P. Olmos

A new approach to automatic radiation spectrum analysis

The application of adaptive methods to the solution of the automatic radioisotope identification problem using the energy spectrum is described. The identification is carried out by means of neural networks, which allow the use of relatively reduced computational structures, while keeping high pattern recognition capability. In this context, it has been found that one of these simple structures, once adequately trained, is quite suitable to identify a given isotope present in a mixture of elements as well as the relative proportions of each identified substance. Preliminary results are presented, and are deemed good enough to consider these adaptive structures as powerful and simple tools in the automatic spectrum analysis. >

Application of neural network techniques in gamma spectroscopy

Abstract The usual methods of automatic radiation spectra analysis, based on fittings of peaks and background to exact mathematical curves, are valid for high resolution detectors. However, these methods are less successful for lower resolution detectors, such as the common scintillators or new room temperature semiconductors. Trying to solve some of the problems inherent in the application of complex fittings to the response of these detectors, we test here a new and less strict approach, based on the use of a neural network algorithm known as “associative memory”. This method appears useful in those cases in which a simple operation and a fast response are needed, together with a reasonable (and not extreme) accuracy. Furthermore, as the pattern recognition is carried out through the rough shape of the whole spectrum, instead of each individual peak, it can be used with advantage for low resolution detectors. With the idea of comparing the behavior of this method with the “classical” ones, the response of the network in the analysis of several spectra, taken with a NaI spectrometer, is presented.

Drift problems in the automatic analysis of gamma-ray spectra using associative memory algorithms

Perturbations affecting nuclear radiation spectrometers during their operation frequently spoil the accuracy of automatic analysis methods. One of the problems usually found in practice refers to fluctuations in the spectrum gain and zero, produced by drifts in the detector and nuclear electronics. The pattern acquired in these conditions may be significantly different from that expected with stable instrumentation, thus complicating the identification and quantification of the radionuclides present in it. The performance of Associative Memory algorithms when dealing with spectra affected by drifts is explored considering a linear energy-calibration function. The formulation of the extended algorithm, constructed to quantify the possible presence of drifts in the spectrometer, is deduced and the results obtained from its application to several practical cases are commented. >

Cocaine reverses the naltrexone-induced reduction in operant ethanol self-administration: The effects on immediate-early gene expression in the rat prefrontal cortex

Naltrexone is a clinically approved medication for alcoholism. We aimed to investigate the effectiveness of naltrexone co-administered with cocaine and the association of these substances with immediate-early gene expression in the rat prefrontal cortex. We used chronic operant ethanol self-administration and oral treatments prescribed for alcoholism and available in pharmacies to maximise the predictive validity in humans. We performed real-time PCR analysis to determine gene expression levels in the prefrontal cortex. Only the highest dose of naltrexone (1, 3, and 10 mg/kg, p.o.) reduced the response to ethanol. Cocaine increased ethanol self-administration in a dose-dependent manner (2.5, 10, 20 mg/kg, i.p.) and reversed the naltrexone-induced reduction. Naltrexone failed to prevent the cocaine-induced increase in locomotor activity observed in these animals. Chronic self-administration of ethanol reduced the expression of the C-fos gene 4- to 12-fold and increased expression of the COX-2 (up to 4-fold) and Homer1a genes in the rat prefrontal cortex. Chronic ethanol self-administration is prevented by naltrexone, but cocaine fully reverses this effect. This result suggests that cocaine may overcome naltrexones effectiveness as a treatment for alcoholism. The ethanol-induced reduction in C-fos gene expression in the prefrontal cortex reveals an abnormal activity of these neurons, which may be relevant in the compulsive consumption of ethanol, the control of reward-related areas and the behavioural phenotype of ethanol addiction.

Effects of topiramate on ethanol‐cocaine interactions and DNA methyltransferase gene expression in the rat prefrontal cortex

Recent and ongoing clinical studies have indicated that topiramate (Topamax®) could be effective in treating ethanol or cocaine abuse. However, the effects of topiramate on the co‐administration of ethanol and cocaine remain largely unknown.

