In vivo evaluation of a hybrid nanoparticle for molecular imaging of amyloid aggregation

International audienceAmyloid-β (Aβ) fibrillization is described as a central event in the pathogenesis of Alzheimer’s disease (AD). Amyloid imaging is expected to play a pivotal role in early and differential diagnosis of dementias, and in the evaluation of anti-Aβ treatments. Luminescent conjugated oligothiophenes (LCO) have been proposed as optical biomarkers of protein fibrillation [1]. In this paper, we evaluated a fluorescent magnetic hybrid nanoprobe (HNP5011), based on gadolinium fluoride nanoparticles functionalized with luminescent conjugated polythiophenes moieties (Fig. 1). The aim of this study was to investigate its potential for molecular imaging in a rat model bearing intracerebral pre-aggregated Aβ peptides

Oscillazioni e turbamenti della distinzione privato-pubblico nella cultura di massa

CULTURA DI MASSA, SFERA PUBBLICA, SFERA PRIVAT

Il grande spreco

Tecnologia e controllo dell'informazione, dibattito sul Rapporto Mc Brid

Information-based analysis of X-ray in-line phase tomography with application to the detection of iron oxide nanoparticles in the brain

International audienceThe study analyzes noise in X-ray in-line phase tomography in a biomedical context. The impact of noise on detection of iron oxide nanoparticles in mouse brain is assessed. The part of the noise due to the imaging system and the part due to biology are quantitatively expressed in a Neyman Pearson detection strategy with two models of noise. This represents a practical extension of previous work on noise in phase-contrast X-ray imaging which focused on the theoretical expression of the signal-to-noise ratio in mono-dimensional phantoms, taking account of the statistical noise of the imaging system only. We also report the impact of the phase retrieval step on detection performance. Taken together, this constitutes a general methodology of practical interest for quantitative extraction of information from X-ray in-line phase tomography, and is also relevant to assessment of contrast agents with a blob-like signature in high resolution imaging

Computer vision tools to optimize reconstruction parameters in x-ray in-line phase tomography.

International audienceIn this article, a set of three computer vision tools, including scale invariant feature transform (SIFT), a measure of focus, and a measure based on tractography are demonstrated to be useful in replacing the eye of the expert in the optimization of the reconstruction parameters in x-ray in-line phase tomography. We demonstrate how these computer vision tools can be used to inject priors on the shape and scale of the object to be reconstructed. This is illustrated with the Paganin single intensity image phase retrieval algorithm in heterogeneous soft tissues of biomedical interest, where the selection of the reconstruction parameters was previously made from visual inspection or physical assumptions on the composition of the sample