In vivo [3H]flunitrazepam binding: imaging of receptor regulation

ABSTRACT ABBREVIATIONS: BDZ, benzodiazepine; GABA, 'y-aminobutyric acid; HO, Huntington's Disease; GP, globus pallidus; SNr, substantia nigra pars reticulata; FLU, flunitrazepam; PET, positron emission tomography; BBB, blood-brain barrier. 74

NMDA receptor channels: Labeling of MK-801 with iodine-125 and fluorine-18

Methods for labeling the glutamate channel blocking agent MK-801 with iodine-125 (125I) and fluorine-18 (18F) are described. Radioiodine was incorporated in the 1- or 3-positions of the aromatic ring of (+/-)MK-801 by solid-state halogen exchange techniques. Attachment of the [18F]fluoromethyl group to the bridgehead methyl position was achieved by reaction of [18F]fluoride with the triflamide alcohol 8 or the novel cyclic sulfamate 9 recently reported by Merck chemists. Radiochemical yields of (+/-)13-[18F]- fluoromethyl-MK-801 were >72%, EOB; radiochemical purity >99%. In competitive binding studies using rat brain homogenates, (+/-)3-bromo-MK-801 showed greater affinity than (+/-)MK-801 for the glutamate-linked channel. The experimental log P (2.1 +/- 0.1) of MK-801 is optimal for transit of the blood-brain barrier. These preliminary findings support further testing of 3-[123I]iodo-MK-801 and (+/-)13-[18F]fluoromethyl-MK-801 as possible agents for in vivo mapping of the glutamate receptor complex.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/27605/1/0000649.pd

GABA and benzodiazepine receptors in basal ganglia function

GABA and its associated benzodiazepine interactions play an important role in basal ganglia function. Distinctive GABA, benzodiazepine and opiate receptor changes occur in response to striatal lesions and in the human neurodegenerative disorder, Huntington's disease (HD). In animal experiments, the in vivo administration of [3H]flunitrazepam labels benzodiazepine receptors and can demonstrate the receptor changes seen after striatal lesions. It should be possible to measure these receptors in vivo in humans using positron-emission tomographic scanning.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24774/1/0000198.pd

Text Analysis of MEDLINE for Discovering Functional Relationships among Genes: Evaluation of Keyword Extraction Weighting Schemes

One of the key challenges of microarray studies is to derive biological insights from the gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the functional links among genes. However, the quality of the keyword lists significantly affects the clustering results. We compared two keyword weighting schemes: normalised z-score and term frequency-inverse document frequency (TFIDF). Two gene sets were tested to evaluate the effectiveness of the weighting schemes for keyword extraction for gene clustering. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords outperformed those produced from normalised z-score weighted keywords. The optimised algorithms should be useful for partitioning genes from microarray lists into functionally discrete clusters

Text mining biomedical literature for discovering gene-to-gene relationships: a comparative study of algorithms

Abstract—Partitioning closely related genes into clusters has become an important element of practically all statistical analyses of microarray data. A number of computer algorithms have been developed for this task. Although these algorithms have demonstrated their usefulness for gene clustering, some basic problems remain. This paper describes our work on extracting functional keywords from MEDLINE for a set of genes that are isolated for further study from microarray experiments based on their differential expression patterns. The sharing of functional keywords among genes is used as a basis for clustering in a new approach called BEA-PARTITION in this paper. Functional keywords associated with genes were extracted from MEDLINE abstracts. We modified the Bond Energy Algorithm (BEA), which is widely accepted in psychology and database design but is virtually unknown in bioinformatics, to cluster genes by functional keyword associations. The results showed that BEA-PARTITION and hierarchical clustering algorithm outperformed k-means clustering and self-organizing map by correctly assigning 25 of 26 genes in a test set of four known gene groups. To evaluate the effectiveness of BEA-PARTITION for clustering genes identified by microarray profiles, 44 yeast genes that are differentially expressed during the cell cycle and have been widely studied in the literature were used as a second test set. Using established measures of cluster quality, the results produced by BEA-PARTITION had higher purity, lower entropy, and higher mutual information than those produced by k-means and self-organizing map. Whereas BEA-PARTITION and the hierarchical clustering produced similar quality of clusters, BEA-PARTITION provides clear cluster boundaries compared to the hierarchical clustering. BEA-PARTITION is simple to implement and provides a powerful approach to clustering genes or to any clustering problem where starting matrices are available from experimental observations. Index Terms—Bond energy algorithm, microarray, MEDLINE, text analysis, cluster analysis, gene function.

