Stimulus properties of some analogues of 4-methylaminorex.

The stimulus properties of aminorex and analogues of 4-methylaminorex, namely (4S,5S)-4-methylaminorex, N-methyl-(4S,5S)-4-methylaminorex, and the regioisomeric (R)- and (S)-2-amino-4-phenyl-2-oxazoline (rexamino) were compared in rats trained to distinguish (S)-amphetamine (1 mg/kg) from saline. The first three compounds, aminorex, (4S,5S)-4-methylaminorex, and N-methyl-(4S,5S)-4-methylaminorex shared discriminative stimulus effects with amphetamine, although the stimulus properties for racemic aminorex were less than those of the other two compounds. The two regioisomers, (R)- and (S)-rexamino, produced only partial generalisation to the amphetamine.

The effects of aminorex and related compounds on brain monoamines and metabolites in CBA mice.

Acute and long-term neurochemical effects of aminorex, an appetite-suppressing drug related to amphetamine in chemical structure, and stereoisomers of its analogues were examined and compared with those of 3.4-methylenedioxymethylamphetamine (MDMA) and fenfluramine. Aminorex and its analogues, with exception of 4S, 5S-dimethylaminorex, did not cause the long-term neurotransmitter depletion in either the dopaminergic or 5-HT-ergic systems that was observed after MDMA or fenfluramine in CBA mice. These results are discussed in terms of possible structurally related mechanisms of neurotoxicity. The acute neurochemical effects showed that aminorex and analogues all produced increases in 5-hydroxytryptamine (5-HT) levels, unlike fenfluramine and MDMA in the present study or in published data. This suggests that inhibition of 5-HT metabolism, rather than direct 5-HT release, may be involved in their anorectic effect. The parallel study of acute dopamine and 3,4-dihydroxyphenylacetic acid (DOPAC) changes suggest that in CBA mice MDMA may be a better dopamine releaser and this may contribute to its dopaminergic neurotoxicity. However the ability to release dopamine or 5-HT, or both, may be important, but not the only factor involved in causing the long-term neurotoxicity observed with amphetamine derivatives.

Rpr1, a gene required for Rpg1-dependent resistance to stem rust in barley.

Rpg1 is a stem rust resistance gene that has protected barley from severe losses for over 60 years in the US and Canada. It confers resistance to many, but not all, pathotypes of the stem rust fungus Puccinia graminis f. sp. tritici. A fast neutron induced deletion mutant, showing susceptibility to stem rust pathotype Pgt-MCC, was identified in barley cv. Morex, which carries Rpg1. Genetic and Rpg1 mRNA and protein expression level analyses showed that the mutation was a suppressor of Rpg1 and was designated Rpr1 (Required for P. graminis resistance). Genome-wide expression profiling, using the Affymetrix Barley1 GeneChip containing approximately 22,840 probe sets, was conducted with Morex and the rpr1 mutant. Of the genes represented on the Barley1 microarray, 20 were up-regulated and 33 were down-regulated by greater than twofold in the mutant, while the Rpg1 mRNA level remained constant. Among the highly down-regulated genes (greater than fourfold), genomic PCR, RT-PCR and Southern analyses identified that three genes (Contig4901_s_at, HU03D17U_s_at, and Contig7061_s_at), were deleted in the rpr1 mutant. These three genes mapped to chromosome 4(4H) bin 5 and co-segregated with the rpr1-mediated susceptible phenotype. The loss of resistance was presumed to be due to a mutation in one or more of these genes. However, the possibility exists that there are other genes within the deletions, which are not represented on the Barley1 GeneChip. The Rpr1 gene was not required for Rpg5- and rpg4-mediated stem rust resistance, indicating that it shows specificity to the Rpg1-mediated resistance pathway.

Barley putative hypersensitive induced reaction genes: genetic mapping, sequence analyses and differential expression in disease lesion mimic mutants.

The hypersensitive response (HR) is one of the most-efficient forms of plant defense against biotrophic pathogens, and results in localized cell death and the formation of necrotic lesions; however, the molecular components of pathways leading to HR remain largely unknown. Barley ( Hordeum vulgare ssp. vulgare L.) cDNAs for putative hypersensitive-induced reaction ( HIR) genes were isolated based on DNA and amino-acid homologies to maize HIR genes. Analyses of the cDNA and genomic sequences and genetic mapping found four distinct barley HIR genes, Hv-hir1, Hv-hir2, Hv-hir3 and Hv-hir4, on chromosomes 4(4H) bin10, 7(5H) bin04, 7(5H) bin07 and 1(7H) bin03, respectively. Hv-hir1, Hv-hir2 and Hv-hir3 genes were highly homologous at both DNA and the deduced amino-acid level, but the Hv-hir4 gene was similar to the other genes only at the amino-acid sequence level. Amino-acid sequence analyses of the barley HIR proteins indicated the presence of the SPFH protein-domain characteristic for the prohibitins and stomatins which are involved in control of the cell cycle and ion channels, as well as in other membrane-associated proteins from bacteria, plants and animals. HIR genes were expressed in all organs and developement stages analyzed, indicating a vital and non-redundant function. Barley fast-neutron mutants exhibiting spontaneous HR (disease lesion mimic mutants) showed up to a 35-fold increase in Hv-hir3 expression, implicating HIR genes in the induction of HR.

Solid state assay of ranitidine HCl as a bulk drug and as active ingredient in tablets using DRIFT spectroscopy with artificial neural networks.

PURPOSE: A new, simple, sensitive and rapid method was developed to analyse the polymorphic purity of crystalline ranitidine-HCI as a bulk drug and from a tablet formulation. METHODS: Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy was combined with Artificial Neural Networks (ANNs) as a data modelling tool. A standard feed-forward network, with backpropagation rule and with single hidden layer architecture was chosen. Reduction and transformation of the spectral data enhanced the ANN performance and reduced the complexity of the ANNs model. Spectral intensities from 1738 wavenumbers were reduced into 173 averaged spectral values. These 173 values were used as inputs for the ANN. Following a sensitivity analysis the number of inputs was reduced to 30, or 35, these being the input windows which had most effect on the output of the ANN. RESULTS: For the bulk drug assay, the ANN model had 30 inputs selected from a sensitivity analysis, one hidden layer, and two output neurons, one for the percentage of each ranitidine hydrochloride crystal form. The model could simultaneously distinguish between crystal forms and quantify them enabling the physical purity of the bulk drug to be checked. For the tablet assay, the ANN model had 173 averaged spectral values as the inputs, one hidden layer and five output neurons, two for the percentage of the two ranitidine hydrochloride crystal forms and three more outputs for tablet excipients and additives. The ANN was able to solve the problem of overlapping peaks and it successfully identified and quantified all components in tablet formulation with reasonable accuracy. CONCLUSIONS: Some of the advantages over conventional analytical methods include simplicity, speed and good selectivity. The results from DRIFT spectral quantification study show the benefits of the neural network approach in analysing spectral data.