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Abstract Background Many peptide-based cancer vaccines have been tested in clinical trials with a limited success, mostly due to difficulties associated with peptide stability and delivery, resulting in inefficient antigen presentation. Therefore, the development of suitable and efficient vaccine carrier systems remains a major challenge. Methods To address this issue, we have engineered polylactic-co-glycolic acid (PLGA) nanoparticles incorporating: (i) two MHC class I-restricted clinically-relevant peptides, (ii) a MHC class II-binding peptide, and (iii) a non-classical MHC class I-binding peptide. We formulated the nanoparticles utilizing a double emulsion-solvent evaporation technique and characterized their surface morphology, size, zeta potential and peptide content. We also loaded human and murine dendritic cells (DC) with the peptide-containing nanoparticles and determined their ability to present the encapsulated peptide antigens and to induce tumor-specific cytotoxic T lymphocytes (CTL) in vitro. Results We confirmed that the nanoparticles are not toxic to either mouse or human dendritic cells, and do not have any effect on the DC maturation. We also demonstrated a significantly enhanced presentation of the encapsulated peptides upon internalization of the nanoparticles by DC, and confirmed that the improved peptide presentation is actually associated with more efficient generation of peptide-specific CTL and T helper cell responses. Conclusion Encapsulating antigens in PLGA nanoparticles offers unique advantages such as higher efficiency of antigen loading, prolonged presentation of the antigens, prevention of peptide degradation, specific targeting of antigens to antigen presenting cells, improved shelf life of the antigens, and easy scale up for pharmaceutical production. Therefore, these findings are highly significant to the development of synthetic vaccines, and the induction of CTL for adoptive immunotherapy.

Monoclonal antibodies (mAb) are an important and growing class of cancer therapeutics, but pharmacokinetic analyses have in many cases been constrained by the lack of standard and robust pharmacologic assays. The goal of this project was to develop a general method for the production of immunoassays that can measure the levels of therapeutic monoclonal antibodies in biologic samples at relevant concentrations.Alemtuzumab and rituximab are monoclonal approved for the treatment of B-cell malignancies and were used as a model system. Phage-displayed peptide libraries were screened for peptide sequences recognized by alemtuzumab (anti-CD52) or rituximab (anti-CD20). Synthetic biotinylated peptides were used in enzyme-linked immunosorbent assays (ELISA). Peptides directly synthesized on polymer resin beads were used in an immunofluorescent-based assay.Peptide mimetope sequences were recovered for both mAb and confirmed by competitive staining and kinetic measurements. A peptide-based ELISA method was developed for each. The assay for rituximab had a limit of detection of 4 μg/ml, and the assay for alemtuzumab had a limit of detection of 1 μg/ml. Antibody-specific staining of peptide conjugated beads could be seen in a dose-dependent manner.Phage-displayed peptide libraries can be a source of highly specific mimetopes for therapeutic mAb. The biotinylated forms of those peptides are compatible with conventional ELISA methods with sensitivities comparable to other assay methods and sufficient for pharmacological studies of those mAb given at high dose. The process outlined here can be applied to any mAb to enable improved pharmacokinetic analysis during the development and clinical use of this class of therapies.

Knowledge discovery from large and complex scientific data is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the growing number of data dimensions and data objects presents tremendous challenges for effective data analysis and data exploration methods and tools. The combination and close integration of methods from scientific visualization, information visualization, automated data analysis, and other enabling technologies —such as efficient data management— supports knowledge discovery from multi-dimensional scientific data. This paper surveys two distinct applications in developmental biology and accelerator physics, illustrating the effectiveness of the described approach.

One of the central challenges in modern science is the need to quickly derive knowledge and understanding from large, complex collections of data. We present a new approach that deals with this challenge by combining and extending techniques from high performance visual data analysis and scientific data management. This approach is demonstrated within the context of gaining insight from complex, time-varying datasets produced by a laser wakefield accelerator simulation. Our approach leverages histogram-based parallel coordinates for both visual information display as well as a vehicle for guiding a data mining operation. Data extraction and subsetting are implemented with state-of-the-art index/query technology. This approach, while applied here to accelerator science, is generally applicable to a broad set of science applications, and is implemented in a production-quality visual data analysis infrastructure. We conduct a detailed performance analysis and demonstrate good scalability on a distributed memory Cray XT4 system. © 2008 IEEE.

One of the central challenges in modern science is the need to quickly derive knowledge and understanding from large, complex collections of data. We present a new approach that deals with this challenge by combining and extending techniques from high performance visual data analysis and scientific data management. This approach is demonstrated within the context of gaining insight from complex, time-varying datasets produced by a laser wakefield accelerator simulation. Our approach leverages histogram-based parallel coordinates for both visual information display as well as a vehicle for guiding a data mining operation. Data extraction and subsetting are implemented with state-of-the-art index/query technology. This approach, while applied here to accelerator science, is generally applicable to a broad set of science applications, and is implemented in a production-quality visual data analysis infrastructure. We conduct a detailed performance analysis and demonstrate good scalability on a distributed memory Cray XT4 system. © 2008 IEEE.

The Utah prairie dog (UPD) was listed as “endangered” in 1973; it was down-listed to “threatened” in 1984. Regulatory agencies have realized that protecting and promoting UPD on federal lands alone is not efficient. The U.S. Fish and Wildlife Service (USFWS) and private landowners desire a shift in the current recovery strategy in order to remove the threatened status of UPD as well as provide for management of UPD damage to private property. The time is right to begin a creative management strategy. One suggested new strategy would combine population counts of UPD living on private and public lands toward the recovery goal, as part of the new recovery plan. A survey of agricultural producers in the region with UPD revealed that 70% of the producers feared working with the USFWS on sensitive species issues, because of possible restrictions to their production. To date, the majority of producers would not be interested in creating conservation easements or safe harbors on their property. However, they are willing to work with local Extension agents and the Utah Farm Bureau to create solutions. Therefore, the first step to trying a new approach to UPD recovery will be to foster trust between local producers and regulatory agencies. New programs will focus on building trust, just compensation for losses, stewardship of the land and community, and cooperation.

Capillary channels of cm-length and at plasma density low compared to gas jets are promising setups for low noise laser wakefield acceleration. Computationally, however, the large discrepancy of the length scales of the plasma and the laser are a big challenge. Methods are therefore sought that relax the need to concurrently resolve both length scales. Average methods, which split the electromagneticfield into a fast and a slowly varying part, allow to relax the constraint to resolve the laser wavelength. Such an envelope model is currently being incorporated into the VORPAL plasma simulation code. Simulation results for benchmark cases and for laser pulse propagation in a cm-scale channel are presented.

The guiding of intense laser pulses in plasma channels is necessary to maximize the energy of electrons accelerated in a laser wakefield accelerator. A significant fraction of the energy in the laser pulse may be lost during and after coupling from vacuum into a channel. For example, imperfect coupling can lead to enhanced leakage of laser energy transversely through the channel walls. We present 2D particle-in-cell (PIC) simulations, using the VORPAL code, of an example problem. We present a numerical diagnostic, based on simultaneous FFT s in space and time, which enables quantitative measurements of forward and backward propagating pulse energy andits spectra. Future work will be directed toward VORPAL parameter studies designed to optimize the amount of laser energy that couples into a channel.

The mission of this library media program is to ensure that students are effective users of ideas and information. This makes meaningful, ongoing collaboration with teachers essential. Creating opportunities for teamwork is a challenge for all school librarians. Online research investigations are an example of systematic, districtwide collaboration between school librarians, district staff , and teachers to facilitate more powerful research by students. (Contains 7 resources.)