Selective vulnerability to atrophy in sporadic Creutzfeldt-Jakob disease.

OBJECTIVE: Identification of brain regions susceptible to quantifiable atrophy in sporadic Creutzfeldt-Jakob disease (sCJD) should allow for improved understanding of disease pathophysiology and development of structural biomarkers that might be useful in future treatment trials. Although brain atrophy is not usually present by visual assessment of MRIs in sCJD, we assessed whether using voxel-based morphometry (VBM) can detect group-wise brain atrophy in sCJD. METHODS: 3T brain MRI data were analyzed with VBM in 22 sCJD participants and 26 age-matched controls. Analyses included relationships of regional brain volumes with major clinical variables and dichotomization of the cohort according to expected disease duration based on prion molecular classification (i.e., short-duration/Fast-progressors (MM1, MV1, and VV2) vs. long-duration/Slow-progressors (MV2, VV1, and MM2)). Structural equation modeling (SEM) was used to assess network-level interactions of atrophy between specific brain regions. RESULTS: sCJD showed selective atrophy in cortical and subcortical regions overlapping with all but one region of the default mode network (DMN) and the insulae, thalami, and right occipital lobe. SEM showed that the effective connectivity model fit in sCJD but not controls. The presence of visual hallucinations correlated with right fusiform, bilateral thalami, and medial orbitofrontal atrophy. Interestingly, brain atrophy was present in both Fast- and Slow-progressors. Worse cognition was associated with bilateral mesial frontal, insular, temporal pole, thalamus, and cerebellum atrophy. INTERPRETATION: Brain atrophy in sCJD preferentially affects specific cortical and subcortical regions, with an effective connectivity model showing strength and directionality between regions. Brain atrophy is present in Fast- and Slow-progressors, correlates with clinical findings, and is a potential biomarker in sCJD.

Genetically engineered plants, endangered species, and risk: a temporal and spatial exposure assessment for Karner blue butterfly larvae and Bt maize pollen.

Genetically engineered maize (Zea mays) containing insecticidal endotoxin proteins from Bacillus thuringiensis (Bt) delta-endotoxin proteins has been adopted widely in the Midwestern United States. The proteins are toxic to several lepidopteran species and because a variety of maize tissues, including pollen, may express the endotoxins, the probability of exposure to nontarget species, including endangered species, needs to be understood. The objective of this study was to assess the potential temporal and spatial exposure of endangered Karner blue butterfly larvae (Lycaeides melissa samuelis) to Bt maize pollen in Wisconsin using probabilistic exposure techniques and geographic information systems analysis. Based on degree-day modeling of butterfly phenology and maize pollen shed, there is some potential for temporal exposure of larvae to maize pollen. However, in the majority of years and locations, maize pollen shed most likely will occur after the majority of larval feeding on wild lupine (Lupinus perennis). The spatial analysis indicates that some Karner blue butterfly populations occur in close proximity to maize fields, but in the vast majority of cases the butterfly's host plant and maize fields are separated by more than 500 m. A small number of potential or existing Karner blue butterfly sites are located near maize fields, including sites in two of the four counties where temporal overlap is most likely. The exposure assessment indicates that these two counties should receive the highest priority to determine if Karner blue butterfly larvae are actually at risk and then, if needed, to reduce or prevent exposure.