Aminopeptidases of malaria parasites:new targets for chemotherapy

Novel targets for new drug development are urgently required to combat malaria, a disease that puts half of the world's population at risk. One group of enzymes identified within the genome of the most lethal of the causative agents of malaria, Plasmodium falciparum, that may have the potential to become new targets for antimalarial drug development are the aminopeptidases. These enzymes catalyse the cleavage of the N-terminal amino acids from proteins and peptides. P. falciparum appears to encode for at least nine aminopeptidases, two neutral aminopeptidases, one aspartyl aminopeptidase, one aminopeptidase P, one prolyl aminopeptidase and four methionine aminopeptidases. Recent advances in our understanding of these genes and their protein products are outlined in this review, including their potential for antimalarial drug development.

An optimisation of Gaussian mixture models for integer processing units

This paper investigates sub-integer implementations of the adaptive Gaussian mixture model (GMM) for background/foreground segmentation to allow the deployment of the method on low cost/low power processors that lack Floating Point Unit (FPU). We propose two novel integer computer arithmetic techniques to update Gaussian parameters. Specifically, the mean value and the variance of each Gaussian are updated by a redefined and generalised "round'' operation that emulates the original updating rules for a large set of learning rates. Weights are represented by counters that are updated following stochastic rules to allow a wider range of learning rates and the weight trend is approximated by a line or a staircase. We demonstrate that the memory footprint and computational cost of GMM are significantly reduced, without significantly affecting the performance of background/foreground segmentation.

Parasites that change predator or prey behaviour can have keystone effects on community composition

Parasites play pivotal roles in structuring communities, often via indirect interactions with non-host species. These effects can be density-mediated (through mortality) or trait-mediated (behavioural, physiological and developmental), and may be crucial to population interactions, including biological invasions. For instance, parasitism can alter intraguild predation (IGP) between native and invasive crustaceans, reversing invasion outcomes. Here, we use mathematical models to examine how parasite-induced trait changes influence the population dynamics of hosts that interact via IGP. We show that trait-mediated indirect interactions impart keystone effects, promoting or inhibiting host coexistence. Parasites can thus have strong ecological impacts, even if they have negligible virulence, underscoring the need to consider trait-mediated effects when predicting effects of parasites on community structure in general and biological invasions in particular.

Interspecific competition in honeybee intracellular gut parasites is asymmetric and favours the spread of an emerging infectious disease

There is increasing appreciation that hosts in natural populations are subject to infection by multiple parasite species. Yet the epidemiological and ecological processes determining the outcome of mixed infections are poorly understood. Here, we use two intracellular gut parasites (Microsporidia), one exotic and one co-evolved in the western honeybee (Apis mellifera), in an experiment in which either one or both parasites were administered either simultaneously or sequentially. We provide clear evidence of within-host competition; order of infection was an important determinant of the competitive outcome between parasites, with the first parasite significantly inhibiting the growth of the second, regardless of species. However, the strength of this ‘priority effect’ was highly asymmetric, with the exotic Nosema ceranae exhibiting stronger inhibition of Nosema apis than vice versa. Our results reveal an unusual asymmetry in parasite competition that is dependent on order of infection. When incorporated into a mathematical model of disease prevalence, we find asymmetric competition to be an important predictor of the patterns of parasite prevalence found in nature. Our findings demonstrate the wider significance of complex multi-host–multi-parasite interactions as drivers of host–pathogen community structure

Instrumental Parasites: Interfacing the Fragile and the Robust

The parasitical relationship between the grand piano and the myriad objects used in its preparation as pioneered by John Cage in the late 1940’s is here discussed from a perspective of free improvisation practice. Preparations can be defined as the use of a “non-instrument” object (screws, bolts, rubbers etc…) to alter or modify the behaviour of an instrument or part of an instrument. Although also present in instrumental practices based on the electric guitar or the drum kit, the piano provides a privileged space of exploration given its large‐scale resonant body. It also highlights the transgressive aspect of preparation (the piano to be prepared often belongs to a venue rather than to the pianist herself, hence highlighting relationships of trust, care and respect). Since 2007 I have used a guitar-object (a small wooden board with strings and pick ups) connected to a small amplifier to prepare the grand piano in my free improvisation practice. This paper addresses the different relationships afforded by this type preparation which is characterised by the fact that the object for preparation is in itself an instrument (albeit a simplified one), and the preparation is ephemeral and intrinsic to the performance. The paper also reflects on the process of designing an interface from and for a particular practice and in collaboration with a guitar luthier.

Accelerating integer-based fully homomorphic encryption using Comba multiplication

Fully Homomorphic Encryption (FHE) is a recently developed cryptographic technique which allows computations on encrypted data. There are many interesting applications for this encryption method, especially within cloud computing. However, the computational complexity is such that it is not yet practical for real-time applications. This work proposes optimised hardware architectures of the encryption step of an integer-based FHE scheme with the aim of improving its practicality. A low-area design and a high-speed parallel design are proposed and implemented on a Xilinx Virtex-7 FPGA, targeting the available DSP slices, which offer high-speed multiplication and accumulation. Both use the Comba multiplication scheduling method to manage the large multiplications required with uneven sized multiplicands and to minimise the number of read and write operations to RAM. Results show that speed up factors of 3.6 and 10.4 can be achieved for the encryption step with medium-sized security parameters for the low-area and parallel designs respectively, compared to the benchmark software implementation on an Intel Core2 Duo E8400 platform running at 3 GHz.