A spontaneous deletion of α-synuclein is associated with an increase in CB1 mRNA transcript and receptor expression in the hippocampus and amygdala: effects on alcohol consumption.

α‐Synuclein (α‐syn) protein and endocannabinoid CB1 receptors are primarily located in presynaptic terminals. An association between α‐syn and CB1 receptors has recently been established in Parkinsons disease, but it is completely unknown whether there is an association between these two proteins in alcohol addiction. Therefore, we aimed to examine the α‐syn mRNA transcript and protein expression levels in the prefrontal cortex, striatum, amygdala and hippocampus. These brain regions are the most frequently implicated in alcohol and other drug addiction. In these studies, we used C57BL/6 mice carrying a spontaneous deletion of the α‐syn gene (C57BL/6Snca‐/‐) and their respective controls (C57BL/6Snca+/+). These animals were monitored for spontaneous alcohol consumption (3–10%) and their response to a hypnotic‐sedative dose of alcohol (3 g kg−1) was also assessed. Compared with the C57BL/6Snca+/+ mice, we found that the C57BL/6Snca‐/‐ mice exhibited a higher expression level of the CB1 mRNA transcript and CB1 receptor in the hippocampus and amygdala. Furthermore, C57BL/6Snca‐/‐ mice showed an increase in alcohol consumption when offered a 10% alcohol solution. There was no significant difference in sleep time after the injection of 3 g/kg alcohol. These results are the first to reveal an association between α‐syn and the CB1 receptor in the brain regions that are most frequently implicated in alcohol and other drug addictions. Synapse 00:000–000, 2013.

Computer simulations of the behaviour of the partial charge collection model in thick HgI2 γ-detectors

Abstract The partial charge collection model has been reported as the most suitable technique to form good-resolution spectra with thick HgI 2 γ-detectors. This method is based on measuring the charge signal induced by the drift of the free carriers generated in the interaction, while the electrons have not reached the positive electrode, instead of taking the total pulse height as a measure of the energy. A computer simulation of the whole process, from the interaction of the γ-ray with the detector to the electronic signal treatment, has been developed. With the help of this tool, several situations concerning thick HgI 2 detectors have been considered, analysing different practical implementations of the partial collection method. In particular, two approaches, one based on shaping at short times and the other using a flash pulse digitation, have been extensively discussed and compared.

Radiation spectroscopy by digital pulse height analysis

Abstract This paper presents a new version of the Digital Pulse-Height Analysis (DPHA) method described in a previous paper, which is based on data acquisition through a personal computer using a flash-ADC card followed by numerical processing of pulses in the same computer. Performance tests carried out with a pulse generator and gamma-ray spectra have been carried out and their results are discussed.

Gamma ray imaging using coded aperture masks: a computer simulation approach

The gamma-ray imaging using coded aperture masks as focusing elements is an extended technique for static position sensitive detectors. Several transfer functions have been proposed to implement mathematically the set of holes in the mask, the uniformly redundant array collimator being the most popular design. A considerable amount of work has been done to improve the digital methods to deconvolve the gamma-ray image, formed at the detector plane, with this transfer function. Here we present a study of the behavior of these techniques when applied to the geometric shadows produced by a set of point emitters. Comparison of the shape of the object reconstructed from these shadows with that resulting from the analytical reconstruction is performed, defining the validity ranges of the usual algorithmic approximations reported in the literature. Finally, several improvements are discussed.

Design of a modified uniform redundant-array mask for portable gamma cameras

Uniform redundant-array masks have been reported as good lenses to form the image of gamma sources, with the correlation between the mask-aperture matrix and the shadows projected on a static position-sensitive detector. We present a modified uniform redundant-array configuration suitable for portable and small-size gamma cameras; its ability to reconstruct the image of several sources is analyzed. We have carried out a Montecarlo simulation of the gamma interactions in the mask, defining the expected response of the correlation process and comparing it with that achieved with the usual uniform redundant-array configurations.