Mineral chemistry of igneous melanite garnets from analcite-bearing volcanic rocks, Alberta, Canada

The mineral chemistry of melanite garnets from the Crowsnest volcanic rocks of SW Alberta, Canada, has been investigated by using electron microprobe scans, quantitative analyses and multivariate statistical analysis. The garnets occur with aegirine-augite, sanidine, analcite and rare plagioclase as phenocrysts in trachyte and phonolite flows, agglomerates and tuffs. Wavelength dispersive microprobe scans reveal complex zonation patterns, both normal and oscillatory. The results of fifty quantitative analyses were subjected to R-mode factor analysis to delineate the chemical exchanges producing the zonation. The chemical zonation of the garnets may be attributed to four independent binary exchanges; Al-Fe3+, Si-Ti, Ca-Mn and Mg-Fe2+. The stoichiometry of these garnets, based on microprobe and wet chemical Fe analyses, combined with the strongly antithetic behavior of Si and Ti lead us to infer that the Ti in these garnets is dominantly tetravalent. It is clear from this study that quantitative modelling of the processes of crystal growth and zonation of melanite garnets in alkaline, undersaturated igneous rocks should be aimed at simulating the four chemical exchanges listed above

In silico assessment of biomedical products: the conundrum of rare but not so rare events in two case studies

In silico clinical trials, defined as “The use of individualized computer simulation in the development or regulatory evaluation of a medicinal product, medical device, or medical intervention,” have been proposed as a possible strategy to reduce the regulatory costs of innovation and the time to market for biomedical products. We review some of the the literature on this topic, focusing in particular on those applications where the current practice is recognized as inadequate, as for example, the detection of unexpected severe adverse events too rare to be detected in a clinical trial, but still likely enough to be of concern. We then describe with more details two case studies, two successful applications of in silico clinical trial approaches, one relative to the University of Virginia/Padova simulator that the Food and Drug Administration has accepted as possible replacement for animal testing in the preclinical assessment of artificial pancreas technologies, and the second, an investigation of the probability of cardiac lead fracture, where a Bayesian network was used to combine in vivo and in silico observations, suggesting a whole new strategy of in silico-augmented clinical trials, to be used to increase the numerosity where recruitment is impossible, or to explore patients’ phenotypes that are unlikely to appear in the trial cohort, but are still frequent enough to be of concern