Inference in Credal Networks Through Integer Programming

A credal network associates a directed acyclic graph with a collection of sets of probability measures; it offers a compact representation for sets of multivariate distributions. In this paper we present a new algorithm for inference in credal networks based on an integer programming reformulation. We are concerned with computation of lower/upper probabilities for a variable in a given credal network. Experiments reported in this paper indicate that this new algorithm has better performance than existing ones for some important classes of networks.

Eaten alive: cannibalism is enhanced by parasites.

Cannibalism is ubiquitous in nature and especially pervasive in consumers with stage-specific resource utilization in resource-limited environments. Cannibalism is thus influential in the structure and functioning of biological communities. Parasites are also pervasive in nature and, we hypothesize, might affect cannibalism since infection can alter host foraging behaviour. We investigated the effects of a common parasite, the microsporidian Pleistophora mulleri, on the cannibalism rate of its host, the freshwater amphipod Gammarus duebeni celticus. Parasitic infection increased the rate of cannibalism by adults towards uninfected juvenile conspecifics, as measured by adult functional responses, that is, the rate of resource uptake as a function of resource density. This may reflect the increased metabolic requirements of the host as driven by the parasite. Furthermore, when presented with a choice, uninfected adults preferred to cannibalize uninfected rather than infected juvenile conspecifics, probably reflecting selection pressure to avoid the risk of parasite acquisition. By contrast, infected adults were indiscriminate with respect to infection status of their victims, probably owing to metabolic costs of infection and the lack of risk as the cannibals were already infected. Thus parasitism, by enhancing cannibalism rates, may have previously unrecognized effects on stage structure and population dynamics for cannibalistic species and may also act as a selective pressure leading to changes in resource use.

Trait-Mediated Effects of Parasites on Invader-Native Interactions.

Parasites have a variety of behavioural effects on their hosts, which can in turn affect species with which the host interacts. Here we review how these trait-mediated indirect effects of parasites can alter the outcomes of invader-native interactions, illustrating with examples from the literature and with particular regard to the invader-native crustacean systems studied in our laboratories. Parasites may potentially inhibit or exacerbate invasions via their effects on host behaviour, in addition to their direct virulence effects on hosts. In several crustacean systems, we have found that parasites influence both host predation rates on intra- and inter-guild prey and host vulnerability to being preyed upon. These trait effects can theoretically alter invasion impact and patterns of coexistence, as they indirectly affect interactions between predators and prey with the potential for further ramifications to other species in the food web. The fitness consequences of parasite-induced trait-mediated effects are rarely considered in traditional parasitological contexts, but demand attention in the context of ecological communities. We can regard these trait effects as a form of cryptic virulence that only becomes apparent when hosts are examined in the context of the other species with which they interact.

Targeting FPGA DSP Slices for a Large Integer Multiplier for Integer Based FHE

Homomorphic encryption offers potential for secure cloud computing. However due to the complexity of homomorphic encryption schemes, performance of implemented schemes to date have been unpractical. This work investigates the use of hardware, specifically Field Programmable Gate Array (FPGA) technology, for implementing the building blocks involved in somewhat and fully homomorphic encryption schemes in order to assess the practicality of such schemes. We concentrate on the selection of a suitable multiplication algorithm and hardware architecture for large integer multiplication, one of the main bottlenecks in many homomorphic encryption schemes. We focus on the encryption step of an integer-based fully homomorphic encryption (FHE) scheme. We target the DSP48E1 slices available on Xilinx Virtex 7 FPGAs to ascertain whether the large integer multiplier within the encryption step of a FHE scheme could fit on a single FPGA device. We find that, for toy size parameters for the FHE encryption step, the large integer multiplier fits comfortably within the DSP48E1 slices, greatly improving the practicality of the encryption step compared to a software implementation. As multiplication is an important operation in other FHE schemes, a hardware implementation using this multiplier could also be used to improve performance of these schemes.

Multilinear and Integer Programming for Markov Decision Processes with Imprecise Probabilities

Markov Decision Processes (MDPs) are extensively used to encode sequences of decisions with probabilistic effects. Markov Decision Processes with Imprecise Probabilities (MDPIPs) encode sequences of decisions whose effects are modeled using sets of probability distributions. In this paper we examine the computation of Γ-maximin policies for MDPIPs using multilinear and integer programming. We discuss the application of our algorithms to “factored” models and to a recent proposal, Markov Decision Processes with Set-valued Transitions (MDPSTs), that unifies the fields of probabilistic and “nondeterministic” planning in artificial intelligence research.