Disease progression in heterosexual patients infected with closely related subtype B strains of HIV type 1 with differing coreceptor usage properties

Previously we described a heterosexual outbreak of HIV-1 subtype B in a town in the north of England (Doncaster) where 11 of 13 infections were shown to be linked by phylogenetic analysis of the env gp120 region. The 11 infections were related to a putative index case, Don1, and further divided into two groups based on the patients' disease status, their viral sequences, and other epidemiological information. Here we describe two further findings. First, we found that viral isolates and gp120 recombinant viruses derived from patients from one group used the CCR5 coreceptor, whereas viruses from the other group could use both the CCR5 and CXCR4 coreceptors. Patients with the X4/R5 dual tropic strains were symptomatic when diagnosed and progressed rapidly, in contrast to the other patient group that has remained asymptomatic, implying a link between the tropism of the strains and disease outcome. Second, we present additional sequence data derived from the index case, demonstrating the presence of sequences from both clades, with an average interclade distance of 9.56%, providing direct evidence of a genetic link between these two groups. This new study shows that Don1 harbored both strains, implying he was either dually infected or that over time intrahost diversification from the R5 to R5/X4 phenotype occurred. These events may account for/have led to the spread of two genetically related strains with different pathogenic properties within the same heterosexual community.

Using the web graph to influence application behaviour

The Web's link structure (termed the Web Graph) is a richly connected set of Web pages. Current applications use this graph for indexing and information retrieval purposes. In contrast the relationship between Web Graph and application is reversed by letting the structure of the Web Graph influence the behaviour of an application. Presents a novel Web crawling agent, AlienBot, the output of which is orthogonally coupled to the enemy generation strategy of a computer game. The Web Graph guides AlienBot, causing it to generate a stochastic process. Shows the effectiveness of such unorthodox coupling to both the playability of the game and the heuristics of the Web crawler. In addition, presents the results of the sample of Web pages collected by the crawling process. In particular, shows: how AlienBot was able to identify the power law inherent in the link structure of the Web; that 61.74 per cent of Web pages use some form of scripting technology; that the size of the Web can be estimated at just over 5.2 billion pages; and that less than 7 per cent of Web pages fully comply with some variant of (X)HTML.

Largest connected component of a star graph with faulty vertices

In order to make a full evaluation of an interconnection network, it is essential to estimate the minimum size of a largest connected component of this network provided the faulty vertices in the network may break its connectedness. Star graphs are recognized as promising candidates for interconnection networks. This article addresses the size of a largest connected component of a faulty star graph. We prove that, in an n-star graph (n >= 3) with up to 2n-4 faulty vertices, all fault-free vertices but at most two form a connected component. Moreover, all fault-free vertices but exactly two form a connected component if and only if the set of all faulty vertices is equal to the neighbourhood of a pair of fault-free adjacent vertices. These results show that star graphs exhibit excellent fault-tolerant abilities in the sense that there exists a large functional network in a faulty star graph.

Optimising memory usage in n-tuple neural networks

The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleksander and Stonham, 1979). They have some significant advantages over the more common and biologically plausible networks, such as multi-layer perceptrons; for example, n-tuple networks have been used for a variety of tasks, the most popular being real-time pattern recognition, and they can be implemented easily in hardware as they use standard random access memories. In operation, a series of images of an object are shown to the network, each being processed suitably and effectively stored in a memory called a discriminator. Then, when another image is shown to the system, it is processed in a similar manner and the system reports whether it recognises the image; is the image sufficiently similar to one already taught? If the system is to be able to recognise and discriminate between m-objects, then it must contain m-discriminators. This can require a great deal of memory. This paper describes various ways in which memory requirements can be reduced, including a novel method for multiple discriminator n-tuple networks used for pattern recognition. By using this method, the memory normally required to handle m-objects can be used to recognise and discriminate between 2^m — 2 objects.