Peptide-based vaccines consist of short antigen fragments derived from a specific pathogen. Alone, these peptide fragments are poorly or non-immunogenic; however, when incorporated into a proper delivery system, they can trigger strong immune responses. To eliminate the need for toxic and often ineffective oral adjuvants, we designed single molecule-based self-adjuvating vaccines against hookworms using natural and unnatural hydrophobic amino acids. Two vaccine conjugates were synthesized, consisting of B-cell epitope p3, derived from the hookworm Na-APR-1 protein; universal T-helper peptide P25; and either double copies of unnatural lipoamino acid (2-amino-D,L-eicosanoic acid), or ten copies of the natural amino acid leucine. After challenge with the model hookworm, Nippostrongylus brasiliensis, mice orally immunized with the conjugates, but without adjuvant, generated antibody responses against the hookworm epitope, resulting in significantly reduced worm and egg burdens compared to control mice. We have demonstrated that vaccine nanoparticles composed exclusively of natural amino acids can be effective even when administered orally.

Increasing demands upon embedded systems for higher level services like networking, user interfaces and file system management, are driving growth in fully-featured operating systems such as embedded Linux. In reconfigurable System-onChip (rSoC) design, a critical issue is efficient integration of custom hardware and software resources, where efficiency must be considered in terms of both design time and run time. Process networks communicating via FIFO queues are a powerful model for real time digital system design, especially for data streaming applications such as multimedia devices. FIFOs also form a central part of Unix and Linux Interprocess Communication (IPC) architectures, where they are more commonly known as pipes. In this paper, we expand on this observation and show how the combination of embedded Linux, reconfigurable System-on-Chip, and FIFO communication models provide a compelling platform for efficient design-and run-time implementation of complex, high performance embedded systems.

Au/La2 O3 nanomaterials were prepared through calcining Au-modified La(OH)3 precursors. Scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffractometry (XRD) were employed to characterize the as-prepared samples. Benzene, a common volatile organic compound, was selected as a model to investigate the cataluminescence (CTL)-sensing properties of the Au/La2 O3 nanomaterials. Results indicated that the as-prepared Au/La2 O3 exhibited outstanding CTL properties such as stable intensity, high signal-to-noise values, and short response and recovery times. Under optimized conditions, the benzene assay exhibited a broad linear range of 1-4000 ppm, with a limit of detection of 0.7 ppm, which was below the standard permitted concentrations. Furthermore, the gas sensor system showed outstanding selectivity for benzene compared with seven other types of common volatile organic compounds (VOCs). The proposed gas sensor showed good characteristics with high selectivity, fast response time and long lifetime, which suggested the promising application of the Au/La2 O3 nanomaterials as a novel highly efficient CTL-sensing material.

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