Comparison of two schemes for automatic keyword extraction from MEDLINE for functional gene clustering

One of the key challenges of microarray studies is to derive biological insights from the unprecedented quatities of data on gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the nature of the functional links among genes within the derived clusters. However, the quality of the keyword lists extracted from biomedical literature for each gene significantly affects the clustering results. We extracted keywords from MEDLINE that describes the most prominent functions of the genes, and used the resulting weights of the keywords as feature vectors for gene clustering. By analyzing the resulting cluster quality, we compared two keyword weighting schemes: normalized z-score and term frequency-inverse document frequency (TFIDF). The best combination of background comparison set, stop list and stemming algorithm was selected based on precision and recall metrics. In a test set of four known gene groups, a hierarchical algorithm correctly assigned 25 of 26 genes to the appropriate clusters based on keywords extracted by the TDFIDF weighting scheme, but only 23 og 26 with the z-score method. To evaluate the effectiveness of the weighting schemes for keyword extraction for gene clusters from microarray profiles, 44 yeast genes that are differentially expressed during the cell cycle were used as a second test set. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords had higher purity, lower entropy, and higher mutual information than those produced from normalized z-score weighted keywords. The optimized algorithms should be useful for sorting genes from microarray lists into functionally discrete cluster

Synthesis and Receptor Binding Studies of ( ± )l-Iodo-MK-801

The glutamate analogue N -methyl-D-aspartate (NMDA) binds to a subset of glutamate receptors that are coupled to a voltage-sensitive cation channel. This NMDA-linked channel is the likely binding locus of the potent anticonvulsant MK-801. To develop single-photon emission computed tomography (SPECT) probes of this brain channel, we synthesized (±)l-iodo-MK-801 and (±)l-[ 125 I]iodo-MK-801. The effect of (±)l-iodo-MK-801 on ligand binding to the NMDA-linked glutamate receptor site was assessed using a rat brain homogenate assay. (±)l-Iodo-MK-801 displaced the dissociative anesthetic ligand [ 3 H] N -[l-(2-thienyl)cyclohexyl]piperidine ([ 3 H]TCP) binding with an IC 50 of 1 µ M , which is a 10-fold lower binding affinity than that of (±)MK-801. In in vivo autoradiographic studies, (±)MK-801 failed to block selective uptake of (±)l-iodo-MK-801 in rat brain. These results suggest that (±)l-iodo-MK-801 may not be a suitable ligand for mapping NMDA-linked glutamate receptor channels.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41537/1/11095_2004_Article_306014.pd

Immunocytochemical localization of the dopamine transporter in human brain

The dopamine transporter (DAT) was localized in normal human brain tissue by light microscopic immunocytochemistry by using highly specific monoclonal antibodies. Regional distribution of DAT was found in areas with established dopaminergic circuitry, e.g., mesostriatal, mesolimbic, and mesocortical pathways. Mesencephalic DAT-immunoreactivity was enriched in the dendrites and cell bodies of neurons in the substantia nigra pars compacta and ventral tegmental area. Staining in the striatum and nucleus accumbens was dense and heterogeneous. Mesocortical DAT immunoreactivity in motor, premotor, anterior cingulate, prefrontal, entorhinal/perirhinal, insular, and visual cortices was detected in scattered varicose and a few nonvaricose fibers. Varicose fibers were relatively enriched in the basolateral and central subnuclei of amygdala, with sparser fibers in lateral and basomedial subnuclei. Double-labeling studies combining DAT and tyrosine hydroxylase (TH) immunostaining in the ventral mesencephalon showed two subpopulations of dopaminergic neurons differentiated by the presence or absence of DAT- immunoreactivity in the A9 and A10 cell groups. In other dopaminergic cell groups (A11, A13-A15), TH-positive hypothalamic neurons showed no detectable DAT-immunoreactivity. However, fine DAT-immunoreactive axons were scattered throughout the hypothalamus, particularly concentrated along the medial border, with more coarse axons present along the lateral border. These findings demonstrate that most mesotelencephalic dopamine neurons of human brain express high levels of DAT throughout their entire somatodendritic and axonal domains, whereas a smaller subpopulation of mesencephalic dopamine cells and all hypothalamic dopamine cell groups examined express little or no DAT. These data indicate that different subpopulations of dopaminergic neurons use different mechanisms to regulate their extracellular dopamine levels

Synthesis of a high specific activity 125I-labeled analog of PK 11195, potential agent for SPECT imaging of the peripheral benzodiazepine binding site

The peripheral benzodiazepine binding site ligand PK 11195 has been 125I-labeled by direct displacement of aromatic chlorine under solid-state conditions in 50-76% radiochemical yield and >94% radiochemical purity. Purification by high pressure liquid chromatography increased the specific activity of the product from an initial 15-17 Ci/mmol to a final activity of 260-910 Ci/mmol. To determine the affinity of this [125I]PK 11195 analog for human glioma cells, saturation experiments were performed on monolayers of U251 human glioblastoma cells. Scatchard analysis of saturation data demonstrated that the [125I]PK 11195 analog binds to a single class of sites with a KD of 8.0 +/- 1.7 nM and maximal binding of 3.8 +/- 0.1 pmol/mg protein. These values are similar to those obtained when [3H]PK 11195 was assayed in U251 cells (KD = 14 +/- 3.4, Bmax = 4.1 +/- 1.3) suggesting that iodination does not appreciably alter the binding of PK 11195 to human glioma cells. In vivo autoradiographic studies of brain in C6 glioma bearing rats demonstrate selective binding of the radioligand to the tumor. These results suggest that this [125I]PK 11195 analog may be a useful radiotracer for the study of peripheral benzodiazepine binding sites.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28191/1/0000643.pd