RESUMO
Neuromyelitis optica is an inflammatory demyelinating disease of the central nervous system that differs from multiple sclerosis. Over the past 20 years, the search for biomarkers for neuromyelitis optica has been ongoing. Here, we used a bibliometric approach to analyze the main research focus in the field of biomarkers for neuromyelitis optica. Research in this area is consistently increasing, with China and the United States leading the way on the number of studies conducted. The Mayo Clinic is a highly reputable institution in the United States, and was identified as the most authoritative institution in this field. Furthermore, Professor Wingerchuk from the Mayo Clinic was the most authoritative expert in this field. Keyword analysis revealed that the terms "neuromyelitis optica" (261 times), "multiple sclerosis" (220 times), "neuromyelitis optica spectrum disorder" (132 times), "aquaporin 4" (99 times), and "optical neuritis" (87 times) were the most frequently used keywords in literature related to this field. Comprehensive analysis of the classical literature showed that the majority of publications provide conclusive research evidence supporting the use of aquaporin-4-IgG and neuromyelitis optica-IgG to effectively diagnose and differentiate neuromyelitis optica from multiple sclerosis. Furthermore, aquaporin-4-IgG has emerged as a highly specific diagnostic biomarker for neuromyelitis optica spectrum disorder. Myelin oligodendrocyte glycoprotein-IgG is a diagnostic biomarker for myelin oligodendrocyte glycoprotein antibody-associated disease. Recent biomarkers for neuromyelitis optica include cerebrospinal fluid immunological biomarkers such as glial fibrillary acidic protein, serum astrocyte damage biomarkers like FAM19A5, serum albumin, and gamma-aminobutyric acid. The latest prospective clinical trials are exploring the potential of these biomarkers. Preliminary results indicate that glial fibrillary acidic protein is emerging as a promising candidate biomarker for neuromyelitis optica spectrum disorder. The ultimate goal of future research is to identify non-invasive biomarkers with high sensitivity, specificity, and safety for the accurate diagnosis of neuromyelitis optica.
RESUMO
Several studies claim that listening to Mozart music affects cognition and can be used to treat neurological conditions like epilepsy. Research into this Mozart effect has not addressed how dynamic interactions between brain networks, i.e. effective connectivity, are affected. The Granger-causality analysis is often used to infer effective connectivity. First, we investigate if a new method, Bayesian topology identification, can be used as an alternative. Both methods are evaluated on simulation data, where the Bayesian method outperforms the Granger-causality analysis in the inference of connectivity graphs of dynamic networks, especially for short data lengths. In the second part, the Bayesian method is extended to enable the inference of changes in effective connectivity between groups of subjects. Next, we apply both methods to fMRI scans of 16 healthy subjects, who were scanned before and after the exposure to Mozart's sonata K448 at least 2 hours a day for 7 days. Here, we investigate if the effective connectivity of the subjects significantly changed after listening to Mozart music. The Bayesian method detected changes in effective connectivity between networks related to cognitive processing and control in the connection from the central executive to the superior sensori-motor network, in the connection from the posterior default mode to the fronto-parietal right network, and in the connection from the anterior default mode to the dorsal attention network. This last connection was only detected in a subgroup of subjects with a longer listening duration. Only in this last connection, an effect was found by the Granger-causality analysis.
