition less than traditional breeding.

The impact of crossing ('stacking') genetically modified (GM) events on maize-grain biochemical composition was compared with the impact of generating nonGM hybrids. The compositional similarity of seven GM stacks containing event DAS-Ø15Ø7-1, and their matched nonGM near-isogenic hybrids (iso-hybrids) was compared with the compositional similarity of concurrently grown nonGM hybrids and these same iso-hybrids. Scatter plots were used to visualize comparisons among hybrids and a coefficient of identity (per cent of variation explained by line of identity) was calculated to quantify the relationships within analyte profiles.

Safe composition levels of transgenic crops assessed via a clinical medicine model.

Substantial equivalence has become established as a foundation concept in the safety evaluation of transgenic crops. In the case of a food and feed crop, no single variety is considered the standard for safety or nutrition, so the substantial equivalence of transgenic crops is investigated relative to the array of commercial crop varieties with a history of safe consumption. Although used extensively in clinical medicine to compare new generic drugs with brand-name drugs, equivalence limits are shown to be a poor model for comparing transgenic crops with an array of reference crop varieties.

Evaluation of logistic and polynomial models for fitting sandwich-ELISA calibration curves.

Appropriately modeled calibration curves are important for accurately estimating the concentrations of proteins in samples evaluated in sandwich-format enzyme-linked immunosorbent assay (ELISA). Calibration curves are commonly fit using polynomial or logistic models. We compared the fit of a quadratic, cubic and 4-parameter logistic model for highly-replicated calibration curves across seven assays used for quantifying transgenic proteins in commercial crops.

Fit of four curve-linear models to decay profiles for pest control substances in soil.

Experiments that investigate the pattern of degradation of pest control substances in soil are often undertaken to estimate the persistence of compounds in the environment. Mathematical models are typically fit to decay data to facilitate the interpretation of the results and make predictions concerning the environmental fate of xenobiotics in soil. Four mathematical models were fit to 61 data sets to compare their performance in conforming to empirical patterns of degradation of pest control substances in soil.

Comparison of linear and nonlinear regression for modeling the first-order degradation of pest-control substances in soil.

First-order kinetic models are often used to profile the degradation of pest-control compounds in soil. This approach is based on enzyme theory and is often favored due to its simplicity and its requirement by regulatory agencies. Here, linear and nonlinear regression approaches to modeling first-order decay are compared.

Binary insecticidal crystal protein from Bacillus thuringiensis, strain PS149B1: effects of individual protein components and mixtures in laboratory bioassays.

A family of novel binary insecticidal crystal proteins, with activity against western corn rootworm, Diabrotica virgifera virgifera LeConte, was identified from Bacillus thuringiensis Berliner. A binary insecticidal crystal protein (bICP) from B. thuringiensis strain PS149B1 is composed of a 14-kDa protein (Cry34Abl) and a 44-kDaprotein (Cry35Ab1).