RESUMEN
We examined heterozygous transgenic (Tg) mice that overexpress V717F amyloid precursor protein (APP) for delay eyeblink conditioning (EBC) and hippocampal volume with magnetic resonance imaging (MRI). Platelet-derived APP mice were significantly impaired on EBC relative to wild type (WT) litter-mate controls. T2-weighted spin echo images (62.5 x 125 x 500 microm) of the same mice were acquired under anesthesia using a 9.4T magnet. Tg mice had hippocampal to brain volume ratios that were significantly smaller than WT controls (31% smaller in the rostral dorsal hippocampus, 13-22% smaller among equal dorsal-ventral thirds of a caudal section). These results indicate that overexpression of APP or beta amyloid profoundly affects learning and memory and hippocampal volume. The results also indicate that eyeblink conditioning and quantitative MRI in mice may be useful assays to follow the progression of disease-related changes, and to test the effectiveness of potential therapeutics against Alzheimer's disease.
Asunto(s)
Enfermedad de Alzheimer/patología , Precursor de Proteína beta-Amiloide/metabolismo , Parpadeo , Condicionamiento Psicológico , Hipocampo/patología , Enfermedad de Alzheimer/metabolismo , Enfermedad de Alzheimer/fisiopatología , Precursor de Proteína beta-Amiloide/genética , Animales , Hipocampo/metabolismo , Aprendizaje , Imagen por Resonancia Magnética , Magnetismo , Masculino , Memoria , Ratones , Ratones TransgénicosRESUMEN
We propose an iterative algorithm for enhancing the resolution of monochrome and color image sequences. Various approaches toward motion estimation are investigated and compared. Improving the spatial resolution of an image sequence critically depends upon the accuracy of the motion estimator. The problem is complicated by the fact that the motion field is prone to significant errors since the original high-resolution images are not available. Improved motion estimates may be obtained by using a more robust and accurate motion estimator, such as a pel-recursive scheme instead of block matching, in processing color image sequences, there is the added advantage of having more flexibility in how the final motion estimates are obtained, and further improvement in the accuracy of the motion field is therefore possible. This is because there are three different intensity fields (channels) conveying the same motion information. In this paper, the choice of which motion estimator to use versus how the final estimates are obtained is weighed to see which issue is more critical in improving the estimated high-resolution sequences. Toward this end, an iterative algorithm is proposed, and two sets of experiments are presented. First, several different experiments using the same motion estimator but three different data fusion approaches to merge the individual motion fields were performed. Second, estimated high-resolution images using the block matching estimator were compared to those obtained by employing a pel-recursive scheme. Experiments were performed on a real color image sequence, and performance was measured by the peak signal to noise ratio (PSNR).