Background Alternaria is one of the most common molds associated with allergic diseases and 80% of Alternaria-sensitive patients produce IgE antibodies to a major protein allergen, Alt a 1. The structure and function of Alt a 1 is unknown. Objective To obtain a high resolution structure of Alt a 1 by X-ray crystallography and to investigate structural relationships between Alt a 1 and other allergens and proteins reported in the Protein Data Bank. Methods X-ray crystallography was used to determine the structure of Alt a 1 using a custom-designed set of crystallization conditions. An initial Alt a 1 model was determined by the application of a Ta6Br122+ cluster and Single-wavelength Anomalous Diffraction. Bioinformatic analyses were used to compare the Alt a 1 sequence and structure with other proteins. Results Alt a 1 is a unique β-barrel comprising 11 β-strands and forms a ‘butterfly-like’ dimer linked by a single disulfide bond, with a large (1345Å2) dimer interface. Intramolecular disulfide bonds are conserved among Alt a 1 homologs. Currently, the Alt a 1 structure has no equivalent in the Protein Data Bank. Bioinformatics analyses suggest that the structure is found exclusively in fungi. Four previously reported putative IgE binding peptides have been located on the Alt a 1 structure. Conclusions Alt a 1 has a unique, dimeric β-barrel structure that appears to define a new protein family with unknown function found exclusively in fungi. The location of IgE antibody binding epitopes is in agreement with the structural analysis of Alt a 1.The Alt a 1 structure will allow mechanistic structure/function studies and immunologic studies directed towards new forms of immunotherapy for Alternaria-sensitive allergic patients.

Allergic reactions to peanuts and tree nuts are major causes of anaphylaxis in the United States. We compare different properties of natural and recombinant versions of Ara h 1, a major peanut allergen, through structural, immunologic, and bioinformatics analyses. Small angle x-ray scattering studies show that natural Ara h 1 forms higher molecular weight aggregates in solution. In contrast, the full-length recombinant protein is partially unfolded and exists as a monomer. The crystal structure of the Ara h 1 core (residues 170 -586) shows that the central part of the allergen has a bicupin fold, which is in agreement with our bioinformatics analysis. In its crystalline state, the core region of Ara h 1 forms trimeric assemblies, while in solution the protein exists as higher molecular weight assemblies. This finding reveals that the residues forming the core region of the protein are sufficient for formation of Ara h 1 trimers and higher order oligomers. Natural and recombinant variants of proteins tested in in vitro gastric and duodenal digestion assays show that the natural protein is the most stable form, followed by the recombinant Ara h 1 core fragment and the full-length recombinant protein. Additionally, IgE binding studies reveal that the natural and recombinant allergens have different patterns of interaction with IgE antibodies. The molecular basis of cross-reactivity between vicilin allergens is also elucidated.

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Electroencephalography (EEG) is a method for recording electrical activity, indicative of cortical brain activity from the scalp. EEG has been used to diagnose neurological diseases and to characterize impaired cognitive states. When the electrical activity of neurons are temporally synchronized, the likelihood to reach their threshold potential for the signal to propagate to the next neuron, increases. This phenomenon is typically analyzed as the spectral intensity increasing from the summation of these neurons firing. Non-linear analysis methods (e.g., entropy) have been explored to characterize neuronal firings, but only analyze temporal information and not the frequency spectrum. By examining temporal and spectral entropic relationships simultaneously, we can better characterize how neurons are isolated, (the signal's inability to propagate to adjacent neurons), an indicator of impairment. A novel time-frequency entropic analysis method, referred to as Activation Complexity (AC), was designed to quantify these dynamics from key EEG frequency bands. The data was collected during a cognitive impairment study at NASA Langley Research Center, involving hypoxia induction in 49 human test subjects. AC demonstrated significant changes in EEG firing patterns characterize within explanatory (p < 0.05) and predictive models (10% increase in accuracy). The proposed work sets the methodological foundation for quantifying neuronal isolation and introduces new potential technique to understand human cognitive impairment for a range of neurological diseases and insults.Electroencephalography (EEG) detects the electrical activity of the brain and analysis of EEG permits tracking variations in brain wave patterns. EEG analysis provides information about a person's cognitive state such as response inhibition, level of concentration, arousal, and even diagnostic information regarding diseases such as Alzheimer's, post-cardiac arrest syndrome (hypoxic encephalopathies), and epilepsy 1-6 . There are many types of analyses designed to extract features from EEG signals that examine coherence, intensity of frequency bands, signal entropy, coupling, and source localization to acquire information about cognitive states 2,7 . These extracted EEG features are then used as the foundation for explanatory and predictive modeling. Typically, two or more of these features are utilized to generate a feature space for predictive models that can predict epilepsy, hypoxia, etc. 2 . Thus, capturing these new EEG features is paramount to uncovering nascent patterns that provide further insight into the complexities of the human brain and distinguishing impairments.Literature has demonstrated that conditions like hypoxia, Alzheimer's, epilepsy, and other neurological issues cause neuronal impairments that change firing patterns. Modification of firing can potentially occur at the intracellular level of an individual neuron or at the intercellular level in how neurons propagate information to each other (neuronal interactions). However, the non-line...