Red Queen Dynamics with Non-Standard Fitness Interactions

Antagonistic coevolution between hosts and parasites can involve rapid fluctuations of genotype frequencies that are known as Red Queen dynamics. Under such dynamics, recombination in the hosts may be advantageous because genetic shuffling can quickly produce disproportionately fit offspring (the Red Queen hypothesis). Previous models investigating these dynamics have assumed rather simple models of genetic interactions between hosts and parasites. Here, we assess the robustness of earlier theoretical predictions about the Red Queen with respect to the underlying host-parasite interactions. To this end, we created large numbers of random interaction matrices, analysed the resulting dynamics through simulation, and ascertained whether recombination was favoured or disfavoured. We observed Red Queen dynamics in many of our simulations provided the interaction matrices exhibited sufficient ‘antagonicity’. In agreement with previous studies, strong selection on either hosts or parasites favours selection for increased recombination. However, fast changes in the sign of linkage disequilibrium or epistasis were only infrequently observed and do not appear to be a necessary condition for the Red Queen hypothesis to work. Indeed, recombination was often favoured even though the linkage disequilibrium remained of constant sign throughout the simulations. We conclude that Red Queen-type dynamics involving persistent fluctuations in host and parasite genotype frequencies appear to not be an artefact of specific assumptions about host-parasite fitness interactions, but emerge readily with the general interactions studied here. Our results also indicate that although recombination is often favoured, some of the factors previously thought to be important in this process such as linkage disequilibrium fluctuations need to be reassessed when fitness interactions between hosts and parasites are complex

A new improved clinical staging system for multiple myeloma based on analysis of 123 treated patients

Abstract The effect of the presenting clinical features on survival time was evaluated in 173 patients of a population of 201 individuals with multiple myeloma observed at Malmo General Hospital during the 11-yr period 1960 to January 1, 1971. Complete follow-up was continued until December 1978. One-hundred and five of the patients came from the city of Malmo and constitute a complete nonselected myeloma population. Bivariate correlation and multivariate regression analyses showed that the survival (i.e., the prognosis) could be accurately predicted in IgG and pure Bence Jones myeloma patients from (A) serum creatinine level, (B) serum calcium level, and (C) bone marrow plasma cell percentage; and in IgA myeloma patients from (A) hemoglobin level, (B) serum calcium level, and (C) serum M-component level. The results were synthesized to produce a simple and reliable clinical staging system with three stages (i.e., risks of death). To facilitate the clinical application, multivariate regression equations were developed to optimally predict the prognosis, and graphs were constructed in order to make the staging of the myeloma patients easier and quicker. The comparison of the duration of survival between the three groups of staged patients confirmed the high reliability of the present staging system.</jats:p

A new improved clinical staging system for multiple myeloma based on analysis of 123 treated patients

The effect of the presenting clinical features on survival time was evaluated in 173 patients of a population of 201 individuals with multiple myeloma observed at Malmo General Hospital during the 11-yr period 1960 to January 1, 1971. Complete follow-up was continued until December 1978. One-hundred and five of the patients came from the city of Malmo and constitute a complete nonselected myeloma population. Bivariate correlation and multivariate regression analyses showed that the survival (i.e., the prognosis) could be accurately predicted in IgG and pure Bence Jones myeloma patients from (A) serum creatinine level, (B) serum calcium level, and (C) bone marrow plasma cell percentage; and in IgA myeloma patients from (A) hemoglobin level, (B) serum calcium level, and (C) serum M-component level. The results were synthesized to produce a simple and reliable clinical staging system with three stages (i.e., risks of death). To facilitate the clinical application, multivariate regression equations were developed to optimally predict the prognosis, and graphs were constructed in order to make the staging of the myeloma patients easier and quicker. The comparison of the duration of survival between the three groups of staged patients confirmed the high reliability of the present staging system.</jats:p