Gap junction structures: Analysis of the x-ray diffraction data

Models for the spatial distribution of protein, lipid and water in gap junction structures have been constructed from the results of the analysis of X-ray diffraction data described here and the electron microscope and chemical data presented in the preceding paper (Caspar, D. L. D., D. A. Goodenough, L. Makowski, and W.C. Phillips. 1977. 74:605-628). The continuous intensity distribution on the meridian of the X-ray diffraction pattern was measured, and corrected for the effects of the partially ordered stacking and partial orientation of the junctions in the X-ray specimens. The electron density distribution in the direction perpendicular to the plane of the junction was calculated from the meridional intensity data. Determination of the interference function for the stacking of the junctions improved the accuracy of the electron density profile. The pair-correlation function, which provides information about the packing of junctions in the specimen, was calculated from the interference function. The intensities of the hexagonal lattice reflections on the equator of the X-ray pattern were used in coordination with the electron microscope data to calculate to the two-dimensional electron density projection onto the plane of the membrane. Differences in the structure of the connexons as seen in the meridional profile and equatorial projections were shown to be correlated to changes in lattice constant. The parts of the junction structure which are variable have been distinguished from the invariant parts by comparison of the X-ray data from different specimens. The combination of these results with electron microscope and chemical data provides low resolution three- dimensional representations of the structures of gap junctions.     

The role of nitric oxide in cancer

Nitric oxide (NO) is a pleiotropic regulator, critical to numerous biological processes, including va-sodilatation, neurotransmission and macrophage-mediated immunity. The family of nitric oxide synthases (NOS) comprises inducible NOS (iNOS), endothelial NOS (eNOS), and neuronal NOS (nNOS). Interestingly, various studies have shown that all three isoforms can be involved in promoting or inhibiting the etiology of cancer. NOS activity has been detected in tumour cells of various histogenetic origins and has been associated with tumour grade, proliferation rate and expression of important signaling components associated with cancer development such as the oestrogen receptor. It appears that high levels of NOS expression (for example, generated by activated macrophages) may be cytostatic or cytotoxic for tumor cells, whereas low level activity can have the opposite effect and promote tumour growth. Paradoxically therefore, NO (and related reactive nitrogen species) may have both genotoxic and angiogenic pro     

Paired sequence difference in ribosomal RNAs: evolutionary and phylogenetic implications

Ribosomal RNAs have secondary structures that are maintained by internal Watson-Crick pairing. Through analysis of chordate, arthropod, and plant 5S ribosomal RNA sequences, we show that Darwinian selection operates on these nucleotide sequences to maintain functionally important secondary structure. Insect phylogenies based on nucleotide positions involved in pairing and the production of secondary structure are incongruent with those constructed on the basis of positions that are not. Furthermore, phylogeny reconstruction using these nonpairing bases is concordant with other, morphological data.      

Mitochondrial gene order is not conserved in arthropods: prostriate and metastriate tick mitochondrial genomes

The entire mitochondrial genome was sequenced in a prostriate tick, Ixodes hexagonus, and a metastriate tick, Rhipicephalus sanguineus. Both genomes encode 22 tRNAs, 13 proteins, and two ribosomal RNAs. Prostriate ticks are basal members of Ixodidae and have the same gene order as Limulus polyphemus. In contrast, in R. sanguineus, a block of genes encoding NADH dehydrogenase subunit 1 (ND1), tRNA(Leu)(UUR), tRNA(Leu)(CUN), 16S rDNA, tRNA(Val), 12S rDNA, the control region, and the tRNA(Ile) and tRNA(Gln) have translocated to a position between the tRNA(Glu) and tRNA(Phe) genes. The tRNA(Cys) gene has translocated between the control region and the tRNA(Met) gene, and the tRNA(Leu)(CUN) gene has translocated between the tRNA(Ser)(UCN) gene and the control region. Furthermore, the control region is duplicated, and both copies undergo concerted evolution. Primers that flank these rearrangements confirm that this gene order is conserved in all metastriate ticks examined. Correspondence analysis of amino acid and codon use in the two ticks and in nine other arthropod mitochondrial genomes indicate a strong bias in R. sanguineus towards amino acids encoded by AT-rich codons.      

Extending Zelterman's approach for robust estimation of population size to zero-truncated clustered Data

Estimation of population size with missing zero-class is an important problem that is encountered in epidemiological assessment studies. Fitting a Poisson model to the observed data by the method of maximum likelihood and estimation of the population size based on this fit is an approach that has been widely used for this purpose. In practice, however, the Poisson assumption is seldom satisfied. Zelterman (1988) has proposed a robust estimator for unclustered data that works well in a wide class of distributions applicable for count data. In the work presented here, we extend this estimator to clustered data. The estimator requires fitting a zero-truncated homogeneous Poisson model by maximum likelihood and thereby using a Horvitz-Thompson estimator of population size. This was found to work well, when the data follow the hypothesized homogeneous Poisson model. However, when the true distribution deviates from the hypothesized model, the population size was found to be underestimated. In the search of a more robust estimator, we focused on three models that use all clusters with exactly one case, those clusters with exactly two cases and those with exactly three cases to estimate the probability of the zero-class and thereby use data collected on all the clusters in the Horvitz-Thompson estimator of population size. Loss in efficiency associated with gain in robustness was examined based on a simulation study. As a trade-off between gain in robustness and loss in efficiency, the model that uses data collected on clusters with at most three cases to estimate the probability of the zero-class was found to be preferred in general. In applications, we recommend obtaining estimates from all three models and making a choice considering the estimates from the three models, robustness and the loss in efficiency.     

Mechanisms and targets for angiogenic therapy after stroke

Stroke remains a major health problem worldwide, and is the leading cause of serious long-term disability. Recent findings now suggest that strategies to enhance angiogenesis after focal cerebral ischemia may provide unique opportunities to improve clinical outcomes during stroke recovery. In this mini-review, we survey emerging mechanisms and potential targets for angiogenic therapies in brain after stroke. Multiple elements may be involved, including growth factors, adhesion molecules and progenitor cells. Furthermore, cross talk between angiogenesis and neurogenesis may also provide additional substrates for plasticity and remodeling in the recovering brain. A better understanding of the molecular interplay between all these complex pathways may lead to novel therapeutic avenues for tackling this difficult disease.Key words: angiogenic therapy, stroke, neuroprotection, neurogenesis, angiogenesis, neurovascular unit, cerebral ischemia, stroke recovery