Antegrade selective cerebral perfusion and moderate hypothermia in aortic arch surgery: clinical outcomes in elderly patients

To evaluate the outcome in elderly patients (≥ 75 years) undergoing elective aortic arch surgery with the aid of selective antegrade cerebral perfusion (SACP) and moderate hypothermic circulatory arrest (HCA).

Selective cloning, characterization, and production of the Culicoides nubeculosus salivary gland allergen repertoire associated with equine insect bite hypersensitivity

Salivary gland proteins of Culicoides spp. have been suggested to be among the main allergens inducing IgE-mediated insect bite hypersensitivity (IBH), an allergic dermatitis of the horse. The aim of our study was to identify, produce and characterize IgE-binding salivary gland proteins of Culicoides nubeculosus relevant for IBH by phage surface display technology. A cDNA library constructed with mRNA derived from C. nubeculosus salivary glands was displayed on the surface of filamentous phage M13 and enriched for clones binding serum IgE of IBH-affected horses. Ten cDNA inserts encoding putative salivary gland allergens were isolated and termed Cul n 2 to Cul n 11. However, nine cDNA sequences coded for truncated proteins as determined by database searches. The cDNA sequences were amplified by PCR, subcloned into high level expression vectors and expressed as hexahistidine-tagged fusion proteins in Escherichia coli. Preliminary ELISA results obtained with these fusions confirmed the specific binding to serum IgE of affected horses. Therefore, the putative complete open reading frames derived from BLAST analyses were isolated by RACE-PCR and subcloned into expression vectors. The full length proteins expressed in Escherichia coli showed molecular masses in the range of 15.5-68.7 kDa in SDS-PAGE in good agreement with the masses calculated from the predicted protein sequences. Western blot analyses of all recombinant allergens with a serum pool of IBH-affected horses showed their ability to specifically bind serum IgE of sensitized horses, and ELISA determinations yielded individual horse recognition patterns with a frequency of sensitization ranging from 13 to 57%, depending on the allergen tested. The in vivo relevance of eight of the recombinant allergens was demonstrated in intradermal skin testing. For the two characterized allergens Cul n 6 and Cul n 11, sensitized horses were not available for intradermal tests. Control horses without clinical signs of IBH did not develop any relevant immediate hypersensitivity reactions to the recombinant allergens. The major contribution of this study was to provide a repertoire of recombinant salivary gland allergens repertoire from C. nubeculosus potentially involved in the pathogenesis of IBH as a starting basis for the development of a component-resolved serologic diagnosis of IBH and, perhaps, for the development of single horse tailored specific immunotherapy depending on their component-resolved sensitization patterns.

THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS

The means through which the nervous system perceives its environment is one of the most fascinating questions in contemporary science. Our endeavors to comprehend the principles of neural science provide an instance of how biological processes may inspire novel methods in mathematical modeling and engineering. The application ofmathematical models towards understanding neural signals and systems represents a vibrant field of research that has spanned over half a century. During this period, multiple approaches to neuronal modeling have been adopted, and each approach is adept at elucidating a specific aspect of nervous system function. Thus while bio-physical models have strived to comprehend the dynamics of actual physical processes occurring within a nerve cell, the phenomenological approach has conceived models that relate the ionic properties of nerve cells to transitions in neural activity. Further-more, the field of neural networks has endeavored to explore how distributed parallel processing systems may become capable of storing memory. Through this project, we strive to explore how some of the insights gained from biophysical neuronal modeling may be incorporated within the field of neural net-works. We specifically study the capabilities of a simple neural model, the Resonate-and-Fire (RAF) neuron, whose derivation is inspired by biophysical neural modeling. While reflecting further biological plausibility, the RAF neuron is also analytically tractable, and thus may be implemented within neural networks. In the following thesis, we provide a brief overview of the different approaches that have been adopted towards comprehending the properties of nerve cells, along with the framework under which our specific neuron model relates to the field of neuronal modeling. Subsequently, we explore some of the time-dependent neurocomputational capabilities of the RAF neuron, and we utilize the model to classify logic gates, and solve the classic XOR problem. Finally we explore how the resonate-and-fire neuron may be implemented within neural networks, and how such a network could be adapted through the temporal backpropagation algorithm.