The paper describes the results from a unique experimental and analytical study in a well-controlled animal model of Sudden Unexpected Death in Epilepsy (SUDEP). As the name implies, SUDEP is difficult to impossible to study in humans due to the uncertainty in the timing of death occurrence over years. It is much easier to do this with animals as they also have much shorter life span. The animal model we employed is one of two most prominent animal models of SUDEP. Our aim was to elucidate potential impairments in the functional connectivity between the brain, heart and lungs that could contribute to our better understanding of the underlying causes of SUDEP. This is the first study of its kind in SUDEP and, as far as we know, the first multivariate study between the heart, brain and lungs, part of the emerging field of organomics. In this contribution, we report for the first time results from tri-organ analysis of concurrent electroencephalographic, electrocardiographic and plethysmographic recordings in a control group (wild-type healthy mice) and a group of mice genetically predisposed to SUDEP and epileptic seizures. We were able to produce strong statistical evidence (p<0.001) that SUDEP-prone animals exhibit statistically significant inter-organ (brain, heart and lungs) abnormalities in specific functional afferent and efferent interactions. The graphic abstract is a schematic representation of the statistically significant (a) decreased and (b) increased neuro-cardio-respiratory network interactions of the KO compared to WT mice averaged over frequencies of 1-200 Hz. The thickness of arrows corresponds to the magnitude, and the (+) or (-) sign above the arrows to the signs of the difference of the ssGPDC values of KO from the ones of WT animals for each interaction. We also show the impact of epileptic seizures on the dynamics of these functional connectivities. These results suggest that the novel measures of neuro-cardio-respiratory connectivity we developed from network analysis in the frequency domain do shed light on potential pathophysiological mechanisms of SUDEP and ictogenesis, could be utilized as biomarkers of susceptibility to SUDEP and seizures, as well as in the assessment and improvement of the efficacy of current and future intervention strategies for treatment of seizures and risk to SUDEP.

Astrocytes, also known as astroglia, are important cells for the structural support of neurons as well as for biochemical balance in the central nervous system (CNS). In this study, the polymerization of dopamine (DA) to polydopamine (PDA) and its effect on astrocytes was investigated. The polymerization of DA, being directly proportional to the DA concentration, raises the prospect of detecting DA concentration from PDA optically using image-processing techniques. It was found here that DA, a naturally occurring neurotransmitter, significantly altered astrocyte cell number, morphology, and metabolism, compared to astrocytes in the absence of DA. Along with these effects on astrocytes, the polymerization of DA to PDA was tracked optically in the same cell culture wells. This polymerization process led to a unique methodology based on multivariate regression analysis that quantified the concentration of DA from optical images of astrocyte cell culture media. Therefore, this developed methodology, combined with conventional imaging equipment, could be used in place of high-end and expensive analytical chemistry instruments, such as spectrophotometry, mass spectrometry, and fluorescence techniques, for quantification of the concentration of DA after polymerization to PDA under in vitro and potentially in vivo conditions.

No abstract

No abstract

No abstract

Carbon monoxide (CO) is known as a deathful gas produced by burning of hydrocarbons in a lack of enough oxygen, in which breathing CO leads to serious issues on human life health quality. Therefore, adsorption of CO gas is an essential task for diagnosis or removal of this dreadful gas in environment. To do this, a HEME-like model of iron-nitrogen-doped beryllium oxide (FeNBeO) monolayer was investigated for adsorbing CO gas by performing density functional theory (DFT) calculations. Two models were obtained for this process, in which relaxation of CO with C-head or O-head towards Fe region of monolayer. The results indicated that the formation of FeNBeO-CO model could be achieved more favorable than the formation of FeNBeO-OC model. The obtained optimized geometers and energies all approved this achievement for favorability of FeNBeO-CO model formation. Moreover, molecular orbital based electronic features indicated variations of such features for the models upon adsorption of CO substance, in which the models could be detectable in a sensor function for the existence of CO gas in the environment. As a consequence, the investigated FeNBeO monolayer could be proposed useful for adsorption of CO gas at least for the CO deathful gas diagnosis purposes.