Hypercapnia induces cleavage and nuclear localization of RelB protein, giving insight into CO2 sensing and signaling

Carbon dioxide (CO(2)) is increasingly being appreciated as an intracellular signaling molecule that affects inflammatory and immune responses. Elevated arterial CO(2) (hypercapnia) is encountered in a range of clinical conditions, including chronic obstructive pulmonary disease, and as a consequence of therapeutic ventilation in acute respiratory distress syndrome. In patients suffering from this syndrome, therapeutic hypoventilation strategy designed to reduce mechanical damage to the lungs is accompanied by systemic hypercapnia and associated acidosis, which are associated with improved patient outcome. However, the molecular mechanisms underlying the beneficial effects of hypercapnia and the relative contribution of elevated CO(2) or associated acidosis to this response remain poorly understood. Recently, a role for the non-canonical NF-?B pathway has been postulated to be important in signaling the cellular transcriptional response to CO(2). In this study, we demonstrate that in cells exposed to elevated CO(2), the NF-?B family member RelB was cleaved to a lower molecular weight form and translocated to the nucleus in both mouse embryonic fibroblasts and human pulmonary epithelial cells (A549). Furthermore, elevated nuclear RelB was observed in vivo and correlated with hypercapnia-induced protection against LPS-induced lung injury. Hypercapnia-induced RelB processing was sensitive to proteasomal inhibition by MG-132 but was independent of the activity of glycogen synthase kinase 3ß or MALT-1, both of which have been previously shown to mediate RelB processing. Taken together, these data demonstrate that RelB is a CO(2)-sensitive NF-?B family member that may contribute to the beneficial effects of hypercapnia in inflammatory diseases of the lung.

REST is a hypoxia-responsive transcriptional repressor

Cellular exposure to hypoxia results in altered gene expression in a range of physiologic and pathophysiologic states. Discrete cohorts of genes can be either up- or down-regulated in response to hypoxia. While the Hypoxia-Inducible Factor (HIF) is the primary driver of hypoxia-induced adaptive gene expression, less is known about the signalling mechanisms regulating hypoxiadependent gene repression. Using RNA-seq, we demonstrate that equivalent numbers of genes are induced and repressed in human embryonic kidney (HEK293) cells. We demonstrate that nuclear localization of the Repressor Element 1-Silencing Transcription factor (REST) is induced in hypoxia and that REST is responsible for regulating approximately 20% of the hypoxia-repressed genes. Using chromatin immunoprecipitation assays we demonstrate that REST-dependent gene repression is at least in part mediated by direct binding to the promoters of target genes. Based on these data, we propose that REST is a key mediator of gene repression in hypoxia.

Sequence distributions in free-radical polymers

This thesis is concerned with demonstrating how the visual representation of the sequence distribution of individual monomer units, of a polymer, that would be observed upon polymerisation, may be utilised in designing and synthesizing polymers with relatively low cell adhesion characteristics, The initial part of this thesis is concerned with demonstrating the use of a computer simulation technique, in illustrating the sequence distribution that would be observed upon the polymerisation of a set of monomers. The power of the computer simulation technique has been demonstrated through the simulation of the sequence distributions of some generic contact lens materials. These generic contact lens materials were chosen simply because in the field of biomaterials their compositions are amongst the most systematically regulated and they present a wide range of compositions. The validity of the computer simulation technique has been assessed through the synthesis and analysis of linear free-radical polymers at different conversions. Two main parameters were examined, that of composition and the number-average sequence lengths of individual monomer units, at various conversions. The polymers were synthesized through the solution polymerisation process. The monomer composition was determined by elemental analysis and 13C nuclear magnetic analysis (NMR). Number-average sequence lengths were determined exclusively through 13C NMR. Although the computer simulation technique provides a visual representation of the monomer sequence distribution up to 100% conversion, these assessments were made on linear polymers at a reasonably high conversion (above 50%) but below 100% conversion of ease for analysis. The analyses proved that the computer simulation technique was reasonably accurate in predicting the sequence distribution of monomer units, upon polymerisation, in the polymer.An approach has been presented which allows one to manipulate the use of monomers, with their reactivity ratios, thereby enabling us to design polymers with controlled sequence distributions.Hydrogel membranes, with relatively controlled sequence distributions and polymerised to 100% conversion, were synthesized to represent prospective biomaterials. Cell adhesion studies were used as a biological probe to investigate the susceptibility of the surface of these membranes to cell adhesion. This was necessary in order to assess the surface biocompatibility or biotolerance of these prospective biomaterials.

Source localization of reaction-diffusion models for brain tumors

We propose a mathematically well-founded approach for locating the source (initial state) of density functions evolved within a nonlinear reaction-diffusion model. The reconstruction of the initial source is an ill-posed inverse problem since the solution is highly unstable with respect to measurement noise. To address this instability problem, we introduce a regularization procedure based on the nonlinear Landweber method for the stable determination of the source location. This amounts to solving a sequence of well-posed forward reaction-diffusion problems. The developed framework is general, and as a special instance we consider the problem of source localization of brain tumors. We show numerically that the source of the initial densities of tumor cells are reconstructed well on both imaging data consisting of simple and complex geometric structures.