Earthquakes, influenza and cycles of Indian kala-azar.

It is suggested that previous data indicate 3 major epidemics of kala-azar in Assam between 1875 and 1950, with inter-epidemic periods of 30-45 and 20 years. This deviates from the popular view of regular cycles with a 10-20 year period. A deterministic mathematical model of kala-azar is used to find the simplest explanation for the timing of the 3 epidemics, paying particular attention to the role of extrinsic (drugs, natural disasters, other infectious diseases) versus intrinsic (host and vector dynamics, birth and death rates, immunity) processes in provoking the second. We conclude that, whilst widespread influenza in 1918-1919 may have magnified the second epidemic, intrinsic population processes provide the simplest explanation for its timing and synchrony throughout Assam. The model also shows that the second inter-epidemic period is expected to be shorter than the first, even in the absence of extrinsic agents, and highlights the importance of a small fraction of patients becoming chronically infectious (with post kala-azar dermal leishmaniasis) after treatment during an epidemic.

A novel method for rapid comparative quantitative analysis of nuclear fuel cycles

One of the greatest obstacles facing the nuclear industry is that of sustainability, both in terms of the finite reserves of uranium ore and the production of highly radiotoxic spent fuel which presents proliferation and environmental hazards. Alternative nuclear technologies have been suggested as a means of delivering enhanced sustainability with proposals including fast reactors, the use of thorium fuel and tiered fuel cycles. The debate as to which is the most appropriate technology continues, with each fuel system and reactor type delivering specific advantages and disadvantages which can be difficult to compare fairly. This paper demonstrates a framework of performance metrics which, coupled with a first-order lumped reactor model to determine nuclide population balances, can be used to quantify the aforementioned pros and cons for a range of different fuel and reactor combinations. The framework includes metrics such as fuel efficiency, spent fuel toxicity and proliferation resistance, and relative cycle performance is analysed through parallel coordinate plots, yielding a quantitative comparison of disparate cycles. © 2011 Elsevier Ltd. All rights reserved.

Population of nonnative states of lysozyme variants drives amyloid fibril formation.

The propensity of protein molecules to self-assemble into highly ordered, fibrillar aggregates lies at the heart of understanding many disorders ranging from Alzheimer's disease to systemic lysozyme amyloidosis. In this paper we use highly accurate kinetic measurements of amyloid fibril growth in combination with spectroscopic tools to quantify the effect of modifications in solution conditions and in the amino acid sequence of human lysozyme on its propensity to form amyloid fibrils under acidic conditions. We elucidate and quantify the correlation between the rate of amyloid growth and the population of nonnative states, and we show that changes in amyloidogenicity are almost entirely due to alterations in the stability of the native state, while other regions of the global free-energy surface remain largely unmodified. These results provide insight into the complex dynamics of a macromolecule on a multidimensional energy landscape and point the way for a better understanding of amyloid diseases.