The range of possibilities for future climate evolution needs to be taken into account when planning climate change mitigation and adaptation strategies. This requires ensembles of multi-decadal simulations to assess both chaotic climate variability and model response uncertainty. Statistical estimates of model response uncertainty, based on observations of recent climate change, admit climate sensitivities--defined as the equilibrium response of global mean temperature to doubling levels of atmospheric carbon dioxide--substantially greater than 5 K. But such strong responses are not used in ranges for future climate change because they have not been seen in general circulation models. Here we present results from the 'climateprediction.net' experiment, the first multi-thousand-member grand ensemble of simulations using a general circulation model and thereby explicitly resolving regional details. We find model versions as realistic as other state-of-the-art climate models but with climate sensitivities ranging from less than 2 K to more than 11 K. Models with such extreme sensitivities are critical for the study of the full range of possible responses of the climate system to rising greenhouse gas levels, and for assessing the risks associated with specific targets for stabilizing these levels.

Abstract-A dynamical model based on three coupled ordinary differential equations is introduced which is capable of generating realistic synthetic electrocardiogram (ECG) signals. The operator can specify the mean and standard deviation of the heart rate, the morphology of the PQRST cycle, and the power spectrum of the RR tachogram. In particular, both respiratory sinus arrhythmia at the high frequencies (HFs) and Mayer waves at the low frequencies (LFs) together with the LF/HF ratio are incorporated in the model. Much of the beat-to-beat variation in morphology and timing of the human ECG, including QT dispersion and R-peak amplitude modulation are shown to result. This model may be employed to assess biomedical signal processing techniques which are used to compute clinical statistics from the ECG.

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Clostridium botulinum is a taxonomic designation for many diverse anaerobic spore-forming rod-shaped bacteria that have the common property of producing botulinum neurotoxins (BoNTs). The BoNTs are exoneurotoxins that can cause severe paralysis and death in humans and other animal species. A collection of 174 C. botulinum strains was examined by amplified fragment length polymorphism (AFLP) analysis and by sequencing of the 16S rRNA gene and BoNT genes to examine the genetic diversity within this species. This collection contained representatives of each of the seven different serotypes of botulinum neurotoxins (BoNT/A to BoNT/G). Analysis of the16S rRNA gene sequences confirmed previous identifications of at least four distinct genomic backgrounds (groups I to IV), each of which has independently acquired one or more BoNT genes through horizontal gene transfer. AFLP analysis provided higher resolution and could be used to further subdivide the four groups into subgroups. Sequencing of the BoNT genes from multiple strains of serotypes A, B, and E confirmed significant sequence variation within each serotype. Four distinct lineages within each of the BoNT A and B serotypes and five distinct lineages of serotype E strains were identified. The nucleotide sequences of the seven toxin genes of the serotypes were compared and showed various degrees of interrelatedness and recombination, as was previously noted for the nontoxic nonhemagglutinin gene, which is linked to the BoNT gene. These analyses contribute to the understanding of the evolution and phylogeny within this species and assist in the development of improved diagnostics and therapeutics for the treatment of botulism.Clostridium botulinum is a taxonomic collection of several distinct species of anaerobic gram-positive spore-forming bacteria that produce the most poisonous substance known, botulinum neurotoxin (BoNT) (1,8). These organisms, along with related neurotoxin-producing species that, for a variety of reasons, were not included under the C. botulinum taxon, pose global health problems that affect both infant and adult humans and can also affect wildlife, waterfowl, and domestic animals. They cause intoxication through ingestion of the neurotoxin in contaminated foods. Toxicoinfections can also occur after contact with bacteria or bacterial spores (6, 17). These pathogens are ubiquitous and can be found in soils and sedi-

The botulinum neurotoxins (BoNTs) cause the paralytic human disease botulism and are one of the highest-risk threat agents for bioterrorism. To generate a pharmaceutical to prevent or treat botulism, monoclonal antibodies (mAbs) were generated by phage display and evaluated for neutralization of BoNT serotype A (BoNT͞A) in vivo. Although no single mAb significantly neutralized toxin, a combination of three mAbs (oligoclonal Ab) neutralized 450,000 50% lethal doses of BoNT͞A, a potency 90 times greater than human hyperimmune globulin. The potency of oligoclonal Ab was primarily due to a large increase in functional Ab binding affinity. The results indicate that the potency of the polyclonal humoral immune response can be deconvoluted to a few mAbs binding nonoverlapping epitopes, providing a route to drugs for preventing and treating botulism and diseases caused by other pathogens and biologic threat agents. monoclonal antibody ͉ immunotherapy ͉ antibody engineering ͉ vaccine ͉ phage display

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Over the last 20 years, climate models have been developed to an impressive level of complexity. They are core tools in the study of the interactions of many climatic processes and justifiably provide an additional strand in the argument that anthropogenic climate change is a critical global problem. Over a similar period, there has been growing interest in the interpretation and probabilistic analysis of the output of computer models; particularly, models of natural systems. The results of these areas of research are being sought and utilized in the development of policy, in other academic disciplines, and more generally in societal decision making. Here, our focus is solely on complex climate models as predictive tools on decadal and longer time scales. We argue for a reassessment of the role of such models when used for this purpose and a reconsideration of strategies for model development and experimental design. Building on more generic work, we categorize sources of uncertainty as they relate to this specific problem and discuss experimental strategies available for their quantification. Complex climate models, as predictive tools for many variables and scales, cannot be meaningfully calibrated because they are simulating a never before experienced state of the system; the problem is one of extrapolation. It is therefore inappropriate to apply any of the currently available generic techniques which utilize observations to calibrate or weight models to produce forecast probabilities for the real world. To do so is misleading to the users of climate science in wider society. In this context, we discuss where we derive confidence in climate forecasts and present some concepts to aid discussion and communicate the state-of-the-art. Effective communication of the underlying assumptions and sources of forecast uncertainty is critical in the interaction between climate science, the impacts communities and society in general.

The botulinum neurotoxins (BoNTs) are category A biothreat agents which have been the focus of intensive efforts to develop vaccines and antibody-based prophylaxis and treatment. Such approaches must take into account the extensive BoNT sequence variability; the seven BoNT serotypes differ by up to 70% at the amino acid level. Here, we have analyzed 49 complete published sequences of BoNTs and show that all toxins also exhibit variability within serotypes ranging between 2.6 and 31.6%. To determine the impact of such sequence differences on immune recognition, we studied the binding and neutralization capacity of six BoNT serotype A (BoNT/A) monoclonal antibodies (MAbs) to BoNT/A1 and BoNT/A2, which differ by 10% at the amino acid level. While all six MAbs bound BoNT/A1 with high affinity, three of the six MAbs showed a marked reduction in binding affinity of 500-to more than 1,000-fold to BoNT/A2 toxin. Binding results predicted in vivo toxin neutralization; MAbs or MAb combinations that potently neutralized A1 toxin but did not bind A2 toxin had minimal neutralizing capacity for A2 toxin. This was most striking for a combination of three binding domain MAbs which together neutralized >40,000 mouse 50% lethal doses (LD 50 s) of A1 toxin but less than 500 LD 50 s of A2 toxin. Combining three MAbs which bound both A1 and A2 toxins potently neutralized both toxins. We conclude that sequence variability exists within all toxin serotypes, and this impacts monoclonal antibody binding and neutralization. Such subtype sequence variability must be accounted for when generating and evaluating diagnostic and therapeutic antibodies.