DNA Immunization for HIV Vaccine Development

DNA vaccination has been studied in the last 20 years for HIV vaccine research. Significant experience has been accumulated in vector design, antigen optimization, delivery approaches and the use of DNA immunization as part of a prime-boost HIV vaccination strategy. Key historical data and future outlook are presented. With better understanding on the potential of DNA immunization and recent progress in HIV vaccine research, it is anticipated that DNA immunization will play a more significant role in the future of HIV vaccine development

Extreme case of Faraday effect: magnetic splitting of ultrashort laser pulses in plasmas

The Faraday effect, caused by a magnetic-field-induced change in the optical properties, takes place in a vast variety of systems from a single atomic layer of graphenes to huge galaxies. Currently, it plays a pivot role in many applications such as the manipulation of light and the probing of magnetic fields and material's properties. Basically, this effect causes a polarization rotation of light during its propagation along the magnetic field in a medium. Here, we report an extreme case of the Faraday effect where a linearly polarized ultrashort laser pulse splits in time into two circularly polarized pulses of opposite handedness during its propagation in a highly magnetized plasma. This offers a new degree of freedom for manipulating ultrashort and ultrahigh power laser pulses. Together with technologies of ultra-strong magnetic fields, it may pave the way for novel optical devices, such as magnetized plasma polarizers. In addition, it may offer a powerful means to measure strong magnetic fields in laser-produced plasmas.Comment: 18 pages, 5 figure

Visual analysis of discrimination in machine learning

The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning. How can we decide whether different treatments are reasonable or discriminatory? In this paper, we investigate discrimination in machine learning from a visual analytics perspective and propose an interactive visualization tool, DiscriLens, to support a more comprehensive analysis. To reveal detailed information on algorithmic discrimination, DiscriLens identifies a collection of potentially discriminatory itemsets based on causal modeling and classification rules mining. By combining an extended Euler diagram with a matrix-based visualization, we develop a novel set visualization to facilitate the exploration and interpretation of discriminatory itemsets. A user study shows that users can interpret the visually encoded information in DiscriLens quickly and accurately. Use cases demonstrate that DiscriLens provides informative guidance in understanding and reducing algorithmic discrimination

The wide utility of rabbits as models of human diseases

Studies using the European rabbit Oryctolagus cuniculus contributed to elucidating numerous fundamental aspects of antibody structure and diversification mechanisms and continue to be valuable for the development and testing of therapeutic humanized polyclonal and monoclonal antibodies. Additionally, during the last two decades, the use of the European rabbit as an animal model has been increasingly extended to many human diseases. This review documents the continuing wide utility of the rabbit as a reliable disease model for development of therapeutics and vaccines and studies of the cellular and molecular mechanisms underlying many human diseases. Examples include syphilis, tuberculosis, HIV-AIDS, acute hepatic failure and diseases caused by noroviruses, ocular herpes, and papillomaviruses. The use of rabbits for vaccine development studies, which began with Louis Pasteur\u27s rabies vaccine in 1881, continues today with targets that include the potentially blinding HSV-1 virus infection and HIV-AIDS. Additionally, two highly fatal viral diseases, rabbit hemorrhagic disease and myxomatosis, affect the European rabbit and provide unique models to understand co-evolution between a vertebrate host and viral pathogens

Structural analysis of a novel rabbit monoclonal antibody R53 targeting an epitope in HIV-1 gp120 C4 region critical for receptor and co-receptor binding

The fourth conserved region (C4) in the HIV-1 envelope glycoprotein (Env) gp120 is a structural element that is important for its function, as it binds to both the receptor CD4 and the co-receptor CCR5/CXCR4. It has long been known that this region is highly immunogenic and that it harbors B-cell as well as T-cell epitopes. It is the target of a number of antibodies in animal studies, which are called CD4-blockers. However, the mechanism by which the virus shields itself from such antibody responses is not known. Here, we determined the crystal structure of R53 in complex with its epitope peptide using a novel anti-C4 rabbit monoclonal antibody R53. Our data show that although the epitope of R53 covers a highly conserved sequence (433)AMYAPPI(439), it is in the gp120 trimer and in the CD4-bound conformation. Our results suggest a masking mechanism to explain how HIV-1 protects this critical region from the human immune system

Rabbit anti-HIV-1 monoclonal antibodies raised by immunization can mimic the antigen-binding modes of antibodies derived from HIV-1-infected humans

The rabbit is a commonly used animal model in studying antibody responses in HIV/AIDS vaccine development. However, no rabbit monoclonal antibodies (MAbs) have been developed previously to study the epitope-specific antibody responses against HIV-1 envelope (Env) glycoproteins, and little is known about how the rabbit immune system can mimic the human immune system in eliciting such antibodies. Here we present structural analyses of two rabbit MAbs, R56 and R20, against the third variable region (V3) of HIV-1 gp120. R56 recognizes the well-studied immunogenic region in the V3 crown, while R20 targets a less-studied region at the C terminus of V3. By comparison of the Fab/epitope complex structures of these two antibodies raised by immunization with that of the corresponding human antibodies derived from patients chronically infected with HIV-1, we found that rabbit antibodies can recognize immunogenic regions of gp120 and mimic the binding modes of human antibodies. This result can provide new insight into the use of the rabbit as an animal model in AIDS vaccine development

User-friendly optimization approach of fed-batch fermentation conditions for the production of iturin A using artificial neural networks and support vector machine

Background: In the field of microbial fermentation technology, how to optimize the fermentation conditions is of great crucial for practical applications. Here, we use artificial neural networks (ANNs) and support vector machine (SVM) to offer a series of effective optimization methods for the production of iturin A. The concentration levels of asparagine (Asn), glutamic acid (Glu) and proline (Pro) (mg/L) were set as independent variables, while the iturin A titer (U/mL) was set as dependent variable. General regression neural network (GRNN), multilayer feed-forward neural networks (MLFNs) and the SVM were developed. Comparisons were made among different ANNs and the SVM. Results: The GRNN has the lowest RMS error (457.88) and the shortest training time (1 s), with a steady fluctuation during repeated experiments, whereas the MLFNs have comparatively higher RMS errors and longer training times, which have a significant fluctuation with the change of nodes. In terms of the SVM, it also has a relatively low RMS error (466.13), with a short training time (1 s). Conclusion: According to the modeling results, the GRNN is considered as the most suitable ANN model for the design of the fed-batch fermentation conditions for the production of iturin A because of its high robustness and precision, and the SVM is also considered as a very suitable alternative model. Under the tolerance of 30%, the prediction accuracies of the GRNN and SVM are both 100% respectively in repeated experiments