Tissue distribution of a plasmid DNA encoding Hsp65 gene is dependent on the dose administered through intramuscular delivery

In order to assess a new strategy of DNA vaccine for a more complete understanding of its action in immune response, it is important to determine the in vivo biodistribution fate and antigen expression. In previous studies, our group focused on the prophylactic and therapeutic use of a plasmid DNA encoding the Mycobacterium leprae 65-kDa heat shock protein (Hsp65) and achieved an efficient immune response induction as well as protection against virulent M. tuberculosis challenge. In the present study, we examined in vivo tissue distribution of naked DNA-Hsp65 vaccine, the Hsp65 message, genome integration and methylation status of plasmid DNA. The DNA-Hsp65 was detectable in several tissue types, indicating that DNA-Hsp65 disseminates widely throughout the body. The biodistribution was dose-dependent. In contrast, RT-PCR detected the Hsp65 message for at least 15 days in muscle or liver tissue from immunized mice. We also analyzed the methylation status and integration of the injected plasmid DNA into the host cellular genome. The bacterial methylation pattern persisted for at least 6 months, indicating that the plasmid DNA-Hsp65 does not replicate in mammalian tissue, and Southern blot analysis showed that plasmid DNA was not integrated. These results have important implications for the use of DNA-Hsp65 vaccine in a clinical setting and open new perspectives for DNA vaccines and new considerations about the inoculation site and delivery system.     

Analysis of binding properties and specificity through identification of the interface forming residues (IFR) for serine proteases <Emphasis Type="Italic">in silico</Emphasis> docked to different inhibitors

Background  

Enzymes belonging to the same super family of proteins in general operate on variety of substrates and are inhibited by wide selection of inhibitors. In this work our main objective was to expand the scope of studies that consider only the catalytic and binding pocket amino acids while analyzing enzyme specificity and instead, include a wider category which we have named the Interface Forming Residues (IFR). We were motivated to identify those amino acids with decreased accessibility to solvent after docking of different types of inhibitors to sub classes of serine proteases and then create a table (matrix) of all amino acid positions at the interface as well as their respective occupancies. Our goal is to establish a platform for analysis of the relationship between IFR characteristics and binding properties/specificity for bi-molecular complexes.     

Model-based interpretation of complex and variable images.

The ultimate goal of machine vision is image understanding-the ability not only to recover image structure but also to know what it represents. By definition, this involves the use of models which describe and label the expected structure of the world. Over the past decade, model-based vision has been applied successfully to images of man-made objects. It has proved much more difficult to develop model-based approaches to the interpretation of images of complex and variable structures such as faces or the internal organs of the human body (as visualized in medical images). In such cases it has been problematic even to recover image structure reliably, without a model to organize the often noisy and incomplete image evidence. The key problem is that of variability. To be useful, a model needs to be specific-that is, to be capable of representing only ''legal'' examples of the modelled object(s). It has proved difficult to achieve this whilst allowing for natural variability. Recent developments have overcome this problem; it has been shown that specific patterns of variability in shape and grey-level appearance can be captured by statistical models that can be used directly in image interpretation. The details of the approach are outlined and practical examples from medical image interpretation and face recognition are used to illustrate how previously intractable problems can now be tackled successfully. It is also interesting to ask whether these results provide any possible insights into natural vision; for example, we show that the apparent changes in shape which result from viewing three-dimensional objects from different viewpoints can be modelled quite well in two dimensions; this may lend some support to the ''characteristic views'' model of natural vision.