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At least 1,621 records · Page 90Linked to original sources
PubMed1995

Embryos created for research purposes.

The creation of embryos for research use has drawn a great deal of criticism. It is difficult to defend an ethical distinction between what one can do to "spare" embryos and what one can do to "research" embryos. The strongest ground on which to argue against the creation of embryos for research is a symbolic one, having to do with respect for human life. Ronald Dworkin's work in Life's Dominion on the symbolic meaning of the abortion debate throws a helpful light on this dispute. By understanding the basic question to be, Does the creation of research embryos weaken or insult our communal respect for the sanctity of human life in some way that in vitro fertilization (IVF) or the experimental use of "spare" embryos does not?, the debate can move in a more constructive direction.

Abortion, Eugenic↗
PubMed2005

The Wolbachia genome of Brugia malayi: endosymbiont evolution within a human pathogenic nematode.

Complete genome DNA sequence and analysis is presented for Wolbachia, the obligate alpha-proteobacterial endosymbiont required for fertility and survival of the human filarial parasitic nematode Brugia malayi. Although, quantitatively, the genome is even more degraded than those of closely related Rickettsia species, Wolbachia has retained more intact metabolic pathways. The ability to provide riboflavin, flavin adenine dinucleotide, heme, and nucleotides is likely to be Wolbachia's principal contribution to the mutualistic relationship, whereas the host nematode likely supplies amino acids required for Wolbachia growth. Genome comparison of the Wolbachia endosymbiont of B. malayi (wBm) with the Wolbachia endosymbiont of Drosophila melanogaster (wMel) shows that they share similar metabolic trends, although their genomes show a high degree of genome shuffling. In contrast to wMel, wBm contains no prophage and has a reduced level of repeated DNA. Both Wolbachia have lost a considerable number of membrane biogenesis genes that apparently make them unable to synthesize lipid A, the usual component of proteobacterial membranes. However, differences in their peptidoglycan structures may reflect the mutualistic lifestyle of wBm in contrast to the parasitic lifestyle of wMel. The smaller genome size of wBm, relative to wMel, may reflect the loss of genes required for infecting host cells and avoiding host defense systems. Analysis of this first sequenced endosymbiont genome from a filarial nematode provides insight into endosymbiont evolution and additionally provides new potential targets for elimination of cutaneous and lymphatic human filarial disease.

Animals↗
PubMed2005

Computational prediction of human drug metabolism.

There is an urgent requirement within the pharmaceutical and biotechnology industries, regulatory authorities and academia to improve the success of molecules that are selected for clinical trials. Although absorption, distribution, metabolism, excretion and toxicity (ADME/Tox) properties are some of the many components that contribute to successful drug discovery and development, they represent factors for which we currently have in vitro and in vivo data that can be modelled computationally. Understanding the possible toxicity and the metabolic fate of xenobiotics in the human body is particularly important in early drug discovery. There is, therefore, a need for computational methodologies for uncovering the relationships between the structure and the biological activity of novel molecules. The convergence of numerous technologies, including high-throughput techniques, databases, ADME/Tox modelling and systems biology modelling, is leading to the foundation of systems-ADME/Tox. Results from experiments can be integrated with predictions to globally simulate and understand the likely complete effects of a molecule in humans. The development and early application of major components of MetaDrug (GeneGo, Inc.) software will be described, which includes rule-based metabolite prediction, quantitative structure-activity relationship models for major drug metabolising enzymes, and an extensive database of human protein-xenobiotic interactions. This represents a combined approach to predicting drug metabolism. MetaDrug can be readily used for visualising Phase I and II metabolic pathways, as well as interpreting high-throughput data derived from microarrays as networks of interacting objects. This will ultimately aid in hypothesis generation and the early triaging of molecules likely to have undesirable predicted properties or measured effects on key proteins and cellular functions.

Computational Biology↗