The Neuroactive Steroid Pregnanolone Glutamate: Anticonvulsant Effect, Metabolites and Its Effect on Neurosteroid Levels in Developing Rat Brains

Pregnanolone glutamate (PA-G) is a neuroactive steroid that has been previously demonstrated to be a potent neuroprotective compound in several biological models in vivo. Our in vitro experiments identified PA-G as an inhibitor of N-methyl-D-aspartate receptors and a potentiator of γ-aminobutyric acid receptors (GABAARs). In this study, we addressed the hypothesis that combined GABAAR potentiation and NMDAR antagonism could afford a potent anticonvulsant effect. Our results demonstrated the strong age-related anticonvulsive effect of PA-G in a model of pentylenetetrazol-induced seizures. PA-G significantly decreased seizure severity in 12-day-old animals, but only after the highest dose in 25-day-old animals. Interestingly, the anticonvulsant effect of PA-G differed both qualitatively and quantitatively from that of zuranolone, an investigational neurosteroid acting as a potent positive allosteric modulator of GABAARs. Next, we identified 17-hydroxy-pregnanolone (17-OH-PA) as a major metabolite of PA-G in 12-day-old animals. Finally, the administration of PA-G demonstrated direct modulation of unexpected neurosteroid levels, namely pregnenolone and dehydroepiandrosterone sulfate. These results suggest that compound PA-G might be a pro-drug of 17-OH-PA, a neurosteroid with a promising neuroprotective effect with an unknown mechanism of action that may represent an attractive target for studying perinatal neural diseases.

A Machine Learning-Based Big EEG Data Artifact Detection and Wavelet-Based Removal: An Empirical Approach

The electroencephalogram (EEG) signals are a big data which are frequently corrupted by motion artifacts. As human neural diseases, diagnosis and analysis need a robust neurological signal. Consequently, the EEG artifacts’ eradication is a vital step. In this research paper, the primary motion artifact is detected from a single-channel EEG signal using support vector machine (SVM) and preceded with further artifacts’ suppression. The signal features’ abstraction and further detection are done through ensemble empirical mode decomposition (EEMD) algorithm. Moreover, canonical correlation analysis (CCA) filtering approach is applied for motion artifact removal. Finally, leftover motion artifacts’ unpredictability is removed by applying wavelet transform (WT) algorithm. Finally, results are optimized by using Harris hawks optimization (HHO) algorithm. The results of the assessment confirm that the algorithm recommended is superior to the algorithms currently in use.

Intravenous injection of cyclophilin A realizes the transient and reversible opening of barrier of neural vasculature through basigin in endothelial cells

Neural vasculature forms the blood–brain barrier against the delivery of systemically administered therapeutic drugs into parenchyma of neural tissues. Therefore, procedures to open the blood–brain barrier with minimal damage to tissues would lead to the great progress in therapeutic strategy for intractable neural diseases. In this study, through analyses with mouse in vitro brain microvascular endothelial cells and in vivo neural vasculature, we demonstrate that the administration of cyclophilin A (CypA), a ligand of basigin which is expressed in barrier-forming endothelial cells, realizes the artificial opening of blood–brain barrier. Monolayers of endothelial cells lost their barrier properties through the disappearance of claudin-5, an integral tight junction molecule, from cell membranes in a transient and reversible manner. Furthermore, the intravenous injection of a single dose of CypA into mice resulted in the opening of blood–brain barrier for a certain period which enabled the enhanced delivery of systemically administered doxorubicin into the parenchyma of neural tissues. These findings that the pre-injection of a single dose of CypA realizes an artificial, transient as well as reversible opening of blood–brain barrier are considered to be a great step toward the establishment of therapeutic protocols to overcome the intractability of neural diseases.

Advances in Tissue Engineering and Innovative Fabrication Techniques for 3-D-Structures: Translational Applications in Neurodegenerative Diseases

In the field of regenerative medicine applied to neurodegenerative diseases, one of the most important challenges is the obtainment of innovative scaffolds aimed at improving the development of new frontiers in stem-cell therapy. In recent years, additive manufacturing techniques have gained more and more relevance proving the great potential of the fabrication of precision 3-D scaffolds. In this review, recent advances in additive manufacturing techniques are presented and discussed, with an overview on stimulus-triggered approaches, such as 3-D Printing and laser-based techniques, and deposition-based approaches. Innovative 3-D bioprinting techniques, which allow the production of cell/molecule-laden scaffolds, are becoming a promising frontier in disease modelling and therapy. In this context, the specific biomaterial, stiffness, precise geometrical patterns, and structural properties are to be considered of great relevance for their subsequent translational applications. Moreover, this work reports numerous recent advances in neural diseases modelling and specifically focuses on pre-clinical and clinical translation for scaffolding technology in multiple neurodegenerative diseases.