Background

Proton pump inhibitors (PPIs) have been associated with a variety of adverse events, although the level of evidence for many of these is weak at best. Recently, one national regulatory authority has mandated a change to the labeling of one PPI based on reports of possible associated rhabdomyolysis. Thus, in this review we summarize the available evidence linking PPI use with rhabdomyolysis. The level of evidence is insufficient to establish a causal relationship and is largely based on sporadic case reports. In general, patients with suspected PPI-associated rhabdomyolysis have not been re-challenged with a PPI after recovery. The mechanism whereby PPIs might have been associated with rhabdomyolysis is unclear but possibly related to interaction with concomitantly administered drugs such as HMG-CoA reductase inhibitors (statins). For patients with rhabdomyolysis, a careful search must be made for possible etiological factors. In patients who recover from an episode of possible PPI-related rhabdomyolysis but do not have a genuine requirement for PPI treatment, the PPI should not be re-introduced. For those with a definite indication for ongoing PPI treatment, the PPI can be re-introduced but should preferably not be administered with a statin.

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Information-Gap Decision Theory (IGDT), an approach to robust decision making under severe uncertainty, is newly considered in the context of a simple life cycle engineering example. IGDT offers a path to a decision in the class of problems where a nominal estimate of an uncertain life cycle parameter is available, but the amount of the deviation of that estimate from the actual value, as well as the implications of that deviation on performance, are not known. The decision rule inherent in IGDT entails relaxing one's demand for optimal performance and choosing designs with maximum immunity, or info-gap robustness, to the effects of deviation from the known estimate. This tradeoff is analyzed graphically using plots of robustness versus performance demand. In this paper, an automotive oil filter design example affected by severe uncertainty is formulated and solved using an IDGT approach. The types of life cycle engineering design problems that the approach could be effective towards are discussed, as are potential limitations that could be encountered when solving more complex problems.

The ionic conductivities of mixtures of ZnO in Na3AlF6 and in xCaF2–yNa3AlF6 mixtures were established with a swept-sine measurement technique. A millivolt sinusoidal voltage at frequencies from 1000 Hz to 25,000 Hz was impressed on a system containing the electrolytes. The system’s frequency response was used to establish the conductivities. The influence of these conductivities on the potential of a solar thermal electrolytic process was evaluated using two process performance parameters: the back-work ratio and the fraction of minimum solar thermal energy required to drive the metal production reaction. We found the conductivity of mixtures of ZnO–Na3AlF6 to be independent of the concentration of ZnO for weight percentages of ZnO from 0.5% to 5%. For temperatures 1240–1325 K the conductivity is close to that of pure Na3AlF6, 3±0.5 Ω−1 cm−1. At temperatures from 1350 K to 1425 K it jumps to 6±0.5 Ω−1 cm−1 When CaF2 is added to the mixture, the electrolyte’s conductivity drops. We thus expect that calcium cations are not present to any important extent in the electrolyte. When CaF2 is part of the chemical system, the concentration of ZnO can have a measurable impact on the electrolyte’s conductivity. Combining the conductivity results with the two solar process performance parameters illustrates the importance of operating the solar process at low current densities when the temperature range is 1200–1500 K. The results further suggest that one should consider studying the electrolytic process at 1800 K.