Sustained release of proteins from a modified vaginal ring device

A new vaginal ring technology, the insert vaginal ring (InVR), is presented. The InVR overcomes the current shortfall of conventional vaginal rings (VRs) that are generally ineffectual for the delivery of hydrophilic and/or macromolecular actives, including peptides, proteins and antibodies, due to their poor permeation characteristics in the hydrophobic polymeric elastomers from which VRs are usually fabricated. Release of the model protein BSA from a variety of insert matrices for the InVR is demonstrated, including modified silicone rods, directly compressed tablets and lyophilised gels, which collectively provided controlled release profiles from several hours to beyond 4 weeks. Furthermore, the InVR was shown to deliver over 1 mg of the monoclonal antibody 2F5 from a single device, offering a potential means of protecting women against the transmission of HIV.

Use of a novel micro-fluidic device to create arrays for multiplex analysis of large and small molecular weight compounds by surface plasmon resonance

There is an increasing demand to develop biosensor monitoring devices capable of biomarker profiling for predicting animal adulteration and detecting multiple chemical contaminants or toxins in food produce. Surface plasmon resonance (SPR) biosensors are label free detection systems that monitor the binding of specific biomolecular recognition elements with binding partners. Essential to this technology are the production of biochips where a selected binding partner, antibody, biomarker protein or low molecular weight contaminant, is immobilised. A micro-fluidic immobilisation device allowing the covalent attachment of up to 16 binding partners in a linear array on a single surface has been developed for compatibility with a prototype multiplex SPR analyser.

The immobilisation unit and multiplex SPR analyser were respectively evaluated in their ability to be fit-for-purpose for binding partner attachment and detection of high and low molecular weight molecules. The multiplexing capability of the dual technology was assessed using phycotoxin concentration analysis as a model system. The parent compounds of four toxin groups were immobilised within a single chip format and calibration curves were achieved. The chip design and SPR technology allowed the compartmentalisation of the binding interactions for each toxin group offering the added benefit of being able to distinguish between toxin families and perform concentration analysis. This model is particularly contemporary with the current drive to replace biological methods for phycotoxin screening.

FPGA montgomery modular multiplication architectures suitable for ECCs over GF(p)

New FPGA architectures for the ordinary Montgomery multiplication algorithm and the FIOS modular multiplication algorithm are presented. The embedded 18×18-bit multipliers and fast carry look-ahead logic located on the Xilinx Virtex2 Pro family of FPGAs are used to perform the ordinary multiplications and additions/subtractions required by these two algorithms. The architectures are developed for use in Elliptic Curve Cryptosystems over GF(p), which require modular field multiplication to perform elliptic curve point addition and doubling. Field sizes of 128-bits and 256-bits are chosen but other field sizes can easily be accommodated, by rapidly reprogramming the FPGA. Overall, the larger the word size of the multiplier, the more efficiently it performs in terms of area/time product. Also, the FIOS algorithm is flexible in that one can tailor the multiplier architecture is to be area efficient, time efficient or a mixture of both by choosing a particular word size. It is estimated that the computation of a 256-bit scalar point multiplication over GF(p) would take about 4.8 ms.

FPGA Implementation of a Pipelined Gaussian Calculation for HMM-Based Large Vocabulary Speech Recognition

A scalable large vocabulary, speaker independent speech recognition system is being developed using Hidden Markov Models (HMMs) for acoustic modeling and a Weighted Finite State Transducer (WFST) to compile sentence, word, and phoneme models. The system comprises a software backend search and an FPGA-based Gaussian calculation which are covered here. In this paper, we present an efficient pipelined design implemented both as an embedded peripheral and as a scalable, parallel hardware accelerator. Both architectures have been implemented on an Alpha Data XRC-5T1, reconfigurable computer housing a Virtex 5 SX95T FPGA. The core has been tested and is capable of calculating a full set of Gaussian results from 3825 acoustic models in 9.03 ms which coupled with a backend search of 5000 words has provided an accuracy of over 80%. Parallel implementations have been designed with up to 32 cores and have been successfully implemented with a clock frequency of 133?MHz.

Comparing the implementation of two-dimensional numerical quadrature on GPU, FPGA and ClearSpeed systems to study electron scattering by atoms

The use of accelerators, with compute architectures different and distinct from the CPU, has become a new research frontier in high-performance computing over the past ?ve years. This paper is a case study on how the instruction-level parallelism offered by three accelerator technologies, FPGA, GPU and ClearSpeed, can be exploited in atomic physics. The algorithm studied is the evaluation of two electron integrals, using direct numerical quadrature, a task that arises in the study of intermediate energy electron scattering by hydrogen atoms. The results of our ‘productivity’ study show that while each accelerator is viable, there are considerable differences in the implementation strategies that must be followed on each.