Neural-network-based classification of cognitively normal, demented, Alzheimer disease and vascular dementia from single photon emission with computed tomography image data from brain.

Single photon emission with computed tomography (SPECT) hexamethylphenylethyleneamineoxime technetium-99 images were analyzed by an optimal interpolative neural network (OINN) algorithm to determine whether the network could discriminate among clinically diagnosed groups of elderly normal, Alzheimer disease (AD), and vascular dementia (VD) subjects. After initial image preprocessing and registration, image features were obtained that were representative of the mean regional tissue uptake. These features were extracted from a given image by averaging the intensities over various regions defined by suitable masks. After training, the network classified independent trials of patients whose clinical diagnoses conformed to published criteria for probable AD or probable/possible VD. For the SPECT data used in the current tests, the OINN agreement was 80 and 86% for probable AD and probable/possible VD, respectively. These results suggest that artificial neural network methods offer potential in diagnoses from brain images and possibly in other areas of scientific research where complex patterns of data may have scientifically meaningful groupings that are not easily identifiable by the researcher.

Direct measurement of nitric oxide generation from nitric oxide synthase

Although nitric oxide synthase (NOS) is widely considered as the major source of NO in biological cells and tissues, direct evidence demonstrating NO formation from the purified enzyme has been lacking. It was recently reported that NOS does not synthesize NO, but rather generates nitroxyl anion (NO−) that is subsequently converted to NO by superoxide dismutase (SOD). To determine if NOS synthesizes NO, electron paramagnetic resonance (EPR) spectroscopy was applied to directly measure NO formation from purified neuronal NOS. In the presence of the NO trap Fe2+-N-methyl-d-glucamine dithiocarbamate, NO gives rise to characteristic EPR signals with g = 2.04 and aN = 12.7 G, whereas NO− is undetectable. In the presence of l-arginine (l-Arg) and cofactors, NOS generated prominent NO signals. This NO generation did not require SOD, and it was blocked by the specific NOS inhibitor N-nitro-l-arginine methyl ester. Isotope-labeling experiments with l-[15N]Arg further demonstrated that NOS-catalyzed NO arose from the guanidino nitrogen of l-Arg. Measurement of the time course of NO formation demonstrated that it paralleled that of l-citrulline. The conditions used in the prior study were shown to result in potent superoxide generation, and this may explain the failure to measure NO formation in the absence of SOD. These experiments provide unequivocal evidence that NOS does directly synthesize NO from l-Arg.

From trial data to practical knowledge: qualitative study of how general practitioners have accessed and used evidence about statin drugs in their management of hypercholesterolaemia

Objectives To explore how general practitioners have accessed and evaluated evidence from trials on the use of statin lipid lowering drugs and incorporated this evidence into their practice. To draw out the practical implications of this study for strategies to integrate clinical evidence into general medical practice.

Complete congruence between gene diversity estimates derived from genotypic data at enzyme and random amplified polymorphic DNA loci in black spruce.

Controversy still exists over the adaptive nature of variation of enzyme loci. In conifers, random amplified polymorphic DNAs (RAPDs) represent a class of marker loci that is unlikely to fall within or be strongly linked to coding DNA. We have compared the genetic diversity in natural populations of black spruce [Picea mariana (Mill.) B.S.P.] using genotypic data at allozyme loci and RAPD loci as well as phenotypic data from inferred RAPD fingerprints. The genotypic data for both allozymes and RAPDs were obtained from at least six haploid megagametophytes for each of 75 sexually mature individuals distributed in five populations. Heterozygosities and population fixation indices were in complete agreement between allozyme loci and RAPD loci. In black spruce, it is more likely that the similar levels of variation detected at both enzyme and RAPD loci are due to such evolutionary forces as migration and the mating system, rather than to balancing selection and overdominance. Furthermore, we show that biased estimates of expected heterozygosity and among-population differentiation are obtained when using allele frequencies derived from dominant RAPD phenotypes.

The life sciences Global Image Database (GID)

Although a vast amount of life sciences data is generated in the form of images, most scientists still store images on extremely diverse and often incompatible storage media, without any type of metadata structure, and thus with no standard facility with which to conduct searches or analyses. Here we present a solution to unlock the value of scientific images. The Global Image Database (GID) is a web-based (http://www.g wer.ch/qv/gid/gid.htm) structured central repository for scientific annotated images. The GID was designed to manage images from a wide spectrum of imaging domains ranging from microscopy to automated screening. The annotations in the GID define the source experiment of the images by describing who the authors of the experiment are, when the images were created, the biological origin of the experimental sample and how the sample was processed for visualization. A collection of experimental imaging protocols provides details of the sample preparation, and labeling, or visualization procedures. In addition, the entries in the GID reference these imaging protocols with the probe sequences or antibody names used in labeling experiments. The GID annotations are searchable by field or globally. The query results are first shown as image thumbnail previews, enabling quick browsing prior to original-sized annotated image retrieval. The development of the GID continues, aiming at facilitating the management and exchange of image data in the scientific community, and at creating new query tools for mining image data.