No abstract

DNA vaccines have the potential of giving rise to a potent cell-mediated immune response by inducing intracellular synthesis and subsequent antigenic presentation of encoded antigens. We have tested a DNA vaccine specific for human immunodeficiency virus type 1 (HIV-1) by the injection of animals with expression plasmids encoding the HIV-1 envelope protein and the Rev regulatory protein. Injection of both plasmids into mice, rabbits, or macaques was found to induce high levels of specific antibodies capable of efficiently inhibiting both HIV-1 infection and envelope-mediated cell fusion. A readily detectable delayed-type hypersensitivity (DTH) response was demonstrable in injected mice and lymphocytes derived from these proliferated in response to an HIV-1 envelope V3 loop-specific peptide. Interestingly, the injected mice or macaques also developed a strong cytotoxic T lymphocyte (CTL) response against target cells pulsed with the V3 peptide. Taken together, these data demonstrate that injection of HIV-1 gene expression plasmids can induce potent humoral and cell-mediated immune responses and suggest that DNA vaccines may prove to be significantly beneficial as a means of immunizing against HIV-1.

To develop effective vaccines against infection with human T cell leukaemia virus type I (HTLV-I), we constructed a recombinant vaccinia virus (WR-SFB5env

Plant associated fungi show diverse lifestyles from pathogenic to mutualistic to the host; however, the principles and mechanisms through which they shift the lifestyles require elucidation. The root fungus Colletotrichum tofieldiae (Ct) promotes Arabidopsis thaliana growth under phosphate limiting conditions. We reveal a Ct strain, designated Ct3, that severely inhibits plant growth. Ct3 pathogenesis occurs through activation of host abscisic acid (ABA) pathways via a fungal secondary metabolism gene cluster related to sesquiterpene ABA and botrydial (BOT) biosynthesis. ABA_BOT cluster activation during root infection suppresses host nutrient uptake-related genes and changes the mineral contents, suggesting its role in manipulating host nutrition states. Conversely, disruption or environmental suppression of the cluster renders Ct3 beneficial for plant growth, in a manner dependent on host phosphate starvation response regulators. Our findings indicate that a fungal metabolism cluster provides a means by which infectious fungi modulate lifestyles along the parasitic_mutualistic continuum in fluctuating environments.

This paper describes word category prediction based on neural network models for constructing an accurate word recognition system. It is difficult to represent hidden linguistic structure and make an N-gram word prediction model using traditional stochastic approaches. In this paper, two neural network models that can learn hidden linguistic structure are proposed. These models can easily be expanded from Bigram to N-gram networks. They were tested by training experiments with an open English text database. The Trigram word category prediction rates show that neural network models are comparable to stochastic models. Trigram neural network models compress information about 150 times, which is the ratio of the Trigram stochastic model free parameters (893 = 704 969) to the neural network model link weights (4649). In addition, this paper proposes a new method that dynamically controls the training parameters, updating step size and momentum. These techniques are effective for calculating the efficiency of this system.