Aspirin-Induced Mortality in AedesaegyptiMosquitoes

The Aedes aegypti mosquito is a vector for many dangerous diseases including yellow fever, Zika, Chikungunya, and Dengue viruses! Currently, the best method for suppressing infection with these viruses is by controlling their arthropod vectors, however the continual use of conventional insecticides to control Ae. aegypti mosquitoes has led to the development of significant levels of resistance to these chemicals. Accordingly, new methods are needed. Anecdotal evidence has suggested that mosquitoes may be sensitive to treatment with aspirin or its metabolites in a blood meal. Previous studies with aspirin in insects have mainly focused on the ability of aspirin to enhance longevity and lifespan in Drosophila melanogaster and crickets2.4, but one study showed that aspirin in water where larvae are developing causes significant mortality and signs of neurotoxicity. While treating larvae in this manner is not practical for vector control, this result, in addition to the anecdotal evidence, prompted the question of whether aspirin consumed in a blood meal can cause mortality in adult mosquitoes. Accordingly, we fed adult female Ae. aegypti mosquitoes differing concentrations of aspirin in human blood and measured mortality for four days following the blood meal. The concentrations chosen correspond to plasma concentrations of aspirin in humans who have consumed 100 mg (a baby aspirin), 1 g (normal adult dose), or 10 g (overdose), respectively. Our results indicate that these concentrations of aspirin are insufficient to cause significant mortality in the mosquitos. Although unsuccessful, modification of our methods, use of a different mosquito species, or use of aspirin metabolites in our bioassays may yet show a significant impact of aspirin consumption on mosquito survival

FloatingCanvas: quantification of 3D retinal structures from spectral-domain optical coherence tomography

Spectral-domain optical coherence tomography (SD-OCT) provides volumetric images of retinal structures with unprecedented detail. Accurate segmentation algorithms and feature quantification in these images, however, are needed to realize the full potential of SD-OCT. The fully automated segmentation algorithm, FloatingCanvas, serves this purpose and performs a volumetric segmentation of retinal tissue layers in three-dimensional image volume acquired around the optic nerve head without requiring any pre-processing. The reconstructed layers are analysed to extract features such as blood vessels and retinal nerve fibre layer thickness. Findings from images obtained with the RTVue-100 SD-OCT (Optovue, Fremont, CA, USA) indicate that FloatingCanvas is computationally efficient and is robust to the noise and low contrast in the images. The FloatingCanvas segmentation demonstrated good agreement with the human manual grading. The retinal nerve fibre layer thickness maps obtained with this method are clinically realistic and highly reproducible compared with time-domain StratusOCT™

A report of available research on the status of science teaching in the state of Kansas, 1936-1971

Digitized by Kansas Correctional Industrie

Incorporation of regional information in optimal 3-D graph search with application for intraretinal layer segmentation of optical coherence tomography images

We present a method for the incorporation of regional image information in a 3-D graph-theoretic approach for optimal multiple surface segmentation. By transforming the multiple surface segmentation task into finding a minimum-cost closed set in a vertex-weighted graph, the optimal set of feasible surfaces with respect to an objective function can be found. In the past, this family of graph search applications only used objective functions which incorporated “on-surface” costs. Here, novel “in-region” costs are incorporated. Our new approach is applied to the segmentation of seven intraretinal layer surfaces of 24 3-D macular optical coherence tomography images from 12 subjects. Compared to an expert-defined independent standard, unsigned border positioning errors are comparable to the inter-observer variability (7.8 ± 5.0 μm and 8.1 ± 3.6 μm, respectively)