119 resultados para Historical biogeography


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This article compares chronologies reconstructed from historical records of prices, wages, grain harvests, and population with corresponding chronologies of growing conditions and climatic variations derived from dendrochronology and Greenland ice-cores. It demonstrates that in pre-industrial, and especially late medieval, England, short-term environmental shocks and more enduring shifts in environmental conditions (sometimes acting in concert with biological agencies) exercised a powerful influence upon the balance struck between population and available resources via their effects upon the reproduction, health and life expectancy of humans, crops, and livestock. Prevailing socio-economic conditions and institutions, in turn, shaped society's susceptibility to these environmental shocks and shifts.

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Malone, C.A.T. and S.K.F. Stoddart, . (co-authored).

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The role of rhodopsin as a structural prototype for the study of the whole superfamily of G protein-coupled receptors (GPCRs) is reviewed in an historical perspective. Discovered at the end of the nineteenth century, fully sequenced since the early 1980s, and with direct three-dimensional information available since the 1990s, rhodopsin has served as a platform to gather indirect information on the structure of the other superfamily members. Recent breakthroughs have elicited the solution of the structures of additional receptors, namely the beta 1- and beta 2-adrenergic receptors and the A(2A) adenosine receptor, now providing an opportunity to gauge the accuracy of homology modeling and molecular docking techniques and to perfect the computational protocol. Notably, in coordination with the solution of the structure of the A(2A) adenosine receptor, the first "critical assessment of GPCR structural modeling and docking" has been organized, the results of which highlighted that the construction of accurate models, although challenging, is certainly achievable. The docking of the ligands and the scoring of the poses clearly emerged as the most difficult components. A further goal in the field is certainly to derive the structure of receptors in their signaling state, possibly in complex with agonists. These advances, coupled with the introduction of more sophisticated modeling algorithms and the increase in computer power, raise the expectation for a substantial boost of the robustness and accuracy of computer-aided drug discovery techniques in the coming years.