Peripheral Delivery of a CNS Targeted, Metalo-Protease Reduces Aβ Toxicity in a Mouse Model of Alzheimer's Disease

Alzheimer's disease (AD), an incurable, progressive neurodegenerative disorder, is the most common form of dementia. Therapeutic options have been elusive due to the inability to deliver proteins across the blood-brain barrier (BBB). In order to improve the therapeutic potential for AD, we utilized a promising new approach for delivery of proteins across the BBB. We generated a lentivirus vector expressing the amyloid β-degrading enzyme, neprilysin, fused to the ApoB transport domain and delivered this by intra-peritoneal injection to amyloid protein precursor (APP) transgenic model of AD. Treated mice had reduced levels of Aβ, reduced plaques and increased synaptic density in the CNS. Furthermore, mice treated with the neprilysin targeting the CNS had a reversal of memory deficits. Thus, the addition of the ApoB transport domain to the secreted neprilysin generated a non-invasive therapeutic approach that may be a potential treatment in patients with AD

Quantitative Effects of Using Thin-Plate Priors in Bayesian SPECT Reconstruction

Maximum a posteriori approaches in the context of a Bayesian framework have played an important role in SPECT reconstruction. The major advantages of these approaches include not only the capability of modeling the character of the data in a natural way but also the allowance of the incorporation of a priori information. Here, we show that a simple modification of the conventional smoothing prior, such as the membrane prior, to one less sensitive to variations in first spatial derivatives - the thin plate (TP) prior - yields improved reconstructions in the sense of low bias at little change in variance. Although the nonquadratic priors, such as the weak membrane and the weak plate, can exhibit good performance, they suffer difficulties in optimization and hyperparameter estimation. On the other hand, the thin plate, which is a quadratic prior, leads to easier optimization and hyperparameter estimation. In this work, we evaluate and compare quantitative performance of MM, TP, and FBP (f..

Computerized Biological Brain Phantom for Evaluation of PET and SPECT Reconstruction

A digital brain phantom was created from available primate autoradiographic (AR) data for use in emission computed tomography studies. The tissue was radio-labelled with a functional analogue of the PET agent [18F]-fluoro-deoxyglucose (FDG). Following sacrifice of the animal, film records from serial 20µm thickness sections were digitized and calibrated to obtain ground truth 2D spatial distributions of relative radionuclide density. A 3D version was constructed by using a video subtraction method to align consecutive slices. In order to assess the effects of accurate modelling of activity, the AR data, containing cortical and basal ganglia structures, was used as a phantom in the context of a partial-volume correction method for obtaining accurate regional quantitation. A second phantom, less realistic in terms of activity assignment, was constructed and also tested. The results indicate that quantitation errors due to effects of nonuniform activity in the AR phantom are significant and comparable..

MECHANICAL MODELS AS PRIORS IN BAYESIAN TOMOGRAPHIC RECONSTRUCTION

We introduce a new prior---the weak plate---to Bayesian tomographic reconstruction. The weak plate captures the piecewise ramplike spatial structure evident in primate autoradiograph source distributions. The weak plate is a part of a family of "mechanical" models---weak membrane (1st order), weak plate (2nd order), and weak quadric (3rd order)---in which a class of smoothness constraints derived from properties of ideal physical materials are used as models in the associated reconstruction problem. Since "weak" priors generate local minima in MAP estimation, we have designed novel Generalized Expectation--Maximization deterministic annealing algorithms to alleviate this problem. Our simulation studies qualitatively demonstrate the improvements over the weak membrane and maximum likelihood reconstructions

Using Ground-Truth Data To Design Priors In Bayesian Spect Reconstruction

. We propose a method for estimating hyperparameters for prior models used in SPECT reconstruction. Our method uses a maximumlikelihood technique to fit hyperparameters to a training set that is itself representative of ground-truth objects to be reconstructed. We argue that autoradiography may be a good source for such exemplars. For a simple smoothing prior, we derive a closed-form expression for the hyperparameter, and for a more complex prior that promotes piecewise smoothness, we evaluate the likelihood expression numerically. Numerical experiments demonstrate that parameters derived from training sets are fairly close to parameter values optimal in the sense of various measures of image quality. 1. Introduction Bayesian methods in SPECT are attractive in that they support accurate models of the imaging system, and allow incorporation of prior information into the solution. Many studies demonstrate that Bayesian reconstruction methods can result in improved, relative to conventio..

Abscesso subdural ao nível da cauda equina: relato de um caso

É relatada a observação de um paciente de 42 anos, com paraplegia flácida devida a abscesso subdural ao nível da cauda equina. É realçada a pobreza de alterações sensitivas e esfincterianas neste caso e enfatizada a importância da cirurgia para obtenção de bons resultados