Accumulation of amyloid beta in human glioblastomas.

Many cancer types are intrinsically associated with specific types of amyloidosis, in which amyloid is accumulated locally inside tumors or systemically. Usually, this condition relates to the hyperproduction of specific amylogenic proteins. Recently, we found that the accumulation of amyloid beta (Aß) peptide immunofluorescence is linked to glioma cells in mouse tumors. Here we report that amyloid-specific histochemical dyes reveal amyloid accumulation in all human glioma samples. Application of two different antibodies against Aß peptide (a polyclonal antibody against human Aß1-42 and a monoclonal pan-specific mAb-2 antibody against Aß) showed that the amyloid in glioma samples contains Aß. Amyloid was linked to glioma cells expressing glial-specific fibrillary acidic protein (GFAP) and to glioma blood vessels. Astrocytes close to the glioma site and to affected vessels also accumulated Aß. We discuss whether amyloid is produced by glioma cells or is the result of systemic production of Aß in response to glioma development due to an innate immunity reaction. We conclude that amyloid build-up in glioma tumors is a part of the tumor environment, and may be used as a target for developing a novel class of anti-tumor drugs and as an antigen for glioma visualization.

Contrast cancellation technique applied to digital x-ray imaging using silicon strip detectors.

Dual-energy mammographic imaging experimental tests have been performed using a compact dichromatic imaging system based on a conventional x-ray tube, a mosaic crystal, and a 384-strip silicon detector equipped with full-custom electronics with single photon counting capability. For simulating mammal tissue, a three-component phantom, made of Plexiglass, polyethylene, and water, has been used. Images have been collected with three different pairs of x-ray energies: 16-32 keV, 18-36 keV, and 20-40 keV. A Monte Carlo simulation of the experiment has also been carried out using the MCNP-4C transport code. The Alvarez-Macovski algorithm has been applied both to experimental and simulated data to remove the contrast between two of the phantom materials so as to enhance the visibility of the third one.