6 research outputs found

    Understanding Variation in Sets of N-of-1 Trials.

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    A recent paper in this journal by Chen and Chen has used computer simulations to examine a number of approaches to analysing sets of n-of-1 trials. We have examined such designs using a more theoretical approach based on considering the purpose of analysis and the structure as regards randomisation that the design uses. We show that different purposes require different analyses and that these in turn may produce quite different results. Our approach to incorporating the randomisation employed when the purpose is to test a null hypothesis of strict equality of the treatment makes use of Nelder's theory of general balance. However, where the purpose is to make inferences about the effects for individual patients, we show that a mixed model is needed. There are strong parallels to the difference between fixed and random effects meta-analyses and these are discussed

    Mineralogical and chemical evolution of the Ernest Henry Fe oxide-Cu-Au ore system, Cloncurry district, northwest Queensland, Australia

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    The Ernest Henry Cu–Au deposit was formed within a zoned, post-peak metamorphic hydrothermal system that overprinted metamorphosed dacite, andesite and diorite (ca 1740–1660 Ma). The Ernest Henry hydrothermal system was formed by two cycles of sodic and potassic alteration where biotite–magnetite alteration produced in the first cycle formed ca 1514±24 Ma, whereas paragenetically later Na–Ca veining formed ca 1529 +11/−8 Ma. These new U–Pbtitanite age dates support textural evidence for incursion of hydrothermal fluids after the metamorphic peak, and overlap with earlier estimates for the timing of Cu–Au mineralization (ca 1540–1500 Ma). A distal to proximal potassic alteration zone correlates with a large (up to 1.5 km) K–Fe–Mn–Ba enriched alteration zone that overprints earlier sodic alteration. Mass balance analysis indicates that K–Fe–Mn–Ba alteration—largely produced during pre-ore biotite- and magnetite-rich alteration—is associated with K–Rb–Cl–Ba–Fe–Mn and As enrichment and Na, Ca and Sr depletion. The aforementioned chemical exchange almost precisely counterbalances the mass changes associated with regional Na–Ca alteration. This initial transition from sodic to potassic alteration may have been formed during the evolution of a single fluid that evolved via alkali exchange during progressive fluid-rock interaction. Cu–Au ore, dominated by co-precipitated magnetite, minor specular hematite, and chalcopyrite as breccia matrix, forms a pipe-like body at the core of a proximal alteration zone dominated by K-feldspar alteration. Both the core and K-feldspar alteration overprint Na–Ca alteration and biotite–magnetite (K–Fe) alteration. Ore was associated with the concentration of a diverse range of elements (e.g. Cu, Au, Fe, Mo, U, Sb, W, Sn, Bi, Ag, F, REE, K, S, As, Co, Ba and Ca). Mineralization also involved the deposition of significant barite, K(–Ba)–feldspar, calcite, fluorite and complexly zoned pyrite. The complexly zoned pyrite and variable K–(Ba)–feldspar versus barite associations are interpreted to indicate fluctuating sulphur and/or barium supply. Together with the alteration zonation geochemistry and overprinting criteria, these data are interpreted to indicate that Cu–Au mineralization occurred as a result of fluid mixing during dilation and brecciation, in the location of the most intense initial potassic alteration. A link between early alteration (Na–Ca and K–Fe) and the later K-feldspathization and the Cu–Au ore is possible. However, the ore-related enrichments in particular elements (especially Ba, Mn, As, Mo, Ag, U, Sb and Bi) are so extreme compared with earlier alteration that another fluid, possibly magmatic in origin, contributed the diverse element suite geochemically independently of the earlier stages. Structural focussing of successive stages produced the distinctive alteration zoning, providing a basis both for exploration for similar deposits, and for an understanding of ore genesis

    A second update on mapping the human genetic architecture of COVID-19

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